Improving standards in brain-behavior correlation analyses

Brain connectivity changes to fast versus slow dopamine increases

The rewarding effects of stimulant drugs such as methylphenidate (MP) depend crucially on how fast they raise dopamine in the brain. Yet how the rate of drug-induced dopamine increases impacts brain network communication remains unresolved. We manipulated route of MP administration to generate fast versus slow dopamine increases. We hypothesized that fast versus slow dopamine increases would result in a differential pattern of global brain connectivity (GBC) in association with regional levels of dopamine D1 receptors, which are critical for drug reward. Twenty healthy adults received MP intravenously (0.5 mg/kg; fast dopamine increases) and orally (60 mg; slow dopamine increases) during simultaneous [11C]raclopride PET-fMRI scans (double-blind, placebo-controlled). We tested how GBC was temporally associated with slow and fast dopamine increases on a minute-to-minute basis. Connectivity patterns were strikingly different for slow versus fast dopamine increases, and whole-brain spatial patterns were negatively correlated with one another (rho = -0.54, pspin < 0.001). GBC showed "fast>slow" associations in dorsal prefrontal cortex, insula, posterior thalamus and brainstem, caudate and precuneus; and "slow>fast" associations in ventral striatum, orbitofrontal cortex, and frontopolar cortex (pFDR < 0.05). "Fast>slow" GBC patterns showed significant spatial correspondence with D1 receptor availability (estimated via normative maps of [11C]SCH23390 binding; rho = 0.22, pspin < 0.05). Further, hippocampal GBC to fast dopamine increases was significantly negatively correlated with self-reported 'high' ratings to intravenous MP across individuals (r(19) = -0.68, pbonferroni = 0.015). Different routes of MP administration produce divergent patterns of brain connectivity. Fast dopamine increases are uniquely associated with connectivity patterns that have relevance for the subjective experience of drug reward.

Temporal interference stimulation targets deep primate brain

Temporal interference (TI) stimulation, a novel non-invasive stimulation strategy, has recently been shown to modulate neural activity in deep brain regions of living mice. Yet, it is uncertain if this method is applicable to larger brains and whether the electric field produced under traditional safety currents can penetrate deep regions as observed in mice. Despite recent model-based simulation studies offering positive evidence at both macro- and micro-scale levels, the absence of electrophysiological data from actual brains hinders comprehensive understanding and potential application of TI. This study aims to directly measure the spatiotemporal properties of the interfered electric field in the rhesus monkey brain and to validate the effects of TI on the human brain. Two monkeys were involved in the measurement, with implantation of several stereo-electroencephalography (SEEG) depth electrodes. TI stimulation was applied to anesthetized monkeys using two pairs of surface electrodes at differing stimulation parameters. Model-based simulations were also conducted and subsequently compared with actual recordings. Additionally, TI stimulation was administered to patients with motor disorders to validate its effects on motor symptoms. Through the integration of computational electric field simulation with empirical measurements, it was determined that the temporally interfering electric fields in the deep central regions are capable of attaining a magnitude sufficient to induce a subthreshold modulation effect on neural signals. Additionally, an improvement in movement disorders was observed as a result of TI stimulation. This study is the first to systematically measure the TI electric field in living non-human primates, offering empirical evidence that TI holds promise as a more focal and precise method for modulating neural activities in deep regions of a large brain. This advancement paves the way for future applications of TI in treating neuropsychiatric disorders.

Mitochondrial calcium uniporter deficiency in dentate granule cells remodels neuronal metabolism and impairs reversal learning

The mitochondrial calcium uniporter (MCU) is the main route of calcium (Ca2+) entry into neuronal mitochondria. This channel has been linked to mitochondrial Ca2+ overload and cell death under neurotoxic conditions, but its physiologic roles for normal brain function remain poorly understood. Despite high expression of MCU in excitatory hippocampal neurons, it is unknown whether this channel is required for learning and memory. Here, we genetically down-regulated the Mcu gene in dentate granule cells (DGCs) of the hippocampus and found that this manipulation increases the overall respiratory activity of mitochondrial complexes I and II, augmenting the generation of reactive oxygen species in the context of impaired electron transport chain. The metabolic remodeling of MCU-deficient neurons also involved changes in the expression of enzymes that participate in glycolysis and the regulation of the tricarboxylic acid cycle, as well as the cellular antioxidant defenses. We found that MCU deficiency in DGCs does not change circadian rhythms, spontaneous exploratory behavior, or cognitive function in middle-aged mice (11-13 months old), when assessed with a food-motivated working memory test with three choices. DGC-targeted down-regulation of MCU significantly impairs reversal learning assessed with an 8-arm radial arm water maze but does not affect their ability to learn the task for the first time. Our results indicate that neuronal MCU plays an important physiologic role in memory formation and may be a potential therapeutic target to develop interventions aimed at improving cognitive function in aging, neurodegenerative diseases, and brain injury.

From learned value to sustained bias: how reward conditioning changes attentional priority

Introduction

Attentional bias to reward-associated stimuli can occur even when it interferes with goal-driven behavior. One theory posits that dopaminergic signaling in the striatum during reward conditioning leads to changes in visual cortical and parietal representations of the stimulus used, and this, in turn, sustains attentional bias even when reward is discontinued. However, only a few studies have examined neural activity during both rewarded and unrewarded task phases.

Methods

In the current study, participants first completed a reward-conditioning phase, during which responses to certain stimuli were associated with monetary reward. These stimuli were then included as non-predictive cues in a spatial cueing task. Participants underwent functional brain imaging during both task phases.

Results

The results show that striatal activity during the learning phase predicted increased visual cortical and parietal activity and decreased ventro-medial prefrontal cortex activity in response to conditioned stimuli during the test. Striatal activity was also associated with anterior cingulate cortex activation when the reward-conditioned stimulus directed attention away from the target.

