R01MH132064
Project Grant
Overview
Grant Description
Neural circuit mechanisms of affective probabilistic learning - 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 psychiatric disorders.
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 psychiatric disorders.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
New York,
New York
100296504
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 302% from $802,783 to $3,230,101.
Icahn School Of Medicine At Mount Sinai was awarded
Neural Circuit Mechanisms of Affective Probabilistic Learning
Project Grant R01MH132064
worth $3,230,101
from the National Institute of Mental Health in September 2023 with work to be completed primarily in New York New York United States.
The grant
has a duration of 4 years 8 months and
was awarded through assistance program 93.242 Mental Health Research Grants.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 6/22/26
Period of Performance
9/1/23
Start Date
5/31/28
End Date
Funding Split
$3.2M
Federal Obligation
$0.0
Non-Federal Obligation
$3.2M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01MH132064
Transaction History
Modifications to R01MH132064
Additional Detail
Award ID FAIN
R01MH132064
SAI Number
R01MH132064-2010079927
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75N700 NIH National Institute of Mental Health
Funding Office
75N700 NIH National Institute of Mental Health
Awardee UEI
C8H9CNG1VBD9
Awardee CAGE
1QSQ9
Performance District
NY-13
Senators
Kirsten Gillibrand
Charles Schumer
Charles Schumer
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of Mental Health, National Institutes of Health, Health and Human Services (075-0892) | Health research and training | Grants, subsidies, and contributions (41.0) | $802,783 | 100% |
Modified: 6/22/26