Our research investigates the neural bases of high-level cognitive processes such as working memory with the aim to translate this knowledge into clinical therapies to treat cognitive deficits. These aims are achieved through several different experimental approaches and methodologies. First, we employ methods such as functional MRI (fMRI), event-related potential (ERP) recording and transcranial magnetic stimulation (TMS) to identify the neural substrates and temporal dynamics of various cognitive processes in healthy individuals. Our focus has been the cognitive functions supported by the prefrontal cortex (PFC). We also perform studies in patient populations with frontal lobe dysfunction (e.g. stroke, traumatic brain injury, Parkinson's disease) as well with healthy older adults. Second, we study the role of neuromodulators such as dopamine and acetylcholine in working memory and PFC function using pharmacological studies during which drugs are administered to healthy and impaired individuals. Third, based on our basic research we are developing targeted interventions aimed at remediating the cognitive deficits found in neuropathological conditions. Finally, we regularly develop novel analytic methods for analyzing fMRI data in both healthy and abnormal populations.
Working memoryrefers to the temporary maintenance of information that was just experienced or just retrieved from long-term memory but no longer exists in the external environment. These internal representations are short-lived, but can be maintained for longer periods of time through active rehearsal strategies, and can be subjected to various operations that manipulate the information in such a way that makes it useful for goal-directed behavior. Working memoryis a critical contributor to such essential cognitive functions and properties as language comprehension, learning, planning, reasoning, and general fluid intelligence. Likewise, almost any daily activity requires the temporary maintenance of some type of information. For example, our ability to talk on our mobile phone while driving a car requires temporary maintenance of the words in the conversation, the intended direction we are driving towards and the location of cars around us that are not in our view. Additionally, individual differences in working memoryperformance predict a remarkable array of “real world” outcome measures, from reading ability to standardized test performance to income and socioeconomic status to personality traits. Thus, insight into the underlying neural mechanisms of working memoryprovide a foundation for understanding the neural basis of many different aspects of cognition. Such an understanding also provides a foundation for developing targeted interventions for treating the cognitive deficits found in a wide range of developmental, neurological and psychiatric disorders that comprise a significant public health burden.
The neural basis of working memory
A complex cognitive process such as working memory is likely to be mediated by a distributed network of distinct brain regions (D’Esposito, 1996, 1999, 2001, 2002, 2003, 2007). However, initial findings from both animal and human studies identified the prefrontal cortex (PFC) as a critical node in the network supporting working memory. The very first fMRI study performed in my laboratory (D’Esposito et. al, 1995), and one of the first published on this function, established a clear link between PFC function and working memory. This study provided a foundation for research in my lab that was aimed at understanding this brain-behavior relationship by identifying the precise mechanisms in which representations held in working memory are maintained over short periods of time. Studies from awake behaving monkeys using recordings from single neurons within the lateral PFC had consistently found persistent, sustained levels of neuronal firing during the retention interval in tasks that require a monkey to retain information over a brief period of time. This sustained activity was thought to provide a bridge between the stimulus cue (e.g. the location of a flash of light) and its contingent response (e.g. a later delayed saccade to the remembered location). Using fMRI in healthy human volunteers, we were able to demonstrate that persistent PFC activity was also observed during the retention period of delay tasks (Zarahn et. al, 1997, 1998). Subsequently, development of improved fMRI methods (D’Esposito et al, 1999; Postle et. al, 2000) allowed us to further demonstrate that the magnitude of PFC activity during the retention interval correlated positively with working memory accuracy (Curtis et al., 2003; 2004). This relationship suggested that the fidelity of the actively maintained representation is reflected in the delay period activity. Thus, the existence of persistent neural activity during blank memory intervals of delay tasks is a powerful empirical finding that lends strong support for the hypothesis that such activity represents a neural mechanism for the active maintenance or storage of task-relevant representations.