Discussion

Our findings suggest that striatal activity during reward conditioning predicts the degree to which reward history biases attention through learning-induced changes in visual and parietal activities.

Neural asymmetry in aligning with generous versus selfish descriptive norms in a charitable donation task

Social alignment is supported by the brain's reward system (ventral striatum), presumably because attaining synchrony generates feelings of connectedness. However, this may hold only for aligning with generous others, while aligning with selfishness might threaten social connectedness. We investigated this postulated asymmetry in an incentivized fMRI charitable donation task. Participants decided how much of their endowment to donate to real charities, and how much to keep for themselves. Compared to a baseline condition, donations significantly increased or decreased in function of the presence of descriptive norms. The fMRI data reveal that processing selfish norms (more than generous ones) recruited the amygdala and anterior insula. Aligning with selfish norms correlated on average with reduced activity in the lateral prefrontal cortex (LPFC) and, at the individual level, with decreasing activity in the ventral striatum (VS). Conversely, as participants aligned more with generous norms, they showed increasing activity in the LPFC and, on average, increased activity in the VS. This increase occurred beyond the increased VS activity which was also observed in the baseline condition. Taken together, this suggests that aligning with generosity, while effortful, provides a "warm glow of herding" associated with collective giving, but that aligning with selfishness does not.

Structural brain feature is associated with changes of masticatory performance in healthy elderly people: Evidence from longitudinal neuroimaging research over two years

BACKGROUND

Human neuroimaging studies have revealed the association between brain structure and masticatory function. However, the majority of the studies adopted a cross-sectional design, which hardly reveals the change in masticatory function and brain structure between different timepoints, and the dynamical association between changes in masticatory function and changes in brain structure has not been elucidated.

OBJECTIVE

With a longitudinal design, we assessed the association between changes in masticatory performance (MP) and regional brain volume.

METHODS

Twenty-two elderly participants received assessments of the number of missing teeth and MP (via colour-changeable chewing gum) when they entered the study (i.e. the initial stage, T0 ), approximately 6 months later (T0.5 ), and approximately 1-2 years later (T1 ). Difficulty of food intake was assessed using a questionnaire. The participants received magnetic resonance imaging (MRI) at T0 and T1 . The brain volume of the motor-related area was estimated using FreeSurfer for MRI data. The associations between different stages were analysed using Spearman's rho correlation coefficients.

RESULTS

(1) Individually, a smaller volume of right primary motor cortex at T0 was associated with increased MP from T0 to T1 , suggesting the brain's role in changing oral functions; (2) higher MP at T0 was associated with an increased volume of the left superior frontal cortex from T0 to T1 p, suggesting a potential effect on brain plasticity, and (3) increased difficulty to eat was associated with decrease MP but not brain volume of motor-related area.

CONCLUSIONS

The preliminary findings revealed a complicated pattern of structural brain features and masticatory function in elderly people, and either the hypothesis that the brain predisposes masticatory function or the hypothesis that mastication reshapes the brain is oversimplified.

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.

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.

Applicability of fractional anisotropy from standardized automated tractography for outcome prediction of patients after stroke

[Purpose] Diffusion-tensor fractional anisotropy has been used for outcome prediction in stroke patients. We assessed the clinical applicability of the two major fractional anisotropy methodologies-fractional anisotropy derived from segmentation maps in the standard brain (region of interest) and fractional anisotropy derived from standardized automated tractography-in relation to outcomes. [Participants and Methods] The study design was a retrospective survey of medical records collected from October 2021 to September 2022. Diffusion-tensor imaging was conducted in the second week after stroke onset. Outcomes were assessed using the total score of the motor component of the Stroke Impairment Assessment Set (null to full, 0 to 25). Correlations between fractional anisotropy and the outcomes were then assessed. [Results] Fourteen patients with hemorrhagic stroke were sampled. The fractional anisotropy from standardized automated tractography of the corticospinal tract on the lesion side (mean ± standard deviation, 0.403 ± 0.070) was significantly and tightly correlated (r=0.813) with the outcomes (13.4 ± 9.2), whereas the fractional anisotropy from a region of interest set in the cerebral peduncle on the lesion side (0.548 ± 0.064) was not significantly correlated with the outcomes (r=0.507). [Conclusion] The findings suggest that fractional anisotropy derived from standardized automated tractography can be more applicable to outcome prediction than that derived from a region of interest defined in the standard brain.

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.

Exploratory Correlation of The Human Structural Connectome with Non-MRI Variables in Alzheimer's Disease

INTRODUCTION

Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers.

METHODS

We used four diffusion-MRI databases, three related to Alzheimer's disease, to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways.

RESULTS

We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity.

DISCUSSION

Our findings help to elucidate which structural brain networks are affected in Alzheimer's disease and aging and highlight the importance of including indirect connections.

Inhibitory temporo-parietal effective connectivity is associated with explicit memory performance in older adults

Successful explicit memory encoding is associated with inferior temporal activations and medial parietal deactivations, which are attenuated in aging. Here we used dynamic causal modeling (DCM) of functional magnetic resonance imaging data to elucidate effective connectivity patterns between hippocampus, parahippocampal place area (PPA), and precuneus during encoding of novel visual scenes. In 117 young adults, DCM revealed pronounced activating input from the PPA to the hippocampus and inhibitory connectivity from the PPA to the precuneus during novelty processing, with both being enhanced during successful encoding. This pattern could be replicated in two cohorts (N = 141 and 148) of young and older adults. In both cohorts, older adults selectively exhibited attenuated inhibitory PPA-precuneus connectivity, which correlated negatively with memory performance. Our results provide insight into the network dynamics underlying explicit memory encoding and suggest that age-related differences in memory-related network activity are, at least partly, attributable to altered temporo-parietal neocortical connectivity.

