The role of the lateral prefrontal cortex (lPFC) in working memory (WM) is debated. Non-human primate (NHP) electrophysiology shows that the lPFC stores WM representations, but human neuroimaging suggests that the lPFC controls WM content in sensory cortices. These accounts are confounded by differences in task training and stimulus exposure. We tested whether long-term training alters lPFC function by densely sampling WM activity using functional MRI. Over 3 months, participants trained on both a WM and serial reaction time (SRT) task, wherein fractal stimuli were embedded within sequences. WM performance improved for trained (but not novel) fractals and, neurally, delay activity increased in distributed lPFC voxels across learning. Item-level WM representations became detectable within lPFC patterns, and lPFC activity reflected sequence relationships from the SRT task. These findings demonstrate that human lPFC develops stimulus-selective responses with learning, and WM representations are shaped by long-term experience, which could reconcile competing accounts of WM functioning.

Brain network definitions typically assume nonoverlap or minimal overlap, ignoring regions' connections to multiple networks. However, new methods are emerging that emphasize network overlap. Here, we investigated the reliability and validity of one assignment method, the mixed membership algorithm, and explored its potential utility for identifying gaps in existing network models of cognition. We first assessed between-sample reliability of overlapping assignments with a split-half design; a bootstrapped Dice similarity analysis demonstrated good agreement between the networks from the two subgroups. Next, we assessed whether overlapping networks captured expected nonoverlapping topographies; overlapping networks captured portions of one to three nonoverlapping topographies, which aligned with canonical network definitions. Following this, a relative entropy analysis showed that a majority of regions participated in more than one network, as is seen biologically, and many regions did not show preferential connection to any one network. Finally, we explored overlapping network membership in regions of the dual-networks model of cognitive control, showing that almost every region was a member of multiple networks. Thus, the mixed membership algorithm produces consistent and biologically plausible networks, which presumably will allow for the development of more complete network models of cognition.

Brain network definitions typically assume nonoverlap or minimal overlap, ignoring regions' connections to multiple networks. However, new methods are emerging that emphasize network overlap. Here, we investigated the reliability and validity of one assignment method, the mixed membership algorithm, and explored its potential utility for identifying gaps in existing network models of cognition. We first assessed between-sample reliability of overlapping assignments with a split-half design; a bootstrapped Dice similarity analysis demonstrated good agreement between the networks from the two subgroups. Next, we assessed whether overlapping networks captured expected nonoverlapping topographies; overlapping networks captured portions of one to three nonoverlapping topographies, which aligned with canonical network definitions. Following this, a relative entropy analysis showed that a majority of regions participated in more than one network, as is seen biologically, and many regions did not show preferential connection to any one network. Finally, we explored overlapping network membership in regions of the dual-networks model of cognitive control, showing that almost every region was a member of multiple networks. Thus, the mixed membership algorithm produces consistent and biologically plausible networks, which presumably will allow for the development of more complete network models of cognition.

The locus coeruleus (LC) is the brain's major source of the neuromodulator norepinephrine, and is also profoundly vulnerable to the development of Alzheimer's disease (AD)-related tau pathology. Norepinephrine plays a role in neuroprotective functions that may reduce AD progression, and also underlies optimal memory performance. Successful maintenance of LC neurochemical function represents a candidate mechanism of protection against the propagation of AD-related pathology and may facilitate the preservation of memory performance despite pathology. Using [F]Fluoro-m-tyrosine ([F]FMT) PET imaging to measure catecholamine synthesis capacity in LC regions of interest, we examined relationships among LC neurochemical function, AD-related pathology, and memory performance in cognitively normal older adults (n = 49). Participants underwent [C]Pittsburgh compound B and [F]Flortaucipir PET to quantify β-amyloid (n = 49) and tau burden (n = 42) respectively. In individuals with substantial β-amyloid, higher LC [F]FMT net tracer influx (Ki) was associated with lower temporal tau. Longitudinal tau-PET analyses in a subset of our sample (n = 30) support these findings to reveal reduced temporal tau accumulation in the context of higher LC [F]FMT Ki. Higher LC catecholamine synthesis capacity was positively correlated with self-reported cognitive engagement and physical activity across the lifespan, established predictors of successful aging measured with the Lifetime Experiences Questionnaire. LC catecholamine synthesis capacity moderated tau's negative effect on memory, such that higher LC catecholamine synthesis capacity was associated with better-than-expected memory performance given an individual's tau burden. These PET findings provide insight into the neurochemical mechanisms of AD vulnerability and cognitive resilience in the living human brain.

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

The intraparietal sulcus (IPS) has been implicated in numerous functions that range from representation of visual stimuli to action planning, but its role in abstract decision-making has been unclear, in part because low-level functions often act as confounds. Here, we address this problem using a task that dissociates abstract decision-making from sensory salience, attentional control, motor planning, and motor output. Functional MRI data were collected from healthy female and male human subjects while they performed a policy abstraction task requiring use of a more abstract (second-order) rule to select between two less abstract (first order) rules that informed the motor response. By identifying IPS subdivisions with preferential connectivity to prefrontal regions that are differentially responsive to task abstraction, we found that a caudal IPS (cIPS) subregion with strongest connectivity to the pre-premotor cortex was preferentially active for second-order cues, whereas a rostral IPS subregion (rIPS) with strongest connectivity to the dorsal premotor cortex was active during attentional control over first-order cues. These effects for abstraction were seen in addition to cIPS activity that was specific to sensory salience, and rIPS activity that was specific to motor output. Notably, topographic responses to the second-order cue were detected along the caudal-rostral axis of IPS, mirroring the broader organization seen in lateral prefrontal cortex (Badre and D'Esposito, 2007). Together, these data demonstrate that subregions within IPS exhibit activity responsive to policy abstraction, and they suggest that IPS may be organized into frontoparietal subnetworks that support hierarchical cognitive control.Abstract decision-making allows us to flexibly adapt our behavior to new contexts. Although much previous work has focused on the role of lateral prefrontal cortex in such decisions, the contributions of parietal cortex have been relatively understudied. Here, we demonstrate that spatially segregated subregions of human IPS with strong functional connections to lateral prefrontal cortex demonstrate activity selective for abstract decisions. This activity can be distinguished from responses because of cognitive processes related to sensory salience, attentional control, motor planning, and movement. Together, these findings indicate that different task demands are reflected in the topography of IPS, and they explicitly reveal a role in abstract decision-making.

Circadian rhythms (lasting approximately 24 hours) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 hours (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.

The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain's low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

Transcranial Magnetic Stimulation (TMS) allows for the direct activation of neurons in the human neocortex and has proven to be fundamental for causal hypothesis testing in cognitive neuroscience. By administering TMS concurrently with functional Magnetic Resonance Imaging (fMRI), the effect of cortical TMS on activity in distant cortical and subcortical structures can be quantified by varying the levels of TMS output intensity. However, TMS generates significant fluctuations in the fMRI time series, and their complex interaction warrants caution before interpreting findings. We present the methodological challenges of concurrent TMS-fMRI and a guide to minimize induced artifacts in experimental design and post-processing. Our study targeted two frontal-striatal circuits: primary motor cortex (M1) projections to the putamen and lateral prefrontal cortex (PFC) projections to the caudate in healthy human participants. We found that TMS parametrically increased the BOLD signal in the targeted region and subcortical projections as a function of stimulation intensity. Together, this work provides practical steps to overcome common challenges with concurrent TMS-fMRI and demonstrates how TMS-fMRI can be used to investigate functional brain networks.

Transcranial Magnetic Stimulation (TMS) allows for the direct activation of neurons in the human neocortex and has proven to be fundamental for causal hypothesis testing in cognitive neuroscience. By administering TMS concurrently with functional Magnetic Resonance Imaging (fMRI), the effect of cortical TMS on activity in distant cortical and subcortical structures can be quantified by varying the levels of TMS output intensity. However, TMS generates significant fluctuations in the fMRI time series, and their complex interaction warrants caution before interpreting findings. We present the methodological challenges of concurrent TMS-fMRI and a guide to minimize induced artifacts in experimental design and post-processing. Our study targeted two frontal-striatal circuits: primary motor cortex (M1) projections to the putamen and lateral prefrontal cortex (PFC) projections to the caudate in healthy human participants. We found that TMS parametrically increased the BOLD signal in the targeted region and subcortical projections as a function of stimulation intensity. Together, this work provides practical steps to overcome common challenges with concurrent TMS-fMRI and demonstrates how TMS-fMRI can be used to investigate functional brain networks.

People's perceptual reports are biased toward percepts they are motivated to see. The arousal system coordinates the body's response to motivationally significant events and is well positioned to regulate motivational effects on perceptual judgments. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here, we measured pupil dilation as a measure of arousal while participants ( = 38) performed a visual categorization task. We used monetary bonuses to motivate participants to perceive one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models suggested that arousal enhanced motivational effects by biasing evidence accumulation in favor of desirable percepts. These results suggest that heightened arousal biases people toward what they want to see and away from an objective representation of the environment.