Functional subdivisions of prefrontal cortex
While there was strong support that lateral PFC was critical for working memory maintenance processes, it was unclear whether functional subdivisions within PFC existed. Goldman-Rakic and colleagues put forth a proposal that different PFC regions were critical for the active maintenance of different types of information. Based on monkey electrophysiological and lesion studies, it was proposed that persistent activity within ventrolateral PFC reflected the temporary maintenance of non-spatial codes (such as an object’s color and shape) whereas dorsolateral PFC activity reflected maintenance of spatial codes (such as the location of an object in space). Another possible axis along which human lateral PFC may be organized is according to the type of operations performed upon information being actively maintained, rather than the type of information being maintained. For example, Petrides proposed that ventrolateral PFC is the site where information is initially received from posterior cortical association areas and where active comparisons of maintained information are made. In contrast, dorsolateral PFC is recruited only when monitoring and manipulation of this information is required.
In numerous published studies, we have tested these models of PFC organization (e.g. D’Esposito et al., 1998; 1999, 2000; Rypma et al., 1999; Postle et al., 1999, 2001). Based on this work, we have determined that PFC organization is likely a hybrid of these two models (e.g Postle & D’Esposito, 2000). That is, distinct PFC subregions can support the temporary storage of different types of information as well as implement different types of working memory processes (e.g. maintenance vs. manipulation). We have recently put forth a more evolved formulation of this model that proposes that the rostro-caudal axis of the frontal lobes is characterized by a functional gradient whereby more anterior regions of the frontal lobe engage more complex or abstract control processes and more posterior regions engage in control lower in the action hierarchy and closer to the motor response (Badre & D’Esposito, 2007). Moreover, beyond these regional PFC differences in abstraction, we have further hypothesized that the frontal lobes are organized hierarchically. Within such an architecture, there should be a dominance relationship whereby higher, more anterior regions influence processing in lower, more posterior regions, more than vice versa. We have recently obtained evidence from studying patients with focal frontal lesions that such a hierarchy seems to exist (Badre et al., submitted). That is, we were able to demonstrate that rostral PFC lesions affect lower order processing but disruption of caudal PFC regions does not affect higher order processing. Our model is consistent with known anatomical connecitivity and physiological properties of the PFC as demonstrated by animal studies and provides a foundation for understanding working memory function.
How does the PFC interact with other brain regions to support working memory?
Neuroimaging data often provides information about localization of function where a particular cognitive function, such as a component of working memory, is ascribed to particular brain region. However, the implementation of discrete cognitive functions are almost surely distributed across many nodes in a network. Importantly, fMRI has the unique ability to simultaneously image multiple regions of the brain. Thus, it has the often-touted potential that is just currently being realized to characterize interactions between the nodes in neural networks, such as the network that supports working memory. In my lab, we have developed and validated several multivariate statistical techniques for fMRI data in order to test network hypotheses (e.g. Sun et al., 2005, 2007; Rissman et al., 2004). For example, we have published several studies that explored the functional connectivity between the PFC and other brain regions during working memory (Gazzaley et al., 2004; Fiebach et al., 2006). Consistently, we have found that the PFC interacts with a network of brain regions during the retention interval of a working memory task. These data provide support for the notion that a plausible mechanism for active maintenance is the coupling of abstracted, higher order information in the PFC and stimuli specific sensory information in posterior association cortex through reverberant activity between these areas. In this manner, areas of multimodal association cortex such as PFC and parietal cortex, are in a position to integrate representations through connectivity to unimodal association cortex (e.g. temporal and occipital cortex). Another study revealed the importance of these functional interactions by showing that when an individual is distracted while trying to remember task relevant information, functional connectivity in the working memory network is disrupted (Yoon et al., 2005). In summary, goal-directed behavior, which is both intentional and flexible, requires the temporary maintenance of a broad range of perceptual, mnemonic, and motor representations through coordinated network interactions.
Top-down control: how we remember what is relevant and ignore what is not
As we and others have demonstrated, in addition to recent sensory information, the PFC maintains the highest level of representations such as rules, goals and intentions. Executive control can stem from active maintenance of these PFC representations. Control processes (also called top-down processes) are those that guide behavior based on internal states such as knowledge from previous experience, expectations and goals. Without such control, behavior is guided by bottom-up processes, or those that are determined by the nature of sensory input. Humans with a faulty cognitive control system, such as those with PFC damage are ‘stimulus-driven’, responding in a habitual, almost reflexive manner, to events in their environment. Thus, the PFC may exert “control” in that the information it represents can bias unimodal association cortex in order to keep neural representations of behaviorally relevant sensory information activated when they are no longer present in the external environment (Miller & D'Esposito 2005). Thus, neural activity throughout the brain that is generated by input from the outside world, may be differentially enhanced or suppressed, presumably from top-down signals emanating from integrative brain regions such as PFC, based on the context of the situation. Thus, in this formulation, the “processing” component of working memory is that the “control” of actively maintained representations within primary and unimodal association cortex stems from the representational power of multimodal association cortex such as the PFC. If the PFC, for example, stores the rules and goals, then activation of such PFC representations will be necessary when behavior must be guided by internal states or intentions.
