Robust correlation analyses: false positive and power validation using a new open source matlab toolbox

The anterior cingulate cortex is involved in intero-exteroceptive integration for spatial image transformation of the self-body

Spatial image transformation of the self-body is a fundamental function of visual perspective-taking. Recent research underscores the significance of intero-exteroceptive information integration to construct representations of our embodied self. This raises the intriguing hypothesis that interoceptive processing might be involved in the spatial image transformation of the self-body. To test this hypothesis, the present study used functional magnetic resonance imaging to measure brain activity during an arm laterality judgment (ALJ) task. In this task, participants were tasked with discerning whether the outstretched arm of a human figure, viewed from the front or back, was the right or left hand. The reaction times for the ALJ task proved longer when the stimulus presented orientations of 0°, 90°, and 270° relative to the upright orientation, and when the front view was presented rather than the back view. Reflecting the increased reaction time, increased brain activity was manifested in a cluster centered on the dorsal anterior cingulate cortex (ACC), suggesting that the activation reflects the involvement of an embodied simulation in ALJ. Furthermore, this cluster of brain activity exhibited overlap with regions where the difference in activation between the front and back views positively correlated with the participants' interoceptive sensitivity, as assessed through the heartbeat discrimination task, within the pregenual ACC. These results suggest that the ACC plays an important role in integrating intero-exteroceptive cues to spatially transform the image of our self-body.

Individual Alpha Frequency Contributes to the Precision of Human Visual Processing

Brain oscillatory activity within the alpha band has been associated with a wide range of processes encompassing perception, memory, decision-making, and overall cognitive functioning. Individual alpha frequency (IAF) is a specific parameter accounting for the mean velocity of the alpha cycling activity, conventionally ranging between ∼7 and ∼13 Hz. One influential hypothesis has proposed a fundamental role of this cycling activity in the segmentation of sensory input and in the regulation of the speed of sensory processing, with faster alpha oscillations resulting in greater temporal resolution and more refined perceptual experience. However, although several recent theoretical and empirical studies would support this account, contradictory evidence suggests caution and more systematic approaches in the assessment and interpretation of this hypothesis. For example, it remains to be explored to what degree IAF shapes perceptual outcomes. In the present study, we investigated whether inter-individual differences in bias-free visual contrast detection threshold in a large sample of individuals in the general population (n = 122) could be explained by inter-individual differences in alpha pace. Our results show that the contrast needed to correctly identify target stimuli (individual perceptual threshold) is associated with alpha peak frequency (not amplitude). Specifically, individuals who require reduced contrast show higher IAF than individuals requiring higher contrasts. This suggests that inter-individual differences in alpha frequency contribute to performance variability in low-level perceptual tasks, supporting the hypothesis that IAF underlies a fundamental temporal sampling mechanism that shapes visual objective performance, with higher frequencies promoting enhanced sensory evidence per time unit.

Electrophysiological analysis of signal detection outcomes emphasizes the role of decisional factors in recognition memory

Introduction

Event-related potential (ERP) studies have identified two time windows associated with recognition memory and interpreted them as reflecting two processes: familiarity and recollection. However, using relatively simple stimuli and achieving high recognition rates, most studies focused on hits and correct rejections. This leaves out some information (misses and false alarms) that according to Signal Detection Theory (SDT) is necessary to understand signal processing.

Methods

We used a difficult visual recognition task with colored pictures of different categories to obtain enough of the four possible SDT outcomes and analyzed them with modern ERP methods.

Results

Non-parametric analysis of these outcomes identified a single time window (470 to 670 ms) which reflected activity within fronto-central and posterior-left clusters of electrodes, indicating differential processing. The posterior-left cluster significantly distinguished all STD outcomes. The fronto-central cluster only distinguished ERPs according to the subject's response: yes vs. no. Additionally, only electrophysiological activity within the posterior-left cluster correlated with the discrimination index (d').

Discussion

We show that when all SDT outcomes are examined, ERPs of recognition memory reflect a single-time window that may reveal a bottom-up factor discriminating the history of items (i.e. memory strength), as well as a top-down factor indicating participants' decision.

GABA, glutamatergic dynamics and BOLD contrast assessed concurrently using functional MRS during a cognitive task

A recurring issue in functional neuroimaging is how to link task-driven haemodynamic blood oxygen level dependent functional MRI (BOLD-fMRI) responses to underlying neurochemistry at the synaptic level. Glutamate and γ-aminobutyric acid (GABA), the major excitatory and inhibitory neurotransmitters respectively, are typically measured with MRS sequences separately from fMRI, in the absence of a task. The present study aims to resolve this disconnect, developing acquisition and processing techniques to simultaneously assess GABA, glutamate and glutamine (Glx) and BOLD in relation to a cognitive task, at 3 T. Healthy subjects (N = 81) performed a cognitive task (Eriksen flanker), which was presented visually in a task-OFF, task-ON block design, with individual event onset timing jittered with respect to the MRS readout. fMRS data were acquired from the medial anterior cingulate cortex during task performance, using an adapted MEGA-PRESS implementation incorporating unsuppressed water-reference signals at a regular interval. These allowed for continuous assessment of BOLD activation, through T2 *-related changes in water linewidth. BOLD-fMRI data were additionally acquired. A novel linear model was used to extract modelled metabolite spectra associated with discrete functional stimuli, building on well established processing and quantification tools. Behavioural outcomes from the flanker task, and activation patterns from the BOLD-fMRI sequence, were as expected from the literature. BOLD response assessed through fMRS showed a significant correlation with fMRI, specific to the fMRS-targeted region of interest; fMRS-assessed BOLD additionally correlated with lengthening of response time in the incongruent flanker condition. While no significant task-related changes were observed for GABA+, a significant increase in measured Glx levels (~8.8%) was found between task-OFF and task-ON periods. These findings verify the efficacy of our protocol and analysis pipelines for the simultaneous assessment of metabolite dynamics and BOLD. As well as establishing a robust basis for further work using these techniques, we also identify a number of clear directions for further refinement in future studies.

EEG-based biomarkers predict individual differences in TMS-induced entrainment of intrinsic brain rhythms

BACKGROUND

Entrainment (increase) and modulation (shift) of intrinsic brain oscillations via rhythmic-TMS (rh-TMS) enables to either increase the amplitude of the individual peak oscillatory frequency, or experimentally slowing/accelerating this intrinsic peak oscillatory frequency by slightly shifting it. Both entrainment, and modulation of brain oscillations can lead to different measurable perceptual and cognitive changes. However, there are noticeable between-participant differences in such experimental entrainment outcomes.

OBJECTIVE/HYPOTHESIS

The current study aimed at explaining these inter-individual differences in entrainment/frequency shift success. Here we hypothesize that the width and the height of the Arnold tongue, i.e., the frequency offsets that can still lead to oscillatory change, can be individually modelled via resting-state neural markers, and may explain and predict efficacy and limitation of successful rhythmic-TMS (rh-TMS) manipulation.

METHODS

Spectral decomposition of resting-state data was used to extract the spectral curve of alpha activity, serving as a proxy of an individual Arnold tongue. These parameters were then used as predictors of the rh-TMS outcome, when increasing alpha-amplitude (i.e., applying pulse train tuned to the individual alpha frequency, IAF), or modulating the alpha-frequency (i.e., making alpha faster or slower by stimulating at IAF±1Hz frequencies).

RESULTS

Our results showed that the height of the at-rest alpha curve predicted how well the entrainment increased the intrinsic oscillatory peak frequency, with a higher at-rest spectral curve negatively predicting amplitude-enhancement during entrainment selectively during IAF-stimulation. In contrast, the wider the resting-state alpha curve, the higher the modulation effects aiming to shift the intrinsic frequency towards faster or slower rhythms.