Application of cluster repeated mini-batch training method to classify electroencephalography for grab and lift tasks

Modern deep neural network training is based on mini-batch stochastic gradient optimization. While using extensive mini-batches improves the computational parallelism, the small batch training proved that it delivers improved generalization performance and allows a significantly smaller memory, which might also improve machine throughput. However, mini-batch size and characteristics, a key factor for training deep neural networks, has not been sufficiently investigated in training correlated group features and looping with highly complex ones. In addition, the unsupervised learning method clusters the data into different groups with similar properties to make the training process more stable and faster. Then, the supervised learning algorithm was applied with the cluster repeated mini-batch training (CRMT) methods. The CRMT algorithm changed the random minibatch characteristics in the training step into training in order of clusters. Specifically, the self-organizing maps (SOM) were used to cluster the information into n groups based on the dataset's labels Then, neural network models (ANN) were trained with each cluster using the cluster repeated mini-batch training method. Experiments conducted on EEG datasets demonstrate the survey of the proposed method and optimize it. In addition, the results in our research outperform other state-of-the-art methods.

Exploratory correlation of the human structural connectome with non-MRI variables in Alzheimer's disease

Introduction

Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers.

Methods

We used four diffusion-MRI databases, three related to Alzheimer's disease (AD), to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways.

Results

We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity.

Discussion

Our findings help to elucidate which structural brain networks are affected in AD and aging and highlight the importance of including indirect connections.

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.

Neurophysiological Measures of Proactive and Reactive Control in Negative Template Use

In a visual search task, knowing features of distractors in advance leads to a more efficient visual search. Although previous studies suggested that the benefits of these negative cues rely on attentional control, it is unclear whether proactive or reactive control is involved. In this study, we analyzed the EEG data of participants performing a visual search task (n = 14). Participants searched for a shape-defined target after receiving a positive cue (target color), negative cue (distractor color), or neutral cue (non-informative). To examine proactive control, we measured EEG after the cue onset but before visual search. Our time-frequency analysis revealed a higher power of theta oscillations over frontoparietal regions after the negative cues compared with the positive and neutral cues, as well as higher theta phase synchronization within the prefrontal region, demonstrating negative cues rely more heavily on proactive control compared with other cue types. To examine reactive control, we measured EEG after the search onset. We found a lateralization of posterior alpha power toward the target side in both positive and negative cues conditions, with a later lateralization observed after negative cues. Interestingly, we observed a significant relationship between the increase of proactive theta power after negative cues and the decrease of reactive alpha power after the search. This suggests the coordination of proactive and reactive mechanisms lead to the most efficient search.

Feasibility of remotely delivered and supported aerobic walking exercise training for cognitive processing speed impairment in fully-ambulatory persons with multiple sclerosis

PURPOSE

The current pilot, single-blind, randomized controlled trial (RCT) examined the feasibility of remotely-delivered and supported aerobic walking exercise training compared with an active control condition on cognitive processing speed (CPS) in 19 fully-ambulatory persons with multiple sclerosis (pwMS) who were pre-screened for impaired CPS.

METHODS

Feasibility was assessed in the domains of process (e.g., recruitment), resource (e.g., monetary costs), management (e.g., time requirements), and scientific outcomes (i.e., treatment effect). Fully-ambulatory, but CPS-impaired pwMS were randomly assigned into either 16-weeks of home-based aerobic walking exercise or home-based stretching and range-of-motion activities. Both conditions involved delivery of informational newsletters and one-on-one, online video chats with a behavior coach. Participants across both conditions tracked their activity using highly accurate wearable motion sensors. Treatment-blinded assessors administered the Symbol Digit Modalities Test (SDMT) remotely before and after the 16-week study period.

RESULTS

The study was cost-effective, accessible, and acceptable. The intervention further was safe. Adherence and compliance rates across both conditions exceeded 80%. There was an overall moderate effect for change in SDMT score between the conditions (d = 0.42). The intervention was associated with a 4.8-point improvement in SDMT scores (d = 0.70; 10% increase) compared with a 1-point improvement for the control condition (d = 0.09; 2% increase).

CONCLUSIONS

This remotely-delivered and supported aerobic walking exercise training intervention was safe and feasible for fully-ambulatory, CPS-impaired pwMS. The pattern of results, including the promising effects on CPS, support the design and implementation of an appropriately-powered RCT on this approach for managing CPS impairment in a large MS sample.

Functional identification of language-responsive channels in individual participants in MEG investigations

Making meaningful inferences about the functional architecture of the language system requires the ability to refer to the same neural units across individuals and studies. Traditional brain imaging approaches align and average brains together in a common space. However, lateral frontal and temporal cortex, where the language system resides, is characterized by high structural and functional inter-individual variability. This variability reduces the sensitivity and functional resolution of group-averaging analyses. This problem is compounded by the fact that language areas often lay in close proximity to regions of other large-scale networks with different functional profiles. A solution inspired by other fields of cognitive neuroscience (e.g., vision) is to identify language areas functionally in each individual brain using a 'localizer' task (e.g., a language comprehension task). This approach has proven productive in fMRI, yielding a number of discoveries about the language system, and has been successfully extended to intracranial recording investigations. Here, we apply this approach to MEG. Across two experiments (one in Dutch speakers, n=19; one in English speakers, n=23), we examined neural responses to the processing of sentences and a control condition (nonword sequences). We demonstrated that the neural response to language is spatially consistent at the individual level. The language-responsive sensors of interest were, as expected, less responsive to the nonwords condition. Clear inter-individual differences were present in the topography of the neural response to language, leading to greater sensitivity when the data were analyzed at the individual level compared to the group level. Thus, as in fMRI, functional localization yields benefits in MEG and thus opens the door to probing fine-grained distinctions in space and time in future MEG investigations of language processing.

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.

Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder

Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.

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.

