# Neural circuit mechanisms of affective probabilistic learning

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $816,865

## Abstract

Project Summary
Pathologically altered affective learning is central to accounts of nearly every psychiatric disorder including
depression and anxiety disorders. In humans, non-human primates, and rodents accurately learning which
stimuli in our environment predict rewards or punishments is dependent on parts of frontal cortex, striatum, and
limbic system, such as amygdala. A considerable amount is known about the neural mechanisms that are
associated with adaptive patterns of learning within the circuits connecting these areas. What happens to these
patterns of neural activity and the specific pathways involved when learning is enhanced or diminished by
psychological processes is much less clear. Obtaining this knowledge is important as it would begin to reveal
the specific mechanisms through which learning can be altered, information that is essential for identifying
biomarkers in and aiding therapies for individuals with pathologically altered learning. Consequently, our aim
here is to begin to establish how bottom-up and top-down processes impact stimulus-reward learning at the level
of single neurons and circuit-level interactions. We specifically focus on the ventrolateral prefrontal cortex (PFC)
and amygdala as prior work in macaque monkeys has shown that these areas, as opposed to other parts of
frontal cortex and striatum, are required for efficient probabilistic stimulus-reward learning. These two areas are
also reciprocally connected and, based on neuroimaging investigations functionally interact during learning
further suggesting that they form part of a functional circuit essential for stimulus-reward learning. Our hypothesis
is that bottom-up and top-down influences on learning impact neural activity within and communication between
ventrolateral PFC and the basolateral nucleus of the amygdala but that bottom-up and top-down learning do so
through different mechanisms and pathways. We will test our hypothesis by recording activity in ventrolateral
PFC and basolateral amygdala as well as interconnected parts of orbital PFC and striatum in macaques learning
in a probabilistic stimulus-reward task. We will assess functional interaction between areas using recurrent neural
network models and measures of coherence when learning is altered by either bottom-up (aim 1) or top-down
(aim 2) processes. To test the causal role of pathways linking amygdala and ventrolateral PFC we will also use
chemogenetic approaches to selectively inhibit activity in these circuits. Thus, using an innovative combination
of behavioral tasks, neural recordings, chemogenetic neuromodulation, and computational approaches we will
establish the patterns of neural activity within and causal importance of PFC-amygdala pathways to bottom-up
and top-down influences on learning. Completing these experiments will shed light on the specific neural
mechanisms and pathways associated with altered learning, information essential for determining the processes
that go awry in p...

## Key facts

- **NIH application ID:** 10916422
- **Project number:** 5R01MH132064-02
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Peter Rudebeck
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $816,865
- **Award type:** 5
- **Project period:** 2023-09-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916422

## Citation

> US National Institutes of Health, RePORTER application 10916422, Neural circuit mechanisms of affective probabilistic learning (5R01MH132064-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10916422. Licensed CC0.

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