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In vivo electrophysiology requires direct access to brain tissue, necessitating the development and refinement of surgical procedures and techniques that promote the health and well-being of animal subjects. Here, we report a series of findings noted on structural magnetic resonance imaging (MRI) scans in monkeys with MRI-compatible implants following small craniotomies that provide access for intracranial electrophysiology. We found distinct brain regions exhibiting hyperintensities in T2-weighted scans that were prominent underneath the sites at which craniotomies had been performed. We interpreted these hyperintensities as edema of the neural tissue and found that they were predominantly present following electric and piezoelectric drilling, but not when manual, hand-operated drills were used. Furthermore, the anomalies subsided within 2-3 wk following surgery. Our report highlights the utility of MRI-compatible implants that promote clinical examination of the animal's brain, sometimes revealing findings that may go unnoticed when incompatible implants are used. We show replicable differences in outcome when using electric versus mechanical devices, both ubiquitous in the field. If electric drills are used, our report cautions against electrophysiological recordings from tissue directly underneath the craniotomy for the first 2-3 wk following the procedure due to putative edema.bNEWamp; NOTEWORTHY/bClose examination of structural MRI in eight nonhuman primates following craniotomy surgeries for intracranial electrophysiology highlights a prevalence of hyperintensities on T2-weighted scans following surgeries conducted using electric and piezoelectric drills, but not when using mechanical, hand-operated drills. We interpret these anomalies as edema of neural tissue that resolved 2-3 wk postsurgery. This finding is especially of interest as electrophysiological recordings from compromised tissue may directly influence the integrity of collected data immediately following surgery.

In-vivo electrophysiology requires direct access to brain tissue, necessitating the development and refinement of surgical procedures and techniques that promote the health and well-being of the animal subjects. Here, we report a series of findings noted on structural magnetic resonance imaging (MRI) scans in monkeys with MRI-compatible implants following small craniotomies that provide access for intracranial electrophysiology. We found distinct brain regions exhibiting hyperintensities in T2-weighted scans that were prominent underneath the sites at which craniotomies had been performed. We interpreted these hyperintensities as edema of the neural tissue and found that they were predominantly present following electric drilling, but not when manual, hand-operated drills were used. Further, the anomalies subsided within 2-3 weeks following surgery. Our report highlights the utility of MRI-compatible implants that promote clinical examination of the animal’s brain, sometimes revealing findings that may go unnoticed when incompatible implants are used. We show replicable differences in outcome when using electric vs. mechanical devices, both ubiquitous in the field. If electric drills are used, our report cautions electrophysiological recordings from tissue directly underneath the craniotomy for the first 2-3 weeks following the procedure due to putative edema.

Contains fulltext : 239574.pdf (Publisher’s version ) (Closed access) Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience. 5 p.

Attention is fundamental to all cognition. In the primate brain, it is implemented by a large-scale network that consists of areas spanning across all major lobes, also including subcortical regions. Classical attention accounts assume that control over the selection process in this network is exerted by 'top-down' mechanisms in the fronto-parietal cortex that influence sensory representations via feedback signals. More recent studies have expanded this view of attentional control. In this review, we will start from a traditional top-down account of attention control, and then discuss more recent findings on feature-based attention, thalamic influences, temporal network dynamics, and behavioral dynamics that collectively lead to substantial modifications. We outline how the different emerging accounts can be reconciled and integrated into a unified theory.

Current models of spoken word recognition have been predominantly based on studies of Indo-European languages. As a result, less is known about the recognition processes involved in the perception of tonal languages (e.g., Mandarin Chinese), and the role of lexical tone in speech perception. One view is that words in tonal languages are processed phonologically through individual segments, while another view is that they are processed lexically as a whole. Moreover, a recent study claimed to be the first to discover an early phonological processing stage in Mandarin (Huang et al., 2014). There seems to be a lack of investigations concerning tonal languages, as no clear conclusions have been reached about the nature of tonal processes, or a model of spoken word recognition that best incorporates lexical tone. The current study addressed these issues by presenting 18 native Mandarin speakers with aural sentences with medial target words. These either matched or mismatched the preceding visually presented sentences with medial target words (e.g, 家 /jia1/home). Violation conditions involved target words that differed in the following ways: tone violation, where only the tone was different (e.g., 价 /jia4/“price”), onset violation, where only the onset was different (e.g., 虾 /xia1/“shrimp”), and syllable violation, where both the tone and the onset were different (e.g., 糖 /tang2/“candy”). We did not find evidence for an early phonological processing stage in Mandarin. Instead, our findings indicate that Mandarin syllables are processed incrementally through phonological segments and that tone is strongly associated with lexical access. These results are discussed with respect to modifications for existing models in spoken word recognition to incorporate the processes involved with tonal language recognition.

