Decomposing neural circuits using model-based analysis: Applying the sSoTS model to fMRI data.
Eirini Mavritsaki, Harriet Allen and Glyn Humphreys
Behavioural Brain Sciences Centre, School of Psychology, University of Birmingham, B15 2TT

We show how a biological plausible model can be used to decompose complex neural circuits found in fMRI studies of human attention, separating circuits concerned with inhibition attention function from those concerned with top-down enhancement. The studies examined preview search as presented by Watson and Humphreys [1].

The model for visual search over time and space (SSoTS) used incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca2+] sensitive K+ current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. It has been shown [2] that when the passive process (frequency adaptation) is coupled with a process of active inhibition, new items can be successfully prioritised over time periods matching those found in psychological studies.

We use the model to examine the time course of the fMRI BOLD signal from studies of preview search. Activity in the model is related to different brain regions (i) by convolving the synaptic activation with the haemodynamic response function as formulated by Glover [3] and comparing the model's BOLD response with fMRI data activation from predefined regions of interest (i.e. inferior parietal lobe and precuneous) and also (ii) we use the synaptic activation from the sSoTS's maps as regressors for brain activity using standard imaging analysis techniques (FSL). We find activation related to SsoTS processes in discrete brain areas including a network of areas relating to active inhibition

[1] D. Watson and G.W. HumphreysPsychological Review. 104:90-122 (1997).
[2] E. Mavritsaki, D. Heinke, G.W. Humphreys and G. Deco, Journal of Physiology. 100:110-124 (2006).
[3] G.H. Glover, NeuroImage. 9:416-429 (1999).