Movement characteristics impact decision-making and vice versa

Previous studies suggest that humans are capable of coregulating the speed of decisions and movements if promoted by task incentives. It is unclear however whether such behavior is inherent to the process of translating decisional information into movements, beyond posing a valid strategy in some task contexts. Therefore, in a behavioral online study we imposed time constraints to either decision- or movement phases of a sensorimotor task, ensuring that coregulating decisions and movements was not promoted by task incentives. We found that participants indeed moved faster when fast decisions were promoted and decided faster when subsequent finger tapping movements had to be executed swiftly. These results were further supported by drift diffusion modelling and inspection of psychophysical kernels: Sensorimotor delays related to initiating the finger tapping sequence were shorter in fast-decision as compared to slow-decision blocks. Likewise, the decisional speed-accuracy tradeoff shifted in favor of faster decisions in fast-tapping as compared to slow-tapping blocks. These findings suggest that decisions not only impact movement characteristics, but that properties of movement impact the time taken to decide. We interpret these behavioral results in the context of embodied decision-making, whereby shared neural mechanisms may modulate decisions and movements in a joint fashion.

Similarity in activity and laterality patterns in the angular gyrus during autobiographical memory retrieval and self-referential processing

Long-term memory is arguably one of the key cognitive functions. At the neural level, the lateral parietal cortex and the angular gyrus, particularly in the left hemisphere, exhibit strong activations during autobiographical and episodic memory retrieval. In a separate sub-field, left-lateralized activations of the angular gyrus are also found during self-referential processing, defined as higher activity when a trait term is judged by participants as being related to them vs. related to someone else. The question is whether episodic/autobiographical memory retrieval and self-referential processing effects are related. In the present study, thirty participants participated in the fMRI study with two separate experiments: autobiographical memory retrieval (Experiment 1) and self-referential processing (Experiment 2). In a series of analyses, including the most critical spatial correlation analysis between experiments, we found neural similarity between autobiographical memory retrieval and self-referential processing. Given that self-referential processing was identified in a selective way, the most plausible interpretation of our findings is that self-referential processing might partly explain the activation of the left angular gyrus during autobiographical memory retrieval. Our results are in line with the seminal view of Endel Tulving that the sense of self is a fundamental attribute of long-term memory recollection. However, it should be emphasized that: a) our results do not imply that the left angular gyrus is not involved in the retrieval of episodic memory details; and b) given that our experiment included an autobiographical memory task, generalization of our results to the episodic memory laboratory tasks has yet to be tested.

Analysis of differentially expressed long non-coding RNAs in LPS-induced human HMC3 microglial cells

BACKGROUND

Long non-coding RNAs (lncRNAs) are emerging as key modulators of inflammatory gene expression, but their roles in neuroinflammation are poorly understood. Here, we identified the inflammation-related lncRNAs and correlated mRNAs of the lipopolysaccharide (LPS)-treated human microglial cell line HMC3. We explored their potential roles and interactions using bioinformatics tools such as gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG), and weighted gene co-expression network analysis (WGCNA).

RESULTS

We identified 5 differentially expressed (DE) lncRNAs, 4 of which (AC083837.1, IRF1-AS1, LINC02605, and MIR3142HG) are novel for microglia. The DElncRNAs with their correlated DEmRNAs (99 total) fell into two network modules that both were enriched with inflammation-related RNAs. However, treatment with the anti-inflammatory agent JQ1, an inhibitor of the bromodomain and extra-terminal (BET) protein BRD4, neutralized the LPS effect in only one module, showing little or even enhancing effect on the other.

CONCLUSIONS

These results provide insight into, and a resource for studying, the regulation of microglia-mediated neuroinflammation and its potential therapy by small-molecule BET inhibitors.

A minimal-complexity light-sheet microscope maps network activity in 3D neuronal systems

In vitro systems mimicking brain regions, brain organoids, are revolutionizing the neuroscience field. However, characterization of their electrical activity has remained a challenge as it requires readout at millisecond timescale in 3D at single-neuron resolution. While custom-built microscopes used with genetically encoded sensors are now opening this door, a full 3D characterization of organoid neural activity has not been performed yet, limited by the combined complexity of the optical and the biological system. Here, we introduce an accessible minimalistic light-sheet microscope to the neuroscience community. Designed as an add-on to a standard inverted microscope it can be assembled within one day. In contrast to existing simplistic setups, our platform is suited to record volumetric calcium traces. We successfully extracted 4D calcium traces at high temporal resolution by using a lightweight piezo stage to allow for 5 Hz volumetric scanning combined with a processing pipeline for true 3D neuronal trace segmentation. As a proof of principle, we created a 3D connectivity map of a stem cell derived neuron spheroid by imaging its activity. Our fast, low complexity setup empowers researchers to study the formation of neuronal networks in vitro for fundamental and neurodegeneration research.

Neural dynamics during emotional video engagement relate to anxiety

Inter-subject correlations (ISCs) of physiological data can reveal common stimulus-driven processing across subjects. ISC has been applied to passive video viewing in small samples to measure common engagement and emotional processing. Here, in a large sample study of healthy adults (N = 163) who watched an emotional film (The Lion Cage by Charlie Chaplin), we recorded electroencephalography (EEG) across participants and measured ISC in theta, alpha and beta frequency bands. Peak ISC on the emotionally engaging video was observed three-quarters into the film clip, during a time period which potentially elicited a positive emotion of relief. Peak ISC in all frequency bands was focused over centro-parietal electrodes localizing to superior parietal cortex. ISC in both alpha and beta frequencies had a significant inverse relationship with anxiety symptoms. Our study suggests that ISC measured during continuous non-event-locked passive viewing may serve as a useful marker for anxious mood.

The effect of mindfulness on the inflammatory, psychological and biomechanical domains of adult patients with low back pain: A randomized controlled clinical trial

Objective

This study aims to study the effect of mindfulness-based program on the psychological, biomechanical and inflammatory domains of patients with chronic low back pain.