Stuss considered the human prefrontal cortex (pFC) as a "cognitive globe" [Stuss, D. T., & Benson, D. F. Neuropsychological studies of the frontal lobes. , , 3-28, 1984] on which functions of the frontal lobe could be mapped. Here, we discuss classic and recent findings regarding the evolution, development, function, and cognitive role of shallow indentations or tertiary sulci in pFC, with the goal of using tertiary sulci to map the "cognitive globe" of pFC. First, we discuss lateral pFC (LPFC) tertiary sulci in classical anatomy and modern neuroimaging, as well as their development, with a focus on those within the middle frontal gyrus. Second, we discuss tertiary sulci in comparative neuroanatomy, focusing on primates. Third, we summarize recent findings showing the utility of tertiary sulci for understanding structural-functional relationships with functional network insights in ventromedial pFC and LPFC. Fourth, we revisit and update unresolved theoretical perspectives considered by C. Vogt and O. Vogt (Allgemeinere ergebnisse unserer hirnforschung. , , 279-462, 1919) and F. Sanides (Structure and function of the human frontal lobe. , , 209-219, 1964) that tertiary sulci serve as landmarks for cortical gradients. Together, the consideration of these classic and recent findings indicate that tertiary sulci are situated in a unique position within the complexity of the "cognitive globe" of pFC: They are the smallest and shallowest of sulci in pFC, yet can offer insights that bridge spatial scales (microns to networks), modalities (functional connectivity to behavior), and species. As such, the map of tertiary sulci within each individual participant serves as a coordinate system specific to that individual on which functions may be further mapped. We conclude with new theoretical and methodological questions that, if answered in future research, will likely lead to mechanistic insight regarding the structure and function of human LPFC.

Extant research indicates that worry is associated with reduced working memory. It remains unclear, however, what mechanisms contribute to impaired performance in worriers. Critically, dopamine in the prefrontal cortex heavily influences the stability of mental representations during working memory tasks, yet no research has probed its role in associations between worry and working memory. To address this gap, the current study was designed to examine the moderating role of dopamine on the association between worry and working memory, using the catechol-o-methyltransferase (COMT) gene as a proxy for basal levels of dopamine. Across four assessments, we examined within- and between-person variation in worry and its interactive effects with COMT to predict working memory performance. Within-person variation in worry interacted with COMT to predict accuracy, such that higher worry across time predicted less accuracy for homozygous Val carriers but not Met carriers. Our findings demonstrate that basal dopamine plays an important role in how increases in worry across time for an individual negatively impact working memory performance.

In MRI studies, spatial normalization is required to infer results at the group level. In the presence of a brain lesion, such as in stroke patients, the normalization process can be affected by tissue loss, spatial deformations, signal intensity changes, and other stroke sequelae that introduce confounds into the group analysis results. Previously, most neuroimaging studies with lesioned brains have used normalization methods optimized for intact brains, raising potential concerns about the accuracy of the resulting transformations and, in turn, their reported group level results. In this study, we demonstrate the benefits of creating an intermediate, cohort-specific template in conjunction with diffeomorphism-based methods to normalize structural MRI images in stroke patients. We show that including this cohort-specific template improves accuracy compared to standard methods for normalizing lesioned brains. Critically, this method reduces overall differences in normalization accuracy between stroke patients and healthy controls, and may improve the localization and connectivity of BOLD signal in functional neuroimaging data.

Post-traumatic stress disorder (PTSD) leads to impairments in both cognitive and affective functioning. Animal work suggests that chronic stress reduces dopamine tone, and both animal and human studies argue that changes in dopamine tone influence working memory, a core executive function. These findings give rise to the hypothesis that increasing cortical dopamine tone in individuals with greater PTSD symptomatology should improve working memory performance. In this pharmacological functional magnetic resonance imaging (fMRI) study, 30 US military veterans exhibiting a range of PTSD severity completed an emotional working memory task. Each subject received both placebo and the catechol-O-methyl transferase inhibitor tolcapone, which increases cortical dopamine tone, in randomized, double-blind, counterbalanced fashion. Mnemonic discriminability (calculated with d', an index of the detectability of working memory signals) and response bias were evaluated in the context of task-related brain activations. Subjects with more severe PTSD showed both greater tolcapone-mediated improvements in d' and larger tolcapone-mediated reductions in liberally-biased responding for fearful stimuli. FMRI revealed that tolcapone augmented activity within bilateral frontoparietal control regions during the decision phase of the task. Specifically, tolcapone increased cortical responses to fearful relative to neutral stimuli in higher severity PTSD subjects, and reduced cortical responses to fearful stimuli for lower severity PTSD subjects. Moreover, tolcapone modulated prefrontal connectivity with areas overlapping the default mode network. These findings suggest that enhancing cortical dopamine tone may represent an approach to remediating cognitive and affective dysfunction in individuals with more severe PTSD symptoms.

Understanding the relationship between neuroanatomy and function in portions of cortex that perform functions largely specific to humans such as lateral prefrontal cortex (LPFC) is of major interest in systems and cognitive neuroscience. When considering neuroanatomical-functional relationships in LPFC, shallow indentations in cortex known as tertiary sulci have been largely unexplored. Here, by implementing a multi-modal approach and manually defining 936 neuroanatomical structures in 72 hemispheres (in both males and females), we show that a subset of these overlooked tertiary sulci serve as a meso-scale link between microstructural (myelin content) and functional (network connectivity) properties of human LPFC in individual participants. For example, the () is a tertiary sulcus with three components that differ in their myelin content, resting state connectivity profiles, and engagement across meta-analyses of 83 cognitive tasks. Further, generating microstructural profiles of myelin content across cortical depths for each component and the surrounding middle frontal gyrus (MFG) shows that both gyral and sulcal components of the MFG have greater myelin content in deeper compared to superficial layers and that the myelin content in superficial layers of the gyral components is greater than sulcal components. These findings support a classic, yet largely unconsidered theory that tertiary sulci may serve as landmarks in association cortices, as well as a modern cognitive neuroscience theory proposing a functional hierarchy in LPFC. As there is a growing need for computational tools that automatically define tertiary sulci throughout cortex, we share probabilistic sulcal maps with the field.: Lateral prefrontal cortex (LPFC) is critical for functions that are thought to be specific to humans compared to other mammals. However, relationships between fine-scale neuroanatomical structures largely specific to hominoid cortex and functional properties of LPFC remain elusive. Here, we show that these structures, which have been largely unexplored throughout history, surprisingly serve as markers for anatomical and functional organization in human LPFC. These findings have theoretical, methodological, developmental, and evolutionary implications for improved understanding of neuroanatomical-functional relationships not only in LPFC, but also in association cortices more broadly. Finally, these findings ignite new questions regarding how morphological features of these neglected neuroanatomical structures contribute to functions of association cortices that are critical for human-specific aspects of cognition.

Domoic acid (DOM) is a neurotoxin produced by some harmful algae blooms in coastal waters. California sea lions (Zalophus californianus) exposed to DOM often strand on beaches where they exhibit a variety of symptoms, including seizures. These animals typically show hippocampal atrophy on MRI scans.

Systems neuroscience approaches with a focus on large-scale brain organization and network analysis are advancing foundational knowledge of how cognitive control processes are implemented in the brain. Over the past decade, technological and computational innovations in the study of brain connectivity have led to advances in our understanding of how brain networks function, inspiring new conceptualizations of the role of prefrontal cortex (PFC) networks in the coordination of cognitive control. In this review, we describe six key PFC networks involved in cognitive control and elucidate key principles relevant for understanding how these networks implement cognitive control. Implementation of cognitive control in a constantly changing environment depends on the dynamic and flexible organization of PFC networks. In this context, we describe major empirical and theoretical models that have emerged in recent years and describe how their functional architecture and dynamic organization supports flexible cognitive control. We take an overarching view of advances made in the past few decades and consider fundamental issues regarding PFC network function, global brain dynamics, and cognition that still need to be resolved. We conclude by clarifying important future directions for research on cognitive control and their implications for advancing our understanding of PFC networks in brain disorders.

Stuss considered the human PFC as a "cognitive globe" [Stuss, D. T., & Benson, D. F. Neuropsychological studies of the frontal lobes. Psychological Bulletin, 95, 3-28, 1984] on which functions of the frontal lobe could be mapped. Here, we discuss classic and recent findings regarding the evolution, development, function, and cognitive role of shallow indentations or tertiary sulci in PFC, with the goal of using tertiary sulci to map the "cognitive globe" of PFC. First, we discuss lateral PFC (LPFC) tertiary sulci in classical anatomy and modern neuroimaging, as well as their development, with a focus on those within the middle frontal gyrus. Second, we discuss tertiary sulci in comparative neuroanatomy, focusing on primates. Third, we summarize recent findings showing the utility of tertiary sulci for understanding structural-functional relationships with functional network insights in ventromedial PFC and LPFC. Fourth, we revisit and update unresolved theoretical perspectives considered by C. Vogt and O. Vogt (Allgemeinere ergebnisse unserer hirnforschung. Journal für Psychologie und Neurologie, 25, 279-462, 1919) and F. Sanides (Structure and function of the human frontal lobe. Neuropsychologia, 2, 209-219, 1964) that tertiary sulci serve as landmarks for cortical gradients. Together, the consideration of these classic and recent findings indicate that tertiary sulci are situated in a unique position within the complexity of the "cognitive globe" of PFC: They are the smallest and shallowest of sulci in PFC, yet can offer insights that bridge spatial scales (microns to networks), modalities (functional connectivity to behavior), and species. As such, the map of tertiary sulci within each individual participant serves as a coordinate system specific to that individual on which functions may be further mapped. We conclude with new theoretical and methodological questions that, if answered in future research, will likely lead to mechanistic insight regarding the structure and function of human LPFC.

Measures of human brain functional connectivity acquired during the resting-state track critical aspects of behavior. Recently, fluctuations in resting-state functional connectivity patterns-typically averaged across in traditional analyses-have been considered for their potential neuroscientific relevance. There exists a lack of research on the differences between traditional "static" measures of functional connectivity and newly considered "time-varying" measures as they relate to human behavior. Using functional magnetic resonance imagining (fMRI) data collected at rest, and a battery of behavioral measures collected outside the scanner, we determined the degree to which each modality captures aspects of personality and cognitive ability. Measures of time-varying functional connectivity were derived by fitting a hidden Markov model. To determine behavioral relationships, static and time-varying connectivity measures were submitted separately to canonical correlation analysis. A single relationship between static functional connectivity and behavior existed, defined by measures of personality and stable behavioral features. However, two relationships were found when using time-varying measures. The first relationship was similar to the static case. The second relationship was unique, defined by measures reflecting trialwise behavioral variability. Our findings suggest that time-varying measures of functional connectivity are capable of capturing unique aspects of behavior to which static measures are insensitive.

