A thalamo–cortico–thalamic neural mass model to study alpha rhythms in Alzheimer’s disease

Basab Bhattacharya, Damien Coyle, LP Maguire

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

We present a lumped computational model of the thalamo–cortico–thalamic circuitry. The model essentially consists of two modules: a thalamic module and a cortical module. The thalamic module circuitry is a modified version of a classic neural mass computational model of the thalamic circuitry to simulate cortical alpha rhythms and which we have used in previous research to study EEG abnormality associated with Alzheimer’s Disease (AD). Here, we introduce a modified synaptic structure representing a neuronal population in the thalamic model. Furthermore, the synaptic organisation and connectivity parameter values in the model are based on experimental data reported from the dorsal Lateral Geniculate Nucleus of different species. The cortical module circuitry is based on a recent work studying cortical brain rhythms. We vary the synaptic connectivity parameters in the thalamic module of the model to simulate the effects of AD on brain synaptic circuitry and study power within the alpha frequency bands. The power and dominant frequencies of the model output are studied in three sub-bands within the alpha band: lower alpha (7–9 Hz), middle alpha (9–11 Hz) and upper alpha (11–13 Hz). Such an analytical method conforms to recent comparative EEG studies on young adults, healthy aged adults and MCI or early stage AD patients. The results show a remarkable role of the synaptic connectivities in the inhibitory thalamic cell populations on the alpha band power and frequency. Furthermore, the total number of active synapses in the thalamic cell populations produces the slowing of alpha rhythms and a simultaneous decrease of alpha band power in the brain as a result of AD.
LanguageEnglish
Pages631-645
Number of pages15
JournalNeural Networks Special Issue: Neurocomputational Models of Brain Disorders
Volume24
Issue number6
DOIs
Publication statusPublished - Aug 2011

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Alpha Rhythm
Alzheimer Disease
Electroencephalography
Brain
Population
Geniculate Bodies
Synapses
Young Adult
Power (Psychology)
Research

Cite this

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abstract = "We present a lumped computational model of the thalamo–cortico–thalamic circuitry. The model essentially consists of two modules: a thalamic module and a cortical module. The thalamic module circuitry is a modified version of a classic neural mass computational model of the thalamic circuitry to simulate cortical alpha rhythms and which we have used in previous research to study EEG abnormality associated with Alzheimer’s Disease (AD). Here, we introduce a modified synaptic structure representing a neuronal population in the thalamic model. Furthermore, the synaptic organisation and connectivity parameter values in the model are based on experimental data reported from the dorsal Lateral Geniculate Nucleus of different species. The cortical module circuitry is based on a recent work studying cortical brain rhythms. We vary the synaptic connectivity parameters in the thalamic module of the model to simulate the effects of AD on brain synaptic circuitry and study power within the alpha frequency bands. The power and dominant frequencies of the model output are studied in three sub-bands within the alpha band: lower alpha (7–9 Hz), middle alpha (9–11 Hz) and upper alpha (11–13 Hz). Such an analytical method conforms to recent comparative EEG studies on young adults, healthy aged adults and MCI or early stage AD patients. The results show a remarkable role of the synaptic connectivities in the inhibitory thalamic cell populations on the alpha band power and frequency. Furthermore, the total number of active synapses in the thalamic cell populations produces the slowing of alpha rhythms and a simultaneous decrease of alpha band power in the brain as a result of AD.",
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A thalamo–cortico–thalamic neural mass model to study alpha rhythms in Alzheimer’s disease. / Bhattacharya, Basab; Coyle, Damien; Maguire, LP.

Vol. 24, No. 6, 08.2011, p. 631-645.

Research output: Contribution to journalArticle

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