Cognitive impairment in amyotrophic lateral sclerosis (ALS) is heterogeneous but now recognized as a feature in non-demented patients and no longer exclusively attributed to executive dysfunction. However, despite common reports of temporal lobe changes and memory deficits in ALS, episodic memory has been less explored. In the current study, we examined how the Papez circuit-a circuit known to participate in memory processes-is structurally and functionally affected in ALS patients (n = 20) compared with healthy controls (n = 15), and whether these changes correlated with a commonly used clinical measure of episodic memory. Our multimodal MRI approach (cortical volume, voxel-based morphometry, diffusion tensor imaging and resting state functional magnetic resonance) showed reduced gray matter in left hippocampus, left entorhinal cortex and right posterior cingulate as well as increased white matter fractional anisotropy and decreased mean diffusivity in the left cingulum bundle (hippocampal part) of ALS patients compared with controls. Interestingly, thalamus, mammillary bodies and fornix were preserved. Finally, we report a decreased functional connectivity in ALS patients in bilateral hippocampus, bilateral anterior and posterior parahippocampal gyrus and posterior cingulate. The results revealed that ALS patients showed statistically significant structural changes, but more important, widespread prominent functional connectivity abnormalities across the regions comprising the Papez circuit. The decreased functional connectivity found in the Papez network may suggest these changes could be used to assess risk or assist early detection or development of memory symptoms in ALS patients even before structural changes are established.

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Resting state functional magnetic resonance imaging (rs-fMRI) has been playing an important role in the study of amyotrophic lateral sclerosis (ALS). Although functional connectivity is widely studied, the patterns of spontaneous neural activity of the resting brain are important mechanisms that have been used recently to study a variety of conditions but remain less explored in ALS. Here we have used fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) to study the regional dynamics of the resting brain of non-demented ALS patients compared with healthy controls. As expected, we found the sensorimotor network (SMN) with changes in fALFF and ReHo but also found the default mode (DMN), frontoparietal (FPN), salience (SN) networks altered and the cerebellum, although no structural changes between ALS patients and controls were reported in the regions with fALFF and ReHo changes. We show an altered pattern in the spontaneous low frequency oscillations that is not confined to the motor areas and reveal a more widespread involvement of nonmotor regions, including those responsible for cognition.

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Amyotrophic lateral sclerosis and behavioural variant frontotemporal dementia are two different diseases recognized to overlap at clinical, pathological and genetic characteristics. Both conditions are traditionally known for relative sparing of episodic memory. However, recent studies have disputed that with the report of patients presenting with marked episodic memory impairment. Besides that, structural and functional changes in temporal lobe regions responsible for episodic memory processing are often detected in neuroimaging studies of both conditions. In this study, we investigated the gray matter features associated with the Papez circuit in amyotrophic lateral sclerosis, behavioural variant frontotemporal dementia and healthy controls to further explore similarities and differences between the two conditions. Our non-demented amyotrophic lateral sclerosis patients showed no episodic memory deficits measured by a short-term delayed recall test while no changes in gray matter of the Papez circuit were found. Compared with the amyotrophic lateral sclerosis group, the behavioural variant frontotemporal dementia group had lower performance on the short-term delayed recall test and marked atrophy in gray matter of the Papez circuit. Bilateral atrophy of entorhinal cortex and mammillary bodies distinguished behavioural variant frontotemporal dementia from amyotrophic lateral sclerosis patients as well as atrophy in left cingulate, left hippocampus and right parahippocampal gyrus. Taken together, our results suggest that sub-regions of the Papez circuit could be differently affected in amyotrophic lateral sclerosis and behavioural variant frontotemporal dementia.

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Detection of underling proteinopathies is becoming increasingly important across neurodegenerative conditions due to upcoming disease intervention trials. In this review, we explored how temporal lobe changes in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) can potentially predict underlying TDP-43 pathology subtypes in FTD. To date, emphasis has been given to frontal lobe changes in the study of the cognitive and behavioural impairments in both syndromes but an increasing number of pathological, imaging and neuropsychological studies suggest how temporal lobe changes could critically affect the cognition and behaviour of these conditions. In this current article, we reviewed pathological, imaging as well as clinical/neuropsychological findings of temporal involvement in the ALS-FTD continuum, how they relate to temporal lobe changes and the underlying TDP-43 pathology in FTD. Findings across studies show that TDP-43 pathology occurs and coincides in many structures in ALS and FTD, but especially in the temporal lobes. In particular, anterior and medial temporal lobes atrophy is consistently found in ALS and FTD. In addition, memory and language impairment as well as emotional and Theory of Mind processing deficits that are characteristics of the two diseases are highly correlated to temporal lobe dysfunction. We conclude by showing that temporal lobe changes due to TDP-43 type B might be particular predictive of TDP-43 type B pathology in behavioural variant FTD, which clearly needs to be investigated further in the future.

The prevalence of health problems during childhood and adolescence is high in developing countries such as Brazil. Social inequality, violence, and malnutrition have strong impact on youth health. To better understand these issues we propose to combine machine-learning methods and graph analysis to build predictive networks applied to the Brazilian National Student Health Survey (PenSE 2015) data, a large dataset that consists of questionnaires filled by the students. By using a combination of gradient boosting machines and centrality hub metric, it was possible to identify potential confounders to be considered when conducting association analyses among variables. The variables were ranked according to their hub centrality to predict the other variables from a directed weighted-graph perspective. The top five ranked confounder variables were "gender", "oral health care", "intended education level", and two variables associated with nutrition habits-"eat while watching TV" and "never eat fast-food". In conclusion, although causal effects cannot be inferred from the data, we believe that the proposed approach might be a useful tool to obtain novel insights on the association between variables and to identify general factors related to health conditions.