I am a computational neuroscientist and currently focus on understanding brain dynamics at rest as well as during learning. The overarching goal of my research is to develop reliable computational methods that will allow for characterizing and modeling temporal dynamics of brain activity, without averaging data in either space or time. I firmly believe that the spatiotemporal richness in brain activity might hold the key to finding the person- and disorder-centric biomarkers. Funded by a career development award (K99/R00; NIMH) and a young investigator award (NARSAD; Brain & Behavior Foundation), I am currently developing methods to model the temporal dynamics of brain activity in individuals with fragile X syndrome and healthy controls. The application of computational modeling to neuroscience and psychiatry is nascent in its development but holds significant promise to affect public health positively. I have a strong interdisciplinary background in (1) computational sciences, (2) neuroscience as well as (3) psychiatry. Integrating neuroscience, psychiatry, and mathematical modeling represents the new frontier in applications and analysis of large neuroimaging datasets and has the potential to revolutionize our understanding of dynamical brain organization in healthy controls and individuals with psychiatric disorders.
Assistant Professor (Research), Psychiatry and Behavioral Sciences - Center for Interdisciplinary Brain Sciences Research
Member, Wu Tsai Neurosciences Institute
Honors & Awards
Tashia and John Morgridge Endowed Faculty Scholar in Pediatric Translational Medicine, Stanford Maternal & Child Health Research Institute (2020-25)
Travel Fellowship Award, Society of Biological Psychiatry (SOBP) (2020)
International Fellow, Institute for Scientific Interchange Foundation, Italy (2019-2022)
Annual Chairman's Award for Advancing Science, Department of Psychiatry & Behavioral Sciences, Stanford University (2019)
NIH Director's New Innovator Award (DP2), National Institute of Health (2018-2023)
NARSAD Young Investigator Grant, Brain & Behavior Research Foundation (2016-2018)
Innovator Grant, Department of Psychiatry & Behavioral Sciences, Stanford University (2016)
NIH Career Development Award (K99/R00), National Institute of Mental Health (2015-2020)
Child Health Research Institute (CHRI) Postdoctoral Grant, Lucile Packard Foundation for Children’s Health (LPFCH) (2013-2014)
Seed-grant Award, Stanford’s Center for Cognitive and Neurobiological Imaging (CNI). (2012-2013)
Francisco J. Varela Memorial Grant Award, Mind and Life Institute (2006-2011)
Merit Scholarship, Indian Institute of Information Technology, Allahabad (IIIT-A), India (2001-2005)
Boards, Advisory Committees, Professional Organizations
Editorial Board Member, NeuroImage (Elsevier) (2020 - Present)
Mentor, Organization of Human Brain Mapping Online Mentoring Program (2020 - Present)
Editorial Board Member, Scientific Reports (Nature Research Journal) (2017 - Present)
Executive Board Member, Society for the Neuroscience of Creativity (2017 - Present)
Faculty Fellow, Stanford Byers Center for Bio Design, Bio Design (2017)
Postdoctoral Fellowship, Stanford University School of Medicine, Psychiatry (2014)
Doctor of Philosophy, University of Texas at Austin, Computer Science (2011)
Master of Science, University of Texas at Austin, Computer Science (2009)
Bachelors in Technology, Indian Institute of Information Technology, Information Technology (2005)
Manish Saggar. "United States Patent 16/171,255 Systems and Methods for Mapping Neuronal Circuitry and Clinical Applications Thereof", Leland Stanford Junior University, Jan 1, 2019
Brain and Learning Sciences
Current Research and Scholarly Interests
I am a computational neuroscientist and currently focus on understanding brain dynamics at rest as well as during learning. The overarching goal of my research is to develop reliable computational methods that will allow for characterizing and modeling temporal dynamics of brain activity, without averaging data in either space or time. I strongly believe that the spatiotemporal richness in brain activity might hold the key to finding the person- and disorder-centric biomarkers. Funded by a career development award (K99/R00; NIMH) and a young investigator award (NARSAD; Brain & Behavior Foundation), I am currently developing methods to model the temporal dynamics of brain activity in individuals with fragile X syndrome and healthy controls. The application of computational modeling to neuroscience and psychiatry is nascent in its development but holds significant promise to positively affect public health. I have a strong interdisciplinary background in (1) computational sciences, (2) neuroscience as well as (3) psychiatry. Integrating neuroscience, psychiatry, and mathematical modeling represents the new frontier in applications and analysis of large neuroimaging datasets and has the potential to revolutionize our understanding of dynamical brain organization in healthy controls and in individuals with psychiatric disorders.