Hierarchical cognitive control enables us to execute actions guided by abstract goals. Previous research has suggested that neuronal oscillations at different frequency bands are associated with top-down cognitive control, however, whether distinct neural oscillations have similar or different functions for cognitive control is not well understood. The aim of the current study was to investigate the oscillatory neuronal mechanisms underlying two distinct components of hierarchical cognitive control: the level of abstraction of a rule, and the number of rules that must be maintained (set-size). We collected electroencephalography (EEG) data in 31 men and women who performed a hierarchical cognitive control task that varied in levels of abstraction and set-size. Results from time-frequency analysis in frontal electrodes showed an increase in theta amplitude for increased set-size, whereas an increase in delta was associated with increased abstraction. Both theta and delta amplitude correlated with behavioral performance in the tasks but in an opposite manner: theta correlated with response time slowing when the number of rules increased whereas delta correlated with response time when rules became more abstract. Phase amplitude coupling analysis revealed that delta phase coupled with beta amplitude during conditions with a higher level of abstraction, whereby beta band may potentially represent motor output that was guided by the delta phase. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.Cognitive control allows us to perform immediate actions while maintaining more abstract, overarching goals in mind and to choose between competing actions. We found distinct oscillatory signatures that correspond to two different components of hierarchical control: the level of abstraction of a rule and the number of rules in competition. An increase in the level of abstraction was associated with delta oscillations, whereas theta oscillations were observed when the number of rules increased. Oscillatory amplitude correlated with behavioral performance in the task. Finally, the expression of beta amplitude was coordinated via the phase of delta oscillations, and theta phase coupled with gamma amplitude. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.

Humans can draw insight from previous experiences in order to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task structure. Human subjects (male and female) completed multiple blocks of a reinforcement learning task that contained a global hierarchical structure governing stimulus-response action mapping. First, behavioral and computational evidence showed that humans successfully discover and transfer the hierarchical rule structure embedded within the task. Next, analysis of fMRI BOLD data revealed activity across a frontal-parietal network that was specifically associated with the discovery of this embedded structure. Finally, activity throughout a cingulo-opercular network supported the transfer and implementation of this discovered structure. Together, these results reveal a division of labor in which dissociable neural systems support the learning and transfer of abstract control structures.A fundamental and defining feature of human behavior is the ability to generalize knowledge from the past in order to support future action. Although the neural circuits underlying more direct forms of learning have been well established over the last century, we still lack a solid framework from which to investigate more abstract, higher order human learning and knowledge generalization. We designed a novel behavioral paradigm in order to specifically isolate a learning process in which previous knowledge, rather than directly indicating the correct action, instead guides the search for the correct action. Moreover, we identify that this learning process is achieved via the coordinated and temporally specific activity of two prominent cognitive control brain networks.

Stable representations of past experience are thought to depend on processes that unfold after events are initially encoded into memory. Post-encoding reactivation and hippocampal-cortical interactions are leading candidate mechanisms thought to support memory retention and stabilization across hippocampal-cortical networks. Although putative consolidation mechanisms have been observed during sleep and periods of awake rest, the direct causal contribution of awake consolidation mechanisms to later behavior is unclear, especially in humans. Moreover, it has been argued that observations of putative consolidation processes are epiphenomenal and not causally important, yet there are few tools to test the functional contribution of these mechanisms in humans. Here, we combined transcranial magnetic stimulation (TMS) and fMRI to test the role of awake consolidation processes by targeting hippocampal interactions with lateral occipital cortex (LOC). We applied theta-burst TMS to LOC (and a control site) to interfere with an extended window (approximately 30-50 min) after memory encoding. Behaviorally, post-encoding TMS to LOC selectively impaired associative memory retention compared to multiple control conditions. In the control TMS condition, we replicated prior reports of post-encoding reactivation and memory-related hippocampal-LOC interactions during periods of awake rest using fMRI. However, post-encoding LOC TMS reduced these processes, such that post-encoding reactivation in LOC and memory-related hippocampal-LOC functional connectivity were no longer present. By targeting and manipulating post-encoding neural processes, these findings highlight the direct contribution of awake time periods to episodic memory consolidation. This combined TMS-fMRI approach provides an opportunity for causal manipulations of human memory consolidation.

In daily life, we use visual working memory (WM) to guide our actions. While attending to currently-relevant information, we must simultaneously maintain future-relevant information, and discard information that is no longer relevant. However, the neural mechanisms by which unattended, but future-relevant, information is maintained in working memory, and future-irrelevant information is discarded, are not well understood. Here, we investigated representations of these different information types, using functional magnetic resonance imaging in combination with multivoxel pattern analysis and computational modeling based on inverted encoding model simulations. We found that currently-relevant WM information in the focus of attention was maintained through representations in visual, parietal and posterior frontal brain regions, whereas deliberate forgetting led to suppression of the discarded representations in early visual cortex. In contrast, future-relevant information was neither inhibited nor actively maintained in these areas. These findings suggest that different neural mechanisms underlie the WM representation of currently- and future-relevant information, as compared to information that is discarded from WM.

Alcohol abuse and alcohol dependence are key factors in the development of alcohol use disorder, which is a pervasive societal problem with substantial economic, medical, and psychiatric consequences. Although our understanding of the neurocircuitry that underlies alcohol use has improved, novel brain regions that are involved in alcohol use and novel biomarkers of alcohol use need to be identified. The present study used a single-cell whole-brain imaging approach to 1) assess whether abstinence from alcohol in an animal model of alcohol dependence alters the functional architecture of brain activity and modularity, 2) validate our current knowledge of the neurocircuitry of alcohol abstinence, and 3) discover brain regions that may be involved in alcohol use. Alcohol abstinence resulted in the whole-brain reorganization of functional architecture in mice and a pronounced decrease in modularity that was not observed in nondependent moderate drinkers. Structuring of the alcohol abstinence network revealed three major brain modules: 1) extended amygdala module, 2) midbrain striatal module, and 3) cortico-hippocampo-thalamic module, reminiscent of the three-stage theory. Many hub brain regions that control this network were identified, including several that have been previously overlooked in alcohol research. These results identify brain targets for future research and demonstrate that alcohol use and dependence remodel brain-wide functional architecture to decrease modularity. Further studies are needed to determine whether the changes in coactivation and modularity that are associated with alcohol abstinence are causal features of alcohol dependence or a consequence of excessive drinking and alcohol exposure.

Sequential sampling models such as the drift diffusion model (DDM) have a long tradition in research on perceptual decision-making, but mounting evidence suggests that these models can account for response time (RT) distributions that arise during reinforcement learning and value-based decision-making. Building on this previous work, we implemented the DDM as the choice rule in inter-temporal choice (temporal discounting) and risky choice (probability discounting) using hierarchical Bayesian parameter estimation. We validated our approach in data from nine patients with focal lesions to the ventromedial prefrontal cortex / medial orbitofrontal cortex (vmPFC/mOFC) and nineteen age- and education-matched controls. Model comparison revealed that, for both tasks, the data were best accounted for by a variant of the drift diffusion model including a non-linear mapping from value-differences to trial-wise drift rates. Posterior predictive checks confirmed that this model provided a superior account of the relationship between value and RT. We then applied this modeling framework and 1) reproduced our previous results regarding temporal discounting in vmPFC/mOFC patients and 2) showed in a previously unpublished data set on risky choice that vmPFC/mOFC patients exhibit increased risk-taking relative to controls. Analyses of DDM parameters revealed that patients showed substantially increased non-decision times and reduced response caution during risky choice. In contrast, vmPFC/mOFC damage abolished neither scaling nor asymptote of the drift rate. Relatively intact value processing was also confirmed using DDM mixture models, which revealed that in both groups >98% of trials were better accounted for by a DDM with value modulation than by a null model without value modulation. Our results highlight that novel insights can be gained from applying sequential sampling models in studies of inter-temporal and risky decision-making in cognitive neuroscience.

Working memory (WM) relies on the prioritization of relevant information and suppression of irrelevant information [1, 2]. Prioritizing relevant information has been linked to theta frequency neural oscillations in lateral prefrontal cortex and suppressing irrelevant information has been linked to alpha oscillations in occipito-parietal cortex [3,11]. Here, we used a retrospective-cue WM paradigm to manipulate prioritization and suppression task demands designed to drive theta oscillations in prefrontal cortex and alpha oscillations in parietal cortex, respectively. To causally test the role of these neural oscillations, we applied rhythmic transcranial magnetic stimulation (TMS) in either theta or alpha frequency to prefrontal and parietal regions identified using functional MRI. The effect of rhythmic TMS on WM performance was dependent on whether the TMS frequency matched or mismatched the expected underlying task-driven oscillations of the targeted region. Functional MRI in the targeted regions predicted subsequent TMS effects across subjects supporting a model by which theta oscillations are excitatory to neural activity, and alpha oscillations are inhibitory. Together, these results causally establish dissociable roles for prefrontal theta oscillations and parietal alpha oscillations in the control of internally maintained WM representations.

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should therefore be a key component of the biologist's toolkit. But, classic chaos-detection tools are highly sensitive to measurement noise and break down for common edge cases, making it difficult to detect chaos in domains, like biology, where measurements are noisy. However, newer tools promise to overcome these limitations. Here, we combine several such tools into an automated processing pipeline, and show that our pipeline can detect the presence (or absence) of chaos in noisy recordings, even for difficult edge cases. As a first-pass application of our pipeline, we show that heart rate variability is not chaotic as some have proposed, and instead reflects a stochastic process in both health and disease. Our tool is easy-to-use and freely available.