CONCLUSION

These results not only offer a theoretical and experimental model for explaining the variance across different rh-TMS studies reporting heterogenous rh-TMS outcomes, but also introduce a potential biomarker and corresponding evaluative tool to develop most optimal and personalized rh-TMS protocols, both in research and clinical applications.

A spatial-attentional mechanism underlies action-related distortions of time judgment

Temporal binding has been understood as an illusion in timing judgment. When an action triggers an outcome (e.g. a sound) after a brief delay, the action is reported to occur later than if the outcome does not occur, and the outcome is reported to occur earlier than a similar outcome not caused by an action. We show here that an attention mechanism underlies the seeming illusion of timing judgment. In one method, participants watch a rotating clock hand and report event times by noting the clock hand position when the event occurs. We find that visual spatial attention is critically involved in shaping event time reports made in this way. This occurs because action and outcome events result in shifts of attention around the clock rim, thereby biasing the perceived location of the clock hand. Using a probe detection task to measure attention, we show a difference in the distribution of visual spatial attention between a single-event condition (sound only or action only) and a two-event agency condition (action plus sound). Participants accordingly report the timing of the same event (the sound or the action) differently in the two conditions: spatial attentional shifts masquerading as temporal binding. Furthermore, computational modeling based on the attention measure can reproduce the temporal binding effect. Studies that use time judgment as an implicit marker of voluntary agency should first discount the artefactual changes in event timing reports that actually reflect differences in spatial attention. The study also has important implications for related results in mental chronometry obtained with the clock-like method since Wundt, as attention may well be a critical confounding factor in the interpretation of these studies.

Agreeableness modulates mental state decoding: Electrophysiological evidence

Agreeableness is one of the five personality traits which is associated with theory of mind (ToM) abilities. One of the critical processes involved in ToM is the decoding of emotional cues. In the present study, we investigated whether this process is modulated by agreeableness using electroencephalography (EEG) while taking into account task complexity and sex differences that are expected to moderate the relationship between emotional decoding and agreeableness. This approach allowed us to identify at which stage of the neural processing agreeableness kicks in, in order to distinguish the impact on early, perceptual processes from slower, inferential processing. Two tasks were employed and submitted to 62 participants during EEG recording: the reading the mind in the eyes (RME) task, requiring the decoding of complex mental states from eye expressions, and the biological (e)motion task, involving the perception of basic emotional actions through point-light body stimuli. Event-related potential (ERP) results showed a significant correlation between agreeableness and the contrast for emotional and non-emotional trials in a late time window only during the RME task. Specifically, higher levels of agreeableness were associated with a deeper neural processing of emotional versus non-emotional trials within the whole and male samples. In contrast, the modulation in females was negligible. The source analysis highlighted that this ERP-agreeableness association engages the ventromedial prefrontal cortex. Our findings expand previous research on personality and social processing and confirm that sex modulates this relationship.

Time for What? Dissociating Explicit Timing Tasks through Electrophysiological Signatures

Estimating durations between hundreds of milliseconds and seconds is essential for several daily tasks. Explicit timing tasks, which require participants to estimate durations to make a comparison (time for perception) or to reproduce them (time for action), are often used to investigate psychological and neural timing mechanisms. Recent studies have proposed that mechanisms may depend on specific task requirements. In this study, we conducted electroencephalogram (EEG) recordings on human participants as they estimated intervals in different task contexts to investigate the extent to which timing mechanisms depend on the nature of the task. We compared the neural processing of identical visual reference stimuli in two different tasks, in which stimulus durations were either perceptually compared or motorically reproduced in separate experimental blocks. Using multivariate pattern analyses, we could successfully decode the duration and the task of reference stimuli. We found evidence for both overlapping timing mechanisms across tasks as well as recruitment of task-dependent processes for comparing intervals for different purposes. Our findings suggest both core and specialized timing functions are recruited to support explicit timing tasks.

Assessing the integrity of auditory sensory memory processing in CLN3 disease (Juvenile Neuronal Ceroid Lipofuscinosis (Batten disease)): an auditory evoked potential study of the duration-evoked mismatch negativity (MMN)

BACKGROUND

We interrogated auditory sensory memory capabilities in individuals with CLN3 disease (juvenile neuronal ceroid lipofuscinosis), specifically for the feature of "duration" processing. Given decrements in auditory processing abilities associated with later-stage CLN3 disease, we hypothesized that the duration-evoked mismatch negativity (MMN) of the event related potential (ERP) would be a marker of progressively atypical cortical processing in this population, with potential applicability as a brain-based biomarker in clinical trials.

METHODS

We employed three stimulation rates (fast: 450 ms, medium: 900 ms, slow: 1800 ms), allowing for assessment of the sustainability of the auditory sensory memory trace. The robustness of MMN directly relates to the rate at which the regularly occurring stimulus stream is presented. As presentation rate slows, robustness of the sensory memory trace diminishes. By manipulating presentation rate, the strength of the sensory memory trace is parametrically varied, providing greater sensitivity to detect auditory cortical dysfunction. A secondary hypothesis was that duration-evoked MMN abnormalities in CLN3 disease would be more severe at slower presentation rates, resulting from greater demand on the sensory memory system.

RESULTS

Data from individuals with CLN3 disease (N = 21; range 6-28 years of age) showed robust MMN responses (i.e., intact auditory sensory memory processes) at the medium stimulation rate. However, at the fastest rate, MMN was significantly reduced, and at the slowest rate, MMN was not detectable in CLN3 disease relative to neurotypical controls (N = 41; ages 6-26 years).

CONCLUSIONS

Results reveal emerging insufficiencies in this critical auditory perceptual system in individuals with CLN3 disease.

The Impact of Linguistic Prediction Violations on Downstream Recognition Memory and Sentence Recall

Predicting upcoming words during language comprehension not only affects processing in the moment but also has consequences for memory, although the source of these memory effects (e.g., whether driven by lingering pre-activations, re-analysis following prediction violations, or other mechanisms) remains underspecified. Here, we investigated downstream impacts of prediction on memory in two experiments. First, we recorded EEG as participants read strongly and weakly constraining sentences with expected, unexpected but plausible, or semantically anomalous endings ("He made a holster for his gun / father / train") and were tested on their recognition memory for the sentence endings. Participants showed similar rates of false alarms for predicted but never presented sentence endings whether the prediction violation was plausible or anomalous, suggesting that these arise from pre-activation of the expected words during reading. During sentence reading, especially in strongly constraining sentences, plausible prediction violations elicited an anterior positivity; anomalous endings instead elicited a posterior positivity, whose amplitude was predictive of later memory for those anomalous words. ERP patterns at the time of recognition differentiated plausible and anomalous sentence endings: Words that had been plausible prediction violations elicited enhanced late positive complex amplitudes, suggesting greater episodic recollection, whereas anomalous sentence endings elicited greater N1 amplitudes, suggesting attentional tagging. In a follow-up behavioral study, a separate group of participants read the same sentence stimuli and were tested for sentence-level recall. We found that recall of full sentences was impaired when sentences ended with a prediction violation. Taken together, the results suggest that prediction violations draw attention and affect encoding of the violating word, in a manner that depends on plausibility, and that this, in turn, may impair future memory of the gist of the sentence.

