Our researchers are bringing together the fields of brain research and artificial intelligence/machine learning to figure out how the brain works using mathematical and computational models. When models are combined with data collected from neuroscience experiments, artificial systems can be designed that are capable of performing realistic behaviors using only the machinery the biological nervous system has access to (i.e., neurons and synapses operating at a fast timescale). Building such systems enables researchers to “reverse engineer” them to reveal the operating principles of the real brain. The resulting integrative theories and models have the potential to transform the study of the brain, by making specific, quantifiable predictions that lead to new experiments and drive new hypotheses about how the brain works—in health and disease.

Scientists in this research area include:

• Baihan Lin, PhD
• Erin L. Rich, MD, PhD
• Peter H Rudebeck, PhD
• Ignacio Saez, PhD
• Evan Schaffer, PhD, MA, MPhil

Computational psychiatry is a nascent research area seeking to characterize mental disorders in terms of aberrant computations at multiple scales. Recent progress in human neuroscience has also highlighted the need for computational models that can bridge the explanatory gap between pathophysiology and psychopathology. The computational expertise and tools required to address this gap exist only across disciplines, combining skills and knowledge from investigators and clinicians that are jointly interested in solving problems of mental health.

Leveraging on the rich clinical resources and computational expertise across departments, the Icahn School of Medicine at Mount Sinai’s Center for Computational Psychiatry is dedicated to deepening our understanding of how both algorithms and biology of the brain contribute to dysfunction like addiction, eating disorder, autism, and personality disorders. The Center is especially interested in a transdiagnostic approach towards mental dysfunction; for example, by examining how aberrant social cognition might manifest itself similarly or differently across a range of distinct diagnostic labels. 

Scientists in this research area include:

• Xiaosi Gu, PhD
• Vincenzo Fiore, PhD
• Laura Berner, PhD
• Baihan Lin, PhD
• Angela Radulescu, PhD
• Ignacio Saez, PhD
• Daniela Schiller, PhD
• Brian Sweis, MD, PhD

The Nash Family Center for Advanced Circuit Therapeutics is an interdisciplinary Center that develops and tests new brain-tuning strategies to accelerate the delivery of state-of-the art individualized surgical treatments for patients with advanced neuropsychiatric disorders. Whether it is those where brain stimulation therapies are already clinically available (e.g., deep brain stimulation (DBS) for Parkinson’s disease, epilepsy, obsessive compulsive disorder, etc.) or more experimental DBS applications, including depression, dementia, eating disorders, and addiction.

The Center further catalyzes integrative research activities involving surgical patients using multimodal imaging, invasive and noninvasive electrophysiology, quantitative performance and behavioral metrics (wearable sensors, motion capture, face/speech analyses), and computational models of behavior and disease mechanisms, all supported by a centralized clinical and research bioinformatics infrastructure. The genesis and evaluation of next-generation implantable devices, computation-based algorithms for treatment delivery, and clinical piloting of novel applications complement ongoing personalized, evidence-based, multidisciplinary care.

Scientists in this research area include:

• Alexander Charney, MD, PhD
• Kisueng Choi, PhD
• Martijn Figee, MD, PhD
• Brian Kopell, MD
• Helen Mayberg, MD
• Shannon O’Neill, PhD
• Ignacio Saez, PhD
• Joohi Shahed, MD
• Allison Waters, PhD