How neural circuits in cerebral cortex balance local circuit computation with intermediate- and long-range integration is unclear. A powerful example is layer (L) 2/3 of primary sensory cortex, where local networks receive dense innervation from their immediate cortical column, as well as cross-columnar, distant cortico- cortical, neuromodulatory and other input. However, it remains unclear whether L2/3 represents nonlocal (integrative) sensory features in rodents, which are dominant animal models for cortical circuit function and disease. This project uses 2-photon population calcium imaging, neurophysiology, and optogenetics to study the neural coding of local and integrative sensory features in L2/3 of mouse somatosensory cortex (S1), and its micro-organization within and across columns. Most prior work in S1 has focused on representation of very local, single-whisker sensory features and their basis in intracolumnar local circuits.
In Aim 1, we demonstrate that despite the strong anatomical columnar structure in S1, there is a highly distributed salt-and-pepper micro-organization of whisker receptive fields. We quantify this organization, test its origin across layers, and test how natural whisker experience affects this structure, with the surprising finding that enriched experience causes a more topographically precise subcolumnar map to form.
In Aim 2, we study neural coding for 2-whisker sequences (the simplest multi-whisker pattern) in L2/3, and test a novel hypothesis for how sequence representation may be organized spatially within and across columns.
In Aim 3, we test whether prominent cortico-cortical input to L2/3 of S1 from auditory and visual cortex allows L2/3 neurons to acquire cross-modal (non-whisker) sensory responses during learning. Preliminary data show robust acquisition of tone responses in L2/3 of S1 for tones that predict reward. We characterize this phenomenon, test whether individual S1 neurons learn to encode specific non-whisker stimuli or the general expectation of reward, and use optogenetics to test whether these learned cross-modal responses are mediated by cortico-cortical projections from other sensory cortices. Overall, these experiments will reveal novel integrative functions and organizational principles within L2/3. Understanding these features in S1 will allow future tests of potential abnormalities in mouse models of autism and schizophrenia, two disorders that may reflect an imbalance between local excitability and long- range integration in cerebral cortex.

Public Health Relevance

Many neurodevelopmental disorders are thought to arise from processing defects in neural circuits within cerebral cortex, including autism and schizophrenia. One hallmark of these disorders is abnormal integration of information. Improved diagnosis and treatment require a more detailed understanding of how neural circuits organize and integrate information, and how this is disrupted in these disorders. Using an animal model system, this project aims to determine (1) how cortical circuits balance local circuit computation with intermediate- and long-range integration, (2) how sensory representations are organized at the microscopic level, and (3) how learning modifies circuit organization and promotes sensory integration. This baseline knowledge about normal cerebral cortex function will enable new, detailed studies of cortical processing defects in autism and other disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Method to Extend Research in Time (MERIT) Award (R37)
Project #
5R37NS092367-04
Application #
9517117
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Gnadt, James W
Project Start
2015-06-01
Project End
2019-05-31
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Neurosciences
Type
Organized Research Units
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Isett, Brian R; Feasel, Sierra H; Lane, Monet A et al. (2018) Slip-Based Coding of Local Shape and Texture in Mouse S1. Neuron 97:418-433.e5