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Combined EEG-fMRI and tractography to visualise propagation of epileptic activity.

Hamandi K, Powell HW, Laufs H, Symms MR, Barker GJ, Parker GJ, Lemieux L, Duncan JS - J. Neurol. Neurosurg. Psychiatr. (2007)

Bottom Line: Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation.Tractography showed connections from the site of temporal lobe activation to the site of occipital activation.This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, Queen Square, London, UK. hamandik@cardiff.ac.uk

ABSTRACT
In a patient with refractory temporal lobe epilepsy, EEG-fMRI showed activation in association with left anterior temporal interictal discharges, in the left temporal, parietal and occipital lobes. Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation. Tractography showed connections from the site of temporal lobe activation to the site of occipital activation. This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity.

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Two dynamic causal models were constructed, each comprising two structurally connected regions (6 mm diameter spheres), both showing interictal epileptiform discharge (IED)-correlated activation in the conventional SPM fMRI analysis: left parahippocampal gyrus (pHip) and left lingual gyrus (lingG). In both models, pHip and lingG were reciprocally connected. In model A (in bold print), IED acted on pHip and its connection to lingG (IED propagation from temporal to occipital lobe); in model B (grey print), IED acted on lingG and its connection to pHip (IED propagation from occipital to temporal lobe). DCM model comparison revealed strong evidence for model A over model B. In dynamic systems, coupling strength is expressed as a rate—typically, 0.5–1 Hz for regional activity. In both models, intrinsic connectivity was stronger from lingG to pHip (1.19 Hz in A, 0.7 in B) than vice versa (0.66 Hz in A and improbable in B). The induced response of IED on pHip was 0.3 Hz in model A and 0.15 Hz on lingG in model B. Combining both models in one to facilitate direct comparison (data not shown), the probability was 99.8% for IED, inducing a direct response in pHip, but only 61.8% in lingG.
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JNN-79-05-0594-f02: Two dynamic causal models were constructed, each comprising two structurally connected regions (6 mm diameter spheres), both showing interictal epileptiform discharge (IED)-correlated activation in the conventional SPM fMRI analysis: left parahippocampal gyrus (pHip) and left lingual gyrus (lingG). In both models, pHip and lingG were reciprocally connected. In model A (in bold print), IED acted on pHip and its connection to lingG (IED propagation from temporal to occipital lobe); in model B (grey print), IED acted on lingG and its connection to pHip (IED propagation from occipital to temporal lobe). DCM model comparison revealed strong evidence for model A over model B. In dynamic systems, coupling strength is expressed as a rate—typically, 0.5–1 Hz for regional activity. In both models, intrinsic connectivity was stronger from lingG to pHip (1.19 Hz in A, 0.7 in B) than vice versa (0.66 Hz in A and improbable in B). The induced response of IED on pHip was 0.3 Hz in model A and 0.15 Hz on lingG in model B. Combining both models in one to facilitate direct comparison (data not shown), the probability was 99.8% for IED, inducing a direct response in pHip, but only 61.8% in lingG.

Mentions: We used DCM to assess effective connectivity.6 Neuronal activities were modelled using the known inputs (IED) and outputs (BOLD responses measured with fMRI). The specific models were that (i) changes in the states of the left lingual gyrus ([−20, −58, 1], table 1) depend on the activity of the left parahippocampal gyrus [−32, −1, −20], table 1) or (ii) vice versa. This dependency was parameterised by effective connectivity: (i) input parameters that describe how much brain regions respond to IED; (ii) intrinsic parameters that characterise effective connectivity among regions; and (iii) modulatory parameters that characterise changes in effective connectivity, here again due to IED. This third set of parameters, the modulatory effects, allows assessment of changes in coupling between the two brain regions. Two models were constructed (fig 2) based on the above GLM applied to alternate slices of the acquisition, resulting in an effective TR of 1.5 seconds, which is required for DCM. The likelihood of each model explaining the data was assessed using Bayesian statistics.7


Combined EEG-fMRI and tractography to visualise propagation of epileptic activity.