Past studies have demonstrated that flexible interactions between brain regions support a wide range of goal-directed behaviors. However, the neural mechanisms that underlie adaptive communication between brain regions are not well understood. In this study, we combined theta-burst transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging to investigate the sources of top-down biasing signals that influence task-evoked functional connectivity. Subjects viewed sequences of images of faces and buildings and were required to detect repetitions (2-back vs. 1-back) of the attended stimuli category (faces or buildings). We found that functional connectivity between ventral temporal cortex and the primary visual cortex (VC) increased during processing of task-relevant stimuli, especially during higher memory loads. Furthermore, the strength of functional connectivity was greater for correct trials. Increases in task-evoked functional connectivity strength were correlated with increases in activity in multiple frontal, parietal, and subcortical (caudate and thalamus) regions. Finally, we found that TMS to superior intraparietal sulcus (IPS), but not to primary somatosensory cortex, decreased task-specific modulation in connectivity patterns between the primary VC and the parahippocampal place area. These findings demonstrate that the human IPS is a source of top-down biasing signals that modulate task-evoked functional connectivity among task-relevant cortical regions.

The brain operates via networked activity in separable groups of regions called modules. The quantification of modularity compares the number of connections within and between modules, with high modularity indicating greater segregation, or dense connections within sub-networks and sparse connections between sub-networks. Previous work has demonstrated that baseline brain network modularity predicts executive function outcomes in older adults and patients with traumatic brain injury after cognitive and exercise interventions. In healthy young adults, however, the functional significance of brain modularity in predicting training-related cognitive improvements is not fully understood. Here, we quantified brain network modularity in young adults who underwent cognitive training with casual video games that engaged working memory and reasoning processes. Network modularity assessed at baseline was positively correlated with training-related improvements on untrained tasks. The relationship between baseline modularity and training gain was especially evident in initially lower performing individuals and was not present in a group of control participants that did not show training-related gains. These results suggest that a more modular brain network organization may allow for greater training responsiveness. On a broader scale, these findings suggest that, particularly in low-performing individuals, global network properties can capture aspects of brain function that are important in understanding individual differences in learning.

Working memory is characterized by neural activity that persists during the retention interval of delay tasks. Despite the ubiquity of this delay activity across tasks, species and experimental techniques, our understanding of this phenomenon remains incomplete. Although initially there was a narrow focus on sustained activation in a small number of brain regions, methodological and analytical advances have allowed researchers to uncover previously unobserved forms of delay activity various parts of the brain. In light of these new findings, this Review reconsiders what delay activity is, where in the brain it is found, what roles it serves and how it may be generated.

Interventions using methods such as cognitive training and aerobic exercise have shown potential to enhance cognitive abilities. However, there is often pronounced individual variability in the magnitude of these gains. Here, we propose that brain network modularity, a measure of brain subnetwork segregation, is a unifying biomarker of intervention-related plasticity. We present work from multiple independent studies demonstrating that individual differences in baseline brain modularity predict gains in cognitive control functions across several populations and interventions, spanning healthy adults to patients with clinical deficits and cognitive training to aerobic exercise. We believe that this predictive framework provides a foundation for developing targeted, personalized interventions to improve cognition.

Trait anxiety has been associated with altered activity within corticolimbic pathways connecting the amygdala and rostral anterior cingulate cortex (rACC), which receive rich dopaminergic input. Though the popular culture uses the term "chemical imbalance" to describe the pathophysiology of psychiatric conditions such as anxiety disorders, we know little about how individual differences in human dopamine neurochemistry are related to variation in anxiety and activity within corticolimbic circuits. We addressed this issue by examining inter-individual variability in dopamine release at rest using [C]raclopride positron emission tomography (PET), functional connectivity between amygdala and rACC using resting-state functional magnetic resonance imaging (fMRI), and trait anxiety measures in healthy adult male and female humans. To measure endogenous dopamine release, we collected two [C]raclopride PET scans per participant. We contrasted baseline [C]raclopride D2/3 receptor binding and D2/3 receptor binding following oral methylphenidate administration. Methylphenidate blocks the dopamine transporter, which increases extracellular dopamine and leads to reduced [C]raclopride D2/3 receptor binding via competitive displacement. We found that individuals with higher dopamine release in the amygdala and rACC self-reported lower trait anxiety. Lower trait anxiety was also associated with reduced rACC-amygdala functional connectivity at baseline. Further, functional connectivity showed a modest negative relationship with dopamine release such that reduced rACC-amygdala functional connectivity was accompanied by higher levels of dopamine release in these regions. Together, these findings contribute to hypodopaminergic models of anxiety and support the utility of combining fMRI and PET measures of neurochemical function to advance our understanding of basic affective processes in humans.It is common wisdom that individuals vary in their baseline levels of anxiety. We all have a friend or colleague we know to be more "tightly wound" than others, or, perhaps, we are the ones marveling at others' ability to "just go with the flow." While such observations about individual differences within non-clinical populations are commonplace, the neural mechanisms underlying normal variation in trait anxiety have not been established. Using multimodal brain imaging in humans, this study takes initial steps in linking intrinsic measures of neuromodulator release and functional connectivity within regions implicated in anxiety disorders. Our findings suggest that in healthy adults, higher levels of trait anxiety may arise, at least in part, from reduced dopamine neurotransmission.

Beta and gamma frequency neuronal oscillations have been implicated in top-down and bottom-up attention. In this study, we used rhythmic TMS to modulate ongoing beta and gamma frequency neuronal oscillations in frontal and parietal cortex, while human participants performed a visual search task that manipulates bottom-up and top-down attention (single feature and conjunction search). Both task conditions will engage bottom-up attention processes, whereas the conjunction search condition will require more top-down attention. Gamma frequency TMS to superior precentral sulcus (sPCS) slowed saccadic RTs during both task conditions and induced a response bias to the contralateral visual field. In contrary, beta frequency TMS to sPCS and intraparietal sulcus decreased search accuracy only during the conjunction search condition that engaged more top-down attention. Furthermore, beta frequency TMS increased trial errors specifically when the target was in the ipsilateral visual field for the conjunction search condition. These results indicate that beta frequency TMS to sPCS and intraparietal sulcus disrupted top-down attention, whereas gamma frequency TMS to sPCS disrupted bottom-up, stimulus-driven attention processes. These findings provide causal evidence suggesting that beta and gamma oscillations have distinct functional roles for cognition.

Persisting difficulties in executive functioning (EF) are common after traumatic brain injury (TBI). Cognitive rehabilitation can be effective, but the impact of pretreatment neurocognitive functioning on long term effects of rehabilitation is unknown. Because this information can impact treatment planning, we examined the relationship between prerehabilitation neurocognitive status and long-term effects of EF training. Archival data were drawn from a trial of Goal-Oriented Attentional Self-Regulation group-format EF training for Veterans with TBI [mild-severe; 11 years postinjury; 96% male, 32% nonwhite, 14.21 years education ( 1.72), 41.13 years old ( 11.39)]. Using prerehabilitation neurocognitive performance, participants were clustered into cognitive difficulty (CD) and cognitively normal (CN) groups. Six-plus months after EF rehabilitation training, participants completed a structured telephone interview and/or in-person cognitive/functional/emotional assessment using standardized measures of cognitive, daily, and emotional functioning frequently employed in TBI research. At 6+ months post-EF training compared to prerehabilitation, CD and CN improved in multiple cognitive (Overall Attention/EF: (1,18) = 26.17, partial  = .59; Total Memory: (1,18) = 6.82, partial  = .28) and functional domains (Goal Processing Scale [GPS] total score: (1,15) = 6.71, partial  = .31). CD improved more than CN on Learning and Memory functional domain [F(1,15) = 6.10, partial  = .29]. Results of our small archival analysis raise the possibility that Veterans with chronic TBI may demonstrate long-term effects of EF training.

: To investigate long-term effects of GOALS executive function training in Veterans with chronic TBI. In a recently completed study Veterans with chronic TBI showed improvement immediately post-GOALS but not control training on measures of executive function, functional task performance, and emotion regulation. We now examine the long-term maintenance of post-GOALS training changes in the same sample. : San Francisco VA Health Care System (SFVAHCS), and VA Northern California Health-Care System (VANCHS) in Martinez. : 24 Veterans with chronic TBI were assessed at baseline, post-GOALS training, and long-term follow-up 6+ months following completion of training with a structured telephone interview, neuropsychological and complex functional performance measures, and self-report measures of daily and emotional functioning. : Participants reported an increased likelihood of involvement in competitive employment/volunteering at follow-up (61%) compared to baseline (26%; χ2 = 5.66, < .01, ѱ = .35). Repeated measures MANOVAS indicated improvement on attention/executive function (F = 13.85, < .01, partial η2 = .42), complex functional task performance (GPS Total: F = 9.12, < .01, partial η2 = .38) and daily functioning (MPAI Total: F = 3.23, < .05, partial η2 = .21), and reduction in overall mood disturbance (POMS Total: F = 3.42, < .05, partial η2 = .22) at follow-up relative to baseline. : Training in attention regulation applied to participant-defined goals is associated with meaningful long-term improvement in cognitive skills, emotion regulation, and daily functioning in Veterans with chronic TBI.