- Methodology of Research in Behavioral Sciences
PSYC 250 (Win)
- Independent Studies (4)
- Prior Year Courses
- Creativity and the Brain: An Editorial Introduction to the Special Issue on the Neuroscience of Creativity. NeuroImage 2021: 117836
Thalamocortical connectivity is associated with autism symptoms in high-functioning adults with autism and typically developing adults.
2021; 11 (1): 93
Alterations in sensorimotor functions are common in individuals with autism spectrum disorder (ASD). Such aberrations suggest the involvement of the thalamus due to its key role in modulating sensorimotor signaling in the cortex. Although previous research has linked atypical thalamocortical connectivity with ASD, investigations of this association in high-functioning adults with autism spectrum disorder (HFASD) are lacking. Here, for the first time, we investigated the resting-state functional connectivity of the thalamus, medial prefrontal, posterior cingulate, and left dorsolateral prefrontal cortices and its association with symptom severity in two matched cohorts of HFASD. The principal cohort consisted of 23 HFASD (mean[SD] 27.1[8.9] years, 39.1% female) and 20 age- and sex-matched typically developing controls (25.1[7.2] years, 30.0% female). The secondary cohort was a subset of the ABIDE database consisting of 58 HFASD (25.4[7.8] years, 37.9% female) and 51 typically developing controls (24.4[6.7] years, 39.2% female). Using seed-based connectivity analysis, between-group differences were revealed as hyperconnectivity in HFASD in the principal cohort between the right thalamus and bilateral precentral/postcentral gyri and between the right thalamus and the right superior parietal lobule. The former was associated with autism-spectrum quotient in a sex-specific manner, and was further validated in the secondary ABIDE cohort. Altogether, we present converging evidence for thalamocortical hyperconnectivity in HFASD that is associated with symptom severity. Our results fill an important knowledge gap regarding atypical thalamocortical connectivity in HFASD, previously only reported in younger cohorts.
View details for DOI 10.1038/s41398-021-01221-0
View details for PubMedID 33536431
Simplicial and topological descriptions of human brain dynamics.
Network neuroscience (Cambridge, Mass.)
2021; 5 (2): 549-568
While brain imaging tools like functional magnetic resonance imaging (fMRI) afford measurements of whole-brain activity, it remains unclear how best to interpret patterns found amid the data's apparent self-organization. To clarify how patterns of brain activity support brain function, one might identify metric spaces that optimally distinguish brain states across experimentally defined conditions. Therefore, the present study considers the relative capacities of several metric spaces to disambiguate experimentally defined brain states. One fundamental metric space interprets fMRI data topographically, that is, as the vector of amplitudes of a multivariate signal, changing with time. Another perspective compares the brain's functional connectivity, that is, the similarity matrix computed between signals from different brain regions. More recently, metric spaces that consider the data's topology have become available. Such methods treat data as a sample drawn from an abstract geometric object. To recover the structure of that object, topological data analysis detects features that are invariant under continuous deformations (such as coordinate rotation and nodal misalignment). Moreover, the methods explicitly consider features that persist across multiple geometric scales. While, certainly, there are strengths and weaknesses of each brain dynamics metric space, wefind that those that track topological features optimally distinguish experimentally defined brain states.
View details for DOI 10.1162/netn_a_00190
View details for PubMedID 34189377
Activation Mutation in the Ras/MAPK Pathway Alters the Functional Resting-State Architecture Underlining Executive Function and Attention
SPRINGERNATURE. 2020: 177–78
View details for Web of Science ID 000596371000337
Sex Differences in Resting-State Functional Connectivity in High-Functioning Adults With Autism
SPRINGERNATURE. 2020: 297–98
View details for Web of Science ID 000596371000549
Finding the neural correlates of collaboration using a three-person fMRI hyperscanning paradigm.
