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Copyright © 2020 Tryon, Baker, Long, Rapp and Mizumori.Dihydroartemisinin (DHA) is an active metabolite of sesquiterpene trioxane lactone extracted from Artemisia annua, which is used to treat malaria worldwide. DHA can activate autophagy, which is the main mechanism to remove the damaged cell components and recover the harmful or useless substances from eukaryotic cells and maintain cell viability through the autophagy lysosomal degradation system. Autophagy activation and autophagy flux correction are playing an important neuroprotective role in the central nervous system, as they accelerate the removal of toxic protein aggregates intracellularly and extracellularly to prevent neurodegenerative processes, such as Alzheimer’s disease (AD). In this study, we explored whether this mechanism can mediate the neuroprotective effect of DHA on the AD model in vitro and in vivo. Three months of DHA treatment improved the memory and cognitive impairment, reduced the deposition of amyloid β plaque, reduced the levels of Aβ40 and Aβ42, and ameliorated excessive neuron apoptosis in APP/PS1 mice brain. In addition, DHA treatment increased the level of LC3 II/I and decreased the expression of p62. After Bafilomycin A1 and Chloroquine (CQ) blocked the fusion of autophagy and lysosome, as well as the degradation of autolysosomes (ALs), DHA treatment increased the level of LC3 II/I and decreased the expression of p62. These results suggest that DHA treatment can correct autophagic flux, improve autophagy dysfunction, inhibit abnormal death of neurons, promote the clearance of amyloid-β peptide (Aβ) fibrils, and have a multi-target effect on the neuropathological process, memory and cognitive deficits of AD. Copyright © 2020 Zhao, Long, Ding, Jiang, Liu, Li, Liu, Peng, Wang, Feng and He.Background Integrity of functional brain networks is closely associated with maintained cognitive performance at old age. Consistently, both carrier status of Apolipoprotein E ε4 allele (APOE4), and age-related aggregation of Alzheimer’s disease (AD) pathology result in altered brain network connectivity. The posterior cingulate and precuneus (PCP) is a node of particular interest due to its role in crucial memory processes. Moreover, the PCP is subject to the early aggregation of AD pathology. The current study aimed at characterizing brain network properties associated with unimpaired cognition in old aged adults. To determine the effects of age-related brain change and genetic risk for AD, pathological proteins β-amyloid and tau were measured by Positron-emission tomography (PET), PCP connectivity as a proxy of cognitive network integrity, and genetic risk by APOE4 carrier status. Methods Fifty-seven cognitively unimpaired old-aged adults (MMSE = 29.20 ± 1.11; 73 ± 8.32 years) were administered 11C PittsbuAPOE4. Additional longitudinal studies may determine protective connectivity patterns associated with healthy aging trajectories of AD-pathology aggregation. Copyright © 2020 Quevenco, van Bergen, Treyer, Studer, Kagerer, Meyer, Gietl, Kaufmann, Nitsch, Hock and Unschuld.Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in the design of the biomimicking geometrical configurations and the simulation parameters can lead to approximation biases. Such pitfalls affect the reliability of the estimated signal, as well as its validity and reproducibility as ground truth data. In this work, we first present a set of experiments in order to study three critical pitfalls encountered in the design of MCDS in the literature, namely, the number of simulated particles and time steps, simplifications in the intra-axonal substrate representation, and the impact of the substrate’s size on the signal stemming from the extra-axonal space. The results obtained show important changes in the simulated signals and the recovered microstructure features when changes in those parameters are introduced. Thereupon, driven by our findings from the first studies, we outline a general framework able to generate complex substrates. We show the framework’s capability to overcome the aforementioned simplifications by generating a complex crossing substrate, which preserves the volume in the crossing area and achieves a high packing density. The results presented in this work, along with the simulator developed, pave the way toward more realistic and reproducible Monte-Carlo simulations for Diffusion-Weighted MRI. Copyright © 2020 Rafael-Patino, Romascano, Ramirez-Manzanares, Canales-Rodríguez, Girard and Thiran.Automatic segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) images is essential for clinical assessment and treatment planning of MS. Recent years have seen an increasing use of Convolutional Neural Networks (CNNs) for this task. Although these methods provide accurate segmentation, their applicability in clinical settings remains limited due to a reproducibility issue across different image domains. MS images can have highly variable characteristics across patients, MRI scanners and imaging protocols; retraining a supervised model with data from each new domain is not a feasible solution because it requires manual annotation from expert radiologists. In this work, we explore an unsupervised solution to the problem of domain shift. We present a framework, Seg-JDOT, which adapts a deep model so that samples from a source domain and samples from a target domain sharing similar representations will be similarly segmented. We evaluated the framework on a multi-site dataset, MICCAI 2016, and showed that the adaptation toward a target site can bring remarkable improvements in a model performance over standard training. Copyright © 2020 Ackaouy, Courty, Vallée, Commowick, Barillot and Galassi.For more than 30 years, deep brain stimulation (DBS) has been used to target the symptoms of a number of neurological disorders and in particular movement disorders such as Parkinson’s disease (PD) and essential tremor (ET). It is known that the loss of dopaminergic neurons in the substantia nigra leads