The divide-and-conquer approach to the study of human cognition has succeeded in focusing researchers' efforts on behavioral phenomena that fall under well-defined categories such as attention, perception, language, memory, emotion, and motor control. The result has been the development of coherent bodies of work in each area replete with successful explanatory theories and a rich collection of paradigms, tasks, and analytic techniques. There has been a renewed in recent years in combining and integrating ideas across these domains, as well as in incorporating neuroscientific data, as a way to build more powerful and general models of cognition. Here we review the history and current state of integration between verbal short-term memory (VeSTM) and language, two domains of study that have significant areas of overlap but have not been fully integrated. We review evidence from cognitive neuroscience that has generally shown VeSTM to greatly depend on the network of brain regions that are known to form the core sensory-motor basis of human language. Whereas classic psychological models of VeSTM posit the existence of dedicated short-term storage buffers, we suggest that temporary verbal memory emerges from the coordinated interplay of a fronto-temporal sensory-motor circuit that has evolved to support the perception and production of speech. Phonological rehearsal in the service of temporary maintenance is achieved by feedforward and feedback pathways connecting the auditory- and motor-speech systems via a sensorymotor interface component situated in the Sylvian-parietal-temporal region (Spt). Reciprocal connectivity between the frontal and temporal speech systems enables the kind of "round-tripping" of dual speech codes long hypothesized by cognitive models such as Baddeley and Hitch's "phonological loop".

Long-range phase synchrony in the α-oscillation band (near 10 Hz) has been proposed to facilitate information integration across anatomically segregated regions. Which areas may top-down regulate such cross-regional integration is largely unknown. We previously found that the moment-to-moment strength of high-α band (10-12 Hz) phase synchrony co-varies with activity in a fronto-parietal (FP) network. This network is critical for adaptive cognitive control functions such as cognitive flexibility required during set-shifting. Using electroencephalography (EEG) in 23 patients with focal frontal lobe lesions (resected tumors), we tested the hypothesis that the FP network is necessary for modulation of high-α band phase synchrony. Global phase-synchrony was measured using an adaptation of the phase-locking value (PLV) in a sliding window procedure, which allowed for measurement of changes in EEG-based resting-state functional connectivity across time. As hypothesized, the temporal modulation (range and standard deviation) of high-α phase synchrony was reduced as a function of FP network lesion extent, mostly due to dorsolateral prefrontal cortex (dlPFC) lesions. Furthermore, patients with dlPFC lesions exhibited reduced cognitive flexibility as measured by the Trail-Making Test (set-shifting). Our findings provide evidence that the FP network is necessary for modulatory control of high-α band long-range phase synchrony, and linked to cognitive flexibility.

Traumatic brain injury (TBI) is common among Veterans, and sequelae frequently include deficits in attention and executive function and problems with emotional regulation. Although rehabilitation has been shown to be effective, it is not clear how patient characteristics such as baseline cognitive status may impact response to rehabilitation in this sample. Explore the relationship between baseline neuropsychological status and postintervention functional outcomes in Veterans with chronic TBI. Thirty-three Veterans with chronic mild-severe TBI completed a neuropsychological evaluation, a functional assessment of executive function (EF), and measures of emotional and everyday functioning pre- and post-EF training or control training. Performance on baseline neuropsychological measures was used to cluster participants. Participants' performance at baseline and postintervention assessments was compared by cluster using multivariate analyses of variance (MANOVAs). Cognitive Difficulty (CD; n = 19) and Cognitively Normal (CN; n = 14) clusters were identified. CD was characterized by z ≤ -.75 on neuropsychological measures of overall attention/EF, working memory, and memory. CD participants performed worse on functional EF assessment and endorsed more PTSD symptoms and community integration problems, at baseline. CD participants improved post-EF training, but not control training, on neuropsychological and functional measures. CN participants did not show statistically significant improvement. For Veterans with chronic TBI, cognitive assessment can aid in identifying functional impairment and assist treatment planning. Cognitive rehabilitation training appears to be a beneficial treatment option for TBI patients with cognitive, emotional, and daily living difficulties.

The human brain network is modular-comprised of communities of tightly interconnected nodes. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities. A mechanistic understanding of these hubs and how they support cognition has not been demonstrated. Here, we leveraged individual differences in hub connectivity and cognition. We show that a model of hub connectivity accurately predicts the cognitive performance of 476 individuals in four distinct tasks. Moreover, there is a general optimal network structure for cognitive performance-individuals with diversely connected hubs and consequent modular brain networks exhibit increased cognitive performance, regardless of the task. Critically, we find evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbors to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance.

Visual working memory (VWM) recruits a broad network of brain regions, including prefrontal, parietal, and visual cortices. Recent evidence supports a "sensory recruitment" model of VWM, whereby precise visual details are maintained in the same stimulus-selective regions responsible for perception. A key question in evaluating the sensory recruitment model is how VWM representations persist through distracting visual input, given that the early visual areas that putatively represent VWM content are susceptible to interference from visual stimulation.To address this question, we employed an fMRI inverted encoding model approach to quantitatively assess the effect of distractors on VWM representations in early visual cortex and the intraparietal sulcus (IPS), another region previously implicated in the storage of VWM information. This approach allowed us to reconstruct VWM representations for orientation, both before and after visual interference, and to examine whether oriented distractors systematically biased these representations. In our human participants (both male and female), we found that orientation information was maintained simultaneously in early visual areas and IPS in anticipation of possible distraction, and these representations persisted in the absence of distraction. Importantly, early visual representations were susceptible to interference; VWM orientations reconstructed from visual cortex were significantly biased toward distractors, corresponding to a small attractive bias in behavior. In contrast, IPS representations did not show such a bias. These results provide quantitative insight into the effect of interference on VWM representations, and suggest a dynamic tradeoff between visual and parietal regions that allows flexible adaptation to task demands in service of VWM.Despite considerable evidence that stimulus-selective visual regions maintain precise visual information in working memory, it remains unclear how these representations persist through subsequent input. Here, we used quantitative model-based fMRI analyses to reconstruct the contents of working memory and examine the effects of distracting input. While representations in the early visual areas were systematically biased by distractors, those in the intraparietal sulcus appeared distractor-resistant. In contrast, early visual representations were most reliable in the absence of distraction. These results demonstrate the dynamic, adaptive nature of visual working memory processes, and provide quantitative insight into the ways in which representations can be affected by interference. Further, they suggest that current models of working memory should be revised to incorporate this flexibility.

Deficits in executive control functions are some of the most common and disabling consequences of both military and civilian brain injury. However, effective interventions are scant. The goal of this study was to assess whether cognitive rehabilitation training that was successfully applied in chronic civilian brain injury would be effective for military Veterans with TBI. In a prior study, participants with chronic acquired brain injury significantly improved after training in goal-oriented attentional self-regulation (GOALS) on measures of attention/executive function, functional task performance, and goal-directed control over neural processing on fMRI. The objective of this study was to assess effects of GOALS training in Veterans with chronic TBI. 33 Veterans with chronic TBI and executive difficulties in their daily life completed either five weeks of manualized Goal-Oriented Attentional Self-Regulation (GOALS) training or Brain-Health Education (BHE) matched in time and intensity. Evaluator-blinded assessments at baseline and post training included neuropsychological and complex functional task performance and self-report measures of emotional regulation. After GOALS, but not BHE training, participants significantly improved from baseline on primary outcome measures of: Overall Complex Attention/Executive Function composite neuropsychological performance score [F = 7.10, p =.01; partial 2 = .19], and on overall complex functional task performance (Goal Processing Scale Overall Performance) [F=6.92, p=.01, partial 2 =.20]. Additionally, post-GOALS participants indicated significant improvement on emotional regulation self-report measures [POMS Confusion Score F=6.05, p=.02, partial2=.20]. Training in attentional self-regulation applied to participant defined goals may improve cognitive functioning in Veterans with chronic TBI. Attention regulation training may not only impact executive control functioning in real world complex tasks, but may also improve emotional regulation and functioning. Implications for treatment of Veterans with TBI are discussed.

The hippocampus plays a critical role in episodic memory, among other cognitive functions. However, few tools exist to causally manipulate hippocampal function in healthy human participants. Recent work has targeted hippocampal-cortical networks by performing TMS to a region interconnected with the hippocampus, posterior inferior parietal cortex (pIPC). Such hippocampal-targeted TMS enhances associative memory and influences hippocampal functional connectivity. However, it is currently unknown which stages of mnemonic processing (encoding or retrieval) are affected by hippocampal-targeted TMS. Here, we examined whether hippocampal-targeted TMS influences the initial encoding of associations (vs. items) into memory. To selectively influence encoding and not retrieval, we performed continuous theta-burst TMS before participants encoded object-location associations and assessed memory after the direct effect of stimulation dissipated. Relative to control TMS and baseline memory, pIPC TMS enhanced associative memory success and confidence. Item memory was unaffected, demonstrating a selective influence on associative versus item memory. The strength of hippocampal-pIPC functional connectivity predicted TMS-related memory benefits, which was mediated by parahippocampal and retrosplenial cortices. Our findings indicate that hippocampal-targeted TMS can specifically modulate the encoding of new associations into memory without directly influencing retrieval processes and suggest that the ability to influence associative memory may be related to the fidelity of hippocampal TMS targeting. Our results support the notion that pIPC TMS may serve as a potential tool for manipulating hippocampal function in healthy participants. Nonetheless, future work combining hippocampal-targeted continuous theta-burst TMS with neuroimaging is needed to better understand the neural basis of TMS-induced memory changes.

The prefrontal cortex (PFC) and basal ganglia (BG) have been associated with cognitive stability and cognitive flexibility, respectively. We hypothesized that increasing PFC dopamine tone by administering tolcapone (a catechol-O-methyltransferase (COMT) inhibitor) to human subjects should promote stability; conversely, increasing BG dopamine tone by administering bromocriptine (a D2 receptor agonist) should promote flexibility.