Proceedings of the National Academy of Sciences of the United States of America
Humans have an extraordinary ability to interact and cooperate with others. Despite the social and evolutionary significance of collaboration, research on finding its neural correlates has been limited partly due to restrictions on the simultaneous neuroimaging of more than one participant (also known as hyperscanning). Several studies have used dyadic fMRI hyperscanning to examine the interaction between two participants. However, to our knowledge, no study to date has aimed at revealing the neural correlates of social interactions using a three-person (or triadic) fMRI hyperscanning paradigm. Here, we simultaneously measured the blood-oxygenation level-dependent signal from 12 triads (n = 36 participants), while they engaged in a collaborative drawing task based on the social game of Pictionary General linear model analysis revealed increased activation in the brain regions previously linked with the theory of mind during the collaborative phase compared to the independent phase of the task. Furthermore, using intersubject correlation analysis, we revealed increased synchronization of the right temporo-parietal junction (R TPJ) during the collaborative phase. The increased synchrony in the R TPJ was observed to be positively associated with the overall team performance on the task. In sum, our paradigm revealed a vital role of the R TPJ among other theory-of-mind regions during a triadic collaborative drawing task.
View details for DOI 10.1073/pnas.1917407117
View details for PubMedID 32843342
Thalamic and prefrontal GABA concentrations but not GABAA receptor densities are altered in high-functioning adults with autism spectrum disorder.
The gamma aminobutyric acid (GABA) neurotransmission system has been implicated in autism spectrum disorder (ASD). Molecular neuroimaging studies incorporating simultaneous acquisitions of GABA concentrations and GABAA receptor densities can identify objective molecular markers in ASD. We measured both total GABAA receptor densities by using [18F]flumazenil positron emission tomography ([18F]FMZ-PET) and GABA concentrations by using proton magnetic resonance spectroscopy (1H-MRS) in 28 adults with ASD and 29 age-matched typically developing (TD) individuals. Focusing on the bilateral thalami and the left dorsolateral prefrontal cortex (DLPFC) as our regions of interest, we found no differences in GABAA receptor densities between ASD and TD groups. However, 1H-MRS measurements revealed significantly higher GABA/Water (GABA normalized by water signal) in the left DLPFC of individuals with ASD than that of TD controls. Furthermore, a significant gender effect was observed in the thalami, with higher GABA/Water in males than in females. Hypothesizing that thalamic GABA correlates with ASD symptom severity in gender-specific ways, we stratified by diagnosis and investigated the interaction between gender and thalamic GABA/Water in predicting Autism-Spectrum Quotient (AQ) and Ritvo Autism Asperger's Diagnostic Scale-Revised (RAADS-R) total scores. We found that gender is a significant effect modifier of thalamic GABA/Water's relationship with AQ and RAADS-R scores for individuals with ASD, but not for TD controls. When we separated the ASD participants by gender, a negative correlation between thalamic GABA/Water and AQ was observed in male ASD participants. Remarkably, in female ASD participants, a positive correlation between thalamic GABA/Water and AQ was found.
View details for DOI 10.1038/s41380-020-0756-y
View details for PubMedID 32376999
Pushing the boundaries of psychiatric neuroimaging to ground diagnosis in biology.
To accurately detect, track progression of, and develop novel treatments for mental illnesses, a diagnostic framework is needed that is grounded in biological features. Here we present the case for utilizing personalized neuroimaging, computational modeling, standardized computing, and ecologically valid neuroimaging to anchor psychiatric nosology in biology.Significance Statement There is a growing recognition that the boundaries of human neuroimaging data acquisition and analysis must be pushed to ground psychiatric diagnosis in biology. For successful clinical translations, we outline several proposals across the four identified domains of human neuroimaging, namely, (a) reliability of findings; (b) effective clinical translation at the individual subject level; (c) capturing mechanistic insights; and (d) enhancing ecological validity of lab findings. Advances across these domains will be necessary for further progress in psychiatric neuroimaging.