Methods

A multicentre randomized and controlled clinical trial of parallel groups in patients with chronic low back pain between March 2019 to March 2020. Participants with no experience in mindfulness based intervention, were randomized to receive (36 patients) or not (34 patients) mindfulness-based stress reduction program for chronic back pain (MBSR-CBP). The program was performed in 9 sessions. Patients with chronic low back pain due to symptomatic discopathy (degenerative disc disease or herniated disc) were included. The principal outcome was changes in the blood level of cortisol and cytokines (tumor necrosis factor- α (TNF- α), interleukin-1β (IL-1β), interleukin-6 (IL-6) and interleukin-17 (IL-17)). Secondary outcomes (psychological factors, pain, and quality of life) were measured by validated questionnaires.

Results

Of the 96 randomized patients, 70 who completed the study were included in the analysis (mean [range] age: 53 [33–73] years; 66% females). MBSR-CBP stopped the increase in cortisol, and reduced pro-inflammatory cytokine IL-1β (p = 0.05). It reduced depression (p = 0.046) and stress (p = 0.0438), perceived pain (p < 0.0001), and limitations related to health (p < 0.0001). It also increased the physical function (p = 0.002) and sleep quality (p = 0.05). Furthermore, it significantly increased life satisfaction (0.006), well-being (p = 0.001) and vitality (p < 0.0001). It also increased self-compassion (p < 0.0001) and significantly reduced the overidentification (p<0.0001) and catastrophization (p = 0.002).

Conclusions

MBSR-CBP could be part of a multidisciplinary approach in the management of patients suffering from chronic low back pain.

Thalamic atrophy moderates associations among aerobic fitness, cognitive processing speed, and walking endurance in persons with multiple sclerosis

BACKGROUND AND OBJECTIVES

Thalamic atrophy (TA) represents a biomarker of neurodegeneration and associated dysfunction/decline in physical and cognitive functioning among persons with multiple sclerosis (MS). Aerobic fitness, as an end point of exercise training, represents a promising target for restoring function in MS, but it is unknown if such effects differ by TA. This cross-sectional study examined whether aerobic fitness was differentially associated with cognitive processing speed and walking endurance in persons with MS who present with and without TA.

METHODS

44 fully ambulatory persons with MS completed a graded exercise test for measuring aerobic fitness (VO_2peak) and underwent 3T MRI for measuring TA, the Symbol Digit Modalities Test (SDMT), and the 6-min walk (6MW). We performed Spearman correlations (r_s) among VO_2peak, SDMT, and 6MW scores overall, and in persons with and without TA. We applied Fisher's z-test for comparing correlations based on TA status.

RESULTS

When controlling for age, EDSS score, and global MRI measures of atrophy, VO_2peak was strongly associated with SDMT scores (pr_s = 0.74, p < 0.01) and 6MW performance (pr_s = 0.77, p < 0.01) in persons with TA, whereas VO_2peak was not associated with SDMT scores (pr_s =  - 0.01, p = 0.99) or 6MW performance (pr_s = 0.25, p = 0.38) in those without TA. The correlations between VO_2peak and SDMT (z = 2.86, p < 0.01) and VO_2peak and 6MW (z = 2.33, p = 0.02) were significantly stronger in the TA group.

DISCUSSION

This study provides initial evidence of strong, selective associations among aerobic fitness, cognitive processing speed, and walking endurance in persons with TA as a biomarker for MS-related neurodegeneration. Such data support TA as a moderator of the association among aerobic fitness, cognitive processing speed, and walking endurance in persons with MS. Future research should carefully consider the role of TA when designing trials of aerobic exercise, cognition, and mobility in MS.

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.

Cingulate cortex morphology impacts on neurofunctional activity and behavioral performance in interference tasks

Inhibitory control is the capacity to withhold or suppress a thought or action intentionally. The anterior Midcingulate Cortex (aMCC) participates in response inhibition, a proxy measure of inhibitory control. Recent research suggests that response inhibition is modulated by individual variability in the aMCC sulcal morphology. However, no study has investigated if this phenomenon is associated with neurofunctional differences during a task. In this study, 42 participants performed an Attention Network Task and a Numerical Stroop task in an MRI scanner. We investigated differences in brain activity and response inhibition efficiency between individuals with symmetric and asymmetric aMCC sulcal patterns. The results showed that aMCC morphological variability is partly associated with inhibitory control, and revealed greater activation in individuals with symmetric patterns during the Stroop task. Our findings provide novel insights into the functional correlates of the relationship between aMCC morphology and executive abilities.

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.

Effects of Concomitant Benzodiazepines and Antidepressants Long-Term Use on Social Decision-Making: Results From the Ultimatum Game

Benzodiazepines and antidepressants have been shown to change responses to unfairness; however, the effects of their combined use on unfairness evaluation are unknown. This study examines the effects of concomitant benzodiazepines and antidepressants long-term use on the evaluation of fair and unfair offers. To analyze behavioral changes on responses to unfairness, we compared the performance of medicated participants and healthy controls in the Ultimatum Game (UG), both in the proposer and in the respondent role. The results showed that long-term psychotropic users had the worse economic strategy by accepting less offers than control subjects. However, in the proposer role, the unfair offers made by participants were similar between groups. The present results suggest that long-term use of psychotropic medication, specifically the combination of benzodiazepines and antidepressants, may increase the sensitivity to unfairness, resulting in higher rejection rates in conditions where this strategy is the most disadvantageous.

Can neurofeedback provide evidence of direct brain-behavior causality?

