Search

Itch is a sensation defined as the urge to scratch. The central mechanisms of itch are being increasingly studied. These studies are usually based on experimental itch induction methods, which can be classified into the following categories: histamine‐induced, induction by other non‐histamine chemicals (e.g. cowhage), physically induced (e.g. electrical) and mentally induced (e.g. audio‐visual). Because pain has been more extensively studied, some extrapolations to itch can be proposed and verified by experiments. Recent studies suggest that the itch‐processing network in the brain could be disrupted in certain diseases. This disruption could be related to the implication of new regions or the exclusion of already engaged brain regions from itch‐processing network in the brain. [ABSTRACT FROM AUTHOR]

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

In recent years, studying the central mechanism of itch has gained momentum. However, a proper meta-analysis has not been conducted in this domain. In this study, we tried to respond to this need. A systematic search and a meta-analysis were carried out to estimate the central mechanism of itch. The itch matrix comprises the thalamus and the parietal, secondary somatosensory, insular and cingulate cortices. We have shown that the basal ganglia (BG) play an important role in itch reduction. Finally, we explored itch processing in AD patients and observed that the itch matrix in these patients was different. In conclusion, this is the first meta-analysis on the central mechanisms of itch perception and processing. Our study demonstrated that different modalities of itch induction can produce a common pattern of activity in the brain and provided further insights into understanding the underlying nature of itch central perception., (Copyright © 2019. Published by Elsevier Masson SAS.)

Quantifying the similarity between two networks is critical in many applications. A number of algorithms have been proposed to compute graph similarity, mainly based on the properties of nodes and edges. Interestingly, most of these algorithms ignore the physical location of the nodes, which is a key factor in the context of brain networks involving spatially defined functional areas. In this paper, we present a novel algorithm called "SimiNet" for measuring similarity between two graphs whose nodes are defined a priori within a 3D coordinate system. SimiNet provides a quantified index (ranging from 0 to 1) that accounts for node, edge and spatiality features. Complex graphs were simulated to evaluate the performance of SimiNet that is compared with eight state-of-art methods. Results show that SimiNet is able to detect weak spatial variations in compared graphs in addition to computing similarity using both nodes and edges. SimiNet was also applied to real brain networks obtained during a visual recognition task. The algorithm shows high performance to detect spatial variation of brain networks obtained during a naming task of two categories of visual stimuli: animals and tools. A perspective to this work is a better understanding of object categorization in the human brain.

For efficient information processing during cognitive activity, functional brain networks have to rapidly and dynamically reorganize on a sub-second time scale. Tracking the spatiotemporal dynamics of large scale networks over this short time duration is a very challenging issue. Here, we tackle this problem by using dense electroencephalography (EEG) recorded during a picture naming task. We found that (i) the picture naming task can be divided into six brain network states (BNSs) characterized by significantly high synchronization of gamma (30-45 Hz) oscillations, (ii) fast transitions occur between these BNSs that last from 30 msec to 160 msec, (iii) based on the state of the art of the picture naming task, we consider that the spatial location of their nodes and edges, as well as the timing of transitions, indicate that each network can be associated with one or several specific function (from visual processing to articulation) and (iv) the comparison with previously-used approach aimed at localizing the sources showed that the network-based approach reveals networks that are more specific to the performed task. We speculate that the persistence of several brain regions in successive BNSs participates to fast and efficient information processing in the brain., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The recent past years have seen a noticeable increase of interest for electroencephalography (EEG) to analyze functional connectivity through brain sources reconstructed from scalp signals. Although considerable advances have been done both on the recording and analysis of EEG signals, a number of methodological questions are still open regarding the optimal way to process the data in order to identify brain networks. In this paper, we analyze the impact of three factors that intervene in this processing: i) the number of scalp electrodes, ii) the combination between the algorithm used to solve the EEG inverse problem and the algorithm used to measure the functional connectivity and iii) the frequency bands retained to estimate the functional connectivity among neocortical sources. Using High-Resolution (hr) EEG recordings in healthy volunteers, we evaluated these factors on evoked responses during picture recognition and naming task. The main reason for selection this task is that a solid literature background is available about involved brain networks (ground truth). From this a priori information, we propose a performance criterion based on the number of connections identified in the regions of interest (ROI) that belong to potentially activated networks. Our results show that the three studied factors have a dramatic impact on the final result (the identified network in the source space) as strong discrepancies were evidenced depending on the methods used. They also suggest that the combination of weighted Minimum Norm Estimator (wMNE) and the Phase Synchronization (PS) methods applied on High-Resolution EEG in beta/gamma bands provides the best performance in term of topological distance between the identified network and the expected network in the above-mentioned cognitive task.