View details for DOI 10.1523/ENEURO.0384-19.2019
View details for PubMedID 31685674
- Large expert-curated database for benchmarking document similarity detection in biomedical literature search DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2019
- Creativity slumps and bumps: Examining the neurobehavioral basis of creativity development during middle childhood NEUROIMAGE 2019; 196: 94–101
- Implementing Evolutionary Optimization to Model Neural Functional Connectivity ASSOC COMPUTING MACHINERY. 2019: 1731–33
- Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis NETWORK NEUROSCIENCE 2019; 3 (3): 763–78
Towards a new approach to reveal dynamical organization of the brain using topological data analysis
2018; 9: 1399
Little is known about how our brains dynamically adapt for efficient functioning. Most previous work has focused on analyzing changes in co-fluctuations between a set of brain regions over several temporal segments of the data. We argue that by collapsing data in space or time, we stand to lose useful information about the brain's dynamical organization. Here we use Topological Data Analysis to reveal the overall organization of whole-brain activity maps at a single-participant level-as an interactive representation-without arbitrarily collapsing data in space or time. Using existing multitask fMRI datasets, with the known ground truth about the timing of transitions from one task-block to next, our approach tracks both within- and between-task transitions at a much faster time scale (~4-9 s) than before. The individual differences in the revealed dynamical organization predict task performance. In summary, our approach distills complex brain dynamics into interactive and behaviorally relevant representations.
View details for PubMedID 29643350
- Creativity in the Twenty-first Century: The Added Benefit of Training and Cooperation DESIGN THINKING RESEARCH: MAKING DISTINCTIONS: COLLABORATION VERSUS COOPERATION 2018: 239–49
Altered Brain Network Segregation in Fragile X Syndrome Revealed by Structural Connectomics
2017; 27 (3): 2249-2259
Fragile X syndrome (FXS), the most common inherited cause of intellectual disability and autism spectrum disorder, is associated with significant behavioral, social, and neurocognitive deficits. Understanding structural brain network topology in FXS provides an important link between neurobiological and behavioral/cognitive symptoms of this disorder. We investigated the connectome via whole-brain structural networks created from group-level morphological correlations. Participants included 100 individuals: 50 with FXS and 50 with typical development, age 11-23 years. Results indicated alterations in topological properties of structural brain networks in individuals with FXS. Significantly reduced small-world index indicates a shift in the balance between network segregation and integration and significantly reduced clustering coefficient suggests that reduced local segregation shifted this balance. Caudate and amygdala were less interactive in the FXS network further highlighting the importance of subcortical region alterations in the neurobiological signature of FXS. Modularity analysis indicates that FXS and typically developing groups' networks decompose into different sets of interconnected sub networks, potentially indicative of aberrant local interconnectivity in individuals with FXS. These findings advance our understanding of the effects of fragile X mental retardation protein on large-scale brain networks and could be used to develop a connectome-level biological signature for FXS.
View details for DOI 10.1093/cercor/bhw055
View details for Web of Science ID 000397636600043
Compensatory Hyperconnectivity in Developing Brains of Young Children With Type 1 Diabetes
2017; 66 (3): 754-762
Sustained dysregulation of blood glucose (hyper or hypoglycemia) associated with type 1 diabetes (T1D) has been linked to cognitive deficits and altered brain anatomy and connectivity. However, a significant gap remains with respect to how T1D affects spontaneous at-rest connectivity in young developing brains. Here, using a large multi-site study, resting state functional Magnetic Resonance Imaging (rsfMRI) data were examined in young children with T1D (N=57, mean age=7.88 years; 27F) as compared to age-matched non-diabetic controls (N=26, mean age=7.43 years; 14F). Using both model-driven seed-based analysis and model-free independent component analysis (ICA) and controlling for age, site and sex, converging results were obtained suggesting increased connectivity in young children with T1D as compared to non-diabetic controls. Further, increased connectivity in children with T1D was observed to be positively associated with cognitive functioning. The observed positive association of connectivity with cognitive functioning in T1D, without overall group differences in cognitive function, suggests a putative compensatory role of hyper-intrinsic connectivity in the brain in children with this condition. Altogether, our study attempts to fill a critical gap in knowledge regarding how dysglycemia in T1D might affect the brain's intrinsic connectivity at very young ages.
View details for DOI 10.2337/db16-0414
View details for Web of Science ID 000394634100020
X-Chromosome Effects on Attention Networks: Insights from Imaging Resting-State Networks in Turner Syndrome.
