# CRCNS: Coordinating learning by top-down gating of plasticity in dendrites

> **NIH NIH R01** · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · 2024 · $399,375

## Abstract

There is a central problem in biological learning known as the “credit assignment problem”: how does 
information about the outcome of a decision or behavior modify the right synapses in the right neurons 
across multiple brain regions to improve future performance? The standard solution to this problem in 
artificial neural networks is to perform direct gradient descent, which minimizes error in the output of a 
network by precisely adjusting the strengths of every connection in proportion to that error. However, it is 
unlikely that the brain is able to compute the impact of each synapse on performance error and 
“backpropagate” fine-grained error signals across multiple layers of neuronal circuitry to every synapse. 
Recent work identified a new candidate biological mechanism for supervised learning in the brain. In 
addition to “bottom-up” connections that process sensory inputs, neurons also send “top-down” 
connections to the dendrites of neurons in lower layers. This feedback drives special events called 
“dendritic calcium spikes” that induce a potent form of synaptic plasticity and cause neurons to become 
selective for stimulus features in as few as a single trial, a phenomenon called “one-shot learning.” This 
project aims to develop new learning theory inspired by these experimental observations, and to 
experimentally test predictions of this theory in awake, behaving mice to better understand how top-down 
instructive signals in the brain coordinate learning across multiple layers of neuronal circuitry by regulating 
dendritic calcium spiking and associated plasticity. 
The team synergizes expertise in neuronal cellular and synaptic physiology, systems and computational 
neuroscience, and machine learning to better understand an important cognitive function - memory 
formation during goal-directed learning. A major objective is to develop and critically test a new theory of 
learning based on the regulation of dendritic calcium spikes and associated synaptic plasticity. 
Computational modeling will directly inform the proposed experiments, which entail imaging and 
manipulating neuronal population activity in vivo during spatial foraging behavior in mice. Preliminary 
results suggest that incorporation of these insights from biology into artificial neural networks leads to 
enhanced performance compared to standard techniques, highlighting the transformative potential of the 
proposed approach.

## Key facts

- **NIH application ID:** 10867475
- **Project number:** 5R01MH135576-02
- **Recipient organization:** RUTGERS BIOMEDICAL AND HEALTH SCIENCES
- **Principal Investigator:** AARON D MILSTEIN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $399,375
- **Award type:** 5
- **Project period:** 2023-06-14 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10867475

## Citation

> US National Institutes of Health, RePORTER application 10867475, CRCNS: Coordinating learning by top-down gating of plasticity in dendrites (5R01MH135576-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10867475. Licensed CC0.

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