There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that event-related potentials (ERPs) measured with electroencephalography (EEG) are persistent neurophysiological markers of past concussions. However, as such evidence is limited to group-level analyzes, the extent to which they enable concussion detection at the individual-level is unclear. One promising avenue of research is the use of machine learning to create quantitative predictive models that can detect prior concussions in individuals. In this paper, we translate the recent group-level findings from ERP studies of concussed individuals into a machine learning framework for performing single-subject prediction of past concussion. We found that a combination of statistics of single-subject ERPs and wavelet features yielded a classification accuracy of 81% with a sensitivity of 82% and a specificity of 80%, improving on current practice. Notably, the model was able to detect concussion effects in individuals who sustained their last injury as much as 30 years earlier. However, failure to detect past concussions in a subset of individuals suggests that the clear effects found in group-level analyses may not provide us with a full picture of the neurophysiological effects of concussion.

A consistent limitation when designing event-related potential paradigms and interpreting results is a lack of consideration of the multivariate factors that affect their elicitation and detection in behaviorally unresponsive individuals. This paper provides a retrospective commentary on three factors that influence the presence and morphology of long-latency event-related potentials—the P3b and N400. We analyze event-related potentials derived from electroencephalographic (EEG) data collected from small groups of healthy youth and healthy elderly to illustrate the effect of paradigm strength and subject age, we analyze ERPs collected from an individual with severe traumatic brain injury to illustrate the effect of stimulus presentation speed. Based on these critical factors, we support that: (1) the strongest paradigms should be used to elicit event-related potentials in unresponsive populations, (2) interpretation of event-related potential results should account for participant age, and (3) speed of stimulus presentation should be slower in unresponsive individuals. The application of these practices when eliciting and recording event-related potentials in unresponsive individuals will help to minimize result interpretation ambiguity, increase confidence in conclusions, and advance the understanding of the relationship between long-latency event-related potentials and states of consciousness.

This cross-linguistic study investigated the impact of spelling errors on reading behavior in five languages (Chinese, English, Finnish, Greek, and Hebrew). Learning theories predict that correct and incorrect spelling alternatives (e.g., "tomorrow" and "tommorrow") provide competing cues to the sound and meaning of a word: The closer the alternatives are to each other in their frequency of occurrence, the more uncertain the reader is regarding the spelling of that word. An information-theoretic measure of entropy was used as an index of uncertainty. Based on theories of learning, we predicted that higher entropy would lead to slower recognition of words even when they are spelled correctly. This prediction was confirmed in eye-tracking sentence-reading experiments in five languages widely variable in their writing systems' phonology and morphology. Moreover, in each language, we observed a characteristic Entropy × Frequency interaction; arguably, its functional shape varied as a function of the orthographic transparency of a given written language. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The current literature presents a discordant view of mild traumatic brain injury and its effects on the human brain. This dissonance has often been attributed to heterogeneities in study populations, aetiology, acuteness, experimental paradigms and/or testing modalities. To investigate the progression of mild traumatic brain injury in the human brain, the present study employed data from 93 subjects (48 healthy controls) representing both acute and chronic stages of mild traumatic brain injury. The effects of concussion across different stages of injury were measured using two metrics of functional connectivity in segments of electroencephalography time-locked to an active oddball task. Coherence and weighted phase-lag index were calculated separately for individual frequency bands (delta, theta, alpha and beta) to measure the functional connectivity between six electrode clusters distributed from frontal to parietal regions across both hemispheres. Results show an increase in functional connectivity in the acute stage after mild traumatic brain injury, contrasted with significantly reduced functional connectivity in chronic stages of injury. This finding indicates a non-linear time-dependent effect of injury. To understand this pattern of changing functional connectivity in relation to prior evidence, we propose a new model of the time-course of the effects of mild traumatic brain injury on the brain that brings together research from multiple neuroimaging modalities and unifies the various lines of evidence that at first appear to be in conflict., We investigate concussion’s effects on the human brain directly after impact and decades post-injury. Functional connectivity between a set of brain areas was heightened in recently concussed subjects and was diminished in subjects who sustained their injuries years prior (compared to age-matched controls). The study highlights the dynamic nature of concussion., Graphical Abstract Graphical Abstract