Differences in eye movements for face recognition between Canadian and Chinese participants are not modulated by social orientation

Face recognition strategies do not generalize across individuals. Many studies have reported robust cultural differences between West Europeans/North Americans and East Asians in eye movement strategies during face recognition. The social orientation hypothesis posits that individualistic vs. collectivistic (IND/COL) value systems, respectively defining West European/North American and East Asian societies, would be at the root of many cultural differences in visual perception. Whether social orientation is also responsible for such cultural contrast in face recognition remains to be clarified. To this aim, we conducted two experiments with West European/North American and Chinese observers. In Experiment 1, we probed the existence of a link between IND/COL social values and eye movements during face recognition, by using an IND/COL priming paradigm. In Experiment 2, we dissected the latter relationship in greater depth, by using two IND/COL questionnaires, including subdimensions to those concepts. In both studies, cultural differences in fixation patterns were revealed between West European/North American and East Asian observers. Priming IND/COL values did not modulate eye movement visual sampling strategies, and only specific subdimensions of the IND/COL questionnaires were associated with distinct eye-movement patterns. Altogether, we show that the typical contrast between IND/COL cannot fully account for cultural differences in eye movement strategies for face recognition. Cultural differences in eye movements for faces might originate from mechanisms distinct from social orientation.

Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students' Attention and the Estimation of Academic Performance in Secondary School

The level of student attention in class greatly affects their academic performance. Teachers typically rely on visual inspection to react to students' attention in time, but this subjective method leads to inconsistencies across classes. Online education exacerbates the issue as students can turn off cameras and microphones to keep their own privacy. To address this, we present a novel, low-cost EEG-based platform for assessing students' attention and estimating their academic performance. In a study involving 34 secondary school students (aged 14 to 16), participants watched an academic video and answered evaluation questions while their EEG activity was recorded using a commercial headset. The results demonstrate a significant correlation (0.53, p-value = 0.003) between the power spectral density (PSD) of the EEG beta band (12-30 Hz) and students' academic performance. Additionally, there was a notable difference in PSD-beta between high and low academic performers. These findings encourage the use of PSD-beta for the immediate and objective assessment of both the student attention and the subsequent academic performance. The platform offers valuable and objective feedback to teachers, enhancing the effectiveness of both face-to-face and online teaching and learning environments.

Correlations for untargeted GC × GC-HRTOF-MS metabolomics of colorectal cancer

INTRODUCTION

Modern comprehensive instrumentations provide an unprecedented coverage of complex matrices in the form of high-dimensional, information rich data sets.

OBJECTIVES

In addition to the usual biomarker research that focuses on the detection of the studied condition, we aimed to define a proper strategy to conduct a correlation analysis on an untargeted colorectal cancer case study with a data set of 102 variables corresponding to metabolites obtained from serum samples analyzed with comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOF-MS). Indeed, the strength of association existing between the metabolites contains potentially valuable information about the molecular mechanisms involved and the underlying metabolic network associated to a global perturbation, at no additional analytical effort.

METHODS

Following Anscombe's quartet, we took particular attention to four main aspects. First, the presence of non-linear relationships through the comparison of parametric and non-parametric correlation coefficients: Pearson's r, Spearman's rho, Kendall's tau and Goodman-Kruskal's gamma. Second, the visual control of the detected associations through scatterplots and their associated regressions and angles. Third, the effect and handling of atypical samples and values. Fourth, the role of the precision of the data on the attribution of the ranks through the presence of ties.

RESULTS

Kendall's tau was found the method of choice for the data set at hand. Its application highlighted 17 correlations significantly altered in the active state of colorectal cancer (CRC) in comparison to matched healthy controls (HC), from which 10 were specific to this state in comparison to the remission one (R-CRC) investigated on distinct patients. 15 metabolites involved in the correlations of interest, on the 25 unique ones obtained, were annotated (Metabolomics Standards Initiative level 2).

CONCLUSIONS

The metabolites highlighted could be used to better understand the pathology. The systematic investigation of the methodological aspects that we expose allows to implement correlation analysis to various fields and many specific cases.

Identifying critical kinematic features of animate motion and contribution to animacy perception

Humans can distinguish flying birds from drones based solely on motion features when no image information is available. However, it remains unclear which motion features of animate motion induce our animacy perception. To address this, we first analyzed the differences in centroid motion between birds and drones, and discovered that birds exhibit greater acceleration, angular speed, and trajectory fluctuations. We further determined the order of their importance in evoking animacy perception was trajectory fluctuations, acceleration, and speed. More interestingly, people judge whether a moving object is alive using a feature-matching strategy, implying that animacy perception is induced in a key feature-triggered way rather than relying on the accumulation of evidence. Our findings not only shed light on the critical motion features that induce animacy perception and their relative contributions but also have important implications for developing target classification algorithms based on motion features.

Changing connectivity between premotor and motor cortex changes inter-areal communication in the human brain

The ventral premotor cortex (PMv) is an important component of cortico-cortical pathways mediating prefrontal control over primary motor cortex (M1) function. Paired associative stimulation (ccPAS) is known to change PMv influence over M1 in humans, which manifests differently depending on the behavioural context. Here we show that these changes in influence are functionally linked to PMv-M1 phase synchrony changes induced by repeated paired stimulation of the two areas. PMv-to-M1 ccPAS leads to increased phase synchrony in alpha and beta bands, while reversed order M1-to-PMv ccPAS leads to decreased theta phase synchrony. These changes are visible at rest but are predictive of changes in oscillatory power in the same frequencies during movement execution and inhibition, respectively. The results unveil a link between the physiology of the motor network and the resonant frequencies mediating its interactions and provide a putative mechanism underpinning the relationship between synaptic efficacy and brain oscillations.

Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models

The alpha rhythm is often associated with relaxed wakefulness or idling and is altered by various factors. Abnormalities in the alpha rhythm have been linked to several neurological and psychiatric disorders, including Alzheimer's disease. Transcranial alternating current stimulation (tACS) has been proposed as a potential tool to restore a disrupted alpha rhythm in the brain by stimulating at the individual alpha frequency (IAF), although some research has produced contradictory results. In this study, we applied an IAF-tACS protocol over parieto-occipital areas to a sample of healthy subjects and measured its effects over the power spectra. Additionally, we used computational models to get a deeper understanding of the results observed in the experiment. Both experimental and numerical results showed an increase in alpha power of 8.02% with respect to the sham condition in a widespread set of regions in the cortex, excluding some expected parietal regions. This result could be partially explained by taking into account the orientation of the electric field with respect to the columnar structures of the cortex, showing that the gyrification in parietal regions could generate effects in opposite directions (hyper-/depolarization) at the same time in specific brain regions. Additionally, we used a network model of spiking neuronal populations to explore the effects that these opposite polarities could have on neural activity, and we found that the best predictor of alpha power was the average of the normal components of the electric field. To sum up, our study sheds light on the mechanisms underlying tACS brain activity modulation, using both empirical and computational approaches. Non-invasive brain stimulation techniques hold promise for treating brain disorders, but further research is needed to fully understand and control their effects on brain dynamics and cognition. Our findings contribute to this growing body of research and provide a foundation for future studies aimed at optimizing the use of non-invasive brain stimulation in clinical settings.

Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial

BACKGROUND

Cognitive flexibility refers to the capacity to shift between conceptual representations particularly in response to changes in instruction and feedback. It enables individuals to swiftly adapt to changes in their environment and has significant implications for learning. The present study focuses on investigating changes in cognitive flexibility following an intervention programme-Structure Learning training.

METHODS

Participants are pseudo-randomised to either the Training or Control group, while matched on age, sex, intelligence and cognitive flexibility performance. In the Training group, participants undergo around 2 weeks of training (at least 13 sessions) on Structure Learning. In the Control group, participants do not have to undergo any training and are never exposed to the Structure Learning task. The effects of Structure Learning training are investigated at both the behavioural and neural level. We measured covariates that can influence an individual's training performance before the training phase and outcome measures that can potentially show training benefits after the training phase. At the behavioural level, we investigated outcomes in both cognitive and social aspects with a primary focus on executive functions. At the neural level, we employed a multimodality approach and investigated potential changes to functional connectivity patterns, neurometabolite concentration in the frontal brain regions, and brain microstructure and myelination.

