Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data
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. Thi...
| Main Authors: | , , |
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| Format: | Article |
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World Scientific Publishing
2008
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| Online Access: | https://eprints.nottingham.ac.uk/44444/ |
| _version_ | 1848796918913695744 |
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| author | Mavritsaki, Eirini Allen, Harriet A. Humphreys, Glyn W. |
| author_facet | Mavritsaki, Eirini Allen, Harriet A. Humphreys, Glyn W. |
| author_sort | Mavritsaki, Eirini |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:55:37Z |
| format | Article |
| id | nottingham-44444 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:55:37Z |
| publishDate | 2008 |
| publisher | World Scientific Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-444442020-05-04T16:27:45Z https://eprints.nottingham.ac.uk/44444/ Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data Mavritsaki, Eirini Allen, Harriet A. Humphreys, Glyn W. 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. World Scientific Publishing 2008-07-16 Article PeerReviewed Mavritsaki, Eirini, 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 http://www.worldscientific.com/doi/abs/10.1142/9789812834232_0033 doi:10.1142/9789812834232_0033 doi:10.1142/9789812834232_0033 |
| spellingShingle | Mavritsaki, Eirini Allen, Harriet A. Humphreys, Glyn W. Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title | Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title_full | Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title_fullStr | Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title_full_unstemmed | Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title_short | Decomposition of neural circuits of human attention using a model based analysis: sSoTs model application to fMRI data |
| title_sort | decomposition of neural circuits of human attention using a model based analysis: ssots model application to fmri data |
| url | https://eprints.nottingham.ac.uk/44444/ https://eprints.nottingham.ac.uk/44444/ https://eprints.nottingham.ac.uk/44444/ |