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We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification of hippocampal shape features. This approach uses spherical harmonics (SPHARM) coefficients to model the shape of the hippocampi, which are segmented from magnetic resonance images (MRI) using a fully automatic method that we previously developed. SPHARM coefficients are used as features in a classification procedure based on support vector machines (SVM). The most relevant features for classification are selected using a bagging strategy. We evaluate the accuracy of our method in a group of 23 patients with AD (10 males, 13 females, age±standard-deviation (SD)=73±6 years, mini-mental score (MMS)=24.4±2.8), 23 patients with amnestic MCI (10 males, 13 females, age±SD=74±8 years, MMS=27.3±1.4) and 25 elderly healthy controls (13 males, 12 females, age±SD=64±8 years), using leave-one-out cross-validation. For AD vs controls, we obtain a correct classification rate of 94%, a sensitivity of 96%, and a specificity of 92%. For MCI vs controls, we obtain a classification rate of 83%, a sensitivity of 83%, and a specificity of 84%. This accuracy is superior to that of hippocampal volumetry and is comparable to recently published SVM-based whole-brain classification methods, which relied on a different strategy. This new method may become a useful tool to assist in the diagnosis of Alzheimer's disease.

Acetylcholinesterase inhibitors are approved drugs currently used for the treatment of Alzheimer’s disease (AD) dementia. Basal forebrain cholinergic system (BFCS) atrophy is reported to precede both entorhinal cortex atrophy and memory impairment in AD, challenging the traditional model of the temporal sequence of topographical pathology associated with AD. We studied the effect of one-year Donepezil treatment on the rate of BFCS atrophy in prodromal AD patients using a double-blind, randomized, placebo-controlled trial of Donepezil (10 mg/day). Reduced annual BFCS rates of atrophy were found in the Donepezil group compared to the Placebo treated arm. Secondary analyses on BFCS subregions demonstrated the largest treatment effects in the Nucleus Basalis of Meynert (NbM) and the medial septum/diagonal band (Ch1/2). Donepezil administered at a prodromal stage of AD seems to substantially reduce the rate of atrophy of the BFCS nuclei with highest concentration of cholinergic neurons projecting to the cortex (NbM), hippocampus and entorhinal cortex (Ch1/2).

There is a growing need for surrogate biomarkers for Parkinson’s disease (PD). Structural analysis using magnetic resonance imaging with T1-weighted sequences has the potential to quantify histopathological changes. Degeneration is typically measured by the volume and shape of morphological changes. However, these changes appear late in the disease, preventing their use as surrogate markers. We investigated texture changes in 108 individuals, divided into three groups, matched in terms of sex and age: (1) healthy controls (n = 32); (2) patients with early-stage PD (n = 39); and (3) patients with late-stage PD and severe L-dopa-related complications (n = 37). All patients were assessed in off-treatment conditions. Statistical analysis of first- and second-order texture features was conducted in the substantia nigra, striatum, thalamus and sub-thalamic nucleus. Regions of interest volumetry and voxel-based morphometry were performed for comparison. Significantly different texture features were observed between the three populations, with some showing a gradual linear progression between the groups. The volumetric changes in the two PD patient groups were not significantly different. Texture features were significantly associated with clinical scores for motor handicap. These results suggest that texture features, measured in the nigrostriatal pathway at PD diagnosis, may be useful in predicting clinical progression of motor handicap.

According to meta-analyses, depression is associated with a smaller hippocampus. Most magnetic resonance imaging (MRI) studies among middle aged acute depressed patients are based on manual segmentation of the hippocampus. Few studies used automated methods such as voxel-based morphometry (VBM) or automated segmentation that can overcome certain drawbacks of manual segmentation (essentially intra- and inter-rater variability and operator time consumption). The aim of our study was to compare the sensitivity of manual segmentation, automated segmentation and VBM to detect hippocampal structural changes in middle aged acute depressed population. Twenty-one middle aged depressed inpatients and 21 matched controls were compared regarding their hippocampal structure using VBM with SPM5, manual segmentation and an automated segmentation algorithm. The VBM-ROI analysis was performed using two different normalization methods: the standard approach implemented in SPM5 and the most recent DARTEL algorithm. Using VBM-DARTEL, when corrected for multiple comparisons, significant volume differences were detected between groups in different regions and more specifically in hippocampus with ROI analyses. Whereas using standard VBM (without DARTEL), ROI analyses did not show bilateral volume between group differences. Significant hippocampal volume reductions between patients and controls were also detected using manual segmentation (− 11.6% volume reduction, p < 0.05) and automated segmentation (− 9.7% volume reduction, p < 0.05). VBM-DARTEL and automated segmentation show equal sensitivity in detecting hippocampal differences in depressed patients, while standard VBM was unable to detect hippocampal changes. Both VBM-DARTEL and automated segmentation could be used to perform large scale volumetric studies in humans. The new automated segmentation technique could further explore and detect hippocampal subpart differences that could be very useful for clarifying physiopathology of psychiatric disorders.