Cerebral cortex (New York, N.Y. : 1991)
Attention deficit hyperactivity disorder (ADHD) is strongly affected by sex, but sex chromosomes' effect on brain attention networks and cognition are difficult to examine in humans. This is due to significant etiologic heterogeneity among diagnosed individuals. In contrast, individuals with Turner syndrome (TS), who have substantially increased risk for ADHD symptoms, share a common genetic risk factor related to the absence of the X-chromosome, thus serving as a more homogeneous genetic model. Resting-state functional MRI was employed to examine differences in attention networks between girls with TS (n = 40) and age- sex- and Tanner-matched controls (n = 33). We compared groups on resting-state functional connectivity measures from data-driven independent components analysis (ICA) and hypothesis-based seed analysis. Using ICA, reduced connectivity was observed in both frontoparietal and dorsal attention networks. Similarly, using seeds in the bilateral intraparietal sulcus (IPS), reduced connectivity was observed between IPS and frontal and cerebellar regions. Finally, we observed a brain-behavior correlation between IPS-cerebellar connectivity and cognitive attention measures. These findings indicate that X-monosomy contributes affects to attention networks and cognitive dysfunction that might increase risk for ADHD. Our findings not only have clinical relevance for girls with TS, but might also serve as a biological marker in future research examining the effects of the intervention that targets attention skills.
View details for PubMedID 28981595
Changes in Brain Activation Associated with Spontaneous Improvization and Figural Creativity After Design-Thinking-Based Training: A Longitudinal fMRI Study.
Creativity is widely recognized as an essential skill for entrepreneurial success and adaptation to daily-life demands. However, we know little about the neural changes associated with creative capacity enhancement. For the first time, using a prospective, randomized control design, we examined longitudinal changes in brain activity associated with participating in a five-week design-thinking-based Creative Capacity Building Program (CCBP), when compared with Language Capacity Building Program (LCBP). Creativity, an elusive and multifaceted construct, is loosely defined as an ability to produce useful/appropriate and novel outcomes. Here, we focus on one of the facets of creative thinking-spontaneous improvization. Participants were assessed pre- and post-intervention for spontaneous improvization skills using a game-like figural Pictionary-based fMRI task. Whole-brain group-by-time interaction revealed reduced task-related activity in CCBP participants (compared with LCBP participants) after training in the right dorsolateral prefrontal cortex, anterior/paracingulate gyrus, supplementary motor area, and parietal regions. Further, greater cerebellar-cerebral connectivity was observed in CCBP participants at post-intervention when compared with LCBP participants. In sum, our results suggest that improvization-based creative capacity enhancement is associated with reduced engagement of executive functioning regions and increased involvement of spontaneous implicit processing.
View details for PubMedID 27307467
Sex differences in neural and behavioral signatures of cooperation revealed by fNIRS hyperscanning
Researchers from multiple fields have sought to understand how sex moderates human social behavior. While over 50 years of research has revealed differences in cooperation behavior of males and females, the underlying neural correlates of these sex differences have not been explained. A missing and fundamental element of this puzzle is an understanding of how the sex composition of an interacting dyad influences the brain and behavior during cooperation. Using fNIRS-based hyperscanning in 111 same- and mixed-sex dyads, we identified significant behavioral and neural sex-related differences in association with a computer-based cooperation task. Dyads containing at least one male demonstrated significantly higher behavioral performance than female/female dyads. Individual males and females showed significant activation in the right frontopolar and right inferior prefrontal cortices, although this activation was greater in females compared to males. Female/female dyad's exhibited significant inter-brain coherence within the right temporal cortex, while significant coherence in male/male dyads occurred in the right inferior prefrontal cortex. Significant coherence was not observed in mixed-sex dyads. Finally, for same-sex dyads only, task-related inter-brain coherence was positively correlated with cooperation task performance. Our results highlight multiple important and previously undetected influences of sex on concurrent neural and behavioral signatures of cooperation.