to PD, while the exact impact of this on the brain dynamics is not fully understood, the presence of beta-band oscillatory activity is thought to be pathological. The cause of ET, however, remains uncertain, however pathological oscillations in the thalamocortical-cerebellar network have been linked to tremor. Both of these movement disorders are treated with DBS, which entails the surgical implantation of electrodes into a patient’s brain. While DBS leads to an improvement in symptoms for many patients, the mechanisms underlying this improvement is not clearly understood, and computational modeling has been used extensively to improve this. Many of the models used to study DBS and its effect on the human brai induced by DBS, and allow us to optimize this clinical therapy, particularly in terms of target selection and parameter setting. Copyright © 2020 Yousif, Bain, Nandi and Borisyuk.The effects of action observation (AO) on motor performance can be modulated by instruction. The effects of two top-down aspects of the instruction on motor performance have not been fully resolved those related to attention to the observed task and the incorporation of motor imagery (MI) during AO. In addition, the immediate vs. 24-h retention test effects of those instruction’s aspects are yet to be elucidated. Forty-eight healthy subjects were randomly instructed to (1) observe reaching movement (RM) sequences toward five lighted units with the intention of reproducing the same sequence as fast and as accurate as possible (Intentional + Attentional group; AO+At); (2) observe the RMs sequence with the intention of reproducing the same sequence as fast and as accurate as possible and simultaneously to the observation to imagine performing the RMs (Intentional + attentional + MI group; AO+At+MI); and (3) observe the RMs sequence (Passive AO group). Subjects’ performance was tested before and immediately afterove subsequent performance more than passive observation. Off-line learning of the sequence in the retention test was improved in comparison to posttest following passive observation only. PF-06873600 Copyright © 2020 Frenkel-Toledo, Einat and Kozol.Neurofeedback (NFB) is an operant conditioning procedure whereby an individual learns to self-regulate the electrical activity of his/her brain. Initially developed as a treatment intervention for pathologies with underlying EEG dysfunctions, NFB is also used as a training tool to enhance specific cognitive states required in high-performance situations. The original idea behind the NFB training effect is that the changes should only be circumscribed to the trained EEG frequencies. The EEG frequencies which are not used as feedback frequencies should be independent and not affected by the neurofeedback training. Despite the success of sensorimotor rhythm NFB training in cognitive performance enhancement, it remains unclear whether all participants can intentionally modify the power densities of specifically selected electroencephalographic (EEG) frequencies. In the present study, participants were randomly assigned to either a control heart rate variability (HRV) biofeedback (HRV) training group or a combination of HRV biofeedback and neurofeedback (HRV/NFB) training group. This randomized mixed design experiment consisted of two introductory theoretical lessons and a training period of 6 weeks. We investigated the evolution of the different EEG frequency bands of our two experimental groups across and within session. All the participants exhibited EEG changes across and within session. However, within the HRV/NFB training group, untrained EEG frequencies have been significantly modified, unlike some of the trained frequencies. Moreover, EEG activity was modified in both the HRV group and the HRV/NFB groups. Hence, the EEG changes were not only circumscribed to the trained frequency bands or to the training modality. Copyright © 2020 Dessy, Mairesse, van Puyvelde, Cortoos, Neyt and Pattyn.The affective state is the combination of emotion and mood, with mood reflecting a running average of sequential emotional events together with an underlying internal affective state. There is now extensive evidence that odors can overtly or subliminally modulate mood and emotion. Relying primarily on neurobiological literature, here we review what is known about how odors can affect emotions/moods and how emotions/moods may affect odor perception. We take the approach that form can provide insight into function by reviewing major brain regions and neural circuits underlying emotion and mood, and then reviewing the olfactory pathway in the context of that emotion/mood network. We highlight the extensive neuroanatomical opportunities for odor-emotion/mood convergence, as well as functional data demonstrating reciprocal interactions between these processes. Finally, we explore how the odor- emotion/mood interplay is, or could be, used in medical and/or commercial applications. Copyright © 2020 Kontaris, East and Wilson.The anatomo-physiological disruptions inherent to different categories of the Fetal Alcohol Spectrum Disorder do not encompass all the negative consequences derived from intrauterine ethanol (EtOH) exposure. Preclinical, clinical and epidemiological studies show that prenatal EtOH exposure also results in early programming of alcohol affinity. This affinity has been addressed through the examination of how EtOH prenatally exposed organisms recognize and prefer the drug’s chemosensory cues and their predisposition to exhibit heightened voluntary EtOH intake during infancy and adolescence. In altricial species these processes are determined by the interaction of at least three factors during stages equivalent to the 2nd and 3rd human gestational trimester (i) fetal processing of the drug’s olfactory and gustatory attributes present in the prenatal milieu; (ii) EtOH’s recruitment of central reinforcing effects that also imply progressive sensitization to the drug’s motivational properties; and (iii) an associative learning process involving the prior two factors.