We have directly studied the neural mechanisms underlying top-down modulation by investigating the processes involved when individuals are instructed to remember relevant and ignore irrelevant information (Ranganath et al., 2004; Gazzaley et al. 2005). For example, we have studied healthy young individuals while they performed a delay task during which on each trial they observed sequences of two faces and two natural scenes presented in a randomized order. However, during different time periods they were given different instructions informing them how to process the stimuli: 1) Remember Faces and Ignore Scenes, 2) Remember Scenes and Ignore Faces, or 3) Passively View faces and scenes without attempting to remember them. This task was performed with both fMRI and event related potential (ERP) recording. This allowed us to capitalize on the high spatial resolution of fMRI and the high temporal resolution of ERP. Our fMRI and ERP data revealed top-down modulation of both activity magnitude and processing speed in visual association cortical areas that process faces and scenes. For example, during the encoding period of the delay task, activity in the face area was enhanced, and occurred earlier, when faces had to be remembered as compared to when they were passively viewed. Likewise, face area activity was suppressed, and occurred later, when faces had to be ignored (with scenes now being retained instead across the delay interval) compared to a condition when they were passively viewed. Thus, there appears to be at least two types of top-down signals, one that serves to enhance task-relevant information, and the other that serves to suppress task-irrelevant information. It is well documented that the nervous system utilizes interleaved inhibitory and excitatory mechanisms throughout the neuroaxis (e.g., spinal reflexes, cerebellar outputs and basal ganglia movement control networks). Thus, it may not be surprising that enhancement and suppression mechanisms may exist to control memory function. By generating contrast via both enhancements and suppressions of activity magnitude and processing speed, top-down signals bias the likelihood of successful representation of relevant information in a competitive system.
Though it has been proposed that the PFC provides a major source of the types of top-down signals that we have described, this hypothesis largely originates from suggestive findings rather than direct empirical evidence. For example, our subsequent fMRI studies using network analyses showed that posterior visual areas were more strongly correlated with the PFC during periods of top-down modulation (ref). However, more recently we have obtained direct evidence that the PFC is the site of these top-down signals by using two different approaches. Using fMRI to measure top-down modulation with the task we described above (Gazzaley et al., 2005), we have investigated whether PFC lesions would reduce top-down signals. Thus, we studied healthy individuals after transcranial magnetic stimulation was applied to their PFC causing temporary disrupted function and patients with focal PFC lesions. In both groups, we found that PFC disruption caused a significant decrease in top-down modulation of posterior association cortex (D’Esposito et al., 2006). We are currently performing follow-up investigations of this notable finding that attempt to determine the precise nature of these top-down signals and their effects on memory function.
The relationship between working memory and long-term memory
Until recently, the dominant view in psychology and neuroscience has been that working memory and long-term memory processes are mediated by distinct memory systems. Consequently, researchers have investigated these forms of memory in isolation, focusing on the role of medial temporal regions (MTL) in long-term memory and PFC in working memory. Research from my laboratory has challenged this idea in several ways. First, we have demonstrated that brain regions involved in storing perceptual representations of different object categories (e.g., faces or houses) are active even when people are maintaining a mental image of an object in working memory (Druzgal et al., 2001, 2003, Ranganath et al., 2004). These findings suggest that working memory relies on activation of stored long-term memory representations in posterior cortex, in contrast to the view that these forms of memory are supported by structurally distinct systems. This neural data is consistent with a cognitive model put forth by Cowan that proposes that the contents of working memory are not maintained within dedicated storage buffers, but rather are simply the subset of information that is within the focus of attention at a given time. Thus, working memory arises from hierarchically arranged faculties comprising long-term memory, the subset of working long-term-memory that is currently activated and the subset of activated memory that is the focus of attention. From a neuroscience perspective, it is counterintuitive that all temporarily stored information during goal-directed behavior requires specialized, dedicated buffers. Clearly, there could not be a sufficient number of independent buffers to accommodate the infinite types of information that need to be actively maintained to accommodate all potential or intended actions.
