Observational learning computations in neurons of the human anterior cingulate cortex
Michael R Hill1,2,3,4, Erie D Boorman2,5,6, Itzhak Fried3,7
1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA.
Nature Communications
|September 7, 2016
Summary
Humans learn by observing others, with neurons in the rostral anterior cingulate cortex (rACC) encoding reward prediction errors (PEs). This neural signal, crucial for observational learning, was not found in the amygdala or medial prefrontal cortex.
Area of Science:
- Neuroscience
- Cognitive Science
- Artificial Intelligence
Background:
- Learning from direct experience involves reward prediction errors (PEs).
- Observational learning, common in humans and other species, is less understood at the neural level.
- Artificial intelligence algorithms utilize PEs as a teaching signal.
Purpose of the Study:
- To investigate neural mechanisms of observational learning in humans.
- To determine if reward prediction errors are encoded during social learning.
- To identify brain regions involved in processing observational learning signals.
Main Methods:
- Recorded neural activity in humans playing a card game.
- Analyzed neuronal encoding of expected value and PE during observation of other players.
- Compared neuronal activity in the rostral anterior cingulate cortex (rACC), amygdala (AMY), and rostromedial prefrontal cortex (rmPFC).
Main Results:
- Neurons in the rACC encoded the expected value of observed choices.
- rACC neurons also encoded reward prediction errors (PEs) after observed outcomes.
- No such encoding of expected value or PE was found in the AMY or rmPFC.
Conclusions:
- The human rACC plays a key role in observational learning.
- Single neurons in the rACC encode observational reward prediction errors.
- This provides a neural basis for how humans learn from watching others.
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