The D'Esposito Lab is a cognitive neuroscience research laboratory within the
Helen Wills Neuroscience Institute
and the Department of Psychology.

Recent Publications

Riddle, J, Hwang K, Cellier D, Dhanani S, D'Esposito M.  2019.  Causal Evidence for the Role of Neuronal Oscillations in Top-Down and Bottom-Up Attention., 2019 Feb 06. Journal of cognitive neuroscience. :1-12. Abstract

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.

Berry, AS, White RL, Furman DJ, Naskolnakorn JR, Shah VD, D'Esposito M, Jagust WJ.  2019.  Dopaminergic mechanisms underlying normal variation in trait anxiety., 2019 Feb 08. The Journal of neuroscience : the official journal of the Society for Neuroscience. Abstract

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.

Gallen, CL, D'Esposito M.  2019.  Brain Modularity: A Biomarker of Intervention-related Plasticity., 2019 Feb 27. Trends in cognitive sciences. Abstract

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.

Sreenivasan, KK, D'Esposito M.  2019.  The what, where and how of delay activity., 2019 May 13. Nature reviews. Neuroscience. Abstract

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.

Baniqued, PL, Gallen CL, Kranz MB, Kramer AF, D'Esposito M.  2019.  Brain network modularity predicts cognitive training-related gains in young adults., 2019 May 24. Neuropsychologia. Abstract

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.