Neurofeedback is a procedure that measures brain activity in real-time and presents it as feedback to an individual, thus allowing them to self-regulate brain activity with effects on cognitive processes inferred from behavior. One common argument is that neurofeedback studies can reveal how the measured brain activity causes a particular cognitive process. The causal claim is often made regarding the measured brain activity being manipulated as an independent variable, similar to brain stimulation studies. However, this causal inference is vulnerable to the argument that other upstream brain activities change concurrently and cause changes in the brain activity from which feedback is derived. In this paper, we outline the inference that neurofeedback may causally affect cognition by indirect means. We further argue that researchers should remain open to the idea that the trained brain activity could be part of a "causal network" that collectively affects cognition rather than being necessarily causally primary. This particular inference may provide a better translation of evidence from neurofeedback studies to the rest of neuroscience. We argue that the recent advent of multivariate pattern analysis, when combined with implicit neurofeedback, currently comprises the strongest case for causality. Our perspective is that although the burden of inferring direct causality is difficult, it may be triangulated using a collection of various methods in neuroscience. Finally, we argue that the neurofeedback methodology provides unique advantages compared to other methods for revealing changes in the brain and cognitive processes but that researchers should remain mindful of indirect causal effects.

Theta oscillations shift towards optimal frequency for cognitive control

Cognitive control allows to flexibly guide behaviour in a complex and ever-changing environment. It is supported by theta band (4-7 Hz) neural oscillations that coordinate distant neural populations. However, little is known about the precise neural mechanisms permitting such flexible control. Most research has focused on theta amplitude, showing that it increases when control is needed, but a second essential aspect of theta oscillations, their peak frequency, has mostly been overlooked. Here, using computational modelling and behavioural and electrophysiological recordings, in three independent datasets, we show that theta oscillations adaptively shift towards optimal frequency depending on task demands. We provide evidence that theta frequency balances reliable set-up of task representation and gating of task-relevant sensory and motor information and that this frequency shift predicts behavioural performance. Our study presents a mechanism supporting flexible control and calls for a reevaluation of the mechanistic role of theta oscillations in adaptive behaviour.

Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil

Social distancing in response to the COVID-19 pandemic brought several modifications in our daily lives. With these changes, some people have reported alterations in their feelings of how fast time was passing. In this study, we assessed whether and how social distancing and the evolution of the COVID-19 pandemic influenced participants' time awareness and production of time intervals. Participants (n = 3855) filled in the first questionnaire approximately 60 days after the start of social distancing in Brazil and weekly questionnaires for 15 weeks during social distancing. Our results indicate that time was perceived as expanded at the beginning, but this feeling decreased across the weeks. Time awareness was strongly associated with psychological factors such as loneliness, stress, and positive emotions, but not with time production. This relation was shown between participants and within their longitudinal reports. Together, our findings show how emotions are a crucial aspect of how time is felt.

Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil

Social distancing in response to the COVID-19 pandemic brought several modifications in our daily lives. With these changes, some people have reported alterations in their feelings of how fast time was passing. In this study, we assessed whether and how social distancing and the evolution of the COVID-19 pandemic influenced participants' time awareness and production of time intervals. Participants (n = 3855) filled in the first questionnaire approximately 60 days after the start of social distancing in Brazil and weekly questionnaires for 15 weeks during social distancing. Our results indicate that time was perceived as expanded at the beginning, but this feeling decreased across the weeks. Time awareness was strongly associated with psychological factors such as loneliness, stress, and positive emotions, but not with time production. This relation was shown between participants and within their longitudinal reports. Together, our findings show how emotions are a crucial aspect of how time is felt.

A Large-Scale Investigation of White Matter Microstructural Associations with Reading Ability

Reading involves the functioning of a widely distributed brain network, and white matter tracts are responsible for transmitting information between constituent network nodes. Several studies have analyzed fiber bundle microstructural properties to shed insights into the neural basis of reading abilities and disabilities. Findings have been inconsistent, potentially due to small sample sizes and varying methodology. To address this, we analyzed a large data set of 686 children ages 5–18 using state-of-the-art neuroimaging acquisitions and processing techniques. We searched for associations between fractional anisotropy (FA) and single-word and single-nonword reading skills in children with diverse reading abilities across multiple tracts previously thought to contribute to reading. We also looked for group differences in tract FA between typically reading children and children with reading disabilities. FA of the white matter increased with age across all participants. There were no significant correlations between overall reading abilities and tract FAs across all children, and no significant group differences in tract FA between children with and without reading disabilities. There were associations between FA and nonword reading ability in older children (ages 9 and above). Higher FA in the right superior longitudinal fasciculus (SLF) and left inferior cerebellar peduncle (ICP) correlated with better nonword reading skills. These results suggest that letter-sound correspondence skills, as measured by nonword reading, are associated with greater white matter coherence among older children in these two tracts, as indexed by higher FA.

Brain Network Segregation and Integration during Painful Thermal Stimulation

The present study aimed to determine changes in brain network integration/segregation during thermal pain using methods optimized for network connectivity events with high temporal resolution. Participants (n = 33) actively judged whether thermal stimuli applied to the volar forearm were painful or not and then rated the warmth/pain intensity after each trial. We show that the temporal evolution of integration/segregation within trials correlates with the subjective ratings of pain. Specifically, the brain shifts from a segregated state to an integrated state when processing painful stimuli. The association with subjective pain ratings occurred at different time points for all networks. However, the degree of association between ratings and integration/segregation vanished for several brain networks when time-varying functional connectivity was measured at lower temporal resolution. Moreover, the increased integration associated with pain is explained to some degree by relative increases in between-network connectivity. Our results highlight the importance of investigating the relationship between pain and brain network connectivity at a single time point scale, since commonly used temporal aggregations of connectivity data may result in that fine-scale changes in network connectivity may go unnoticed. The interplay between integration/segregation reflects shifting demands of information processing between brain networks and this adaptation occurs both for cognitive tasks and nociceptive processing.