IntroductionComa is a deep state of unconsciousness that can be caused by a variety of clinical conditions. Traditional tests for coma outcome prediction are based mainly on a set of clinical observations. Recently, certain event-related potentials (ERPs), which are transient electroencephalogram (EEG) responses to auditory, visual or tactile stimuli, have been introduced as useful predictors of a positive coma outcome (ie, emergence). However, such tests require the skills of clinical neurophysiologists, who are not commonly available in many clinical settings. Additionally, none of the current standard clinical approaches have sufficient predictive accuracies to provide definitive prognoses.ObjectiveThe objective of this study is to develop improved machine learning procedures based on EEG/ERP for determining emergence from coma.Methods and analysisData will be collected from 50 participants in coma. EEG/ERP data will be recorded for 24 consecutive hours at a maximum of five time points spanning 30 days from the date of recruitment to track participants’ progression. The study employs paradigms designed to elicit brainstem potentials, middle-latency responses, N100, mismatch negativity, P300 and N400. In the case of patient emergence, data are recorded on that occasion to form an additional basis for comparison. A relevant data set will be developed from the testing of 20 healthy controls, each spanning a 15-hour recording period in order to formulate a baseline. Collected data will be used to develop an automated procedure for analysis and detection of various ERP components that are salient to prognosis. Salient features extracted from the ERP and resting-state EEG will be identified and combined to give an accurate indicator of prognosis.Ethics and disseminationThis study is approved by the Hamilton Integrated Research Ethics Board (project number 4840). Results will be disseminated through peer-reviewed journal articles and presentations at scientific conferences.Trial registration numberNCT03826407.

Concussion has been shown to leave the afflicted with significant cognitive and neurobehavioural deficits. The persistence of these deficits and their link to neurophysiological indices of cognition, as measured by event-related potentials (ERP) using electroencephalography (EEG), remains restricted to population level analyses that limit their utility in the clinical setting. In the present paper, a convolutional neural network is extended to capitalize on characteristics specific to EEG/ERP data in order to assess for post-concussive effects. An aggregated measure of single-trial performance was able to classify accurately (85%) between 26 acutely to post-acutely concussed participants and 28 healthy controls in a stratified 10-fold cross-validation design. Additionally, the model was evaluated in a longitudinal subsample of the concussed group to indicate a dissociation between the progression of EEG/ERP and that of self-reported inventories. Concordant with a number of previous studies, symptomatology was found to be uncorrelated to EEG/ERP results as assessed with the proposed models. Our results form a first-step towards the clinical integration of neurophysiological results in concussion management and motivate a multi-site validation study for a concussion assessment tool in acute and post-acute cases.

Objective The present study sought to determine: 1) whether concussed adolescents exhibited deficits in neurocognitive functioning as reflected by neurophysiological alterations; 2) if neurophysiological alterations could be linked to supplementary data such as the number of previous concussions and days since injury; and 3) if deficits in psychological health and behavioural tests increased during diagnosis duration. Methods Twenty-six concussed adolescents were compared to twenty-eight healthy controls with no prior concussions. Self-report inventories evaluated depressive and concussive symptomatology, while behavioral tests evaluated cognitive ability qualitatively. To assess neurophysiological markers of cognitive function, two separate auditory oddball tasks were employed: 1) an active oddball task measuring executive control and attention as reflected by the N2b and P300, respectively; and 2) a passive oddball task assessing the early, automatic pre-conscious awareness processes as reflected by the MMN. Results Concussed adolescents displayed delayed N2b and attenuated P300 responses relative to controls; showed elevated levels of depressive and concussive symptomatology; scored average-to- low-average in behavioral tests; and exhibited N2b response latencies that correlated with number of days since injury. Conclusion These findings demonstrate that concussed adolescents exhibit clear deficiencies in neurocognitive function, and that N2b response latency may be a marker of concussion recovery.

