Barrerasalisbury4682

The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.Texture information plays a critical role in the rapid perception of scenes, objects, and materials. Here, we propose a novel model in which visual texture perception is essentially determined by the 1st-order (2D-luminance) and 2nd-order (4D-energy) spectra. This model is an extension of the dimensionality of the Filter-Rectify-Filter (FRF) model, and it also corresponds to the frequency representation of the Portilla-Simoncelli (PS) statistics. We show that preserving two spectra and randomizing phases of a natural texture image result in a perceptually similar texture, strongly supporting the model. Based on only two single spectral spaces, this model provides a simpler framework to describe and predict texture representations in the primate visual system. The idea of multi-order spectral analysis is consistent with the hierarchical processing principle of the visual cortex, which is approximated by a multi-layer convolutional network.The inclusion of music into the treatment plan for persons with Parkinson's disease (PD) may be a viable strategy to target multiple motor symptoms. However, potential mechanisms to explain why music has an impact on multiple motor symptoms in persons with PD remain understudied. The purpose of this study was to examine the acute effects of 1 h of group therapeutic singing (GTS) on physiological measures of stress and clinical motor symptoms in persons with PD. We posit that improvement in motor symptoms after GTS may be related to stress reduction. Seventeen participants with PD completed 1 h of GTS and eight participants completed 1 h of a quiet reading (control session). Cortisol was collected via passive drool immediately before and after the singing and control session. The Unified Parkinson's Disease Rating Scale (UPDRS) Part-III (motor examination) was also video-recorded immediately before and after the singing and control session and scored by two raters masked to time and condition. Secondary outcome measures for quality of life, depression, and mood were collected. Results revealed no significant change in cortisol or motor UPDRS scores, as well as no significant relationship between cortisol and motor UPDRS scores. There was a trend for the singing group to report feeling less sad compared to the control group after the 1-h session (effect size = 0.86), and heart rate increased in the singing group while heart rate decreased in the control group after the 1-h session. These results suggest that an acute session of GTS is not unduly stressful and promotes the use of GTS for persons with PD. Multiple mechanisms may underlie the benefits of GTS for persons with PD. Further exploring potential mechanisms by which singing improves motor symptoms in persons with PD will provide greater insight on the therapeutic use of music for persons with PD.Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.The ability to produce novel ideas is central to societal progress and innovation; however, little is known about the biological basis of creativity. Here, we investigate the organization of brain networks that support creativity by combining functional neuroimaging data with gene expression information. Given the multifaceted nature of creative thinking, we hypothesized that distributed connectivity would not only be related to individual differences in creative ability, but also delineate the cortical distributions of genes involved in synaptic plasticity. We defined neuroimaging phenotypes using a graph theory approach that detects local and distributed network circuits, then characterized the spatial associations between functional connectivity and cortical gene expression distributions. Our findings reveal strong spatial correlations between connectivity maps and sets of genes devoted to synaptic assembly and signaling. This connectomic-transcriptome approach thus identifies gene expression profiles associated with high creative ability, linking cognitive flexibility to neural plasticity in the human brain.Behavioral and neuroimaging studies show that people trust and collaborate with others based on a quick assessment of the facial appearance. Based on the morphological characteristics of the face, i.e., features, shape, or color, it is possible to determine health, attractiveness, trust, and some personality traits. The study attempts to indicate the features influencing the perception of attractiveness and trust. In order to select individual factors, a model of backward stepwise logistic regression was used, analyzing the results of the psychological tests and the attractiveness and trust survey. Statistical analysis made it possible to select the most important personality traits related to attractiveness and trust assessments.The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types database. The study is conducted on two different levels neurons and their cell-type aggregation into Cre lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre lines. Moreover, the proposed methodology locates other Cre lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.Resting-state neural oscillations are used as biomarkers for functional diseases such as dementia, epilepsy, and stroke. However, accurate interpretation of clinical outcomes requires the identification and minimisation of potential confounding factors. While several studies have indicated that the menstrual cycle also alters brain activity, most of these studies were based on visual inspection rather than objective quantitative measures. In the present study, we aimed to clarify the effect of the menstrual cycle on spontaneous neural oscillations based on quantitative magnetoencephalography (MEG) parameters. Resting-state MEG activity was recorded from 25 healthy women with normal menstrual cycles. For each woman, resting-state brain activity was acquired twice using MEG once during their menstrual period (MP) and once outside of this period (OP). Our results indicated that the median frequency and peak alpha frequency of the power spectrum were low, whereas Shannon spectral entropy was high, during the MP. Theta intensity within the right temporal cortex and right limbic system was significantly lower during the MP than during the OP. High gamma intensity in the left parietal cortex was also significantly lower during the MP than during the OP. Similar differences were also observed in the parietal and occipital regions between the proliferative (the late part of the follicular phase) and secretory phases (luteal phase). Our findings suggest that the menstrual cycle should be considered to ensure accurate interpretation of functional neuroimaging in clinical practice.