View details for DOI 10.1038/srep26492
View details for Web of Science ID 000377330900001
View details for PubMedID 27270754
View details for PubMedCentralID PMC4897646
Surface-based morphometry reveals distinct cortical thickness and surface area profiles in Williams syndrome
AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS
2016; 171 (3): 402-413
Morphometric investigations of brain volumes in Williams syndrome (WS) consistently show significant reductions in gray matter volume compared to controls. Cortical thickness (CT) and surface area (SA) are two constituent parts of cortical gray matter volume that are considered genetically distinguishable features of brain morphology. Yet, little is known about the independent contribution of cortical CT and SA to these volumetric differences in WS. Thus, our objectives were: (i) to evaluate whether the microdeletion in chromosome 7 associated with WS has a distinct effect on CT and SA, and (ii) to evaluate age-related variations in CT and SA within WS. We compared CT and SA values in 44 individuals with WS to 49 age- and sex-matched typically developing controls. Between-group differences in CT and SA were evaluated across two age groups: young (age range 6.6-18.9 years), and adults (age range 20.2-51.5 years). Overall, we found contrasting effects of WS on cortical thickness (increases) and surface area (decreases). With respect to brain topography, the between-group pattern of CT differences showed a scattered pattern while the between-group surface area pattern was widely distributed throughout the brain. In the adult subgroup, we observed a cluster of increases in cortical thickness in WS across the brain that was not observed in the young subgroup. Our findings suggest that extensive early reductions in surface area are the driving force for the overall reduction in brain volume in WS. The age-related cortical thickness findings might reflect delayed or even arrested development of specific brain regions in WS. © 2016 Wiley Periodicals, Inc.
View details for DOI 10.1002/ajmg.b.32422
View details for Web of Science ID 000373029100011
Understanding the influence of personality on dynamic social gesture processing: An fMRI study.
2016; 80: 71-78
This fMRI study aimed at investigating how differences in personality traits affect the processing of dynamic and natural gestures containing social versus nonsocial intent. We predicted that while processing gestures with social intent extraversion would be associated with increased activity within the reticulothalamic-cortical arousal system (RTCS), while neuroticism would be associated with increased activity in emotion processing circuits. The obtained findings partly support our hypotheses. We found a positive correlation between bilateral thalamic activity and extraversion scores while participants viewed social (versus nonsocial) gestures. For neuroticism, the data revealed a more complex activation pattern. Activity in the bilateral frontal operculum and anterior insula, extending into bilateral putamen and right amygdala, was moderated as a function of actor-orientation (i.e., first versus third-person engagement) and face-visibility (actor faces visible versus blurred). Our findings point to the existence of factors other than emotional valence that can influence social gesture processing in particular, and social cognitive affective processing in general, as a function of personality.
View details for DOI 10.1016/j.neuropsychologia.2015.10.039
View details for PubMedID 26541443
View details for PubMedCentralID PMC4698311
Estimating individual contribution from group-based structural correlation networks.
2015; 120: 274-284
Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n=100) consisting of individuals with fragile X syndrome (FXS; n=50) and age-matched typically developing individuals (TD; n=50). We tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders.
View details for DOI 10.1016/j.neuroimage.2015.07.006
View details for PubMedID 26162553
Neural Correlates of Self-Injurious Behavior in Prader-Willi Syndrome
HUMAN BRAIN MAPPING
2015; 36 (10): 4135-4143
Individuals with Prader-Willi syndrome (PWS), a genetic disorder caused by mutations to the q11-13 region on chromosome 15, commonly show severe skin-picking behaviors that can cause open wounds and sores on the body. To our knowledge, however, no studies have examined the potential neural mechanisms underlying these behaviors. Seventeen individuals with PWS, aged 6-25 years, who showed severe skin-picking behaviors, were recruited and scanned on a 3T scanner. We used functional magnetic resonance imaging (fMRI) while episodes of skin picking were recorded on an MRI-safe video camera. Three participants displayed skin picking continuously throughout the scan, three participants did not display skin picking, and the data for one participant evidenced significant B0 inhomogeneity that could not be corrected. The data for the remaining 10 participants (six male, four female) who displayed a sufficient number of picking and nonpicking episodes were subjected to fMRI analysis. Results showed that regions involved in interoceptive, motor, attention, and somatosensory processing were activated during episodes of skin-picking behavior compared with nonpicking episodes. Scores obtained on the Self-Injury Trauma scale were significantly negatively correlated with mean activation within the right insula and left precentral gyrus. These data indicate that itch and pain processes appear to underlie skin-picking behaviors in PWS, suggesting that interoceptive disturbance may contribute to the severity and maintenance of abnormal skin-picking behaviors in PWS. Implications for treatments are discussed. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
View details for DOI 10.1002/hbm.22903
View details for Web of Science ID 000364219100031
View details for PubMedID 26173182
Examining the neural correlates of emergent equivalence relations in fragile X syndrome
