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In Vivo Optical Calcium Imaging of Learning-Induced Synaptic Plasticity in Drosophila melanogaster

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Published on: October 8, 2019

Single-Neuron Encoding of Learnability in the Dorsal Anterior Cingulate Cortex.

Yuhao Jin^1,2, Greg Jensen^3,4,2, Vincent Ferrera^4,5,2

¹Department of Biological Sciences, Columbia University, New York, NY 10027.

Biorxiv : the Preprint Server for Biology

|November 19, 2025

Summary

This summary is machine-generated.

Monkeys can distinguish learnable from unlearnable associations, a skill encoded by dorsal anterior cingulate cortex (dACC) neurons. This brain region helps animals focus on true patterns and avoid false inferences from random data.

Keywords:

Anterior cingulate cortex Learnability Monkey Transitive inference

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Area of Science:

Neuroscience
Cognitive Science
Animal Behavior

Background:

Organisms must differentiate learnable patterns from random associations to optimize cognitive resource allocation.
The neural mechanisms enabling the detection of learnability remain largely unknown.

Purpose of the Study:

To investigate the neural basis for distinguishing learnable from unlearnable associations.
To identify brain regions involved in monitoring pattern learnability.

Main Methods:

Electrophysiological recordings from dorsal anterior cingulate cortex (dACC) neurons in monkeys performing a transitive inference task.
Analysis of neuronal responses related to trial learnability (learnable vs. unlearnable sets) and decision outcomes.
Correlation of neuronal activity with behavioral performance in avoiding spurious pattern inference.

Main Results:

dACC neurons exhibited distinct responses differentiating learnable from unlearnable trial sets prior to outcome delivery.
Neuronal selectivity for reward outcomes was modulated by trial learnability, being stronger for learnable sets.
The strength of dACC responses correlated with the monkeys' ability to refrain from inferring false order in unlearnable sets.

Conclusions:

The dorsal anterior cingulate cortex (dACC) plays a critical role in detecting the learnability of associations.
dACC activity enables animals to focus learning on genuine regularities and avoid errors from random data.
These findings suggest the dACC is part of a neural network essential for adaptive learning and decision-making in complex environments.