DISCUSSION

We reported the development of a novel training programme based on Structure Learning that aims to hone a general learning ability to potentially achieve extensive transfer benefits across various cognitive constructs. Potential transfer benefits can be exhibited through better performance in outcome measures between Training and Control participants, and positive associations between training performance and outcomes after the training in Training participants. Moreover, we attempt to substantiate behavioural findings with evidence of neural changes across different imaging modalities by the Structure Learning training.

TRIAL REGISTRATION

National Institutes of Health U.S. National Library of Medicine ClinicalTrials.gov NCT05611788. Registered on 7 November 2022.

PROTOCOL VERSION

11 May 2023.

Flexible structure learning under uncertainty

Experience is known to facilitate our ability to interpret sequences of events and make predictions about the future by extracting temporal regularities in our environments. Here, we ask whether uncertainty in dynamic environments affects our ability to learn predictive structures. We exposed participants to sequences of symbols determined by first-order Markov models and asked them to indicate which symbol they expected to follow each sequence. We introduced uncertainty in this prediction task by manipulating the: (a) probability of symbol co-occurrence, (b) stimulus presentation rate. Further, we manipulated feedback, as it is known to play a key role in resolving uncertainty. Our results demonstrate that increasing the similarity in the probabilities of symbol co-occurrence impaired performance on the prediction task. In contrast, increasing uncertainty in stimulus presentation rate by introducing temporal jitter resulted in participants adopting a strategy closer to probability maximization than matching and improving in the prediction tasks. Next, we show that feedback plays a key role in learning predictive statistics. Trial-by-trial feedback yielded stronger improvement than block feedback or no feedback; that is, participants adopted a strategy closer to probability maximization and showed stronger improvement when trained with trial-by-trial feedback. Further, correlating individual strategy with learning performance showed better performance in structure learning for observers who adopted a strategy closer to maximization. Our results indicate that executive cognitive functions (i.e., selective attention) may account for this individual variability in strategy and structure learning ability. Taken together, our results provide evidence for flexible structure learning; individuals adapt their decision strategy closer to probability maximization, reducing uncertainty in temporal sequences and improving their ability to learn predictive statistics in variable environments.

Two Oscillatory Correlates of Attention Control in the Alpha-Band with Distinct Consequences on Perceptual Gain and Metacognition

Behavioral consequences and neural underpinnings of visuospatial attention have long been investigated. Classical studies using the Posner paradigm have found that visual perception systematically benefits from the use of a spatially informative cue pointing to the to-be-attended spatial location, compared with a noninformative cue. Lateralized α amplitude modulation during visuospatial attention shifts has been suggested to account for such perceptual gain. However, recent studies on spontaneous fluctuations of prestimulus α amplitude have challenged this notion. These studies showed that spontaneous fluctuations of prestimulus α amplitude were associated with the subjective appreciation of stimulus occurrence, while objective accuracy was instead best predicted by the frequency of α oscillations, with faster prestimulus α frequency accounting for better perceptual performance. Here, in male and female humans, by using an informative cue in anticipation of lateralized stimulus presentation, we found that the predictive cue not only modulates preparatory α amplitude but also α frequency in a retinotopic manner. Behaviorally, the cue significantly impacted subjective performance measures (metacognitive abilities [meta-d']) and objective performance gain (d'). Importantly, α amplitude directly accounted for confidence levels, with ipsilateral synchronization and contralateral desynchronization coding for high-confidence responses. Crucially, the contralateral α amplitude selectively predicted interindividual differences in metacognitive abilities (meta-d'), thus anticipating decision strategy and not perceptual sensitivity, probably via excitability modulations. Instead, higher perceptual accuracy both within and across participants (d') was associated with faster contralateral α frequency, likely by implementing higher sampling at the attended location. These findings provide critical new insights into the neural mechanisms of attention control and its perceptual consequences.SIGNIFICANCE STATEMENT Prior knowledge serves the anticipation of sensory input to reduce sensory ambiguity. The growing interest in the neural mechanisms governing the integration of sensory input into our internal representations has highlighted a pivotal role of brain oscillations. Here we show that distinct but interacting oscillatory mechanisms are engaged during attentional deployment: one relying on α amplitude modulations and reflecting internal decision processes, associated with subjective perceptual experience and metacognitive abilities; the other relying on α frequency modulations and enabling mechanistic sampling of the sensory input at the attended location to influence objective performance. These insights are crucial for understanding how we reduce sensory ambiguity to maximize the efficiency of our conscious experience, but also in interpreting the mechanisms of atypical perceptual experiences.

Central role for neurally dysregulated IL-17A in dynamic networks of systemic and local inflammation in combat casualties

Dynamic Network Analysis (DyNA) and Dynamic Hypergraphs (DyHyp) were used to define protein-level inflammatory networks at the local (wound effluent) and systemic circulation (serum) levels from 140 active-duty, injured service members (59 with TBI and 81 non-TBI). Interleukin (IL)-17A was the only biomarker elevated significantly in both serum and effluent in TBI vs. non-TBI casualties, and the mediator with the most DyNA connections in TBI wounds. DyNA combining serum and effluent data to define cross-compartment correlations suggested that IL-17A bridges local and systemic circulation at late time points. DyHyp suggested that systemic IL-17A upregulation in TBI patients was associated with tumor necrosis factor-α, while IL-17A downregulation in non-TBI patients was associated with interferon-γ. Correlation analysis suggested differential upregulation of pathogenic Th17 cells, non-pathogenic Th17 cells, and memory/effector T cells. This was associated with reduced procalcitonin in both effluent and serum of TBI patients, in support of an antibacterial effect of Th17 cells in TBI patients. Dysregulation of Th17 responses following TBI may drive cross-compartment inflammation following combat injury, counteracting wound infection at the cost of elevated systemic inflammation.

A robust and fast two-sample test of equal correlations with an application to differential co-expression

A robust and fast two-sample test for equal Pearson correlation coefficients (PCCs) is important in solving many biological problems, including, for example, analysis of differential co-expression. However, few existing methods for this test can achieve robustness against deviation from normal distributions, accuracy under small sample sizes, and computational efficiency simultaneously. Here, we propose a new method for testing differential correlation using a saddlepoint approximation of the residual bootstrap (DICOSAR). To achieve robustness, accuracy, and efficiency, DICOSAR combines the ideas underlying the pooled residual bootstrap, the signed root of a likelihood ratio statistic, and a multivariate saddlepoint approximation. Through a comprehensive simulation study and a real data analysis of gene co-expression, we demonstrate that DICOSAR is accurate and robust in controlling the type I error rate for detecting differential correlation and provides a faster alternative to the bootstrap and permutation methods. We further show that DICOSAR can also be used for testing differential correlation matrices. These results suggest that DICOSAR provides an analytical approach to facilitate rapid testing for the equality of PCCs in large-scale analysis.

Negative impact of daily screen use on inhibitory control network in preadolescence: A two-year follow-up study

The COVID-19 pandemic has made an unprecedented shift in children's daily lives. Children are increasingly spending time with screens to learn and connect with others. As the online environment rapidly substitutes in-person experience, understanding children's neuropsychological trajectories associated with screen experiences is important. Previous findings suggest that excessive screen use can lead children to prefer more immediate rewards over delayed outcomes. We hypothesized that increased screen time delays a child's development of inhibitory control system in the brain (i.e., fronto-striatal circuitry). By analyzing neuropsychological data from 8324 children (9-11ys) from the ABCD Study, we found that children who had more screen time showed a higher reward orientation and weaker fronto-striatal connectivity. Importantly, we found that the daily screen exposure mediated the effect of reward sensitivity on the development of the inhibitory control system in the brain over a two year period. These findings suggest possible negative long-term impacts of increased daily screen time on children's neuropsychological development. The results further demonstrated that screen time influences dorsal striatum connectivity, which suggests that the effect of daily screen use is a habitual seeking behavior. The study provides neural and behavioral evidence for the negative impact of daily screen use on developing children.