Second, we have shown that MTL regions—traditionally associated exclusively in long-term memory such as the hippocampus—in fact contribute to working memory maintenance (Ranganath & D’Esposito, 2001). This study sparked significant controversy, but the findings were subsequently replicated in at least four other labs. Of course, we are well aware that neuroimaging studies are correlative and cannot demonstrate that the MTL is necessary for any transient form of memory. However, contrary to popular belief, studies of amnesic patients are consistent with the idea that the MTL are necessary for some forms of working memory maintenance. These assertions prompted new research by several labs (e.g. Neal Cohen and colleagues), each of whom have shown that under some circumstances, the MTL may be necessary for normal short-term retention.
Thus, working memory can be considered an emergent property of brain systems that have evolved to accomplish sensory-, representation-, and/or- action-related functions. That is, there are no special-purpose working memory systems or modules. Rather, the sustained retention of information is a general property of the brain issuing from attentional mechanisms that are also important for many non-memory behaviors. This framework has implications that challenge currently prevailing views of working memory at both cognitive/theoretical and neurobiological levels of analysis. For example, at the theoretical level, it challenges the idea that working memory is supported by a neural system that has evolved to perform this special function (in the way that, e.g., the visual system is specialized for visual perception). I have recently presented these theoretical notions at the Royal Society in London (D’Esposito, 2007 ).
Breakdown of working memory function caused by neuropathological processes
In my opinion, a greater understanding of normal memory function will be achieved by a greater understanding of memory dysfunction due to neuropathological conditions. Likewise, identifying the neural mechanisms underlying normal memory function provides a foundation for developing theory-driven approaches towards remediating memory deficits. Thus, based on the research I have described above, my laboratory has spent a considerable amount of effort towards characterizing working memory impairments in various neurological conditions as well as during normal aging. For example, we have documented and characterized the working memory impairments in patients with various conditions such as traumatic brain injury (e.g. McDowell et al., 1997), stroke (e.g D’Esposito et al., 1996), multiple sclerosis (e.g. D’Esposito et al., 1996), Parkinson’s disease (e.g. D’Esposito & Postle, 2000), attention deficit disorder (e.g. Sheridan et al., 2007), addiction (e.g. Mitchell et al., 2005) and normal aging (e.g Rypma et al., 2000; Gazzaley et al., 2007).
Let me provide one example of the specific type of working memory impairment that can be found in individuals with frontal systems dysfunction. In a study of healthy older adults (ages 60-80), we have found a selective age-related neural deficit in the ability to suppress or ignore task-irrelevant information during working memory tasks documented using fMRI (Gazzaley et al., 2005). In other words, on the task we described above in which individuals must remember faces but ignore scenes, older individuals encode scenes into memory despite being instructed not to do so. Furthermore, we observed that those older adults with a greater suppression deficit as documented with fMRI had a more significant working memory deficit. Also, those older adults with more difficulty suppressing or ignoring irrelevant information during the working memory task were more likely to remember this information at a later time (as compared to younger adults) when given a surprise post-experiment memory test. This finding that older adults had increased incidental long-term memory of information they were told to ignore is consistent with the neural data that task-irrelevant representations were not appropriately suppressed.
Thus, this very specific finding that precisely characterizes both the behavioral deficit and its neural underpinning provides a foundation for developing cognitive interventions for remediating memory deficits (described in next section). We have also found a very similar deficit to this (although different in degree) in patients with more severe frontal systems dysfunction such as those with traumatic brain injury or stroke. Thus, our approach has been to identify a brain system impairment that may be affected by many disorders. This is not a traditional approach in the development of medical treatments since most focus on developing treatments that are specific to the particular disease. However, it is an approach that I strongly believe will have a greater impact on helping a wider range of neuropathological conditions that affect memory function. In this way, all memory disorders and conditions that exhibit frontal systems dysfunction (regardless of underlying neuropathological causes) could potentially respond to a targeted frontal systems intervention. Of course, this type of intervention can also be coupled with disease-oriented therapies aimed at specific neuropathological processes (e.g. anti-amyloid agents for Alzheimer’s disease).