Background Isolated subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are the prodromal phases of dementia with Lewy bodies (DLB). MEMENTO is a nationwide study of patients with SCI and MCI with clinic, neuropsychology, biology, and brain imaging data. We aimed to compare SCI and MCI patients with symptoms of prodromal DLB to others in this study at baseline. Methods Participants of the French MEMENTO cohort study were recruited for either SCI or MCI. Among them, 892 were included in the Lewy sub-study, designed to search specifically for symptoms of DLB. Probable prodromal DLB diagnosis (pro-DLB group) was done using a two-criteria cutoff score among the four core clinical features of DLB. This Pro-DLB group was compared to two other groups at baseline: one without any core symptoms (NS group) and the one with one core symptom (1S group). A comprehensive cognitive battery, questionnaires on behavior, neurovegetative and neurosensory symptoms, brain 3D volumetric MRI, CSF, FDG PET, and amyloid PET were done. Results The pro-DLB group comprised 148 patients (16.6%). This group showed more multidomain (59.8%) MCI with slower processing speed and a higher proportion of patients with depression, anxiety, apathy, constipation, rhinorrhea, sicca syndrome, and photophobia, compared to the NS group. The pro-DLB group had isolated lower P-Tau in the CSF (not significant after adjustments for confounders) and on brain MRI widening of sulci including fronto-insular, occipital, and olfactory sulci (FDR corrected), when compared to the NS group. Evolution to dementia was not different between the three groups over a median follow-up of 2.6 years. Conclusions Patients with symptoms of prodromal DLB are cognitively slower, with more behavioral disorders, autonomic symptoms, and photophobia. The occipital, fronto-insular, and olfactory bulb involvement on brain MRI was consistent with symptoms and known neuropathology. The next step will be to study the clinical, biological, and imaging evolution of these patients. Trial registration Clinicaltrials.gov , NCT01926249

Amygdala is a key brain region for face perception. While the role of amygdala in the perception of facial emotion and gaze has been extensively highlighted with fMRI, the unfolding in time of amydgala responses to emotional versus neutral faces with different gaze directions is scarcely known. Here we addressed this question in healthy subjects using MEG combined with an original source imaging method based on individual amygdala volume segmentation and the localization of sources in the amygdala volume. We found an early peak of amygdala activity that was enhanced for fearful relative to neutral faces between 130 and 170 ms. The effect of emotion was again significant in a later time range (310-350 ms). Moreover, the amygdala response was greater for direct relative averted gaze between 190 and 350 ms, and this effect was selective of fearful faces in the right amygdala. Altogether, our results show that the amygdala is involved in the processing and integration of emotion and gaze cues from faces in different time ranges, thus underlining its role in multiple stages of face perception.

Background One out of three patients with schizophrenia failed to respond adequately to antipsychotics and continue to experience debilitating symptoms such as auditory hallucinations and negative symptoms. The development of additional therapeutic approaches for these persistent symptoms constitutes a major goal for patients. Here, we develop a randomized-controlled trial testing the efficacy of high-frequency transcranial random noise stimulation (hf-tRNS) for the treatment of resistant/persistent symptoms of schizophrenia in patients with various profiles of symptoms, cognitive deficits and illness duration. We also aim to investigate the biological and cognitive effects of hf-tRNS and to identify the predictors of clinical response. Methods In a randomized, double-blind, 2-arm parallel-group, controlled, multicentre study, 144 patients with schizophrenia and persistent symptoms despite the prescription of at least one antipsychotic treatment will be randomly allocated to receive either active ( n = 72) or sham ( n = 72) hf-tRNS. hf-tRNS (100–500 Hz) will be delivered for 20 min with a current intensity of 2 mA and a 1-mA offset twice a day on 5 consecutive weekdays. The anode will be placed over the left dorsolateral prefrontal cortex and the cathode over the left temporoparietal junction. Patients’ symptoms will be assessed prior to hf-tRNS (baseline), after the 10 sessions, and at 1-, 3- and 6-month follow-up. The primary outcome will be the number of responders defined as a reduction of at least 25% from the baseline scores on the Positive and Negative Syndrome Scale (PANSS) after the 10 sessions. Secondary outcomes will include brain activity and connectivity, source monitoring performances, social cognition, other clinical (including auditory hallucinations) and biological variables, and attitude toward treatment. Discussion The results of this trial will constitute a first step toward establishing the usefulness of hf-tRNS in schizophrenia whatever the stage of the illness and the level of treatment resistance. We hypothesize a long-lasting effect of active hf-tRNS on the severity of schizophrenia symptoms as compared to sham. This trial will also have implications for the use of hf-tRNS as a preventive intervention of relapse in patients with schizophrenia. Trial registration ClinicalTrials.gov NCT02744989. Prospectively registered on 20 April 2016