Objective Recent studies demonstrate that sports-related concussions can have negative consequences on long-term brain health. The goal of the present study was to determine whether retired Canadian Football League (CFL) athletes with a history of concussions exhibit alterations in neurocognitive functioning, along with changes in physical, social, and psychological health. Methods Our study compared nineteen retired CFL athletes’ concussion histories to eighteen healthy age-matched controls with no history of concussion. Self-report inventories were used to assess depression, memory, attention, and general health. Neurophysiological markers of cognitive function were evaluated with event-related brain potentials (ERPs) as measured in two protocols: (1) A Mismatch Negativity (MMN) protocol for assessing the automatic early attentional brain mechanism; and, (2) a P300 auditory oddball task for assessing consciously controlled attention. Results Relative to controls, CFL players exhibited: response delays and reduced amplitudes in neurophysiological responses; overall decreases in cognitive function; and poorer scores on self-reports of physical, social, and psychological health; reflecting problems in all three categories. Conclusion Our findings demonstrate that multiple concussions sustained over several years can lead to altered cognitive and psychosocial function. Significance Neurophysiological markers of conscious and pre-conscious attention provide an objective assessment for evaluating long-term cognitive consequences of concussion.

Background Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings. New method To translate ERP capabilities from the lab to clinical applications, we have developed methods like the Halifax Consciousness Scanner (HCS). HCS is essentially a rapid, automated ERP evaluation of brain functional status. The present study describes the ERP components evoked from auditory tones and speech stimuli. ERP results were obtained using a 5-min test in 100 healthy individuals. The HCS sequence was designed to evoke the N100, the mismatch negativity (MMN), P300, the early negative enhancement (ENE), and the N400. These components reflected sensation, perception, attention, memory, and language perception, respectively. Component detection was examined at group and individual levels, and evaluated across both statistical and classification approaches. Results All ERP components were robustly detected at the group level. At the individual level, nonparametric statistical analyses showed reduced accuracy relative to support vector (SVM) machine classification, particularly for speech-based ERPs. Optimized SVM results were MMN: 95.6%; P300: 99.0%; ENE: 91.8%; and N400: 92.3%. Conclusions A spectrum of individual-level ERPs can be obtained in a very short time. Machine learning classification improved detection accuracy across a large healthy control sample. Translating ERPs into clinical applications is increasingly possible at the individual level.

Event-related potentials (ERPs) are tiny electrical brain responses in the human electroencephalogram that are typically not detectable until they are isolated by a process of signal averaging. Owing to the extremely smallsize of ERP components (ranging from less than 1 μV to tens of μV), compared to background brain rhythms, statistical analyses of ERPs are predominantly carried out in groups of subjects. This limitation is a barrier to the translation of ERP-based neuroscience to applications such as medical diagnostics. We show here that support vector machines (SVMs) are a useful method to detect ERP components in individual subjects with a small set of electrodes and a small number of trials for a mismatch negativity (MMN) ERP component. Such a reduced experiment setup is important for clinical applications. One hundred healthy individuals were presented with an auditory pattern containing pattern-violating deviants to evoke the MMN. Two-class SVMs were then trained to classify averaged ERP waveforms in response to the standard tone (tones that match the pattern) and deviant tone stimuli (tones that violate the pattern). The influence of kernel type, number of epochs, electrode selection, and temporal window size in the averaged waveform were explored. When using all electrodes, averages of all available epochs, and a temporal window from 0 to 900-ms post-stimulus, a linear SVM achieved 94.5 % accuracy. Further analyses using SVMs trained with narrower, sliding temporal windows confirmed the sensitivity of the SVM to data in the latency range associated with the MMN.

Up to 40% of individuals with unresponsive wakefulness syndrome (UWS) actually might be conscious. Recent attempts to detect covert consciousness in behaviorally unresponsive patients via neurophysiological patterns are limited by the need to compare data from brain-­injured patients to healthy controls. In this report, we pilot an alternative within-­subject approach by using propofol to perturb the brain state of a patient diagnosed with UWS. An auditory stimulation series was presented to the patient before, during, and after exposure to propofol while high-­density electroencephalograph (EEG) was recorded. Baseline analysis revealed residual markers in the continuous EEG and event-­related potentials (ERPs) that have been associated with conscious processing. However, these markers were significantly distorted by the patient’s pathology, challenging the interpretation of their functional significance. Upon exposure to propofol, changes in EEG characteristics were similar to what is seen in healthy individuals and ERPs associated with conscious processing disappeared. At the 1-­month follow up, the patient had regained consciousness. We offer three alternative explanations for these results: (1) the patient was covertly consciousness, and was anesthetized by propofol administration; (2) the patient was unconscious, and the observed EEG changes were a propofol-­specific phenomenon; and (3) the patient was unconscious, but his brain networks responded normally in a way that heralded the possibility of recovery. These alternatives will be tested in a larger study, and raise the intriguing possibility of using a general anesthetic as a probe of brain states in behaviorally unresponsive patients.