# Implicit serial learning

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $767,372

## Abstract

Project Summary
Reinforcement learning (RL) is a powerful framework for understanding outcome-driven behavior and its neural
basis. A key issue for RL is how to incorporate an ability to make inferences that allow appropriate responding
to novel conditions not encountered during training. Inference relies on the detection of latent relationships that
predict rewards but are not signaled by explicit cues. In the previous funding period, we developed behavioral
and computational approaches to rigorously address this problem, and made single-cell neurophysiological
observations that began to reveal how the brain represents latent structures. Here, we re-conceptualize this
problem as one of using a cognitive map to represent latent order and support inference. We propose to test
this idea with a newly developed behavioral approach, which allows unprecedented insight into the role of
cortico-striatal neural circuits and ascending neuromodulatory systems in model-based RL. These
investigations will focus on brain regions that neurophysiology, neuroimaging, and lesion studies suggest have
important roles in implicit serial learning, specifically dorsolateral (dlPFC) and ventromedial prefrontal cortex
(vmPFC), and dorsal striatum. Three aims will 1. Test NHPs ability to make model-based inferences in the
presence of countervailing reward incentives, 2. Identify neural circuitry of serial learning in the dlPFC, vmPFC,
and caudate nucleus, and 3. Test if changes in Ach and DA concentrations are correlated with serial learning,
particularly during transfer. Inferential reasoning is impaired in many psychiatric illnesses including
schizophrenia and bipolar disorder. This impairment may underlie thought disorders such as delusions and
paranoia.

## Key facts

- **NIH application ID:** 10850813
- **Project number:** 5R01MH111703-07
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** VINCENT P FERRERA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $767,372
- **Award type:** 5
- **Project period:** 2018-07-05 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10850813

## Citation

> US National Institutes of Health, RePORTER application 10850813, Implicit serial learning (5R01MH111703-07). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10850813. Licensed CC0.

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