Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Formation of Structure in Cortical Networks through Spike Timing-Dependent Plasticity

Ocker, Gabriel (2016) Formation of Structure in Cortical Networks through Spike Timing-Dependent Plasticity. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF (Dissertation, Gabriel Kock Ocker)
Primary Text

Download (7MB)

Abstract

The connectivity of mammalian brains exhibits structure at a wide variety of spatial scales, from the broad (which brain areas connect to which) to the extremely fine (where synapses form on the morphology of individual neurons). Two striking features of the neuron-to- neuron connectivity are 1) the strong over-representation of multi-synapse connectivity pat- terns compared to simple random-network models and 2) a strong relationship between neurons’ local connectivity and their stimulus preferences, so that local network structure plays a large role in the computations neurons perform. A central question in systems neu- roscience is how such structures emerge. Answers to this question are confounded by the mutual interactions of neuronal activity and neural network structure. Patterns of synaptic connectivity influence neurons’ joint activity, while the synapses between neurons are plastic and strengthen or weaken depending on the activity of the pre- and postsynaptic neurons. In this thesis, I develop a self-consistent framework for the coevolution of network struc- ture and spiking activity. Subsequent chapters leverage this to develop low-dimensional sets of equations that directly describe the plasticity of connectivity patterns in large spiking networks. I examine plasticity during spontaneous activity and then how the structure of external stimuli can shape network structure and subsequent spontaneous plasticity. These studies provide a step towards understanding how the structure of neuronal networks and neurons’ joint activity interact to allow network computations.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ocker, Gabrielgko1@pitt.eduGKO1
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairDoiron, Brentbdoiron@pitt.eduBDOIRON
Committee MemberOswald, Anne-Marie Mamoswald@pitt.eduAMOSWALD
Committee MemberErmentrout, Bardbard@pitt.eduBARD
Committee MemberRubin, Jonathanjonrubin@pitt.eduJONRUBIN
Committee MemberTzounopoulos, Thanosthanos@pitt.eduTHANOS
Date: 21 January 2016
Date Type: Publication
Defense Date: 18 September 2015
Approval Date: 21 January 2016
Submission Date: 2 October 2015
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 162
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Neuroscience
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: synaptic plasticity, neuronal networks, theoretical neuroscience, computational neuroscience
Related URLs:
Date Deposited: 21 Jan 2016 21:31
Last Modified: 15 Nov 2016 14:30
URI: http://d-scholarship.pitt.edu/id/eprint/26169

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item