Flexible interactions between brain regions enable neural systems to adaptively transfer and process information. However, the neural substrates that regulate adaptive communications between brain regions are understudied. In this human fMRI study, we investigated this issue by tracking time-varying, task-evoked changes in functional connectivity between localized occipitotemporal regions while participants performed different tasks on the same visually presented stimuli. We found that functional connectivity between ventral temporal and the primary visual regions selectively increased during the processing of task-relevant information. Further, additional task demands selectively strengthen these targeted connectivity patterns. To identify candidate regions that contribute to this increase in inter-regional coupling, we regressed the task-specific time-varying connectivity strength between primary visual and occipitotemporal regions against voxel-wise activity patterns elsewhere in the brain. This allowed us to identify a set of frontal and parietal regions whose activity increased as a function of task-evoked functional connectivity. These results suggest that frontoparietal regions may provide top-down biasing signals to influence task-specific interactions between brain regions.

We examined imaging surrogates of white matter microstructural abnormalities which may precede white matter lesions (WML) and represent a relevant marker of cerebrovascular injury in adults in midlife.

The intrinsic white matter connections of the frontal cortex are highly complex, and the organization of these connections is not fully understood. Quantitative graph-theoretical methods, which are not solely reliant on human observation and interpretation, can be powerful tools for describing the organizing network principles of frontal cortex. Here, we examined the network structure of frontal cortical subregions by applying graph-theoretical community detection analyses to a graph of frontal cortex compiled from over 400+ macaque white-matter tracing studies. We find evidence that the lateral frontal cortex can be partitioned into distinct modules roughly organized along the dorsoventral and rostrocaudal axis.

Working memory refers to a system involved in the online maintenance and manipulation of information in the absence of external input. Due to the importance of working memory in higher-level cognition, a wealth of neuroscience studies has investigated its neural basis. These studies have often led to conflicting viewpoints regarding the importance of the prefrontal cortex (PFC) and posterior sensory cortices. Here, we review evidence for each position. We suggest that the relative contributions of the PFC and sensory cortices to working memory can be understood with respect to processing demands. We argue that procedures that minimize processing demands lead to increased importance of sensory representations, while procedures that permit transformational processing lead to representational abstraction that relies on the PFC. We suggest that abstract PFC representations support top-down control over posterior representations while also providing bottom-up inputs into higher-level cognitive processing. Although a number of contemporary studies have studied working memory while using procedures that minimize the role of the PFC, we argue that consideration of the PFC is critical for our understanding of working memory and higher-level cognition more generally.

The lateral prefrontal cortex (LPFC) is essential for higher-level cognition, but how its interactions support cognitive control remains elusive. Previously (Nee and D'Esposito, 2016), dynamic causal modeling (DCM) indicated that mid LPFC integrates abstract, rostral and concrete, caudal influences to inform context-appropriate action. Here, we use continuous theta-burst transcranial magnetic stimulation (cTBS) to causally test this model. cTBS was applied to three LPFC sites and a control site in counterbalanced sessions. Behavioral modulations resulting from cTBS were largely predicted by information flow within the previously estimated DCM. However, cTBS to caudal LPFC unexpectedly impaired processes presumed to involve rostral LPFC. Adding a pathway from caudal to mid-rostral LPFC significantly improved the model fit and accounted for the observed behavioral findings. These data provide causal evidence for LPFC dynamics supporting cognitive control and demonstrate the utility of combining DCM with causal manipulations to test and refine models of cognition.

While older adults are able to attend to goal-relevant information, the capacity to ignore irrelevant or distracting information declines with advancing age. This decline in selective attention has been associated with poor modulation of brain activity in sensory cortices by anterior brain regions implicated in cognitive control.

The neuromodulator acetylcholine (ACh) modulates spatial integration in visual cortex by altering the balance of inputs that generate neuronal receptive fields. These cholinergic effects may provide a neurobiological mechanism underlying the modulation of visual representations by visual spatial attention. However, the consequences of cholinergic enhancement on visuospatial perception in humans are unknown. We conducted two experiments to test whether enhancing cholinergic signaling selectively alters perceptual measures of visuospatial interactions in human subjects. In Experiment 1, a double-blind placebo-controlled pharmacology study, we measured how flanking distractors influenced detection of a small contrast decrement of a peripheral target, as a function of target/flanker distance. We found that cholinergic enhancement with the cholinesterase inhibitor donepezil improved target detection, and modeling suggested that this was mainly due to a narrowing of the extent of facilitatory perceptual spatial interactions. In Experiment 2, we tested whether these effects were selective to the cholinergic system or would also be observed following enhancements of related neuromodulators dopamine (DA) or norepinephrine (NE). Unlike cholinergic enhancement, DA (bromocriptine) and NE (guanfacine) manipulations did not improve performance or systematically alter the spatial profile of perceptual interactions between targets and distractors. These findings reveal mechanisms by which cholinergic signaling influences visual spatial interactions in perception and improves processing of a visual target among distractors - effects that are notably similar to those of spatial selective attention.Significance StatementAcetylcholine influences how visual cortical neurons integrate signals across space - perhaps providing a neurobiological mechanism for the effects of visual selective attention. However, the influence of cholinergic enhancement on visuospatial perception remains unknown. Here we demonstrate that cholinergic enhancement improves detection of a target flanked by distractors, consistent with sharpened visuospatial perceptual representations. Furthermore, while most pharmacological studies focus on a single neurotransmitter, many neuromodulators can have related effects on cognition and perception. Thus, we also demonstrate that enhancing noradrenergic and dopaminergic systems does not systematically improve visuospatial perception or alter its tuning. Our results link visuospatial tuning effects of acetylcholine at the neuronal and perceptual levels and provide insights into the connection between cholinergic signaling and visual attention.

Positron Emission Tomography (PET) imaging allows the estimation of multiple aspects of dopamine function including dopamine synthesis capacity, dopamine release, and D2/3 receptor binding. Though dopaminergic dysregulation characterizes a number of neuropsychiatric disorders including schizophrenia and addiction, there has been relatively little investigation into the nature of relationships across dopamine markers within healthy individuals. Here we used PET imaging in 40 healthy adults to compare, within individuals, estimates of dopamine synthesis capacity (Ki) using 6-[(18)F]fluoro-l-m-tyrosine ([(18)F]FMT; a substrate for aromatic amino acid decarboxylase), baseline D2/3 receptor binding potential using [(11)C]raclopride (a weak competitive D2/3 receptor antagonist), and dopamine release using [(11)C]raclopride paired with oral methylphenidate administration. Methylphenidate increases synaptic dopamine by blocking the dopamine transporter. We estimated dopamine release by contrasting baseline D2/3 receptor binding and D2/3 receptor binding following methylphenidate. Analysis of relationships among the three measurements within striatal regions of interest revealed a positive correlation between [(18)F]FMT Ki and the baseline (placebo) [(11)C]raclopride measure, such that participants with greater synthesis capacity showed higher D2/3 receptor binding potential. In contrast, there was no relationship between [(18)F]FMT and methylphenidate-induced [(11)C]raclopride displacement. These findings shed light on the nature of regulation between pre- and postsynaptic dopamine function in healthy adults, which may serve as a template from which to identify and describe alteration with disease.Neuropsychopharmacology accepted article preview online, 17 August 2017. doi:10.1038/npp.2017.180.

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex, as well as maintain the modular structure of cortical functional networks.SIGNIFICANCE STATEMENTThe thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions displays network properties capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks.

Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults (N = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, especially in low-performing individuals, global network properties can capture individual differences in neuroplasticity.

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic "activity-silent" synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior.

A critical feature of the human brain that gives rise to complex cognition is its ability to reconfigure its network structure dynamically and adaptively in response to the environment. Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during the performance of a variety of cognitive tasks, there are meaningful differences as well. In this study, we related intrinsic, resting state network organization to reconfigured network organization during the performance of two tasks: a sequence tapping task, which is thought to probe motor execution and likely engages a single brain network, and an n-back task, which is thought to probe working memory and likely requires coordination across multiple networks. We implemented graph theoretical analyses using functional connectivity data from fMRI scans to calculate whole-brain measures of network organization in healthy young adults. We focused on quantifying measures of network segregation (modularity, system segregation, local efficiency, number of provincial hub nodes) and measures of network integration (global efficiency, number of connector hub nodes). Using these measures, we found converging evidence that local, within-network communication is critical for motor execution, whereas integrative, between-network communication is critical for working memory. These results confirm that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition.

Although recent research has shown that the frontal cortex has a critical role in perceptual decision making, an overarching theory of frontal functional organization for perception has yet to emerge. Perceptual decision making is temporally organized such that it requires the processes of selection, criterion setting, and evaluation. We hypothesized that exploring this temporal structure would reveal a large-scale frontal organization for perception. A causal intervention with transcranial magnetic stimulation revealed clear specialization along the rostrocaudal axis such that the control of successive stages of perceptual decision making was selectively affected by perturbation of successively rostral areas. Simulations with a dynamic model of decision making suggested distinct computational contributions of each region. Finally, the emergent frontal gradient was further corroborated by functional MRI. These causal results provide an organizational principle for the role of frontal cortex in the control of perceptual decision making and suggest specific mechanistic contributions for its different subregions.

Many decisions involve a trade-off between the temporal proximity of a reward and its magnitude. A range of clinical conditions are associated with poor self-control during such intertemporal choices, such that smaller rewards that are received sooner are preferred over larger rewards that are received later to a greater extent [1, 2]. According to a prominent neural model of self-control [3-6], subjective reward values are represented in the medial orbitofrontal cortex (mOFC) at the time of choice [7-9]. Successful self-control in this model is then thought to depend on a modulation of these mOFC value representations via the lateral prefrontal cortex (lPFC) [3, 6]. Here we directly tested three key predictions of this model in patients with lesions to the mOFC (n = 9) and matched controls (n = 19). First, we show that mOFC lesions disrupt choice-free valuation ratings. This finding provides causal evidence for a role of the mOFC in reward valuation and contrasts with the effects of lPFC disruption [6]. Second, we show that mOFC damage indeed decreases self-control during intertemporal choice, replicating previous findings [10]. Third, extending these previous observations, we show that the effect of mOFC damage on intertemporal choice depends on the actual self-control demands of the task. Our findings thus provide causal evidence for a role of mOFC in reward valuation and are compatible with the idea that mOFC damage affects self-control specifically under conditions that might normally require a modulation of mOFC value representations, e.g., by the lPFC.