White matter hyperintensities (WMH) on T2 or FLAIR sequences have been commonly observed on MR images of elderly people. They have been associated with various disorders and have been shown to be a strong risk factor for stroke and dementia. WMH studies usually required visual evaluation of WMH load or time-consuming manual delineation. This paper introduced WHASA (White matter Hyperintensities Automated Segmentation Algorithm), a new method for automatically segmenting WMH from FLAIR and T1 images in multicentre studies. Contrary to previous approaches that were based on intensities, this method relied on contrast: non linear diffusion filtering alternated with watershed segmentation to obtain piecewise constant images with increased contrast between WMH and surroundings tissues. WMH were then selected based on subject dependant automatically computed threshold and anatomical information. WHASA was evaluated on 67 patients from two studies, acquired on six different MRI scanners and displaying a wide range of lesion load. Accuracy of the segmentation was assessed through volume and spatial agreement measures with respect to manual segmentation; an intraclass correlation coefficient (ICC) of 0.96 and a mean similarity index (SI) of 0.72 were obtained. WHASA was compared to four other approaches: Freesurfer and a thresholding approach as unsupervised methods; k-nearest neighbours (kNN) and support vector machines (SVM) as supervised ones. For these latter, influence of the training set was also investigated. WHASA clearly outperformed both unsupervised methods, while performing at least as good as supervised approaches (ICC range: 0.87-0.91 for kNN; 0.89-0.94 for SVM. Mean SI: 0.63-0.71 for kNN, 0.67-0.72 for SVM), and did not need any training set.

Neuroimaging studies show the hippocampus is a crucial node in the neural network supporting episodic autobiographical memory retrieval. Stress-related psychiatric disorders, namely Major Depression and Post Traumatic Stress Disorder (PTSD), are related to reduced hippocampus volume. However, this is not the case for remitted breast cancer patients with co-morbid stress-related psychiatric disorders. This exception may be due to the fact that, consequently to the cancer experience as such, this population might already be characterized by a reduced hippocampus with an episodic autobiographical memory deficit. We scanned, with a 3T Siemens TRIO, 16 patients who had lived through a \"standard experience of breast cancer\" (breast cancer and a standard treatment in remission since 18 month) in the absence of any associated stress-related psychiatric or neurological disorder and 21 matched controls. We then assessed their episodic autobiographical memory retrieval ability. Remitted breast cancer patients had both a significantly smaller hippocampus and a significant deficit in episodic autobiographical memory retrieval. The hippocampus atrophy was characterized by a smaller posterior hippocampus. The posterior hippocampus volume was intimately related to the ability to retrieve negative memories and to the past experience of breast cancer or not. These results provide two main findings: (1) we identify a new population with a specific reduction in posterior hippocampus volume that is independent of any psychiatric or neurological pathology; (2) we show the intimate relation of the posterior hippocampus to the ability to retrieve episodic autobiographical memories. These are significant findings as it is the first demonstration that indicates considerable long-term effects of living through the experience of breast cancer and shows very specific hippocampal atrophy with a functional deficit without any presence of psychiatric pathology.

Background This work aimed to investigate the potential pathways involved in the association between social and lifestyle factors, biomarkers of Alzheimer’s disease and related dementia (ADRD), and cognition. Methods The authors studied 2323 participants from the Memento study, a French nationwide clinical cohort. Social and lifestyle factors were education level, current household incomes, physical activity, leisure activities, and social network from which two continuous latent variables were computed: an early to midlife (EML) and a latelife (LL) indicator. Brain magnetic resonance imaging (MRI), lumbar puncture, and amyloid-positron emission tomography (PET) were used to define three latent variables: neurodegeneration, small vessel disease (SVD), and AD pathology. Cognitive function was defined as the underlying factor of a latent variable with four cognitive tests. Structural equation models were used to evaluate cross-sectional pathways between social and lifestyle factors and cognition. Results Participants’ mean age was 70.9 years old, 62% were women, 28% were apolipoprotein-ε4 carriers, and 59% had a Clinical Dementia Rating (CDR) score of 0.5. Higher early to midlife social indicator was only directly associated with better cognitive function (direct β  = 0.364 (0.322; 0.405), with no indirect pathway through ADRD biomarkers (total β  = 0.392 (0.351; 0.429)). In addition to a direct effect on cognition (direct β  = 0.076 (0.033; 0.118)), the association between latelife lifestyle indicator and cognition was also mostly mediated by an indirect effect through lower neurodegeneration (indirect β  = 0.066 (0.042; 0.090) and direct β  =  − 0.116 (− 0.153; − 0.079)), but not through AD pathology nor SVD. Conclusions Early to midlife social factors are directly associated with higher cognitive functions. Latelife lifestyle factors may help preserve cognitive functions through lower neurodegeneration.