Jana Schaich Borg

Jana Schaich Borg

Associate Research Professor in the Social Science Research Institute

Overview

Dr. Jana Schaich Borg uses neuroscience, computational modeling, and emerging technologies to study how we make social decisions that influence, or that are influenced by, other people.  As a neuroscientist, she employs neuroimaging, ECOG, simultaneous electrophysiological recordings in rats, and 3-D videos to gain insight into how humans and rodents make social decisions.  As a data scientist, she works on interdisciplinary teams to develop new statistical approaches to analyze these high-dimensional multi-modal data in order to uncover principles of how the brain integrates complex social information with internal representations of value to motivate social actions.

Dr. Schaich Borg’s current research projects include developing a Moral Artificial Intelligence, mapping the oscillatory networks that lead rats to help other rats, modeling neuroimaging data to determine the neural mechanisms that underlie psychopath’s predispositions to harm others, and developing “social synchrony” and machine vision algorithms for automated measures of empathy.  Issues related to these research projects have led her become involved in efforts to develop ethical guidelines for AI development and data sharing, as well as passionate about initiatives to use storytelling and data visualization to communicate the impact of complex analytical problems to diverse audiences.

Education & Training

  • Ph.D., Stanford University 2013

  • B.A., Dartmouth College 2002

Selected Grants

Schaich Borg, J. “Of Mice and Men: The Influence of Animal Models of Empathy and Social Decision-Making on Human Models of Morality.” Moral Brains: The Neuroscience of Morality, edited by M. Liao, Oxford University Press, 2016, pp. 246–79.

Schaich Borg, Jana, et al. “Rat intersubjective decisions are encoded by frequency-specific oscillatory contexts..” Brain Behav, vol. 7, no. 6, June 2017. Pubmed, doi:10.1002/brb3.710. Full Text Open Access Copy

Fede, Samantha J., et al. “Distinct neuronal patterns of positive and negative moral processing in psychopathy..” Cognitive, Affective & Behavioral Neuroscience, vol. 16, no. 6, Dec. 2016, pp. 1074–85. Epmc, doi:10.3758/s13415-016-0454-z. Full Text

Fede, Samantha J., et al. “Abnormal fronto-limbic engagement in incarcerated stimulant users during moral processing..” Psychopharmacology, vol. 233, no. 17, Sept. 2016, pp. 3077–87. Epmc, doi:10.1007/s00213-016-4344-4. Full Text

Hashemi, J., et al. “A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study.” Mobihealth 2015  5th Eai International Conference on Wireless Mobile Communication and Healthcare  Transforming Healthcare Through Innovations in Mobile and Wireless Technologies, Dec. 2015. Scopus, doi:10.4108/eai.14-10-2015.2261939. Full Text

Schaich Borg, Jana, et al. “Subcomponents of psychopathy have opposing correlations with punishment judgments..” Journal of Personality and Social Psychology, vol. 105, no. 4, Oct. 2013, pp. 667–87. Epmc, doi:10.1037/a0033485. Full Text

Schaich Borg, Jana, et al. “Neural basis of moral verdict and moral deliberation..” Social Neuroscience, vol. 6, no. 4, Jan. 2011, pp. 398–413. Epmc, doi:10.1080/17470919.2011.559363. Full Text

Rolls, Asya, et al. “Sleep and metabolism: Role of hypothalamic neuronal circuitry.” Best Practice & Research Clinical Endocrinology & Metabolism, vol. 24, no. 5, Elsevier BV, Oct. 2010, pp. 817–28. Crossref, doi:10.1016/j.beem.2010.08.002. Full Text

Cope, Lora M., et al. “Hemispheric Asymmetries during Processing of Immoral Stimuli..” Frontiers in Evolutionary Neuroscience, vol. 2, Jan. 2010. Epmc, doi:10.3389/fnevo.2010.00110. Full Text

Carter, Matthew E., et al. “The brain hypocretins and their receptors: mediators of allostatic arousal.” Current Opinion in Pharmacology, vol. 9, no. 1, Elsevier BV, Feb. 2009, pp. 39–45. Crossref, doi:10.1016/j.coph.2008.12.018. Full Text

Pages

Kramer, M. F., et al. “When Do People Want AI to Make Decisions?.” Aies 2018  Proceedings of the 2018 Aaai/Acm Conference on Ai, Ethics, and Society, 2018, pp. 204–09. Scopus, doi:10.1145/3278721.3278752. Full Text

Conitzer, V., et al. “Moral decision making frameworks for artificial intelligence.” 31st Aaai Conference on Artificial Intelligence, Aaai 2017, 2017, pp. 4831–35.

Carlson, D. E., et al. On the relationship between LFP & spiking data. Vol. 3, pp. 2060–68.

Ulrich, K., et al. Analysis of brain states from multi-region LFP time-series. Vol. 3/January, pp. 2483–91.