Literature DB >> 15078571

Cooperation and biased competition model can explain attentional filtering in the prefrontal cortex.

Miruna Szabo1, Rita Almeida, Gustavo Deco, Martin Stetter.   

Abstract

Recent neurophysiological experimental results suggest that the prefrontal cortex plays an important role in filtering out unattended visual inputs. Here we propose a neurodynamical computational model of a part of the prefrontal cortex to account for the neural mechanisms defining this attentional filtering effect. Similar models have been employed to explain experimental results obtained during the performance of attention and working memory tasks. In this previous work the principle of biased competition was shown to successfully account for the experimental data. To model the attentional filtering effect, the biased competition model was extended to enable cooperation between stimulus selective neurons. We show that, in a biological relevant minimal model, competition and cooperation between the neurons are sufficient conditions for reproducing the attentional effect. Furthermore, a characterization of the parameter regime where the cooperation effect is observed is presented. Finally, we also reveal parameter regimes where the network has different modes of operation: selective working memory, attentional filtering, pure competition and noncompetitive amplification.

Mesh:

Year:  2004        PMID: 15078571     DOI: 10.1111/j.1460-9568.2004.03211.x

Source DB:  PubMed          Journal:  Eur J Neurosci        ISSN: 0953-816X            Impact factor:   3.386


  5 in total

1.  A neuroanatomically grounded Hebbian-learning model of attention-language interactions in the human brain.

Authors:  Max Garagnani; Thomas Wennekers; Friedemann Pulvermüller
Journal:  Eur J Neurosci       Date:  2008-01       Impact factor: 3.386

2.  Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex.

Authors:  Tatyana Turova; Edmund T Rolls
Journal:  Front Comput Neurosci       Date:  2019-07-31       Impact factor: 2.380

3.  Crossmodal links between vision and touch in spatial attention: a computational modelling study.

Authors:  Elisa Magosso; Andrea Serino; Giuseppe di Pellegrino; Mauro Ursino
Journal:  Comput Intell Neurosci       Date:  2009-10-22

4.  Structure of spike count correlations reveals functional interactions between neurons in dorsolateral prefrontal cortex area 8a of behaving primates.

Authors:  Matthew L Leavitt; Florian Pieper; Adam Sachs; Ridha Joober; Julio C Martinez-Trujillo
Journal:  PLoS One       Date:  2013-04-22       Impact factor: 3.240

Review 5.  The dynamic brain: from spiking neurons to neural masses and cortical fields.

Authors:  Gustavo Deco; Viktor K Jirsa; Peter A Robinson; Michael Breakspear; Karl Friston
Journal:  PLoS Comput Biol       Date:  2008-08-29       Impact factor: 4.475

  5 in total

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