Augmented pain inhibition and higher integration of pain modulatory brain networks in women with self-injury behavior

Individuals who engage in nonsuicidal self-injury (NSSI) have demonstrated insensitivity to pain compared with individuals without NSSI. Yet, the neural mechanisms behind this difference are unknown. The objective of the present study was to determine which aspects of the pain regulatory system that account for this decreased sensitivity to pain. In a case-control design, 81 women, aged 18-35 (mean [SD] age, 23.4 [3.9]), were included (41 with NSSI and 40 healthy controls). A quantitative sensory testing protocol, including heat pain thresholds, heat pain tolerance, pressure pain thresholds, conditioned pain modulation (assessing central down-regulation of pain), and temporal summation (assessing facilitation of pain signals) was used. Pain-evoked brain responses were assessed by means of fMRI scanning during thermal pain. NSSI participants showed a more effective central down-regulation of pain, compared to controls, assessed with conditioned pain modulation. The neural responses to painful stimulation revealed a stronger relation between nociceptive and pain modulatory brain regions in NSSI compared to controls. In line with previous studies, pressure and heat pain thresholds were higher in participants with NSSI, however, there were no correlations between pain outcomes and NSSI clinical characteristics. The augmented pain inhibition and higher involvement of pain modulatory brain networks in NSSI may represent a pain insensitive endophenotype associated with a greater risk for developing self-injurious behavior.

White matter variability, cognition, and disorders: a systematic review

Inter-individual differences can inform treatment procedures and—if accounted for—have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional, and connectional anatomy. Brain connections are essential to facilitate functional organization and, when severed, cause impairments or complete loss of function. Hence, the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate cognitive functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not correlated with one, but multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract–function correlations might still be a promising tool in identifying biomarkers for precision medicine. They can characterize variations in brain anatomy, differences in functional organization, and predicts resilience and recovery in patients.

Contributions of diagnostic, cognitive, and somatovisceral information to the prediction of fear ratings in spider phobic and non-spider-fearful individuals

BACKGROUND

Physiological responding is a key characteristic of fear responses. Yet, it is unknown whether the time-consuming measurement of somatovisceral responses ameliorates the prediction of individual fear responses beyond the accuracy reached by the consideration of diagnostic (e.g., phobic vs. non phobic) and cognitive (e.g., risk estimation) factors, which can be more easily assessed.

METHOD

We applied a machine learning approach to data of an experiment, in which spider phobic and non-spider fearful participants (diagnostic factor) faced pictures of spiders. For each experimental trial, participants specified their personal risk of encountering the spider (cognitive factor), as well as their subjective fear (outcome variable) on quasi-continuous scales, while diverse somatovisceral responses were registered (heart rate, electrodermal activity, respiration, facial muscle activity).

RESULTS

The machine-learning analyses revealed that fear ratings were predominantly predictable by the diagnostic factor. Yet, when allowing for learning of individual patterns in the data, somatovisceral responses contributed additional information on the fear ratings, yielding a prediction accuracy of 81% explained variance. Moreover, heart rate prior to picture onset, but not heart rate reactivity increased predictive power.

LIMITATIONS

Fear was solely assessed by verbal reports, only 27 females were considered, and no generalization to other anxiety disorders is possible.

CONCLUSIONS

After training the algorithm to learn about individual-specific responding, somatovisceral patterns can be successfully exploited. Our findings further point to the possibility that the expectancy-related autonomic state throughout the experiment predisposes an individual to experience specific levels of fear, with less influence of the actual visual stimulations.

Range-Adaptive Value Representation in Different Stages of Schizophrenia: A Proof of Concept Study

Amotivation is related to value representation. A comprehensive account of amotivation requires a mechanistic understanding of how the brain exploits external information to represent value. To achieve maximal value discriminability, brain valuation system will dynamically adapt its coding sensitivity to the range of values available in any given condition, so-called range adaptive coding. We administered an experimental task to 30 patients with chronic schizophrenia (C-SCZ), 30 first-episode schizophrenia (FE-SCZ), 34 individuals with high social anhedonia (HSoA), and their paired controls to assess range adaptation ability. C-SCZ patients exhibited over-adaptation and their performances were negatively correlated with avolition symptoms and positive symptoms and positively correlated with blunted-affect symptoms and self-reported consummatory interpersonal pleasure scores, though the results were non-significant. FE-SCZ patients exhibited reduced adaptation, which was significantly and negatively correlated with avolition symptoms and positively correlated with the overall proportion of choosing to exert more effort. Although HSoA participants exhibited comparable range adaptation to controls, their performances were significantly and negatively correlated with the proportion of choosing to exert more effort under the lowest value condition. Our results suggest that different stages of schizophrenia spectrum showed distinct range adaptation patterns. Range adaptation impairments may index a possible underlying mechanism for amotivation symptoms in FE-SCZ and more complicated and pervasive effects on clinical symptoms in C-SCZ.

Dissociating the Neural Correlates of Consciousness and Task Relevance in Face Perception Using Simultaneous EEG-fMRI

Current theories of visual consciousness disagree about whether it emerges during early stages of processing in sensory brain regions or later when a widespread frontoparietal network becomes involved. Moreover, disentangling conscious perception from task-related postperceptual processes (e.g., report) and integrating results across different neuroscientific methods remain ongoing challenges. The present study addressed these problems using simultaneous EEG-fMRI and a specific inattentional blindness paradigm with three physically identical phases in female and male human participants. In phase 1, participants performed a distractor task during which line drawings of faces and control stimuli were presented centrally. While some participants spontaneously noticed the faces in phase 1, others remained inattentionally blind. In phase 2, all participants were made aware of the task-irrelevant faces but continued the distractor task. In phase 3, the faces became task-relevant. Bayesian analysis of brain responses demonstrated that conscious face perception was most strongly associated with activation in fusiform gyrus (fMRI) as well as the N170 and visual awareness negativity (EEG). Smaller awareness effects were revealed in the occipital and prefrontal cortex (fMRI). Task-relevant face processing, on the other hand, led to strong, extensive activation of occipitotemporal, frontoparietal, and attentional networks (fMRI). In EEG, it enhanced early negativities and elicited a pronounced P3b component. Overall, we provide evidence that conscious visual perception is linked with early processing in stimulus-specific sensory brain areas but may additionally involve prefrontal cortex. In contrast, the strong activation of widespread brain networks and the P3b are more likely associated with task-related processes.SIGNIFICANCE STATEMENT How does our brain generate visual consciousness-the subjective experience of what it is like to see, for example, a face? To date, it is hotly debated whether it emerges early in sensory brain regions or later when a widespread frontoparietal network is activated. Here, we use simultaneous fMRI and EEG for high spatial and temporal resolution and demonstrate that conscious face perception is predominantly linked to early and occipitotemporal processes, but also prefrontal activity. Task-related processes (e.g., decision-making), on the other hand, elicit brain-wide activations including late and strong frontoparietal activity. These findings challenge numerous previous studies and highlight the importance of investigating the neural correlates of consciousness in the absence of task relevance.