Differential Recruitment of Inhibitory Control Processes by Directed Forgetting and Thought Substitution

Humans have the ability to intentionally forget information via different strategies, included suppression of encoding (directed forgetting) and mental replacement of the item to encode (thought substitution). These strategies may rely on different neural mechanisms; namely, encoding suppression may induce prefrontally mediated inhibition, whereas thought substitution is potentially accomplished through modulating contextual representations. Yet, few studies have directly related inhibitory processing to encoding suppression, or tested its involvement in thought substitution. Here, we directly tested whether encoding suppression recruits inhibitory mechanisms with a cross-task design, relating the behavioral and neural data from male and female participants in a Stop Signal task (a task specifically testing inhibitory processing) to a directed forgetting task with both encoding suppression (Forget) and thought substitution (Imagine) cues. Behaviorally, Stop Signal task performance (stop signal reaction times) was related to the magnitude of encoding suppression, but not thought substitution. Two complementary neural analyses corroborated the behavioral result. Namely, brain-behavior analysis demonstrated that the magnitude of right-frontal beta activity following stop signals was related to stop signal reaction times and successful encoding suppression, but not thought substitution; and classifiers trained to discriminate successful and unsuccessful stopping in the Stop Signal task could also classify successful and unsuccessful forgetting following Forget cues, but not Imagine cues. Importantly, inhibitory neural mechanisms were engaged following Forget cues at a later time than motor stopping. These findings not only support an inhibitory account of directed forgetting, and that thought substitution engages separate mechanisms, but also potentially identify a specific time in which inhibition occurs when suppressing encoding.SIGNIFICANCE STATEMENT Forgetting often seems like an unintended experience, but forgetting can be intentional, and can be accomplished with multiple strategies. These strategies, including encoding suppression and thought substitution, may rely on different neural mechanisms. Here, we test the hypothesis that encoding suppression engages domain-general prefrontally driven inhibitory control mechanisms, while thought substitution does not. Using cross-task analyses, we provide evidence that encoding suppression engages the same inhibitory mechanisms used for stopping motor actions, but these mechanisms are not engaged by thought substitution. These findings not only support the notion that mnemonic encoding processes can be directly inhibited, but also have broad relevance, as certain populations with disrupted inhibitory processing may be more successful accomplishing intentional forgetting through thought substitution strategies.

Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making

Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.

An Updated Guide to Robust Statistical Methods in Neuroscience

There is a vast array of new and improved methods for comparing groups and studying associations that offer the potential for substantially increasing power, providing improved control over the probability of false positives, and yielding a deeper and more nuanced understanding of data. These new techniques effectively deal with four insights into when and why conventional methods can be unsatisfactory. But for the non-statistician, this vast array of techniques for comparing groups and studying associations can seem daunting. This article briefly reviews when and why conventional methods can have relatively low power and yield misleading results. The main goal is to suggest guidelines regarding the use of modern techniques that improve upon classic approaches such as Pearson's correlation, ordinary linear regression, ANOVA, and ANCOVA. This updated version includes recent advances dealing with effect sizes, including situations where there is a covariate. The R code, figures, and accompanying notebooks have been updated as well. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Cortical morphometric vulnerability to generalised epilepsy reflects chromosome- and cell type-specific transcriptomic signatures

AIMS

Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level.

METHODS

We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas.

RESULTS

GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS.

CONCLUSIONS

By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes.

The Relation Between the Power of Prefrontal Gamma in Rest-state EEG Under Normal Sleep and Reactive Aggression Behaviour After Sleep Deprivation

Whether sleep deprivation affects aggressive behaviour is still under debate. The present study examined the influence of individual differences in reactive aggressive behaviour after sleep deprivation and preliminarily explored an electrophysiological marker to identify individuals with more aggressive behaviour after sleep deprivation. Thirty participants performed the Taylor Aggression Paradigm task under two sleep conditions: normal sleep (NS, one night of regular sleep) and total sleep deprivation (SD, 30 h of wakefulness), and 5-minute resting-state electroencephalogram (EEG) acquisition was completed under the NS condition. The results found that although sleep deprivation did not have significant effects on aggressive behaviour in the overall analysis, the participants can be classified as an increased group (n = 16) and a no-increased group (n = 14) by different changes in the two sleep conditions (SD-NS). In addition, prefrontal gamma (γ) power was significantly lower in the increased group than in the no-increased group, which may reflect the difference in ability on inhibition. Furthermore, more critical is that γ power was significantly negatively correlated with change in the reactive aggressive behaviour. These results indicate that the effect of SD on reactive aggression varies between individuals, and prefrontal γ power may be an effective electrophysiological marker for identifying people at risk of aggressive behaviour after SD.

Lateralization of orthographic processing in fixed-gaze and natural reading conditions

Lateralized processing of orthographic information is a hallmark of proficient reading. However, how this finding obtained for fixed-gaze processing of orthographic stimuli translates to ecologically valid reading conditions remained to be clarified. To address this shortcoming, here we assessed the lateralization of early orthographic processing in fixed-gaze and natural reading conditions using concurrent eye-tracking and EEG data recorded from young adults without reading difficulties. Sensor-space analyses confirmed the well-known left-lateralized negative-going deflection of fixed-gaze EEG activity throughout the period of early orthographic processing. At the same time, fixation-related EEG activity exhibited left-lateralized followed by right-lateralized processing of text stimuli during natural reading. A strong positive relationship was found between the early leftward lateralization in fixed-gaze and natural reading conditions. Using source-space analyses, early left-lateralized brain activity was obtained in lateraloccipital and posterior ventral occipito-temporal cortices reflecting letter-level processing in both conditions. In addition, in the same time interval, left-lateralized source activity was found also in premotor and parietal brain regions during natural reading. While brain activity remained left-lateralized in later stages representing word-level processing in posterior and middle ventral temporal regions in the fixed-gaze condition, fixation-related source activity became stronger in the right hemisphere in medial and more anterior ventral temporal brain regions indicating higher-level processing of orthographic information. Although our results show a strong positive relationship between the lateralization of letter-level processing in the two reading modes and suggest lateralized brain activity as a general marker for processing of orthographic information, they also clearly indicate the need for reading research in ecologically valid conditions to identify the neural basis of visuospatial attentional, oculomotor and higher-level processes specific to natural reading.

WildLab: A naturalistic free viewing experiment reveals previously unknown electroencephalography signatures of face processing

Neural mechanisms of face perception are predominantly studied in well-controlled experimental settings that involve random stimulus sequences and fixed eye positions. Although powerful, the employed paradigms are far from what constitutes natural vision. Here, we demonstrate the feasibility of ecologically more valid experimental paradigms using natural viewing behaviour, by combining a free viewing paradigm on natural scenes, free of photographer bias, with advanced data processing techniques that correct for overlap effects and co-varying non-linear dependencies of multiple eye movement parameters. We validate this approach by replicating classic N170 effects in neural responses, triggered by fixation onsets (fixation event-related potentials [fERPs]). Importantly, besides finding a strong correlation between both experiments, our more natural stimulus paradigm yielded smaller variability between subjects than the classic setup. Moving beyond classic temporal and spatial effect locations, our experiment furthermore revealed previously unknown signatures of face processing: This includes category-specific modulation of the event-related potential (ERP)'s amplitude even before fixation onset, as well as adaptation effects across subsequent fixations depending on their history.

