The Neurodis Foundation Fondation Neurodis

Sainte-Foy-lès-Lyon, France

The Neurodis Foundation Fondation Neurodis

Sainte-Foy-lès-Lyon, France

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Butler C.,University of Oxford | van Erp W.,Nijmegen Medical Center | Bhaduri A.,Highgate Mental Health Center | Hammers A.,The Neurodis Foundation Fondation Neurodis | And 4 more authors.
Epilepsy and Behavior | Year: 2013

Transient epileptic amnesia (TEA) is a recently described epilepsy syndrome characterized by recurrent episodes of isolated memory loss. It is associated with two unusual forms of interictal memory impairment: accelerated long-term forgetting (ALF) and autobiographical amnesia. We investigated the neural basis of TEA using manual volumetry and automated multi-atlas-based segmentation of whole-brain magnetic resonance imaging data from 40 patients with TEA and 20 healthy controls. Both methods confirmed the presence of subtle, bilateral hippocampal atrophy. Additional atrophy was revealed in perirhinal and orbitofrontal cortices. The volumes of these regions correlated with anterograde memory performance. No structural correlates were found for ALF or autobiographical amnesia. The results support the hypothesis that TEA is a focal medial temporal lobe epilepsy syndrome but reveal additional pathology in connected brain regions. The unusual interictal memory deficits of TEA remain unexplained by structural pathology and may reflect physiological disruption of memory networks by subclinical epileptiform activity. © 2013 Elsevier Inc.


Traynor C.,King's College London | Heckemann R.A.,Imperial College London | Heckemann R.A.,The Neurodis Foundation Fondation Neurodis | Hammers A.,Imperial College London | And 5 more authors.
NeuroImage | Year: 2010

Reliable identification of thalamic nuclei is required to improve targeting of electrodes used in Deep Brain Stimulation (DBS), and for exploring the role of thalamus in health and disease. A previously described method using probabilistic tractography to segment the thalamus based on connections to cortical target regions was implemented. Both within- and between-subject reproducibility were quantitatively assessed by the overlap of the resulting segmentations; the effect of two different numbers of target regions (6 and 31) on reproducibility of the segmentation results was also investigated. Very high reproducibility was observed when a single dataset was processed multiple times using different starting conditions. Thalamic segmentation was also very reproducible when multiple datasets from the same subject were processed using six cortical target regions. Within-subject reproducibility was reduced when the number of target regions was increased, particularly in medial and posterior regions of the thalamus. A large degree of overlap in segmentation results from different subjects was obtained, particularly in thalamic regions classified as connecting to frontal, parietal, temporal and pre-central cortical target regions. © 2010 Elsevier Inc.


Gousias I.S.,Imperial College London | Hammers A.,Imperial College London | Hammers A.,The Neurodis Foundation Fondation Neurodis | Counsell S.J.,Imperial College London | And 11 more authors.
PLoS ONE | Year: 2013

We studied methods for the automatic segmentation of neonatal and developing brain images into 50 anatomical regions, utilizing a new set of manually segmented magnetic resonance (MR) images from 5 term-born and 15 preterm infants imaged at term corrected age called ALBERTs. Two methods were compared: individual registrations with label propagation and fusion; and template based registration with propagation of a maximum probability neonatal ALBERT (MPNA). In both cases we evaluated the performance of different neonatal atlases and MPNA, and the approaches were compared with the manual segmentations by means of the Dice overlap coefficient. Dice values, averaged across regions, were 0.81±0.02 using label propagation and fusion for the preterm population, and 0.81±0.02 using the single registration of a MPNA for the term population. Segmentations of 36 further unsegmented target images of developing brains yielded visibly high-quality results. This registration approach allows the rapid construction of automatically labeled age-specific brain atlases for neonates and the developing brain. © 2013 Gousias et al.


Klein-Koerkamp Y.,French National Center for Scientific Research | Heckemann R.A.,Sahlgrenska University Hospital | Heckemann R.A.,The Neurodis Foundation Fondation Neurodis | Heckemann R.A.,Imperial College London | And 11 more authors.
Current Alzheimer Research | Year: 2014

Current research suggests that amygdalar volumes in patients with Alzheimer's disease (AD) may be a relevant measure for its early diagnosis. However, findings are still inconclusive and controversial, partly because studies did not focus on the earliest stage of the disease. In this study, we measured amygdalar atrophy in 48 AD patients and 82 healthy controls (HC) by using a multi-atlas procedure, MAPER. Both hippocampal and amygdalar volumes, normalized by intracranial volume, were significantly reduced in AD compared with HC. The volume loss in the two structures was of similar magnitude (~24%). Amygdalar volume loss in AD predicted memory impairment after we controlled for age, gender, education, and, more important, hippocampal volume, indicating that memory decline correlates with amygdalar atrophy over and above hippocampal atrophy. Amygdalar volume may thus be as useful as hippocampal volume for the diagnosis of early AD. In addition, it could be an independent marker of cognitive decline. The role of the amygdala in AD should be reconsidered to guide further research and clinical practice. © 2014 Bentham Science Publishers.


PubMed | The Neurodis Foundation Fondation Neurodis
Type: Journal Article | Journal: NeuroImage | Year: 2011

This paper presents a novel, publicly available repository of anatomically segmented brain images of healthy subjects as well as patients with mild cognitive impairment and Alzheimers disease. The underlying magnetic resonance images have been obtained from the Alzheimers Disease Neuroimaging Initiative (ADNI) database. T1-weighted screening and baseline images (1.5T and 3T) have been processed with the multi-atlas based MAPER procedure, resulting in labels for 83 regions covering the whole brain in 816 subjects. Selected segmentations were subjected to visual assessment. The segmentations are self-consistent, as evidenced by strong agreement between segmentations of paired images acquired at different field strengths (Jaccard coefficient: 0.8020.0146). Morphometric comparisons between diagnostic groups (normal; stable mild cognitive impairment; mild cognitive impairment with progression to Alzheimers disease; Alzheimers disease) showed highly significant group differences for individual regions, the majority of which were located in the temporal lobe. Additionally, significant effects were seen in the parietal lobe. Increased left/right asymmetry was found in posterior cortical regions. An automatically derived white-matter hypointensities index was found to be a suitable means of quantifying white-matter disease. This repository of segmentations is a potentially valuable resource to researchers working with ADNI data.

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