Predictive Novelty Detection in Songbird Auditory Cortex

In order to make sense of complicated sensory landscapes, the brain privileges the processing of novel stimuli. Detecting novelty is therefore a fundamental problem for the brain to solve. And it turns out to be complicated, as stimuli can be completely novel, or just novel relative to certain certain contexts or expectations. To better understand how the brain detects both types of novelty, we studied an auditory region of the avian brain that performs both absolute and relative novelty detection. We introduce a predictive model, called the Agnotron, that is capable of performing both kinds of novelty detection with the same circuit mechanism. Armed with predictions made by the Agnotron, we perform experiments to confirm the existence of Agnotron-like circuitry in the brain. While we fail to find evidence that the various novelty signals in this brain area are produced by the same mechanism, we do find support for predictive circuitry for some novelty signals. We continue with an advanced investigation of one absolute novelty signal in particular, known as the Song-Specific Adaptation. After recapitulating classical results with state-of-the-art technology, we report novel phenomena that rule out predictive circuit mechanisms for the SSA. Taken together, our results suggest that predictive mechanisms can explain some novelty signals in the avian brain, but not the SSA, which seems to have a more simplistic feed-forward mechanism of generation.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Happ, Michael Liu

Advisor dc:contributor.advisor

• Fee, Michale S.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/152579

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/152579