Aging is accompanied by declines in executive control abilities and changes in underlying brain network architecture. Here, we examined brain networks in young and older adults during a task-free resting state and an N-back task and investigated age-related changes in the modular network organization of the brain. Compared with young adults, older adults showed larger changes in network organization between resting state and task. Although young adults exhibited increased connectivity between lateral frontal regions and other network modules during the most difficult task condition, older adults also exhibited this pattern of increased connectivity during less-demanding task conditions. Moreover, the increase in between-module connectivity in older adults was related to faster task performance and greater fractional anisotropy of the superior longitudinal fasciculus. These results demonstrate that older adults who exhibit more pronounced network changes between a resting state and task have better executive control performance and greater structural connectivity of a core frontal-posterior white matter pathway.

Insidious declines in normal aging are well-established. Emerging evidence suggests that non-pharmacological interventions, specifically cognitive and physical training, may counter diminishing age-related cognitive and brain functions. This randomized trial compared effects of two training protocols: cognitive training (CT) vs. physical training (PT) on cognition and brain function in adults 56-75 years. Sedentary participants (N = 36) were randomized to either CT or PT group for 3 h/week over 12 weeks. They were assessed at baseline-, mid-, and post-training using neurocognitive, MRI, and physiological measures. The CT group improved on executive function whereas PT group's memory was enhanced. Uniquely deploying cerebral blood flow (CBF) and cerebral vascular reactivity (CVR) MRI, the CT cohort showed increased CBF within the prefrontal and middle/posterior cingulate cortex (PCC) without change to CVR compared to PT group. Improvements in complex abstraction were positively associated with increased resting CBF in dorsal anterior cingulate cortex (dACC). Exercisers with higher CBF in hippocampi bilaterally showed better immediate memory. The preliminary evidence indicates that increased cognitive and physical activity improves brain health in distinct ways. Reasoning training enhanced frontal networks shown to be integral to top-down cognitive control and brain resilience. Evidence of increased resting CBF without changes to CVR implicates increased neural health rather than improved vascular response. Exercise did not improve cerebrovascular response, although CBF increased in hippocampi of those with memory gains. Distinct benefits incentivize testing effectiveness of combined protocols to strengthen brain health.

Higher-level cognition depends on the lateral prefrontal cortex (LPFC), but its functional organization has remained elusive. An influential proposal is that the LPFC is organized hierarchically whereby progressively rostral areas of the LPFC process/represent increasingly abstract information facilitating efficient and flexible cognition. However, support for this theory has been limited. Here, human fMRI data revealed rostral/caudal gradients of abstraction in the LPFC. Dynamic causal modeling revealed asymmetrical LPFC interactions indicative of hierarchical processing. Contrary to dominant assumptions, the relative strength of efferent versus afferent connections positioned mid LPFC as the apex of the hierarchy. Furthermore, cognitive demands induced connectivity modulations towards mid LPFC consistent with a role in integrating information for control operations. Moreover, the strengths of these dynamics were related to trait-measured higher-level cognitive ability. Collectively, these results suggest that the LPFC is hierarchically organized with the mid LPFC positioned to synthesize abstract and concrete information to control behavior.

Cognitive training interventions are a promising approach to mitigate cognitive deficits common in aging and, ultimately, to improve functioning in older adults. Baseline neural factors, such as properties of brain networks, may predict training outcomes and can be used to improve the effectiveness of interventions. Here, we investigated the relationship between baseline brain network modularity, a measure of the segregation of brain sub-networks, and training-related gains in cognition in older adults. We found that older adults with more segregated brain sub-networks (i.e., more modular networks) at baseline exhibited greater training improvements in the ability to synthesize complex information. Further, the relationship between modularity and training-related gains was more pronounced in sub-networks mediating "associative" functions compared with those involved in sensory-motor processing. These results suggest that assessments of brain networks can be used as a biomarker to guide the implementation of cognitive interventions and improve outcomes across individuals. More broadly, these findings also suggest that properties of brain networks may capture individual differences in learning and neuroplasticity. Trail Registration: ClinicalTrials.gov, NCT#00977418.

People live in a continuous environment in which the visual scene changes on a slow timescale. It has been shown that to exploit such environmental stability, the brain creates a continuity field in which objects seen seconds ago influence the perception of current objects. What is unknown is whether a similar mechanism exists at the level of metacognitive representations. In three experiments, we demonstrated a robust intertask confidence leak-that is, confidence in one's response on a given task or trial influencing confidence on the following task or trial. This confidence leak could not be explained by response priming or attentional fluctuations. Better ability to modulate confidence leak predicted higher capacity for metacognition as well as greater gray matter volume in the prefrontal cortex. A model based on normative principles from Bayesian inference explained the results by postulating that observers subjectively estimate the perceptual signal strength in a stable environment. These results point to the existence of a novel metacognitive mechanism mediated by regions in the prefrontal cortex.

Treating patient populations with significant psychiatric and neurocognitive symptomatology can present a unique clinical dilemma: progress in psychotherapy can be significantly fettered by cognitive deficits, whereas neurocognitive rehabilitation efforts can be ineffective because of psychiatric overlay. Application of mindfulness-based interventions to address either cognitive or psychiatric symptoms in isolation appears efficacious in many contexts; however, it remains unclear whether this type of intervention might help address simultaneous neurocognitive and psychiatric symptomatology. In a pre-post mixed methods design pilot study, nine Veterans with post-traumatic stress disorder (PTSD) and a history of mild traumatic brain injury with chronic cognitive complaints participated in Mindfulness-Based Stress Reduction (MBSR). Clinical interview, questionnaires, and attention and PTSD measures were administered immediately before, immediately after, and 3 months after MBSR completion. Qualitative and quantitative findings suggest high levels of safety, feasibility, and acceptability. Measurement of attention revealed significant improvement immediately following MBSR (p < 0.05, d = 0.57) and largely sustained improvement 3 months after completion of MBSR (p < 0.10, d = 0.48). Significant reduction in PTSD symptoms was found immediately after MBSR (p < 0.05, d = -1.56), and was sustained 3 months following MBSR completion (p < 0.05, d = -0.93). These results warrant a randomized controlled trial follow-up. Potential mechanisms for the broad effects observed will be explored.

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules' processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author-topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network's modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules' functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain's modular yet integrated implementation of cognitive functions.

The role of dopamine is extensively documented in weight regulation and food intake in both animal models and humans. Yet the role of dopamine has not been well studied in individual differences for food desirability. Genotype status of the dopamine-related catechol-O-methyltransferase (COMT) gene has been shown to influence dopamine levels, with greater COMT enzymatic activity in val/val individuals corresponding to greater degradation of dopamine. Decreased dopamine has been associated with poorer cognitive control and diminished goal-directed behavior in various behavioral paradigms. Additionally, dopaminergic-rich regions such as the frontal cortex and dorsal striatum have been shown to be important for supporting food-related decision-making. However, the role of dopamine, as assessed by COMT genotype status, in food desirability has not been fully explored. Therefore, we utilized an individual's COMT genotype status (n=61) and investigated food desirability based on self-rated "healthy" and "unhealthy" food perceptions. Here we found val/val individuals (n=19) have greater desirability for self-rated "unhealthy" food items, but not self-rated "healthy" food items, as compared to val/met (n=24) and met/met (n=18) individuals (p<0.005). Utilizing an objective health measure for the food items, we also found val/val and val/met individuals have greater desirability for objectively defined "unhealthy" food items, as compared to met/met individuals (p<0.01). This work further substantiates a role of dopamine in food-related behaviors and more specifically in relationship to food desirability for "unhealthy" food items.

We tested the value of measuring modularity, a graph theory metric indexing the relative extent of integration and segregation of distributed functional brain networks, for predicting individual differences in response to cognitive training in patients with brain injury.

Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22-40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.

Humans have a capacity for hierarchical cognitive control-the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4-8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80-150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.

To evaluate the evidence basis of single-domain cognitive tests frequently used by behavioral neurologists in an effort to improve the quality of clinical cognitive assessment.

The frontal cortex mediates cognitive control and motivation to shape human behavior. It is generally observed that medial frontal areas are involved in motivational aspects of behavior, whereas lateral frontal regions are involved in cognitive control. Recent models of cognitive control suggest a rostro-caudal gradient in lateral frontal regions, such that progressively more rostral (anterior) regions process more complex aspects of cognitive control. How motivation influences such a control hierarchy is still under debate. Although some researchers argue that both systems work in parallel, others argue in favor of an interaction between motivation and cognitive control. In the latter case it is yet unclear how motivation would affect the different levels of the control hierarchy. This was investigated in the present functional MRI study applying different levels of cognitive control under different motivational states (low vs high reward anticipation). Three levels of cognitive control were tested by varying rule complexity: stimulus-response mapping (low-level), flexible task updating (mid-level), and sustained cue-task associations (high-level). We found an interaction between levels of cognitive control and motivation in medial and lateral frontal subregions. Specifically, flexible updating (mid-level of control) showed the strongest beneficial effect of reward and only this level exhibited functional coupling between dopamine-rich midbrain regions and the lateral frontal cortex. These findings suggest that motivation differentially affects the levels of a control hierarchy, influencing recruitment of frontal cortical control regions depending on specific task demands.