Mixed-effects multilevel analysis followed by canonical correlation analysis is an effective fMRI tool for the investigation of idiosyncrasies

We report that regions-of-interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed-effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). A real-world dataset for the neuronal response to nicotine use was acquired using a custom-made MRI-compatible apparatus for the smoking of electronic cigarettes (e-cigarettes). Nineteen participants smoked e-cigarettes in an MRI scanner using the apparatus with two experimental conditions: e-cigarettes with nicotine (ECIG) and sham e-cigarettes without nicotine (SCIG) and subjective ratings were collected. The right insula was identified in the ECIG condition from the χ² -test of the MEMA but not from the t-test, and the corresponding activations were significantly associated with the similarity scores (r = -.52, p = .041, confidence interval [CI] = [-0.78, -0.17]) and the urge-to-smoke scores (r = .73, p <.001, CI = [0.52, 0.88]). From the contrast between the two conditions (i.e., ECIG > SCIG), the right orbitofrontal cortex was identified from the χ² -tests, and the corresponding neuronal activations showed a statistically meaningful association with similarity (r = -.58, p = .01, CI = [-0.84, -0.17]) and the urge to smoke (r = .34, p = .15, CI = [0.09, 0.56]). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was further evaluated using the fMRI and behavioral data acquired from the working memory and gambling tasks available from the Human Connectome Project.

Associations between brain and behavioral processing of facial expressions of emotion and sensory reactivity in young children

The ability to decode and accurately identify information from facial emotions may advantage young children socially. This capacity to decode emotional information may likewise be influenced by individual differences in children's temperament. This study investigated whether sensory reactivity and perceptual awareness, two dimensions of temperament, as well as children's ability to accurately label emotions relates to the neural processing of emotional content in faces. Event related potentials (ERPs) of 4 to 6 year-old children (N  = 119) were elicited from static displays of anger, happy, fearful, sad, and neutral emotion faces. Children, as a group, exhibited differential early (N290) and mid-latency (P400) event-related potentials (ERPs) in response to facial expressions of emotion. Individual differences in children's sensory reactivity were associated with enhanced P400 amplitudes to neutral, sad, and fearful faces. In a separate task, children were asked to provide an emotional label for the same images. Interestingly, children less accurately labeled the same neutral, sad, and fearful faces, suggesting that, contrary to previous work showing enhanced attentional processing to threatening cues (i.e., fear), children higher in sensory reactivity may deploy more attentional resources when decoding ambiguous emotional cues.

Identifying Mobile Sensing Indicators of Stress-Resilience

Resident physicians (residents) experiencing prolonged workplace stress are at risk of developing mental health symptoms. Creating novel, unobtrusive measures of resilience would provide an accessible approach to evaluate symptom susceptibility without the perceived stigma of formal mental health assessments. In this work, we created a system to find indicators of resilience using passive wearable sensors and smartphone-delivered ecological momentary assessment (EMA). This system identified indicators of resilience during a medical internship, the high stress first-year of a residency program. We then created density estimation approaches to predict these indicators before mental health changes occurred, and validated whether the predicted indicators were also associated with resilience. Our system identified resilience indicators associated with physical activity (step count), sleeping behavior, reduced heart rate, increased mood, and reduced mood variability. Density estimation models were able to replicate a subset of the associations between sleeping behavior, heart rate, and resilience. To the best of our knowledge, this work provides the first methodology to identify and predict indicators of resilience using passive sensing and EMA. Researchers studying resident mental health can apply this approach to design resilience-building interventions and prevent mental health symptom development.

A 4-year longitudinal neuroimaging study of cognitive control using latent growth modeling: developmental changes and brain-behavior associations

Despite theoretical models suggesting developmental changes in neural substrates of cognitive control in adolescence, empirical research has rarely examined intraindividual changes in cognitive control-related brain activation using multi-wave multivariate longitudinal data. We used longitudinal repeated measures of brain activation and behavioral performance during the multi-source interference task (MSIT) from 167 adolescents (53% male) who were assessed annually over four years from ages 13 to 17 years. We applied latent growth modeling to delineate the pattern of brain activation changes over time and to examine longitudinal associations between brain activation and behavioral performance. We identified brain regions that showed differential change patterns: (1) the fronto-parietal regions that involved bilateral insula, bilateral middle frontal gyrus, left pre-supplementary motor area, left inferior parietal lobule, and right precuneus; and (2) the rostral anterior cingulate cortex (rACC) region. Longitudinal confirmatory factor analyses of the fronto-parietal regions revealed strong measurement invariance across time implying that multivariate functional magnetic resonance imaging data during cognitive control can be measured reliably over time. Latent basis growth models indicated that fronto-parietal activation decreased over time, whereas rACC activation increased over time. In addition, behavioral performance data, age-related improvement was indicated by a decreasing trajectory of intraindividual variability in response time across four years. Testing longitudinal brain-behavior associations using multivariate growth models revealed that better behavioral cognitive control was associated with lower fronto-parietal activation, but the change in behavioral performance was not related to the change in brain activation. The current findings suggest that reduced effects of cognitive interference indicated by fronto-parietal recruitment may be a marker of a maturing brain that underlies better cognitive control performance during adolescence.