Hamandi K, Powell HW, Laufs H, Symms MR, Barker GJ, Parker GJ, Lemieux L, Duncan JS - J. Neurol. Neurosurg. Psychiatr. (2007)

Two dynamic causal models were constructed, each comprising two structurally connected regions (6 mm diameter spheres), both showing interictal epileptiform discharge (IED)-correlated activation in the conventional SPM fMRI analysis: left parahippocampal gyrus (pHip) and left lingual gyrus (lingG). In both models, pHip and lingG were reciprocally connected. In model A (in bold print), IED acted on pHip and its connection to lingG (IED propagation from temporal to occipital lobe); in model B (grey print), IED acted on lingG and its connection to pHip (IED propagation from occipital to temporal lobe). DCM model comparison revealed strong evidence for model A over model B. In dynamic systems, coupling strength is expressed as a rate—typically, 0.5–1 Hz for regional activity. In both models, intrinsic connectivity was stronger from lingG to pHip (1.19 Hz in A, 0.7 in B) than vice versa (0.66 Hz in A and improbable in B). The induced response of IED on pHip was 0.3 Hz in model A and 0.15 Hz on lingG in model B. Combining both models in one to facilitate direct comparison (data not shown), the probability was 99.8% for IED, inducing a direct response in pHip, but only 61.8% in lingG.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2571962&req=5

JNN-79-05-0594-f02: Two dynamic causal models were constructed, each comprising two structurally connected regions (6 mm diameter spheres), both showing interictal epileptiform discharge (IED)-correlated activation in the conventional SPM fMRI analysis: left parahippocampal gyrus (pHip) and left lingual gyrus (lingG). In both models, pHip and lingG were reciprocally connected. In model A (in bold print), IED acted on pHip and its connection to lingG (IED propagation from temporal to occipital lobe); in model B (grey print), IED acted on lingG and its connection to pHip (IED propagation from occipital to temporal lobe). DCM model comparison revealed strong evidence for model A over model B. In dynamic systems, coupling strength is expressed as a rate—typically, 0.5–1 Hz for regional activity. In both models, intrinsic connectivity was stronger from lingG to pHip (1.19 Hz in A, 0.7 in B) than vice versa (0.66 Hz in A and improbable in B). The induced response of IED on pHip was 0.3 Hz in model A and 0.15 Hz on lingG in model B. Combining both models in one to facilitate direct comparison (data not shown), the probability was 99.8% for IED, inducing a direct response in pHip, but only 61.8% in lingG.
Mentions: We used DCM to assess effective connectivity.6 Neuronal activities were modelled using the known inputs (IED) and outputs (BOLD responses measured with fMRI). The specific models were that (i) changes in the states of the left lingual gyrus ([−20, −58, 1], table 1) depend on the activity of the left parahippocampal gyrus [−32, −1, −20], table 1) or (ii) vice versa. This dependency was parameterised by effective connectivity: (i) input parameters that describe how much brain regions respond to IED; (ii) intrinsic parameters that characterise effective connectivity among regions; and (iii) modulatory parameters that characterise changes in effective connectivity, here again due to IED. This third set of parameters, the modulatory effects, allows assessment of changes in coupling between the two brain regions. Two models were constructed (fig 2) based on the above GLM applied to alternate slices of the acquisition, resulting in an effective TR of 1.5 seconds, which is required for DCM. The likelihood of each model explaining the data was assessed using Bayesian statistics.7

Bottom Line: Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation.Tractography showed connections from the site of temporal lobe activation to the site of occipital activation.This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, Queen Square, London, UK. hamandik@cardiff.ac.uk

ABSTRACT
In a patient with refractory temporal lobe epilepsy, EEG-fMRI showed activation in association with left anterior temporal interictal discharges, in the left temporal, parietal and occipital lobes. Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation. Tractography showed connections from the site of temporal lobe activation to the site of occipital activation. This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity.

Show MeSH
Related in: MedlinePlus