Signal propagation in recurrent networks of mouse barrel cortex
| dc.contributor.advisor | Koester, Helmut, 1926- | en |
| dc.contributor.committeeMember | Johnston, Daniel | en |
| dc.contributor.committeeMember | Geisler, Wilson | en |
| dc.contributor.committeeMember | Fiete, Ila | en |
| dc.contributor.committeeMember | Dunn, Andrew | en |
| dc.creator | Nattar Ranganath, Gayathri | en |
| dc.date.accessioned | 2012-02-03T17:48:59Z | en |
| dc.date.available | 2012-02-03T17:48:59Z | en |
| dc.date.issued | 2011-12 | en |
| dc.date.submitted | December 2011 | en |
| dc.date.updated | 2012-02-03T17:49:55Z | en |
| dc.description | text | en |
| dc.description.abstract | Sensory signals are represented and propagated as spiking activity in multiple neuronal populations to lead to cognitive or motor behavior in organisms. Neural processing underlying sensory-motor behavior is understood by uncovering the governing computational principles and the biophysical mechanisms that implement the principles. While these mechanisms have been studied extensively at the single-neuron and system levels, activity within neuronal networks significantly impact neural processing. For example, there are spatiotemporal interactions (neural correlations) between responses of neurons within populations that could potentially impact signal representation and propagation. Furthermore, the effects of associative plasticity are also expected to alter network activity and its propagation. The effects of plasticity on network activity cannot be predicted from individual neuronal responses due to the complex, non-linear interactions within neuronal networks. Thus examining neural correlations in network activity and the propagation of network activity, requires recording spiking activity from large, heterogeneous, populations of spatially distributed neurons simultaneously. Studies addressing the propagation of network activity have been limited to theoretical approaches. Empirical studies have been limited by the technical difficulties in recording from a large number of neurons simultaneously. To overcome this challenge we developed a novel technique, dithered random-access functional calcium imaging. This imaging technique records and extracts suprathreshold activity from a large number of neurons. This technique also has a high spike detection efficiency and millisecond temporal precision. We applied this technique to measure the propagation of activity and neural correlations in activity evoked by afferent, thalamocortical inputs in the recurrent cortical networks of the mouse barrel cortex. We found that the cortical activity evoked by novel (naïve), thalamocortical inputs showed limited propagation of activity and decrease in propagation of neural correlations (measured from neuronal pairs within each population) from L4 to L2/3 network of the responding column. However, associative cortical plasticity was induced from pairing thalamocortical inputs with intracortical inputs. This pairing resulted in increased propagation of activity. The pairing also modified the propagation of neural correlations. Our results suggest that synaptic plasticity in intracortical circuits contributes to the modified propagation of activity and neural correlations. The modified propagation of neural correlations could in turn contribute to behavioral performance in vivo following perceptual learning. | en |
| dc.description.department | Neuroscience | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.slug | 2152/ETD-UT-2011-12-4577 | en |
| dc.identifier.uri | http://hdl.handle.net/2152/ETD-UT-2011-12-4577 | en |
| dc.language.iso | eng | en |
| dc.subject | Random-access scanning | en |
| dc.subject | Functional calcium imaging | en |
| dc.subject | Barrel cortex | en |
| dc.subject | Acousto-optical deflectors | en |
| dc.subject | Plasticity, network | en |
| dc.title | Signal propagation in recurrent networks of mouse barrel cortex | en |
| dc.type.genre | thesis | en |
| thesis.degree.department | Neuroscience | en |
| thesis.degree.discipline | Neuroscience | en |
| thesis.degree.grantor | University of Texas at Austin | en |
| thesis.degree.level | Doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |