Manish Saggar is a Research Associate in Psychiatry department at the Stanford University School of Medicine. He is working with Dr. Allan Reiss in the Center for Interdisciplinary Brain Sciences Research (CIBSR). His research focuses on the intersections of cognitive science, neuroimaging, and computational modeling. The goal of his research is to develop novel experimental designs and computational analyses to better understand typical and atypical brain functioning. He is currently working on several projects including (a) finding the neural correlates of creativity and its enhancement across lifespan; (b) developing multi-person neuroimaging paradigms to assess the neural correlates of social interaction; and (c) constructing methods to characterize and model dynamics of brain’s intrinsic activity. Manish is also part of Stanford’s teaching team, where he is actively involved in teaching design thinking principles and their relation to mental health.

Manish received his Ph.D. in Computer Science from the University of Texas at Austin. As part of his doctoral work, he developed a computational model of brain processes underlying meditation training. He holds a Masters in Computer Science from the University of Texas at Austin and a Bachelors degree in Information Technology from the Indian Institute of Information Technology, Allahabad (India).

Honors & Awards

  • 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)

Education & Certifications

  • 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)


Journal Articles

  • Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training NeuroImage Saggar, M., et al 2015
  • Early signs of anomalous neural functional connectivity in healthy offspring of parents with bipolar disorder BIPOLAR DISORDERS Singh, M. K., Chang, K. D., Kelley, R. G., Saggar, M., Reiss, A. L., Gotlib, I. H. 2014; 16 (7): 678-689

    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 NEUROIMAGE Saggar, M., Shelly, E. W., Lepage, J., Hoeft, F., Reiss, A. L. 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

  • Creativity training enhances goal-directed attention and information processing THINKING SKILLS AND CREATIVITY Bott, N., Quintin, E., Saggar, M., Kienitz, E., Royalty, A., Hong, D. W., Liu, N., Chien, Y., Hawthorne, G., Reiss, A. L. 2014; 13: 120-128
  • Targeted intervention to increase creative capacity and performance: A randomized controlled pilot study THINKING SKILLS AND CREATIVITY Kienitz, E., Quintin, E., Saggar, M., Bott, N. T., Royalty, A., Hong, D. W., Liu, N., Chien, Y., Hawthorne, G., Reiss, A. L. 2014; 13: 57-66
  • Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity FRONTIERS IN HUMAN NEUROSCIENCE Saggar, M., King, B. G., Zanesco, A. P., MacLean, K. A., Aichele, S. R., Jacobs, T. L., Bridwell, D. A., Shaver, P. R., Rosenberg, E. L., Sahdra, B. K., Ferrer, E., Tang, A. C., Mangun, G. R., Wallace, B. A., Miikkulainen, R., Saron, C. D. 2012; 6


    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

  • Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming BRAIN RESEARCH Saggar, M., Miikkulainen, R., Schnyer, D. M. 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 Saggar M., Miikkulainen R., Schnyer D. M. 2008
  • System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks International Joint Conference on Neural Networks Saggar M, Mericli, T., Andoni, S., Miikkulainen, R. 2007: 2239 -2244
  • A computational model of the motivation-learning interface Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN Saggar M., Markman A.B., Maddox W.T., Miikkulainen R. 2007
  • Autonomous Learning of Stable Quadruped Locomotion RoboCup 2006: Robot Soccer World Cup X, Lecture Notes in Computer Science Saggar M, DSilva T, Kohl N, Stone P 2007; 4434/2007: 98-109
  • Optimization of association rule mining using improved genetic algorithms IEEE International Conference on Systems, Man and Cybernetics Saggar M, Agrawal, A.K. , Lad, A. 2004; 4434/2007: 3725 - 3729

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