BEHAVIORAL AND NEUROPSYCHOLOGICAL RESEARCH IN READING AND SPELLING HAS PROVIDED EVIDENCE FOR THE ROLE OF THE FOLLOWING TYPES OF ORTHOGRAPHIC REPRESENTATIONS IN LETTER WRITING: letter shapes, letter case, and abstract letter identities. We report on the results of an fMRI investigation designed to identify the neural substrates of these different representational types. Using an fMRI adaptation paradigm we examined the neural distribution of inhibition and release from inhibition in a letter-writing task in which, on every trial, participants produced three repetitions of the same letter and a fourth letter that was either identical to (no-change trial) or different from the previous three (change trial). Change trials involved a change in the shape, case, and/or identity of the letter. After delineating the general letter writing network by identifying areas that exhibited significant neural adaptation effects on no-change trials, we used deconvolution analysis to examine this network for effects of release from inhibition on change trials. In this way we identified regions specifically associated with the representation of letter shape (in the left SFS and SFG/pre-CG) and letter identity [in the left fusiform gyrus (FG)] or both [right cerebellum, left post-central gyrus (post-CG), and left middle frontal gyrus (MFG)]. No regions were associated with the representation of letter case. This study showcases an investigational approach that allows for the differentiation of the neurotopography of the representational types that are key to our ability to produce written language.

Background: Cortical and subcortical electrostimulation mapping during awake brain surgery for tumor removal is usually used to minimize deficits., Objective: To use electrostimulation to study neuronal substrates involved in spatial awareness in humans., Methods: Spatial neglect was studied using a line bisection task in combination with electrostimulation mapping of the right hemisphere in 50 cases. Stimulation sites were identified with Talairach coordinates. The behavioral effects induced by stimulation, especially eye movements and deviations from the median, were quantified and compared with preoperative data and a control group., Results: Composite and highly individualized spatial neglect maps were generated. Both rightward and leftward deviations were induced, sometimes in the same patient but for different stimulation sites. Group analysis showed that specific and reproducible line deviations were induced by stimulation of discrete cortical areas located in the posterior part of the right superior and middle temporal gyri, inferior parietal lobe, and inferior postcentral and inferior frontal gyri (P < .05). Fiber tracking identified stimulated subcortical areas important to spare as sections of fronto-occipital and superior longitudinal II fascicles. According to preoperative and postoperative neglect battery tests, the specificity and sensitivity of intraoperative line bisection tests were 94% and 83%, respectively., Conclusion: In humans, discrete cortical areas that are variable in location between individuals but mainly located within the right posterior Sylvian fissure sustain visuospatial attention specifically toward the contralateral or ipsilateral space direction. Line bisection mapping was found to be a reliable method for minimizing spatial neglect caused by brain tumor surgery.

This research is directed at charting the neurotopography of the component processes of the spelling system by using fMRI to identify the neural substrates that are sensitive to the factors of lexical frequency and word length. In spelling, word frequency effects index orthographic long-term memory whereas length effects, as measured by the number of letters, index orthographic working memory (grapheme buffering). Using the task of spelling to dictation in the scanner, we found a highly differentiated neural distribution of sensitivity to the factors of length and lexical frequency, with areas exhibiting sensitivity to length but not frequency and vice versa. In addition, a direct comparison with the results of a previous study [Rapp, B., & Lipka, K. The literate brain: The relationship between spelling and reading. Journal of Cognitive Neuroscience, 23, 1180-1197, 2011] that used a very different spelling task yielded a converging pattern of findings regarding the neural substrates of the central components of spelling. Also, with regard to relationship between reading and spelling, we replicated previous functional neuroimaging studies that have shown overlapping regions of activation in the left posterior inferior frontal gyrus and midfusiform gyrus for word reading and spelling.

Objective: In 1881, Exner first described a "graphic motor image center" in the middle frontal gyrus. Current psycholinguistic models of handwriting involve the conversion of abstract, orthographic representations into motor representations before a sequence of appropriate hand movements is produced. Direct cortical stimulation and functional magnetic resonance imaging (fMRI) were used to study the human frontal areas involved in writing., Methods: Cortical electrical stimulation mapping was used intraoperatively in 12 patients during the removal of brain tumors to identify the areas involved in oral language (sentence reading and naming) and writing, and to spare them during surgery. The fMRI activation experiment involved 12 right-handed and 12 left-handed healthy volunteers using word dictation (without visual control) and 2 control tasks., Results: Direct cortical electrical stimulation of restricted areas rostral to the primary motor hand area (Brodmann area [BA] 6) impaired handwriting in 6 patients, without disturbing hand movements or oral language tasks. In 6 other patients, stimulation of lower frontal regions showed deficits combining handwriting with other language tasks. fMRI also revealed selective activation during word handwriting in left versus right BA6 depending on handedness. This area was anatomically matched to those areas that affected handwriting on electrical stimulation., Interpretation: An area in middle frontal gyrus (BA6) that we have termed the graphemic/motor frontal area supports bridging between orthography and motor programs specific to handwriting.