# Uncovering the neural architecture underlying decisions abstracted from movements

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2022 · $410,944

## Abstract

Project Abstract
Decision making is a core component of normal and abnormal cognitive function. Understanding the
neural mechanisms of decision-making will lead to advances in the diagnosis, classification and future
treatments of disorders affecting thought and control. Mathematical models of the decision process,
based on bounded evidence accumulation, have been developed over decades and are being
increasingly leveraged to gain deeper insights into the origins of cognitive deficits arising from a range
of brain disorders. However, major gaps remain in our understanding of the neural mechanisms
responsible for decision-making, thereby limiting the validity and utility of the models. A successful line
of research on perceptual decision-making has established that neurons in the parietal and prefrontal
cortex of the rhesus monkey (Macaca mulatta) encode the accumulating evidence bearing on the
alternatives. These observations are mainly from neurons in areas of the macaque cortex that are
associated with preparation of the actions (e.g. hand or eye movements) for reporting the decision
alternatives. However, decisions are often formed without knowledge of what actions they might call
for, and under such conditions, effector-selective neural activity does not appear to reflect accumulation
dynamics. Recent studies, have identified a novel ‘abstract’ decision signal in non-invasive
electrophysiological (EEG) recordings from human decision makers. The signal, termed the central
parietal positivity (CPP), represents the accumulation of evidence for decisions irrespective of the
sensory or motor requirements of the task, hence the designation, abstract. The neural circuits that
give rise to the CPP are likely to explain the capacity to flexibly link decisions to various actions
depending on context and goals. However, because the signal has thus far only been observed in EEG
recordings from humans, its neural basis is unknown. The proposed aims will (1) establish the neural
underpinnings of the CPP by establishing its analogues in single-neuron, multi-neuron, local field
potentials and EEG of the macaque and (2) localizing its source in humans through the use of
neuroimaging, and electrocorticography (ECoG) from patients undergoing neurosurgery. Both aims
draw on an integrated computational effort that combines biophysical modeling, neural networks, and
mathematical characterization of the decision process. The knowledge gained through these
investigations will increase our understanding of core cognitive capacities whose deficiency contributes
to major brain disorders while bridging long-standing methodological gaps in human versus non-human
animal investigations.

## Key facts

- **NIH application ID:** 10337282
- **Project number:** 5R01MH122513-03
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Stephan Bickel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $410,944
- **Award type:** 5
- **Project period:** 2020-04-13 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10337282

## Citation

> US National Institutes of Health, RePORTER application 10337282, Uncovering the neural architecture underlying decisions abstracted from movements (5R01MH122513-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10337282. Licensed CC0.

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