Nonlinear Representation of Auditory Stimuli Across the Auditory Cortex

<p>The neural evoke activity to pure tones in primary auditory cortex has been systematically studied for many years, as has the spatial organization of these responses. Unlike pure tones, natural sounds possess complex spectro-temporal structures across frequencies. How simple tuning properties scale across ensembles of neurons to represent more complex sensory environments is still a question of active investigation and debate. To better understand the coding principles used to represent complex auditory sounds, we performed 2-photon calcium imaging of neural activity of the entire auditory cortex in awake mice, while playing sounds composed of single or multiple frequencies. While we observed simple tuning in response to single frequency stimuli, the calcium responses to combinations of tones displayed characteristic nonlinearities. Moreover, we could not reconstruct the multi-tone response from the responses to the individual constituent tones alone. The subset of neurons most exhibiting such nonlinearities were found to perform certain fuzzy logic operations, on the input signal and were topographically organized across the auditory cortex. Such neurons increased the effective dimensionality of the sensory representation, enhancing the decodability and classification of complex stimuli. Together, our results reveal that the auditory cortex contains a topographical map of spatially-clustered computational ensembles able to detect specific combinations of spectral features. We further hypothesize that local non-linear computations such as these may contribute to high dimensional representation across different sensory modalities.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Thesis

Year

2022

Author dc:creator

• Leon, Frank Tejera

Contributors dc:contributor

• Alipasha Vaziri

• auditory cortex
• nonlinearities
• multi-tone stimuli
• two-photon calcium imaging
• fuzzy logic
• topographical map
• Life Sciences

Repository record dc:identifier

https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/747

OAI identifier oai:identifier

oai:digitalcommons.rockefeller.edu:student_theses_and_dissertations-1752