Multidimensional Firing Rate Dynamics in a Neural Integrator
The neural mechanisms underlying short-term memory remain largely unknown. The horizontal velocity-to-position neural integrator (hVPNI) is a compelling model for circuit-level short-term memory, transforming transient eye velocity command signals into persistent firing that encodes eye position and...
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| Format: | Dissertation |
| Language: | English |
| Published: |
ProQuest Dissertations & Theses
01-01-2011
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| Online Access: | Get full text |
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| Summary: | The neural mechanisms underlying short-term memory remain largely unknown. The horizontal velocity-to-position neural integrator (hVPNI) is a compelling model for circuit-level short-term memory, transforming transient eye velocity command signals into persistent firing that encodes eye position and stabilizes gaze during spontaneous eye movement. We developed a preparation for studying the hVPNI in the awake larval zebrafish using a custom-built microscope enabling synchronized eye position tracking and two-photon laser scanning fluorescence imaging of cellular calcium fluctuations. A statistical approach was devised that allows behaviorally-correlated neurons to be rapidly identified from fluorescence image time series for subsequent targeted activity measurement and perturbation. The use of these methods revealed heterogeneous firing rate persistence across hVPNI neurons within individual larvae, inconsistent with line attractor-based hVPNI models, as well as gradients in this persistence mapped along the rostrocaudal and dorsoventral axes. Analysis of eye plant dynamics suggests that gaze stability requires a transformation somewhat distinct from temporal integration. The heterogeneous firing rate persistence of hVPNI neurons matches that required of this transformation. We used a novel fitting method to derive circuit architectures for the hVPNI directly from experimental data. The connection matrices resulting from these fits show a significant tendency for cells with more similar persistence times to be more strongly coupled. This implies that the gradients of persistence observed experimentally could emerge from a proximity bias in connectivity likelihood. Analysis of these models has elucidated multidimensional dynamics of persistent firing in the hVPNI that reconcile a number of previous observations in adult vertebrates. |
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| ISBN: | 9781124932989 1124932984 |