Converging evidence links individual differences in mesolimbic and mesocortical dopamine (DA) to variation in the tendency to choose immediate rewards ("Now") over larger, delayed rewards ("Later"), or "Now bias". However, to date, no study of healthy young adults has evaluated the relationship between Now bias and DA using positron emission tomography (PET). Sixteen healthy adults (ages 24-34; 50% female) completed a delay-discounting task that quantified aspects of intertemporal reward choice, including Now bias and reward magnitude sensitivity. Participants also underwent PET scanning with 6-[(18)F]-fluoro-L-m-tyrosine (FMT), a radiotracer that measures DA synthesis capacity. Lower putamen FMT signal predicted elevated Now bias, a more rapidly declining discount rate with increasing delay time, and reduced willingness to accept low interest rate delayed rewards. In contrast, lower FMT signal in the midbrain predicted greater sensitivity to increasing magnitude of the Later reward. These data demonstrate that intertemporal reward choice in healthy humans varies with region-specific measures of DA processing, with regionally distinct associations with sensitivity to delay and to reward magnitude.

Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We examined vascular risk factors with respect to a cerebrovascular measure of brain functioning in subjects in mid-life, which could represent a marker of brain changes in later life. Breath-hold functional MRI (fMRI) was performed in 541 women and men (mean age 50.4 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Cerebrovascular reactivity (CVR) was quantified as percentage change in blood-oxygen level dependent (BOLD) signal in activated voxels, which was mapped to a common brain template and log-transformed. Mean CVR was calculated for anatomic regions underlying the default-mode network (DMN) - a network implicated in AD and other brain disorders - in addition to areas considered to be relatively spared in the disease (e.g. occipital lobe), which were utilized as reference regions. Mean CVR was significantly reduced in the posterior cingulate/precuneus (β = -0.063, 95% CI: -0.106, -0.020), anterior cingulate (β = -0.055, 95% CI: -0.101, -0.010), and medial frontal lobe (β = -0.050, 95% CI: -0.092, -0.008) relative to mean CVR in the occipital lobe, after adjustment for age, sex, race, education, and smoking status, in subjects with pre-hypertension/hypertension compared to normotensive subjects. By contrast, mean CVR was lower, but not significantly, in the inferior parietal lobe (β = -0.024, 95% CI: -0.062, 0.014) and the hippocampus (β = -0.006, 95% CI: -0.062, 0.050) relative to mean CVR in the occipital lobe. Similar results were observed in subjects with diabetes and dyslipidemia compared to those without these conditions, though the differences were non-significant. Reduced CVR may represent diminished vascular functionality for the DMN for individuals with prehypertension/ hypertension in mid-life, and may serve as a preclinical marker for brain dysfunction in later life.

The dorsolateral prefrontal cortex (DLPFC) and the frontal eye fields (FEF) have both been implicated in the executive control of saccades, yet possible dissociable roles of each region have not been established. Specifically, both establishing a "task set" as well as suppressing an inappropriate response have been linked to DLPFC and FEF activity, with behavioral outcome measures of these mechanisms mainly being the percentage of pro-saccade errors made on anti-saccade trials. We used continuous theta-burst stimulation (cTBS) to disrupt FEF or DLPFC function in humans during an anti-saccade task to assess the causal role of these regions in these executive control processes, and in programming saccades towards (pro-saccade) or away (anti-saccade) from visual targets. After right FEF cTBS, as compared to control cTBS to the right primary somatosensory cortex (rS1), anti-saccade amplitude of the first saccade decreased and the number of anti-saccades to acquire final position increased; however direction errors to the visual target were not different. In contrast, after left DLPFC cTBS, as compared to left S1 cTBS, subjects displayed greater direction errors for contralateral anti-saccades; however, there were no impairments on the number of saccades or the saccade amplitude. These results are consistent with the notion that DLPFC is necessary for executive control of saccades, whereas FEF is necessary for visuo-motor aspects of anti-saccade programming.

It is proposed that feedback signals from the prefrontal cortex (PFC) to extrastriate cortex are essential for goal-directed processing, maintenance, and selection of information in visual working memory (VWM). In a previous study, we found that disruption of PFC function with transcranial magnetic stimulation (TMS) in healthy individuals impaired behavioral performance on a face/scene matching task and decreased category-specific tuning in extrastriate cortex as measured with functional magnetic resonance imaging (fMRI). In this study, we investigated the effect of disruption of left inferior frontal gyrus (IFG) function on the fidelity of neural representations of two distinct information codes: (1) the stimulus category and (2) the goal-relevance of viewed stimuli. During fMRI scanning, subjects were presented face and scene images in pseudo-random order and instructed to remember either faces or scenes. Within both anatomical and functional regions of interest (ROIs), a multi-voxel pattern classifier was used to quantitatively assess the fidelity of activity patterns representing stimulus category: whether a face or a scene was presented on each trial, and goal relevance, whether the presented image was task relevant (i.e., a face is relevant in a "Remember Faces" block, but irrelevant in a "Remember Scenes" block). We found a reduction in the fidelity of the stimulus category code in visual cortex after left IFG disruption, providing causal evidence that lateral PFC modulates object category codes in visual cortex during VWM. In addition, we found that IFG disruption caused a reduction in the fidelity of the goal relevance code in a distributed set of brain regions. These results suggest that the IFG is involved in determining the task-relevance of visual input and communicating that information to a network of regions involved in further processing during VWM. Finally, we found that participants who exhibited greater fidelity of the goal relevance code in the non-disrupted right IFG after TMS performed the task with the highest accuracy.

To identify early changes in brain structure and function that are associated with cardiovascular risk factors (CVRF).

For more than 50 years, psychologists and neuroscientists have recognized the importance of a working memory to coordinate processing when multiple goals are active and to guide behavior with information that is not present in the immediate environment. In recent years, psychological theory and cognitive neuroscience data have converged on the idea that information is encoded into working memory by allocating attention to internal representations, whether semantic long-term memory (e.g., letters, digits, words), sensory, or motoric. Thus, information-based multivariate analyses of human functional MRI data typically find evidence for the temporary representation of stimuli in regions that also process this information in non-working memory contexts. The prefrontal cortex (PFC), on the other hand, exerts control over behavior by biasing the salience of mnemonic representations and adjudicating among competing, context-dependent rules. The "control of the controller" emerges from a complex interplay between PFC and striatal circuits and ascending dopaminergic neuromodulatory signals. Expected final online publication date for the Annual Review of Psychology Volume 66 is November 30, 2014. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

While many neuroimaging studies have investigated verbal working memory (WM) by manipulating memory load, the subvocal rehearsal rate at these various memory loads has generally been left uncontrolled. Therefore, the goal of this study was to investigate how mnemonic load and the rate of subvocal rehearsal modulate patterns of activity in the core neural circuits underlying verbal working memory. Using fMRI in healthy subjects, we orthogonally manipulated subvocal rehearsal rate and memory load in a verbal WM task with long 45-s delay periods. We found that middle frontal gyrus (MFG) and superior parietal lobule (SPL) exhibited memory load effects primarily early in the delay period and did not exhibit rehearsal rate effects. In contrast, we found that inferior frontal gyrus (IFG), premotor cortex (PM) and Sylvian-parietal-temporal region (area Spt) exhibited approximately linear memory load and rehearsal rate effects, with rehearsal rate effects lasting through the entire delay period. These results indicate that IFG, PM and area Spt comprise the core articulatory rehearsal areas involved in verbal WM, while MFG and SPL are recruited in a general supervisory role once a memory load threshold in the core rehearsal network has been exceeded.

Dopamine has long been implicated in the online maintenance of information across short delays. Specifically, dopamine has been proposed to modulate the strength of working memory representations in the face of intervening distracters. This hypothesis has not been tested in humans. We fill this gap using pharmacological neuroimaging. Healthy young subjects were scanned after intake of the dopamine receptor agonist bromocriptine or placebo (in a within-subject, counterbalanced, and double-blind design). During scanning, subjects performed a delayed match-to-sample task with face stimuli. A face or scene distracter was presented during the delay period (between the cue and the probe). Bromocriptine altered distracter-resistance, such that it impaired performance after face relative to scene distraction. Individual differences in the drug effect on distracter-resistance correlated negatively with drug effects on delay period signal in the prefrontal cortex, as well as on functional connectivity between the prefrontal cortex and the fusiform face area. These results provide evidence for the hypothesis that dopaminergic modulation of the prefrontal cortex alters resistance of working memory representations to distraction. Moreover, we show that the effects of dopamine on the distracter-resistance of these representations are accompanied by modulation of the functional strength of connections between the prefrontal cortex and stimulus-specific posterior cortex.

Appetitive and aversive processes share a number of features such as their relevance for action and learning. On a neural level, reward and its predictors are associated with increased firing of dopaminergic neurons, whereas punishment processing has been linked to the serotonergic system and to decreases in dopamine transmission. Recent data indicate, however, that the dopaminergic system also responds to aversive stimuli and associated actions.

Many individuals with traumatic brain injury (TBI) suffer difficulty regulating fundamental aspects of attention (focus, sustained attention) and may also exhibit hypo- or hyper-states of alertness. Deficits in the state of attention may underlie or exacerbate higher order executive dysfunction. Recent studies indicate that computerized cognitive training targeting attentional control and alertness can ameliorate attention deficits evident in patients with TBI or acquired brain injury. The current study examined whether improvements in attentional state following training can also influence performance on higher-order executive function and mood in individuals with mild TBI (mTBI). The current study examined five patients with executive control deficits as a result of mTBI, with or without persistent anxiety. Three patients engaged in ~5 hours of an executive control training task targeting inhibitory control and sustained attention; two additional patients were re-tested following the same period of time. Performance on standard neuropsychological measures of attention, executive function, and mood were evaluated pre- and post-training. The results indicate that tonic and phasic alertness training may improve higher-order executive function and mood regulation in individuals with TBI.