Biomaterial Database

The linearity of emergent spectro-temporal receptive fields in a model of auditory cortex. 2008

M Coath, and E Balaguer-Ballester, and S L Denham, and M Denham

Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, UK. mcoath@plymouth.ac.uk

The responses of cortical neurons are often characterized by measuring their spectro-temporal receptive fields (STRFs). The STRF of a cell can be thought of as a representation of its stimulus 'preference' but it is also a filter or 'kernel' that represents the best linear prediction of the response of that cell to any stimulus. A range of in vivo STRFs with varying properties have been reported in various species, although none in humans. Using a computational model it has been shown that responses of ensembles of artificial STRFs, derived from limited sets of formative stimuli, preserve information about utterance class and prosody as well as the identity and sex of the speaker in a model speech classification system. In this work we help to put this idea on a biologically plausible footing by developing a simple model thalamo-cortical system built of conductance based neurons and synapses some of which exhibit spike-time-dependent plasticity. We show that the neurons in such a model when exposed to formative stimuli develop STRFs with varying temporal properties exhibiting a range of heterotopic integration. These model neurons also, in common with neurons measured in vivo, exhibit a wide range of non-linearities; this deviation from linearity can be exposed by characterizing the difference between the measured response of each neuron to a stimulus, and the response predicted by the STRF estimated for that neuron. The proposed model, with its simple architecture, learning rule, and modest number of neurons (<1000), is suitable for implementation in neuromorphic analogue VLSI hardware and hence could form the basis of a developmental, real time, neuromorphic sound classification system.

UI	MeSH Term	Description	Entries
D008954	Models, Biological	Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.	Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D009474	Neurons	The basic cellular units of nervous tissue. Each neuron consists of a body, an axon, and dendrites. Their purpose is to receive, conduct, and transmit impulses in the NERVOUS SYSTEM.	Nerve Cells,Cell, Nerve,Cells, Nerve,Nerve Cell,Neuron
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D001303	Auditory Cortex	The region of the cerebral cortex that receives the auditory radiation from the MEDIAL GENICULATE BODY.	Brodmann Area 41,Brodmann Area 42,Brodmann's Area 41,Heschl Gyrus,Heschl's Gyrus,Auditory Area,Heschl's Convolutions,Heschl's Gyri,Primary Auditory Cortex,Temporal Auditory Area,Transverse Temporal Gyri,Area 41, Brodmann,Area 41, Brodmann's,Area 42, Brodmann,Area, Auditory,Area, Temporal Auditory,Auditory Areas,Auditory Cortex, Primary,Brodmanns Area 41,Cortex, Auditory,Cortex, Primary Auditory,Gyrus, Heschl,Gyrus, Heschl's,Gyrus, Transverse Temporal,Heschl Convolutions,Heschl Gyri,Heschls Convolutions,Heschls Gyri,Heschls Gyrus,Primary Auditory Cortices,Temporal Auditory Areas,Temporal Gyrus, Transverse,Transverse Temporal Gyrus
D001307	Auditory Perception	The process whereby auditory stimuli are selected, organized, and interpreted by the organism.	Auditory Processing,Perception, Auditory,Processing, Auditory
D013569	Synapses	Specialized junctions at which a neuron communicates with a target cell. At classical synapses, a neuron's presynaptic terminal releases a chemical transmitter stored in synaptic vesicles which diffuses across a narrow synaptic cleft and activates receptors on the postsynaptic membrane of the target cell. The target may be a dendrite, cell body, or axon of another neuron, or a specialized region of a muscle or secretory cell. Neurons may also communicate via direct electrical coupling with ELECTRICAL SYNAPSES. Several other non-synaptic chemical or electric signal transmitting processes occur via extracellular mediated interactions.	Synapse
D019295	Computational Biology	A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.	Bioinformatics,Molecular Biology, Computational,Bio-Informatics,Biology, Computational,Computational Molecular Biology,Bio Informatics,Bio-Informatic,Bioinformatic,Biologies, Computational Molecular,Biology, Computational Molecular,Computational Molecular Biologies,Molecular Biologies, Computational