Metacognitive Domains Are Not Aligned along a Dimension of Internal-External Information Source

It is still debated whether metacognition, or the ability to monitor our own mental states, relies on processes that are “domain-general” (a single set of processes can account for the monitoring of any mental process) or “domain-specific” (metacognition is accomplished by a collection of multiple monitoring modules, one for each cognitive domain). It has been speculated that two broad categories of metacognitive processes may exist: those that monitor primarily externally generated versus those that monitor primarily internally generated information. To test this proposed division, we measured metacognitive performance (using m-ratio, a signal detection theoretical measure) in four tasks that could be ranked along an internal-external axis of the source of information, namely memory, motor, visuomotor, and visual tasks. We found correlations between m-ratios in visuomotor and motor tasks, but no correlations between m-ratios in visual and visuomotor tasks, or between motor and memory tasks. While we found no correlation in metacognitive ability between visual and memory tasks, and a positive correlation between visuomotor and motor tasks, we found no evidence for a correlation between motor and memory tasks. This pattern of correlations does not support the grouping of domains based on whether the source of information is primarily internal or external. We suggest that other groupings could be more reflective of the nature of metacognition and discuss the need to consider other non-domain task-features when using correlations as a way to test the underlying shared processes between domains.

Inducing forgetting of unwanted memories through subliminal reactivation

Processes that might facilitate the forgetting of unwanted experiences typically require the actual or imagined re-exposure to reminders of the event, which is aversive and carries risks to people. But it is unclear whether awareness of aversive content is necessary for effective voluntary forgetting. Disrupting hippocampal function through retrieval suppression induces an amnesic shadow that impairs the encoding and stabilization of unrelated memories that are activated near in time to people's effort to suppress retrieval. Building on this mechanism, here we successfully disrupt retention of unpleasant memories by subliminally reactivating them within this amnesic shadow. Critically, whereas unconscious forgetting occurs on these affective memories, the amnesic shadow itself is induced by conscious suppression of unrelated and benign neutral memories, avoiding conscious re-exposure of unwelcome content. Combining the amnesic shadow with subliminal reactivation may offer a new approach to voluntary forgetting that bypasses the unpleasantness in conscious exposure to unwanted memories.

Precise motor rhythmicity relies on motor network responsivity

Rhythmic movements are the building blocks of human behavior. However, given that rhythmic movements are achieved through complex interactions between neural modules, it remains difficult to clarify how the central nervous system controls motor rhythmicity. Here, using a novel tempo-precision trade-off paradigm, we first modeled interindividual behavioral differences in tempo-dependent rhythmicity for various external tempi. We identified 2 behavioral extremes: conventional and paradoxical tempo-precision trade-off types. We then explored the neural substrates of these behavioral differences using task and resting-state functional magnetic resonance imaging. We found that the responsibility of interhemispheric motor network connectivity to tempi was a key to the behavioral repertoire. In the paradoxical trade-off type, interhemispheric connectivity was low at baseline but increased in response to increasing tempo; in the conventional trade-off type, strong baseline connectivity was coupled with low responsivity. These findings suggest that tunable interhemispheric connectivity underlies tempo-dependent rhythmicity control.

Effects of 12 weeks of aerobic exercise combined with resistance training on neurocognitive performance in obese women

Background/Objectives

To the best of our knowledge, there have been no previous studies conducted on the long-term effects of an exercise intervention on deficits in inhibitory control in obese individuals. The aim of this study was thus to examine the effect of 12 weeks of a combination of aerobic and resistance exercise on behavioral and cognitive electrophysiological performance involving cognitive interference inhibition in obese individuals.

Methods

Thirty-two qualified healthy obese women were randomly divided into either an exercise group (EG, age: 34.76 ± 5.52 years old; BMI: 29.35 ± 3.52 kg/m²) or a control group (CG, age: 33.84 ± 7.05 years old; BMI: 29.61 ± 4.31 kg/m²). All participants performed the Stroop task, with electrophysiological signals being collected simultaneously before and after a 12-week intervention. The estimated V̇O₂max, muscular strength, and body fat percentage (measured with dual-energy X-ray absorptiometry) were also assessed within one week before and after the intervention. Participants in the EG group engaged in 30 min of moderate-intensity aerobic exercise combined with resistance exercise, 5 sessions per week for 12 weeks, while the participants in the CG group maintained their regular lifestyle without engaging in any type of exercise.

Results

The results revealed that although a 12-week exercise intervention did not enhance the behavioral indices [e.g., accuracy rates (ARs) and reaction times (RTs)] in the EG group, significantly shorter N2 and P3 latencies and greater P2 and P3 amplitudes were observed. Furthermore, the fat percentage distribution (e.g. total body fat %, trunk fat %, and leg fat %) and level of physical fitness (e.g. estimated V̇O₂max and muscular strength) in the EG group were significantly improved. The changes prior to and after the intervention in the P3 amplitude and trunk fat percentage were significantly negatively correlated in the EG group (r = −0.521, p = 0.039).

Conclusions

These findings suggested that 12 weeks of aerobic exercise combined with resistance exercise in obese women affects cognitive function broadly, but not specifically in terms of inhibitory control. The percentage of decreased trunk fat may play a potential facilitating role in inhibition processing in obesity.

Age-related increases in reaction time result from slower preparation, not delayed initiation

Recent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times would suggest, leaving a seemingly unnecessary delay of 80-100 ms before responding. Here, we examined how the preparation of movements, initiation of movements, and the delay between them are affected by aging. Participants made planar reaching movements in two conditions. The "free reaction time" condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The "forced reaction time" condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the free reaction time and to prepare movements in the forced response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants' self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (∼90 ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.NEW & NOTEWORTHY Previous research argues that older adults have slower response times because they hesitate to react, favoring accuracy over speed. The present results challenge this proposal. We found the delay between the minimum time required to prepare movements and the self-selected time at which they initiated remained consistent at ∼90 ms from ages 21 to 80. We therefore suggest older adults' slower response times can be attributed to changes in their ability to process stimuli and prepare movements.

Predicting individual differences in motor learning: a critical review

The ability to predict individual differences in motor learning has significant implications from both theoretical and applied perspectives. However, there is high variability in the methodological and analytical strategies employed as evidence for such predictions. Here, we critically examine the evidence for predictions of individual differences in motor learning by reviewing the literature from a 20-year period (2000-2020). Specifically, we examined four factors: (i) the predictor and predicted variables used, (ii) the strength of the prediction and associated sample size, (iii) the timescale over which the prediction was made, and (iv) the type of motor task used. Overall, the results highlight several issues that raise concerns about the quality of the evidence for such predictions. First, there was a large variation in both predictor and predicted variables, suggesting the presence of a large number of researcher degrees of freedom. Second, sample sizes tended to be small, and the strength of the correlation showed an inverse relation with sample size. Third, the timescale of most predictions was very short, mostly constrained to a single day. Last, most studies were largely restricted to two experimental paradigms - adaptation and sequence learning. Based on these issues, we highlight recommendations for future studies to improve the quality of evidence for predicting individual differences in motor learning.

Excessive Functional Coupling With Less Variability Between Salience and Default Mode Networks in Autism Spectrum Disorder

BACKGROUND

Atypical activity in the salience network (SN) and default mode network (DMN) has been previously reported in individuals with autism spectrum disorder (ASD). However, no study to date has investigated the nature and dynamics of the interaction between these two networks in ASD.

METHODS

Here, we aimed to characterize the functional connectivity between the SN and the DMN by using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange and comparing individuals with ASD (n = 325) to a typically developing group (n = 356). We examined static and dynamic levels of functional connectivity using the medial prefrontal cortex (mPFC) seed as a core region of the DMN.

RESULTS

We found that individuals with ASD have higher mPFC connectivity with the insula, a core region of the SN, when compared with the typical development group. Moreover, the mPFC-insula coupling showed less variability in ASD compared with the typical development group. A novel semblance-based network dynamic analysis further confirmed that the strong mPFC-insula coupling in the ASD group reduced spontaneous attentional shift for possible external elements of the environment. Indeed, we found that excessive mPFC-insula coupling was significantly associated with a tendency for reduced social responsiveness.