Cognitive interventions to improve memory function
Unfortunately, there is currently no effective cognitive therapy for treating patients with memory deficits secondary to frontal systems dysfunction (Gazzaley & D’Esposito, 2005). In my opinion, rehabilitation of working memory dysfunction through cognitive training may be considered a process of guiding mechanisms of plasticity for the ‘re-integration’ of functional PFC networks (Ances & D’Esposito, 2000; Chen et al., 2006; D’Esposito et al., 2006). That is, mechanisms of plasticity following any neuropathological process include the possibilities of re-organization of available network components, or the generation of new network components. Mechanisms of plasticity at the cellular level that may support re-organization or regeneration include alterations in metabolism, synaptogenesis and synaptic pruning, including growth of new long-distance projections, and perhaps neurogenesis. Ultimately, for these neuronal changes to affect neurological function, they must be translated into changes in the functioning of networks of neurons. It is suggested that effective training guides these neuronal changes to achieve functionally integrated networks and coherent behavioral output.
When brain injury (or normal aging) affects the networks involving memory function, cognitive rehabilitation treatments may guide the cellular mechanisms discussed above to enhance the functional re-integration of networks. At least two different levels of change may support re-integration of network function. First, integration of residual intact PFC regions with relevant posterior regions may be supported by synaptic re-organization and synaptogenesis. Second, with respect to functional recovery, it is possible that there is some redundancy in PFC circuitry, such that residual intact areas may be able to re-organize to take over function previously supported through other regions. Cognitive training would, in essence, help in making damaged, poorly integrated collections of neurons into more efficient, better integrated functional networks for the performance of relevant tasks.
Recently, we are developing several types of cognitive interventions, one type I will describe briefly, calledgoal management training(D’Esposito et al., 2006). This training approach focuses on improving PFC function in the context of achieving particular goals. The content of the goals, and thus the content of the tasks, can be individualized to each patient. Neural sub-processes involved in goal management may be trained regardless of the specific content. For example, patients are asked to go through five main steps. First, patients are asked to stop, and explicitly outline the goals of their actions. Patients are guided in generating personally-relevant goals, which may include achieving everyday tasks such as planning a meal or making a doctor’s appointment. Subsequent management of goal-generated tasks would require steps that would further engage PFC networks. These steps include generation of sub-goals and listing of associated tasks; learning and recalling goals and sub-goals; and executing the goal-oriented tasks. These steps may require processes including sustaining attention, holding information in working memory, and self-evaluation of performance through comparing the intended outcomes with actual outcomes.
Over the past year, our neurorehabilitation team has been enrolling patients with traumatic brain injury and healthy older adults in our cognitive intervention programs to treat cognitive and memory deficits attributable to frontal systems dysfunction. Additionally, we have partnered with the Center for Brain Health the University of Texas to increased our enrollment in this program. This 5-week cognitive training program consists of 20 hours of group training (2 hr sessions, 2 days per week), 3 hours of individual training (1.5 hours at the beginning, 1.5 hours halfway through training), and approximately 20 hours of home practice (approximately 1 hr per day). In addition, we obtain cognitive testing and fMRI scans before training, immediately after, and 6 months after training. Thus far, the results of our interventions have been extremely promising. On neuropsychological assessments, all patients and older adults have significantly improved on various measures of attention, working memory and executive function. Our traumatic brain injury patients have reported improvement in their ability to perform tasks in daily life and, in particular, reduced distractibility. Moreover, using our fMRI biomarkers of frontal systems function (see below), we have been able to demonstrate alterations in functional brain responses following our cognitive intervention that accompanies these cognitive and functional gains. Our ultimate goal is to refine these interventions and make them widely available to clinicians.
The pharmacology of memory function
Since publishing my very first paper in 1991 when I was a Neurology resident entitled “The Pharmacology of Memory”, I have been motivated to investigate the neurochemical basis of cognitive processes with the ultimate goal of developing pharmacological approaches towards remediating cognitive deficits suffered by patients with neurological or psychiatric disorders as well as healthy adults. I have predominantly studied the dopaminergic system, but more recently my lab has begun complimentary studies of the cholinergic system (e.g. Silver et al., in press).
