ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude (�100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure

Multiple indices of diffusion identifies white matter damage in mild cognitive impairment and Alzheimer's disease

The study of multiple indices of diffusion, including axial (DA), radial (DR) and mean diffusion (MD), as well as fractional anisotropy (FA), enables WM damage in Alzheimer's disease (AD) to be assessed in detail. Here, tract-based spatial statistics (TBSS) were performed on scans of 40 healthy elders, 19 non-amnestic MCI (MCIna) subjects, 14 amnestic MCI (MCIa) subjects and 9 AD patients. Significantly higher DA was found in MCIna subjects compared to healthy elders in the right posterior cingulum/precuneus. Significantly higher DA was also found in MCIa subjects compared to healthy elders in the left prefrontal cortex, particularly in the forceps minor and uncinate fasciculus. In the MCIa versus MCIna comparison, significantly higher DA was found in large areas of the left prefrontal cortex. For AD patients, the overlap of FA and DR changes and the overlap of FA and MD changes were seen in temporal, parietal and frontal lobes, as well as the corpus callosum and fornix. Analysis of differences between the AD versus MCIna, and AD versus MCIa contrasts, highlighted regions that are increasingly compromised in more severe disease stages. Microstructural damage independent of gross tissue loss was widespread in later disease stages. Our findings suggest a scheme where WM damage begins in the core memory network of the temporal lobe, cingulum and prefrontal regions, and spreads beyond these regions in later stages. DA and MD indices were most sensitive at detecting early changes in MCIa

Visual Target Modulation of Functional Connectivity Networks Revealed by Self-Organizing Group ICA

We applied a data-driven analysis based on self-organizing group independent component analysis (sogICA) to fMRI data from a three-stimulus visual oddball task. SogICA is particularly suited to the investigation of the underlying functional connectivity and does not rely on a predefined model of the experiment, which overcomes some of the limitations of hypothesis-driven analysis. Unlike most previous applications of ICA in functional imaging, our approach allows the analysis of the data at the group level, which is of particular interest in high order cognitive studies. SogICA is based on the hierarchical clustering of spatially similar independent components, derived from single subject decompositions. We identified four main clusters of components, centered on the posterior cingulate, bilateral insula, bilateral prefrontal cortex, and right posterior parietal and prefrontal cortex, consistently across all participants. Post hoc comparison of time courses revealed that insula, prefrontal cortex and right fronto-parietal components showed higher activity for targets than for distractors. Activation for distractors was higher in the posterior cingulate cortex, where deactivation was observed for targets. While our results conform to previous neuroimaging studies, they also complement conventional results by showing functional connectivity networks with unique contributions to the task that were consistent across subjects. SogICA can thus be used to probe functional networks of active cognitive tasks at the group-level and can provide additional insights to generate new hypotheses for further study

Association between Psychotic Symptoms and Cortical Thickness Reduction across the Schizophrenia Spectrum

The current study provides a complete MRI analysis of thickness throughout the cerebral cortical mantle in patients with schizophrenia (SZ) and rigorously screened and matched unaffected relatives and controls and an assessment of its relation to psychopathology and subjective cognitive function. We analyzed 3D-anatomical magnetic resonance imaging data sets, obtained at 3 Tesla, from three different subject groups: 25 SZ patients, 29 first-degree relatives and 37 healthy control subjects. We computed whole-brain cortical thickness using the Freesurfer software and assessed group differences. We also acquired clinical and psychometric data. The results showed markedly reduced cortical thickness in SZ patients compared with controls, most notably in the frontal and temporal lobes, in the superior parietal lobe and several limbic areas, with intermediate levels of cortical thickness in relatives. In both patients and relatives, we found an association between subjective cognitive dysfunction and reduced thickness of frontal cortex, and predisposition towards hallucinations and reduced thickness of the superior temporal gyrus. Our findings suggest that changes in specific cortical areas may predispose to specific symptoms, as exemplified by the association between temporal cortex thinning and hallucinations

Tracking the mind's image in the brain II: Differential effects of repetitive transcranial magnetic stimulation of the right and left parietal lobe.