CONCLUSIONS

These findings suggest that the internally oriented cognition in individuals with ASD may be due to excessive coupling between the DMN and the SN.

Gradual enhancement of corticomotor excitability during cortico-cortical paired associative stimulation

Cortico-cortical paired associative stimulation (ccPAS) is an effective transcranial magnetic stimulation (TMS) method for inducing associative plasticity between interconnected brain areas in humans. Prior ccPAS studies have focused on protocol’s aftereffects. Here, we investigated physiological changes induced “online” during ccPAS administration. We tested 109 participants receiving ccPAS over left ventral premotor cortex (PMv) and primary motor cortex (M1) using a standard procedure (90 paired-pulses with 8-ms interstimulus interval, repeated at 0.1 Hz frequency). On each paired-pulse, we recorded a motor-evoked potential (MEP) to continuously trace the emergence of corticomotor changes. Participant receiving forward-ccPAS (on each pair, a first TMS pulse was administered over PMv, second over M1, i.e., PMv-to-M1) showed a gradual and linear increase in MEP size that did not reach a plateau at the end of the protocol and was greater in participants with low motor threshold. Participants receiving reverse-ccPAS (i.e., M1-to-PMv) showed a trend toward inhibition. Our study highlights the facilitatory and inhibitory modulations that occur during ccPAS administration and suggest that online MEP monitoring could provide insights into the malleability of the motor system and protocol’s effectiveness. Our findings open interesting prospects about ccPAS potential optimization in experimental and clinical settings.

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

Background and objective

Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect.

Methods

Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2×2×2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change.

Results

In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = –3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis.

Conclusions

Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

On the relationship between GABA+ and glutamate across the brain

Equilibrium between excitation and inhibition (E/I balance) is key to healthy brain function. Conversely, disruption of normal E/I balance has been implicated in a range of central neurological pathologies. Magnetic resonance spectroscopy (MRS) provides a non-invasive means of quantifying in vivo concentrations of excitatory and inhibitory neurotransmitters, which could be used as diagnostic biomarkers. Using the ratio of excitatory and inhibitory neurotransmitters as an index of E/I balance is common practice in MRS work, but recent studies have shown inconsistent evidence for the validity of this proxy. This is underscored by the fact that different measures are often used in calculating E/I balance such as glutamate and Glx (glutamate and glutamine). Here we used a large MRS dataset obtained at ultra-high field (7 T) measured from 193 healthy young adults and focused on two brain regions - prefrontal and occipital cortex - to resolve this inconsistency. We find evidence that there is an inter-individual common ratio between GABA+ (γ-aminobutyric acid and macromolecules) and Glx in the occipital, but not prefrontal cortex. We further replicate the prefrontal result in a legacy dataset (n = 78) measured at high-field (3 T) strength. By contrast, with ultra-high field MRS data, we find extreme evidence that there is a common ratio between GABA+ and glutamate in both prefrontal and occipital cortices, which cannot be explained by participant demographics, signal quality, fractional tissue volume, or other metabolite concentrations. These results are consistent with previous electrophysiological and theoretical work supporting E/I balance. Our findings indicate that MRS-detected GABA+ and glutamate (but not Glx), are a reliable measure of E/I balance .

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

Bootstrap confidence intervals for 11 robust correlations in the presence of outliers and leverage observations

Researchers often examine whether two continuous variables (X and Y) are linearly related. Pearson’s correlation (r) is a widely-employed statistic for assessing bivariate linearity. However, the accuracy of r is known to decrease when data contain outliers and/or leverage observations, a circumstance common in behavioral and social sciences research. This study compares 11 robust correlations with r and evaluates the associated bootstrap confidence intervals [bootstrap standard interval (BSI), bootstrap percentile interval (BPI), and bootstrap bias-corrected-and-accelerated interval (BCaI)] across conditions with and without outliers and/or leverage observations. The simulation results showed that the median-absolute-deviation correlation (r-MAD), median-based correlation (r-MED), and trimmed correlation (r-TRIM) consistently outperformed the other estimates, including r, when data contain outliers and/or leverage observations. This study provides an easy-to-use R code for computing robust correlations and their associated confidence intervals, offers recommendations for their reporting, and discusses implications of the findings for future research.

First Novel Workflow for Semiquantification of Emerging Contaminants in Environmental Samples Analyzed by Gas Chromatography-Atmospheric Pressure Chemical Ionization-Quadrupole Time of Flight-Mass Spectrometry

The ionization efficiency of emerging contaminants was modeled for the first time in gas chromatography-high-resolution mass spectrometry (GC-HRMS) which is coupled to an atmospheric pressure chemical ionization source (APCI). The recent chemical space has been expanded in environmental samples such as soil, indoor dust, and sediments thanks to recent use of high-resolution mass spectrometric techniques; however, many of these chemicals have remained unquantified. Chemical exposure in dust can pose potential risk to human health, and semiquantitative analysis is potentially of need to semiquantify these newly identified substances and assist with their risk assessment and environmental fate. In this study, a rigorously tested semiquantification workflow was proposed based on GC-APCI-HRMS ionization efficiency measurements of 78 emerging contaminants. The mechanism of ionization of compounds in the APCI source was discussed via a simple connectivity index and topological structure. The quantitative structure–property relationship (QSPR)-based model was also built to predict the APCI ionization efficiencies of unknowns and later use it for their quantification analyses. The proposed semiquantification method could be transferred into the household indoor dust sample matrix, and it could include the effect of recovery and matrix in the predictions of actual concentrations of analytes. A suspect compound, which falls inside the application domain of the tool, can be semiquantified by an online web application, free of access at http://trams.chem.uoa.gr/semiquantification/.

Functional Significance of Human Resting-State Networks Hubs Identified Using MEG During the Transition From Childhood to Adulthood

Cortical hubs identified within resting-state networks (RSNs), areas of the cortex that have a higher-than-average number of connections, are known to be critical to typical cognitive functioning and are often implicated in disorders leading to abnormal cognitive functioning. Functionally defined cortical hubs are also known to change with age in the developing, maturing brain, mostly based on studies carried out using fMRI. We have recently used magnetoencephalography (MEG) to study the maturation trajectories of RSNs and their hubs from age 7 to 29 in 131 healthy participants with high temporal resolution. We found that maturation trajectories diverge as a function of the underlying cortical rhythm. Specifically, we found the beta band (13–30 Hz)-mediated RSNs became more locally efficient with maturation, i.e., more organized into clusters and connected with nearby regions, while gamma (31–80 Hz)-mediated RSNs became more globally efficient with maturation, i.e., prioritizing faster signal transmission between distant cortical regions. We also found that different sets of hubs were associated with each of these networks. To better understand the functional significance of this divergence, we wanted to examine the cortical functions associated with the identified hubs that grew or shrunk with maturation within each of these networks. To that end, we analyzed the results of the prior study using Neurosynth, a platform for large-scale, automated synthesis of fMRI data that links brain coordinates with their probabilistically associated terms. By mapping the Neurosynth terms associated with each of these hubs, we found that maturing hubs identified in the gamma band RSNs were more likely to be associated with bottom-up processes while maturing hubs identified in the beta band RSNs were more likely to be associated with top-down functions. The results were consistent with the idea that beta band-mediated networks preferentially support the maturation of top-down processing, while the gamma band-mediated networks preferentially support the maturation of bottom-up processing.