The function of the cerebral cortex is clearly influenced by the diffuse inputs from brainstem neuromodulatory systems mediated by neurotransmitters such as dopamine and acetylcholine. Yet, little is known about the relationship between neurotransmitter function and cognition. Furthermore, few targeted pharmacological treatments for cognitive deficits are available to clinicians. Thus, in my opinion, a key to understanding the neural basis of memory function and developing effective memory drugs will arise from an understanding of how memory function is modulated by such brainstem projections. Based on the anatomical distribution of brainstem dopaminergic projections, there is a logical basis for proposing a role for dopamine in working memory. The mesocortical and mesolimbic dopaminergic systems project with the highest concentration to the PFC. The link between dopamine, working memory and PFC function has been established in animal studies. First, in monkeys depletion of PFC dopamine or pharmacological blockade of dopamine receptors induces working memory impairments. This impairment is as severe as in monkeys with PFC lesions, and is not observed in monkeys in which other neurotransmitters, such as serotonin or norepinephrine, are depleted. Furthermore, dopaminergic agonists administered to these same monkeys reverses their working memory impairments.
My goal has to build on these animal findings to determine the role of dopamine on working memory function in humans. One approach for assessing dopamine’s influence on cognitive function in humans is by testing Parkinson’s disease patients “on” and “off” their dopaminergic replacement medications. Using this approach, we have repeatedly demonstrated that Parkinson's patients improve on working memory function after taking their dopaminergic medications (e.g D’Esposito & Postle, 2000). Our second approach is to administer dopamine receptor agonists to healthy young volunteers. Two such drugs we have used are bromocriptine (a D-2 agonist) and pergolide (a D-1 and D-2 agonist). In our first studies of each drug, we demonstrated that healthy young human subjects when given bromocriptine (Kimberg et al., 1997), or pergolide (Kimberg and D'Esposito, 2003) perform better on working memory tasks when compared to when they are given a placebo. In these studies, the dopaminergic medication had a very specific effect on working memory since it had no effect on other cognitive abilities.
Interestingly, in these studies we discovered that the effects of dopaminergic agonists on PFC function were not the same for all subjects, but interacted with the subject's working memory capacity. That is, subjects with a lower baseline working memory capacity exhibited cognitive improvement on the drug, while those with higher baseline working memory capacity worsened on the drug. This relationship between working memory capacity and the effects of bromocriptine on working memory performance has been replicated many times since by us and other labs. Moreover, we have recently demonstrated that lower working memory capacity reflects lower dopamine synthesis capacity as measured by PET scanning (Cools et. al., 2008). We have further been able to explain that individual differences in working memory function is accounted for by estrogen levels (in woman) and polymorphism of the COMT (catechol-O-methyltransferase) gene. Further characterizing these individual differences will be critical for developing rational therapies to treat individuals with memory deficits due to dopamine depletion. Our more recent efforts have been to combine administration of dopaminergic agonists with fMRI scanning (e.g Kimberg et al., 2001; 2003, Gibbs et al., 2005; 2006). This method has allowed us to identify the neural mechanisms underlying the drug effects that we have observed. For example, in one recent study (Cools et al., 2007), we found that dopamine modulated striatal activity during the flexible gating of information into working memory whereas dopamine modulated PFC activity during the stable maintenance of working memory representations.
Pharmacological interventions to improve memory function
Based on our findings with dopaminergic agonists in healthy individuals, we have also tested the effects of these drugs in patients with neurological disorders. In one study (McDowell et al., 1998), patients who suffered PFC damage from traumatic brain injury were assessed on and off bromocriptine while performing several clinical experimental measures of PFC function (e.g. Stroop task, the Wisconsin card sorting task, the Trailmaking task, dual-task). Significant improvement in performance of traumatic brain injury patients was observed on bromocriptine, as compared to placebo, on all tasks required significant demands on working memory and executive control processes thought to rely on intact PFC function. In contrast, bromocriptine did not improve performance on other cognitive measures. This finding led neurologists such as myself who treat patients with traumatic brain injury or stroke to integrate dopaminergic interventions into our practice. Our next goal, is to determine if combining dopaminergic agonist therapy with the cognitive interventions described above (e.g. goal management training) is more effective than either therapy given alone. This clinical trial is currently underway in my laboratory.