2015; 233 (3): 373-379
The neural mechanisms underlying the formation of stimulus equivalence relations are poorly understood, particularly in individuals with specific learning impairments. As part of a larger study, we used functional magnetic resonance imaging (fMRI) while participants with fragile X syndrome (FXS), and age- and IQ-matched controls with intellectual disability, were required to form new equivalence relations in the scanner. Following intensive training on matching fractions to pie charts (A=B relations) and pie charts to decimals (B=C relations) outside the scanner over a 2-day period, participants were tested on the trained (A=B, B=C) relations, as well as emergent symmetry (i.e., B=A and C=B) and transitivity/equivalence (i.e., A=C and C=A) relations inside the scanner. Eight participants with FXS (6 female, 2 male) and 10 controls, aged 10-23 years, were able to obtain at least 66.7% correct on the trained relations in the scanner and were included in the fMRI analyses. Across both groups, results showed that the emergence of symmetry relations was correlated with increased brain activation in the left inferior parietal lobule, left postcentral gyrus, and left insula, broadly supporting previous investigations of stimulus equivalence research in neurotypical populations. On the test of emergent transitivity/equivalence relations, activation was significantly greater in individuals with FXS compared with controls in the right middle temporal gyrus, left superior frontal gyrus and left precuneus. These data indicate that neural execution was significantly different in individuals with FXS than in age- and IQ-matched controls during stimulus equivalence formation. Further research concerning how gene-brain-behavior interactions may influence the emergence of stimulus equivalence in individuals with intellectual disabilities is needed.
View details for DOI 10.1016/j.pscychresns.2015.06.009
View details for Web of Science ID 000360563800010
Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training
2015; 114: 88-104
Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and anatomy into account, to formally model brain processes associated with intensive meditation training. The observed changes in model parameters inform theoretical accounts of attention training through meditation, and may motivate future study on the use of meditation in a variety of clinical populations.
View details for DOI 10.1016/j.neuroimage.2015.03.073
View details for Web of Science ID 000355002900007
View details for PubMedID 25862265
Pictionary-based fMRI paradigm to study the neural correlates of spontaneous improvisation and figural creativity
A novel game-like and creativity-conducive fMRI paradigm is developed to assess the neural correlates of spontaneous improvisation and figural creativity in healthy adults. Participants were engaged in the word-guessing game of Pictionary(TM), using an MR-safe drawing tablet and no explicit instructions to be "creative". Using the primary contrast of drawing a given word versus drawing a control word (zigzag), we observed increased engagement of cerebellum, thalamus, left parietal cortex, right superior frontal, left prefrontal and paracingulate/cingulate regions, such that activation in the cingulate and left prefrontal cortices negatively influenced task performance. Further, using parametric fMRI analysis, increasing subjective difficulty ratings for drawing the word engaged higher activations in the left pre-frontal cortices, whereas higher expert-rated creative content in the drawings was associated with increased engagement of bilateral cerebellum. Altogether, our data suggest that cerebral-cerebellar interaction underlying implicit processing of mental representations has a facilitative effect on spontaneous improvisation and figural creativity.
View details for DOI 10.1038/srep10894
View details for Web of Science ID 000355548100001
View details for PubMedID 26018874
View details for PubMedCentralID PMC4446895
Early signs of anomalous neural functional connectivity in healthy offspring of parents with bipolar disorder
2014; 16 (7): 678-689
Bipolar disorder (BD) has been associated with dysfunctional brain connectivity and with family chaos. It is not known whether aberrant connectivity occurs before illness onset, representing vulnerability for developing BD amidst family chaos. We used resting-state functional magnetic resonance imaging (fMRI) to examine neural network dysfunction in healthy offspring living with parents with BD and healthy comparison youth.Using two complementary methodologies [data-driven independent component analysis (ICA) and hypothesis-driven region-of-interest (ROI)-based intrinsic connectivity], we examined resting-state fMRI data in 8-17-year-old healthy offspring of a parent with BD (n = 24; high risk) and age-matched healthy youth without any personal or family psychopathology (n = 25; low risk).ICA revealed that, relative to low-risk youth, high-risk youth showed increased connectivity in the ventrolateral prefrontal cortex (VLPFC) subregion of the left executive control network (ECN), which includes frontoparietal regions important for emotion regulation. ROI-based analyses revealed that high-risk versus low-risk youth had decreased connectivities between the left amygdala and pregenual cingulate, between the subgenual cingulate and supplementary motor cortex, and between the left VLPFC and left caudate. High-risk youth showed stronger connections in the VLPFC with age and higher functioning, which may be neuroprotective, and weaker connections between the left VLPFC and caudate with more family chaos, suggesting an environmental influence on frontostriatal connectivity.Healthy offspring of parents with BD show atypical patterns of prefrontal and subcortical intrinsic connectivity that may be early markers of resilience to or vulnerability for developing BD. Longitudinal studies are needed to determine whether these patterns predict outcomes.
