title: How does non-random spontaneous activity contribute to brain development?
abstract: Highly non-random forms of spontaneous activity are proposed to play an instrumental role in the early development of the visual system. However, both the fundamental properties of spontaneous activity required to drive map formation, as well as the exact role of this information remain largely unknown. Here, a realistic computational model of spontaneous retinal waves is employed to demonstrate that both the amplitude and frequency of waves may play determining roles in retinocollicular map formation. Furthermore, results obtained with different learning rules show that spike precision in the order of milliseconds may be instrumental to neural development: a rule based on precise spike interactions (spike-timing-dependent plasticity) reduced the density of aberrant projections to the SC to a markedly greater extent than a rule based on interactions at much broader time-scale (correlation-based plasticity). Taken together, these results argue for an important role of spontaneous yet highly non-random activity, along with temporally precise learning rules, in the formation of neural circuits.
authors.affiliation: Department of Psychological and Brain Sciences, Indiana University, 1101 East Tenth Street, Bloomington, IN 47405, USA. jp.thivierge@gmail.com
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Thivierge
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001921:Brain / Q000254:growth & development*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000254:growth & development / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D017711:Nonlinear Dynamics; D012160:Retina / Q000502:physiology; D013223:Statistics as Topic; D013569:Synapses / Q000502:physiology; D013997:Time Factors; D014795:Visual Pathways / Q000254:growth & development* / Q000502:physiology