In another study, we have found that children with attention-deficit disorder (ADD) perform with greater accuracy on working memory tasks while on their stimulant medications, presumably due to dopaminergic stimulation (Sheridan et al., submitted). Using fMRI, we have been able to identify the neural correlates of these behavioral effects. Specifically, similar to our studies of normal aging, ADD subjects generally show a decrease in neural efficiency (i.e. increase PFC activity with poorer performance), which improves on medication. It is our hope that by obtaining neural data combined with pharmacological interventions, we can develop strategies that can help guide the type of pharmacological therapy given to such children.
Development of fMRI biomarkers to assess and guide cognitive and pharmacological interventions
Given that there are many potential neural mechanisms for recovery of function, it is imperative to develop biomarkers that would not only give insight into these mechanisms but could guide cognitive and pharmacological therapy and assess the effectiveness of such treatments. For example, we propose that after effective rehabilitation training aimed at enhancing PFC function (e.g. cognitive or pharmacological), PFC activity should become better integrated, and there should be evidence of increased anterior-posterior functional connectivity. As evidence of improved functional integration, there should be increased task-relevant modulation of posterior brain activity as measured by fMRI. Task-related activity in the PFC may be actually increased with training or drugs, relating to increased strength or capacity to exert modulatory control. Examining plasticity in PFC function at this level of theoretical detail is a new frontier that bridges cognitive neuroscience and clinical rehabilitation. Thus, a major emphasis in my lab currently and in the future will be to develop and validate fMRI biomarkers that can be used to assess and guide cognitive and pharmacological interventions.
Summary and concluding remarks
Elucidation of the cognitive and neural mechanisms underlying human memory function has been an important focus of cognitive neuroscience, neurology and neuropsychology for decades. My approach has been to use a variety of methods to achieve these goals. The perfect method to study brain-behavior relationships in healthy individuals would allow non-invasive simultaneous recording of all neurons in the brain on a millisecond timescale. Obviously, such a method does not exist and therefore we must rely on methods with different strengths and weaknesses. Studies of patients with brain damage and fMRI studies, for example, provide complementary, but different types of information regarding brain-behavior relationships. Clearly, both of these types of studies are necessary to provide an inferentially sound basis for drawing conclusions about the neural basis of cognition.Converging evidence from both types of studies is necessary because of inferential limitations of of each method when performed in isolation.
One conclusion that arises from my research program is that working memory, a faculty that enables temporary storage and manipulation of information in the service of behavioral goals, can be viewed as neither a unitary, nor a dedicated system. Data from numerous neuropsychological and neurophysiological studies in animals and humans demonstrates that a network of brain regions, including the PFC, is critical for the active maintenance of internal representations. Moreover, it appears that the PFC has functional subdivisions that are organized by the abstractness of these representations (e.g. features, rules, goals). The PFC likely exerts “control” in that the information it represents can bias processing occurring in the rest of the brain in order to keep neural representations of behaviorally relevant sensory information activated when they are no longer present in the external environment. Finally, working memory function is not localized to a single brain region but likely an emergent property of the functional interactions between the PFC and other posterior regions. Numerous questions remain regarding the neural basis of this complex cognitive system, but studies such as those performed in my laboratory should continue to provide converging evidence for these questions that will arise in the future.
A wide range of neuropathology such as traumatic brain, stroke and neoplasms can affect PFC function. Moreover, there are many other conditions such as attention-deficit disorder, addiction, schizophrenia and normal aging, where a selective dysfunction of frontal systems has been proposed as a possible etiology of their cognitive deficits. Hopefully, further insight into the neural mechanisms underlying normal frontal lobe function will ultimately help us understand our patients, and lead to effective interventions for their devastating clinical condition by translating what we have learned from healthy volunteers that have participated in our research. Unfortunately, there are few therapeutic options for clinicians who treat these patients, thus, it is vital that we translate basic cognitive neuroscience into clinical applications.