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. 2011 Oct 15;58(4):1121-30.
doi: 10.1016/j.neuroimage.2011.06.085. Epub 2011 Jul 7.

Heterogeneity of functional activation during memory encoding across hippocampal subfields in temporal lobe epilepsy

Affiliations

Heterogeneity of functional activation during memory encoding across hippocampal subfields in temporal lobe epilepsy

Sandhitsu R Das et al. Neuroimage. .

Abstract

Pathology studies have shown that the anatomical subregions of the hippocampal formation are differentially affected in various neurological disorders, including temporal lobe epilepsy (TLE). Analysis of structure and function within these subregions using magnetic resonance imaging (MRI) has the potential to generate insights on disease associations as well as normative brain function. In this study, an atlas-based normalization method (Yushkevich, P.A., Avants, B.B., Pluta, J., Das, S., Minkoff, D., Mechanic-Hamilton, D., Glynn, S., Pickup, S., Liu, W., Gee, J.C., Grossman, M., Detre, J.A., 2009. A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T. NeuroImage 44 (2), 385-398) was used to label hippocampal subregions, making it possible to examine subfield-level functional activation during an episodic memory task in two different cohorts of healthy controls and subjects diagnosed with intractable unilateral TLE. We report, for the first time, functional activation patterns within hippocampal subfields in TLE. We detected group differences in subfield activation between patients and controls as well as inter-hemispheric activation asymmetry within subfields in patients, with dentate gyrus (DG) and the anterior hippocampus region showing the greatest effects. DG was also found to be more active than CA1 in controls, but not in patients' epileptogenic side. These preliminary results will encourage further research on the utility of subfield-based biomarkers in TLE.

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Figures

Fig. 1
Fig. 1
Postmortem atlas (top) and an example of normalization of an in vivo image (bottom). From left to right: sagittal MRI slice, coronal MRI slice, whole hippocampus label, subfield labels, and subfield labels with head, body and tail regions separately rendered to facilitate visualization of internal structures.
Fig. 2
Fig. 2
An example of subfield labels (left) and volume rendering of the task contrast map (right) in the hippocampus of a subject. Hotter colors indicate greater task-related activation.
Fig. 3
Fig. 3
Group differences in activation within ROI: Activation is generally greater in non-epileptogenic (contralateral, red) side than epileptogenic (ipsilateral, magenta) side in patients, with largest effect in HIPP, DG and HEAD. Activations aren’t significantly different between left (green) and right (blue) sides in controls, except in TAIL in the TLE-HR dataset. Lines connecting bars with stars on top indicate significant group difference (p<0.05 uncorrected) in activation between the two groups. Red stars denote the significant differences at an FDR-corrected threshold of p<0.05. p-values are shown in each case. Activation in controls is averaged over left and right sides for the purpose of comparing with patients’ contralateral or ipsilateral sides.
Fig. 4
Fig. 4
Within-group differences in functional activation between DG and CA1 subfields. DG has significantly greater activation in controls in both sides. There is no such significant group difference in activation between DG and CA1 in the epileptogenic side of patients in both datasets. Activations are normalized by the respective subfield volumes.
Fig. 5
Fig. 5
Boxplots showing activation asymmetry index within ROIs computed as (left − right)/(left + right). Data from TLE-HR and TLE-SR are shown separately. Each panel shows data from left TLE (LTLE) on the left, right TLE (RTLE) in the middle and controls (CTL) on the right. Patients show lateralization consistent with seizure side in the whole hippocampus, as well as several subfields, with the strongest effects in DG and HEAD. Controls do not show significant asymmetric activation within any ROI – AI isn’t significantly different from zero in any subfield. p-values for significant separation of AI between LTLE and RTLE are indicated. “* ” indicates those below the threshold at a false discovery rate (FDR) = 0.05.

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