Chronic fatigue is a prominent symptom in many sarcoidosis patients, affecting quality of life and interfering with treatment. This study investigated neuropsychobiological mechanisms and markers of chronic fatigue in sarcoidosis.

Thirty patients with a histological diagnosis of sarcoidosis were included. The Multidimensional Fatigue Inventory was used to define patients with and without chronic fatigue. All patients were then characterised using several depression, quality of life questionnaires, and executive functioning. Cognitive functioning and underlying neural correlates were assessed using an n-back task measuring working memory and (sustained) attention during functional magnetic resonance imaging. Sarcoidosis disease activity was determined using lung function, laboratory parameters, and exercise capacity.

Nineteen patients had chronic fatigue and 11 did not; both groups had similar demographic and disease activity characteristics. Chronic fatigue patients showed more symptoms of depression aner 26, 2019, retrospectively registeredURL https//clinicaltrials.gov/ct2/show/NCT04178239.[This corrects the article DOI 10.3389/fnint.2021.662293.].The programmed cell death protein-1/programmed death ligand-1 (PD-1/PD-L1) axis is a widely studied immune checkpoint that modulates signaling pathways related to T cell activation. Dabrafenib The use of PD-1/PD-L1 inhibitors is a promising immune therapy strategy for cancer patients. However, individuals treated with PD-1/PD-L1 inhibitors may develop immune-related adverse events due to excessive immune reactions. Multiple sclerosis (MS) is a chronic demyelinating and neurodegenerative disease of the central nervous system. T cells and the PD-1/PD-L1 axis play vital roles in the pathogenesis of MS. A better understanding of the complex relationship between the PD-1/PD-L1 axis and T cells may extend our knowledge of the molecular mechanisms and therapeutic approaches for MS. In this review, we summarize the most recent findings regarding the role of the PD-1/PD-L1 axis in MS and discuss the potential therapeutic strategies to modulate the expression of PD-1/PD-L1 in MS.The pedunculopontine nucleus (PPN), a structure known as a cholinergic member of the reticular activating system (RAS), is source and target of cholinergic neuromodulation and contributes to the regulation of the sleep-wakefulness cycle. The M-current is a voltage-gated potassium current modulated mainly by cholinergic signaling. KCNQ subunits ensemble into ion channels responsible for the M-current. In the central nervous system, KCNQ4 expression is restricted to certain brainstem structures such as the RAS nuclei. Here, we investigated the presence and functional significance of KCNQ4 in the PPN by behavioral studies and the gene and protein expressions and slice electrophysiology using a mouse model lacking KCNQ4 expression. We found that this mouse has alterations in the adaptation to changes in light-darkness cycles, representing the potential role of KCNQ4 in the regulation of the sleep-wakefulness cycle. As cholinergic neurons from the PPN participate in the regulation of this cycle, we investigated whether the cholinergic PPN might also possess functional KCNQ4 subunits.