Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data

Mavritsaki, Eirini and Allen, Harriet A. and Humphreys, Glyn W. (2008) Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data. Progress in Neural Processing, 18 . pp. 401-414. ISSN 2010-2895

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Abstract

The complex neural circuits found in fMRI studies of human attention were decomposed using a model of spiking neurons. The model for visual search over time and space (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on IAHP current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. It has been shown [1] that when the passive process (frequency adaptation) is coupled with a process of active inhibition, new items can be successfully prioritized over time periods matching those found in psychological studies. In this study we use the model to decompose the neural regions mediating the processes of active attentional guidance, and the inhibition of distractors, in search. Activity related to excitatory guidance and inhibitory suppression was extracted from the model and related to different brain regions by using the synaptic activation from sSoTS’s maps as regressors for brain activity derived from standard imaging analysis techniques. The results show that sSoTS pulls-apart discrete brain areas mediating excitatory attentional guidance and active distractor inhibition.

Item Type: Article
Additional Information: Electronic version of an article published as Progress in Neural Processing, Volume 18, 2009, p. 401-414, doi:10.1142/9789812834232_0033. © 2009 copyright World Scientific Publishing Company. http://www.worldscientific.com/series/pnp
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Psychology
Identification Number: 10.1142/9789812834232_0033
Depositing User: Allen, Harriet
Date Deposited: 27 Jul 2017 13:20
Last Modified: 12 Oct 2017 23:29
URI: http://eprints.nottingham.ac.uk/id/eprint/44444

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