The functional relevance of brain activity during visuospatial tasks was investigated by combining functional magnetic resonance imaging with unilateral repetitive transcranial magnetic stimulation (rTMS). The cognitive tasks involved visuospatial operations on visually presented and mentally imagined material (“mental clock task”). While visuospatial operations were associated with activation of the intraparietal sulcus region bilaterally, only the group which received rTMS to the right parietal lobe showed an impairment of performance during and immediately after rTMS. This functional parietal asymmetry might indicate a capacity of the right parietal lobe to compensate for a temporary suppression of the left. This is compatible with current theories of spatial hemineglect and constitutes a constraint for models of distributed information processing in the parietal lobes

Using Support Vector Machines with Multiple Indices of Diffusion for Automated Classification of Mild Cognitive Impairment

Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical

Altered apolipoprotein C expression in association with cognition impairments and hippocampus volume in schizophrenia and bipolar disorder

Proteomic analyses facilitate the interpretation of molecular biomarker probes which are very helpful in diagnosing schizophrenia (SZ). In the current study, we attempt to test whether potential differences in plasma protein expressions in SZ and bipolar disorder (BD) are associated with cognitive deficits and their underlying brain structures. Forty-two plasma proteins of 29 SZ patients, 25 BD patients and 93 non-clinical controls were quantified and analysed using multiple reaction monitoring-based triple quadrupole mass spectrometry approach. We also computed group comparisons of protein expressions between patients and controls, and between SZ and BD patients, as well. Potential associations of protein levels with cognitive functioning (psychomotor speed, executive functioning, crystallised intelligence) as well as underlying brain volume in the hippocampus were explored, using bivariate correlation analyses. The main finding of this study was that apolipoprotein expression differed between patients and controls and that these alterations in both disease groups were putatively related to cognitive impairments as well as to hippocampus volumes. However, none of the protein level differences were related to clinical symptom severity. In summary, altered apolipoprotein expression in BD and SZ was linked to cognitive decline and underlying morphological changes in both disorders. Our results suggest that the detection of molecular patterns in association with cognitive performance and its underlying brain morphology is of great importance for understanding of the pathological mechanisms of SZ and BD, as well as for supporting the diagnosis and treatment of both disorders

Transcriptome Analysis of Synaptoneurosomes Identifies Neuroplasticity Genes Overexpressed in Incipient Alzheimer's Disease

In Alzheimer's disease (AD), early deficits in learning and memory are a consequence of synaptic modification induced by toxic beta-amyloid oligomers (oAβ). To identify immediate molecular targets downstream of oAβ binding, we prepared synaptoneurosomes from prefrontal cortex of control and incipient AD (IAD) patients, and isolated mRNAs for comparison of gene expression. This novel approach concentrates synaptic mRNA, thereby increasing the ratio of synaptic to somal mRNA and allowing discrimination of expression changes in synaptically localized genes. In IAD patients, global measures of cognition declined with increasing levels of dimeric Aβ (dAβ). These patients also showed increased expression of neuroplasticity related genes, many encoding 3′UTR consensus sequences that regulate translation in the synapse. An increase in mRNA encoding the GluR2 subunit of the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) was paralleled by elevated expression of the corresponding protein in IAD. These results imply a functional impact on synaptic transmission as GluR2, if inserted, maintains the receptors in a low conductance state. Some overexpressed genes may induce early deficits in cognition and others compensatory mechanisms, providing targets for intervention to moderate the response to dAβ

Sexual Dimorphism in Healthy Aging and Mild Cognitive Impairment: A DTI Study

Previous PET and MRI studies have indicated that the degree to which pathology translates into clinical symptoms is strongly dependent on sex with women more likely to express pathology as a diagnosis of AD, whereas men are more resistant to clinical symptoms in the face of the same degree of pathology. Here we use DTI to investigate the difference between male and female white matter tracts in healthy older participants (24 women, 16 men) and participants with mild cognitive impairment (21 women, 12 men). Differences between control and MCI participants were found in fractional anisotropy (FA), radial diffusion (DR), axial diffusion (DA) and mean diffusion (MD). A significant main effect of sex was also reported for FA, MD and DR indices, with male control and male MCI participants having significantly more microstructural damage than their female counterparts. There was no sex by diagnosis interaction. Male MCIs also had significantly less normalised grey matter (GM) volume than female MCIs. However, in terms of absolute brain volume, male controls had significantly more brain volume than female controls. Normalised GM and WM volumes were found to decrease significantly with age with no age by sex interaction. Overall, these data suggest that the same degree of cognitive impairment is associated with greater structural damage in men compared with women