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Registration
Apr. 15
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Hasan Ayaz, PhD
Hasan Ayaz, PhDApr. 15
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Alana Campbell, PhD
Alana Campbell, PhDApr. 15
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Coffee Break
Apr. 15
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Shaping Children’s Emotional Worlds: New Insights from the COPE Study
Lauren K. White, PhDApr. 15
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Lunch
Apr. 15
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Neural Signatures of Dual-Task Walking Demands in Individuals at Risk of Cognitive Impairment
Pierfilippo de Sanctis, PhDApr. 15
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Poster Session
Apr. 15
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fNIRS Workshop
OptohiveApr. 15
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Registration
Apr. 16
Event ANT Neuromeeting 2026 - Philadelphia
starts on
Apr 15, 2026, 3:30:00 AM
(US/Eastern)
Towards a multimodal platform to understand brain-body interactions underlying effort-based decision-making
4/15/26, 1:35 PM
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4/15/26, 2:10 PM
(US/Eastern)
(35 minutes)
Sankaraleengam Alagapan, PhD
Research Scientist II
at Georgia Institute of Technology
Sankaraleengam Alagapan, PhD
Research Scientist II
at Georgia Institute of Technology
Dr. Sankar Alagapan is a research faculty member in the School of Electrical and Computer Engineering at the Georgia Institute of Technology, where he co-directs the Structured Information for Precision Neuroengineering Lab (SIPLab). His work sits at the cutting edge of neuroscience, machine learning, and neuroengineering, with a particular focus on advancing precision medicine for psychiatric disorders.
Dr. Alagapan’s research investigates the complex brain-body interactions underlying conditions such as depression. By integrating multimodal physiological data acquisition, including neural, autonomic, and systemic signals, the lab develops novel behavioral assays in naturalistic settings. This approach aims to move beyond traditional clinical settings to capture the dynamic reality of mental health in daily life.
His background includes a Ph.D. in Biomedical Engineering from the University of Florida and postdoctoral training at UNC Chapel Hill and Georgia Tech. Dr. Alagapan’s expertise spans the study of neural circuits, deep brain stimulation (DBS), and the application of latent variable models to decode the mechanisms of cognitive and emotional regulation.
Motivational deficits represent a core transdiagnostic challenge across a broad spectrum of neurological and psychiatric conditions, including major depressive disorder, Parkinson’s disease, and schizophrenia. These deficits, manifesting as anhedonia, apathy, and amotivation, severely impair a patient’s capacity to engage in goal-directed behavior, ultimately leading to a profoundly diminished quality of life. Despite their clinical prevalence, the development of targeted therapeutic interventions is hindered by a fragmented understanding of the underlying neural circuit mechanisms.
A primary obstacle in contemporary research is the reliance on traditional effort-based decision-making (EBDM) paradigms. These models often utilize low-stakes laboratory tasks, such as repetitive button-pressing, which fail to capture the complex physiological demands and metabolic costs inherent in daily activities. To address this limitation, we develop novel experimental frameworks that integrate multimodal brain-body measurements with behavioral assays requiring naturalistic effort expenditure. By synchronizing high-resolution brain recordings with physiological indices of exertion, our approach integrates cognitive decision-making and physiological costs of real-world activities.
Our preliminary results from healthy volunteers identify neural signatures within the anterior cingulate cortex (ACC) that track effort perception and substrate utilization. Furthermore, data obtained from clinical subjects undergoing invasive neurophysiological monitoring reveal that neural signatures of decision-making are distinct when tasks involve high physiological demand compared to typical stationary conditions. These findings suggest that the physiological demands play a critical role on the neural processes governing motivation. By characterizing these integrated brain-body interactions, our research aims to provide an ecologically valid foundation for identifying new biomarkers and developing next-generation treatments for motivational dysfunction.