View details for DOI 10.1111/bdi.12221
View details for Web of Science ID 000344373100002
Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility
2014; 84: 648-656
Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks was found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus was found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) was partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom.
View details for DOI 10.1016/j.neuroimage.2013.09.046
View details for Web of Science ID 000328868600059
View details for PubMedID 24084068
View details for PubMedCentralID PMC3903510
- Creativity training enhances goal-directed attention and information processing THINKING SKILLS AND CREATIVITY 2014; 13: 120-128
- Targeted intervention to increase creative capacity and performance: A randomized controlled pilot study THINKING SKILLS AND CREATIVITY 2014; 13: 57-66
Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity
FRONTIERS IN HUMAN NEUROSCIENCE
The capacity to focus one's attention for an extended period of time can be increased through training in contemplative practices. However, the cognitive processes engaged during meditation that support trait changes in cognition are not well characterized. We conducted a longitudinal wait-list controlled study of intensive meditation training. Retreat participants practiced focused attention (FA) meditation techniques for three months during an initial retreat. Wait-list participants later undertook formally identical training during a second retreat. Dense-array scalp-recorded electroencephalogram (EEG) data were collected during 6 min of mindfulness of breathing meditation at three assessment points during each retreat. Second-order blind source separation, along with a novel semi-automatic artifact removal tool (SMART), was used for data preprocessing. We observed replicable reductions in meditative state-related beta-band power bilaterally over anteriocentral and posterior scalp regions. In addition, individual alpha frequency (IAF) decreased across both retreats and in direct relation to the amount of meditative practice. These findings provide evidence for replicable longitudinal changes in brain oscillatory activity during meditation and increase our understanding of the cortical processes engaged during meditation that may support long-term improvements in cognition.
View details for DOI 10.3389/fnhum.2012.00256
View details for Web of Science ID 000309107100001
View details for PubMedID 22973218
View details for PubMedCentralID PMC3437523
Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming
2010; 1315: 75-91
Repetition priming (RP) is a form of learning, whereby classification or identification performance is improved with item repetition. Various theories have been proposed to understand the basis of RP, including alterations in the representation of an object and associative stimulus-response bindings. There remain several aspects of RP that are still poorly understood, and it is unclear whether previous theories only apply to well-established object representations. This paper integrates behavioral, neuroimaging, and computational modeling experiments in a new RP study using novel objects. Behavioral and neuroimaging results were inconsistent with existing theories of RP, thus a new perceptual memory-based caching mechanism is formalized using computational modeling. The model instantiates a viable neural mechanism that not only accounts for the pattern seen in this experiment but also provides a plausible explanation for previous results that demonstrated residual priming after associative linkages were disrupted. Altogether, the current work helps advance our understanding of how brain utilizes repetition for faster information processing.
View details for DOI 10.1016/j.brainres.2009.11.074
View details for Web of Science ID 000275131300009
View details for PubMedID 20005215
- Memory Processes in Perceptual Decision Making Proceedings of the 30th Annual Conference of the Cognitive Science Society, Nashville, TN 2008
- A computational model of the motivation-learning interface Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN 2007
Autonomous learning of stable quadruped locomotion
ROBOCUP 2006: ROBOT SOCCER WORLD CUP X
2007; 4434: 98-109
View details for Web of Science ID 000250044700009
System identification for the Hodgkin-Huxley model using artificial neural networks
2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6
View details for Web of Science ID 000254291102027
- Optimization of association rule mining using improved genetic algorithms IEEE International Conference on Systems, Man and Cybernetics 2004; 4434/2007: 3725 - 3729