Learning enhances encoding of time and temporal surprise in primary sensory cortex
By: Rebecca Rabinovich
Publisher: [publisher not identified]
Published: 2022
Place of publication: [New York, N.Y.?]
Language: eng
Description: Primary sensory cortex has long been believed to play a straightforward role in the initial processing of sensory information. Yet, the superficial layers of cortex overall are sparsely active, even during strong sensory stimulation; moreover, cortical activity is influenced by other modalities, task context, reward, and behavioral state. The experiments described in this thesis demonstrate that reinforcement learning dramatically alters representations among longitudinally imaged neurons in superficial layers of mouse primary somatosensory cortex. Cells were confirmed to be sparsely active in naïve animals; however, learning an object detection task recruited previously unresponsive neurons, enlarging the neuronal population sensitive to tactile stimuli. In contrast, cortical responses habituated, decreasing upon repeated exposure to unrewarded stimuli. In addition, after conditioning, the cell population as well as individual neurons better encoded the rewarded stimuli, as well as behavioral choice.

Furthermore, in well-trained mice, the neuronal population encoded of the passage of time. We further found evidence that the temporal information was contained in sequences of cell activity, meaning that different cells in the population activated at different moments within the trial. This kind of time-keeping was not observed in naïve animals, nor did it arise after repeated stimulus exposure. Finally, unexpected deviations in trial timing elicited even stronger responses than touch did. In conclusion, the superficial layers of sensory cortex exhibit a high degree of learning-dependent plasticity and are strongly modulated by non-sensory but behaviorally-relevant features, such as timing and surprise.
Notes: Department: Neurobiology and Behavior.

Thesis advisor: Randy Bruno.

Thesis (Ph.D.)--Columbia University, 2022.