Effects of Rhythmic Transcranial Magnetic Stimulation in the Alpha-Band on Visual Perception Depend on Deviation From Alpha-Peak Frequency: Faster Relative Transcranial Magnetic Stimulation Alpha-Pace Improves Performance

Alpha-band oscillatory activity over occipito-parietal areas is involved in shaping perceptual and cognitive processes, with a growing body of electroencephalographic (EEG) evidence indicating that pre-stimulus alpha-band amplitude relates to the subjective perceptual experience, but not to objective measures of visual task performance (discrimination accuracy). The primary aim of the present transcranial magnetic stimulation (TMS) study was to investigate whether causality can be established for this relationship, using rhythmic (alpha-band) TMS entrainment protocols. It was anticipated that pre-stimulus 10 Hz-TMS would induce changes in subjective awareness ratings but not accuracy, in the visual hemifield contralateral to TMS. To test this, we administered 10 Hz-TMS over the right intraparietal sulcus prior to visual stimulus presentation in 17 participants, while measuring their objective performance and subjective awareness in a visual discrimination task. Arrhythmic and 10 Hz sham-TMS served as control conditions (within-participant design). Resting EEG was used to record individual alpha frequency (IAF). A study conducted in parallel to ours with a similar design but reported after we completed data collection informed further, secondary analyses for a causal relationship between pre-stimulus alpha-frequency and discrimination accuracy. This was explored through a regression analysis between rhythmic-TMS alpha-pace relative to IAF and performance measures. Our results revealed that contrary to our primary expectation, pre-stimulus 10 Hz-TMS did not affect subjective measures of performance, nor accuracy, relative to control-TMS. This null result is in accord with a recent finding showing that for influencing subjective measures of performance, alpha-TMS needs to be applied post-stimulus. In addition, our secondary analysis showed that IAF was positively correlated with task accuracy across participants, and that 10 Hz-TMS effects on accuracy—but not awareness ratings—depended on IAF: The slower (or faster) the IAF, relative to the fixed 10 Hz TMS frequency, the stronger the TMS-induced performance improvement (or worsening), indicating that 10 Hz-TMS produced a gain (or a loss) in individual performance, directly depending on TMS-pace relative to IAF. In support of recent reports, this is evidence for alpha-frequency playing a causal role in perceptual sensitivity likely through regulating the speed of sensory sampling.

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

Slow fluctuations in ongoing brain activity decrease in amplitude with ageing yet their impact on task-related evoked responses is dissociable from behavior

In humans, ageing is characterized by decreased brain signal variability and increased behavioral variability. To understand how reduced brain variability segregates with increased behavioral variability, we investigated the association between reaction time variability, evoked brain responses and ongoing brain signal dynamics, in young (N=36) and older adults (N=39). We studied the electroencephalogram (EEG) and pupil size fluctuations to characterize the cortical and arousal responses elicited by a cued go/no-go task. Evoked responses were strongly modulated by slow (<2 Hz) fluctuations of the ongoing signals, which presented reduced power in the older participants. Although variability of the evoked responses was lower in the older participants, once we adjusted for the effect of the ongoing signal fluctuations, evoked responses were equally variable in both groups. Moreover, the modulation of the evoked responses caused by the ongoing signal fluctuations had no impact on reaction time, thereby explaining why although ongoing brain signal variability is decreased in older individuals, behavioral variability is not. Finally, we showed that adjusting for the effect of the ongoing signal was critical to unmask the link between neural responses and behavior as well as the link between task-related evoked EEG and pupil responses.

GPU-accelerated connectome discovery at scale

Diffusion magnetic resonance imaging and tractography enable the estimation of anatomical connectivity in the human brain, in vivo. Yet, without ground-truth validation, different tractography algorithms can yield widely varying connectivity estimates. Although streamline pruning techniques mitigate this challenge, slow compute times preclude their use in big-data applications. We present 'Regularized, Accelerated, Linear Fascicle Evaluation' (ReAl-LiFE), a GPU-based implementation of a state-of-the-art streamline pruning algorithm (LiFE), which achieves >100× speedups over previous CPU-based implementations. Leveraging these speedups, we overcome key limitations with LiFE's algorithm to generate sparser and more accurate connectomes. We showcase ReAl-LiFE's ability to estimate connections with superlative test-retest reliability, while outperforming competing approaches. Moreover, we predicted inter-individual variations in multiple cognitive scores with ReAl-LiFE connectome features. We propose ReAl-LiFE as a timely tool, surpassing the state of the art, for accurate discovery of individualized brain connectomes at scale. Finally, our GPU-accelerated implementation of a popular non-negative least-squares optimization algorithm is widely applicable to many real-world problems.

Stress-related cognitive style is related to volumetric change of the hippocampus and FK506 binding protein 5 polymorphism in post-traumatic stress disorder

BACKGROUND

Patients with post-traumatic stress disorder (PTSD) show a different stress-related cognitive style compared with healthy controls (HC). The FK506 binding protein 5 gene (FKBP5), one of the PTSD known risk factors, is involved in the stress response through the hypothalamic-pituitary-adrenal axis and brain volumetric alterations. The present study aimed to uncover the neural correlates of stress-related cognitive styles through the analysis of the regional brain volumes and FKBP5 genotype in patients with PTSD compared with HC.

METHODS

In this study, 51 patients with PTSD and 94 HC were assessed for stress-related cognitive styles, PTSD symptoms severity, and genotype of FKBP5 single nucleotide polymorphisms, and underwent T1-weighted structural magnetic resonance imaging. Diagnosis-by-genotype interaction for regional brain volumes was examined in 16 brain regions of interest.

RESULTS

Patients with PTSD showed significantly higher levels of catastrophizing, ruminative response, and repression, and reduced distress aversion and positive reappraisal compared with HC (p < 0.001). Significant diagnosis-by-genotype interactions for regional brain volumes were observed for bilateral hippocampi and left frontal operculum. A significant positive correlation between the severity of the repression and left hippocampal volume was found in a subgroup of patients with PTSD with FKBP5 rs3800373 (AA genotype) or rs1360780 (CC genotype).

CONCLUSIONS

The present study showed the influences of FKBP5 genotype on the distorted cognitive styles in PTSD by measuring the volumetric alteration of hippocampal regions, providing a possible role of the hippocampus and left frontal operculum as significant neurobiological correlates of PTSD.

A Simulation Study of the Ecological Speciation Conditions in the Galician Marine Snail Littorina saxatilis

In the last years, the interest in evolutionary divergence at small spatial scales has increased and so did the study of speciation caused by ecologically based divergent natural selection. The evolutionary interplay between gene flow and local adaptation can lead to low-dispersal locally adapted specialists. When this occurs, the evolutionary interplay between gene flow and local adaptation could eventually lead to speciation. The L. saxatilis system consists of two ecotypes displaying a microhabitat-associated intraspecific dimorphism along the wave-exposed rocky shores of Galicia. Despite being a well-known system, the dynamics of the ecotype formation remain unclear and cannot be studied from empirical evidence alone. In this study, individual-based simulations were used to incorporate relevant ecological, spatial, and genetic information, to check different evolutionary scenarios that could evolve non-random mating preferences and finally may facilitate speciation. As main results, we observed the evolution of intermediate values of choice which matches the estimates from empirical data of L. saxatilis in Galician shores and coincides with previous theoretical outcomes. Also, the use of the mating correlation as a proxy for assortative mating led to spuriously inferring greater reproductive isolation in the middle habitat than in the others, which does not happen when directly considering the choice values from the simulations. We also corroborate the well-known fact that the occurrence of speciation is influenced by the strength of selection. Taken together, this means, also according to other L. saxatilis systems, that speciation is not an immediate consequence of local divergent selection and mating preferences, but a fine tuning among several factors including the ecological conditions in the shore levels, the selection strength, the mate choice stringency, and cost to choosiness. The L. saxatilis system could correspond to a case of incomplete reproductive isolation, where the choice intensity is intermediate and local adaptation within the habitat is strong. These results support previous interpretations of the L. saxatilis model system and indicate that further empirical studies would be interesting to test whether the mate choice mechanism functions as a similarity-like mechanism as has been shown in other littorinids.