Distributed Brain Activity Research Articles

Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain

A central challenge of neuroscience is to elucidate how brain function supports consciousness. Here, we combine the specificity of focal deep brain stimulation with fMRI coverage of the entire cortex, in awake and anaesthetised non-human primates. During propofol, sevoflurane, or ketamine anaesthesia, and subsequent restoration of responsiveness by electrical stimulation of the central thalamus, we investigate how loss of consciousness impacts distributed patterns of structure-function organisation across scales. We report that distributed brain activity under anaesthesia is increasingly constrained by brain structure across scales, coinciding with anaesthetic-induced collapse of multiple dimensions of hierarchical cortical organisation. These distributed signatures are observed across different anaesthetics, and they are reversed by electrical stimulation of the central thalamus, coinciding with recovery of behavioural markers of arousal. No such effects were observed upon stimulating the ventral lateral thalamus, demonstrating specificity. Overall, we identify consistent distributed signatures of consciousness that are orchestrated by specific thalamic nuclei.

Building cognitive functions from distributed brain activity

With recordings from temporal, parietal, and frontal regions of the behaving monkey brain, accompanied by a powerful method for optogenetic silencing of the frontal region, Mendoza-Halliday etal. compare network functions for working memory and visual selective attention.

Principles of nociceptive coding in the anterior cingulate cortex

The perception of pain is a multidimensional sensory and emotional/affective experience arising from distributed brain activity. However, the involved brain regions are not specific for pain. Thus, how the cortex distinguishes nociception from other aversive and salient sensory stimuli remains elusive. Additionally, the resulting consequences of chronic neuropathic pain on sensory processing have not been characterized. Using invivo miniscope calcium imaging with cellular resolution in freely moving mice, we elucidated the principles of nociceptive and sensory coding in the anterior cingulate cortex, a region essential for pain processing. We found that population activity, not single-cell responses, allowed discriminating noxious from other sensory stimuli, ruling out the existence of nociception-specific neurons. Additionally, single-cell stimulus selectivity was highly dynamic over time, but stimulus representation at the population level remained stable. Peripheral nerve injury-induced chronic neuropathic pain led to dysfunctional encoding of sensory events by exacerbation of responses to innocuous stimuli and impairment of pattern separation and stimulus classification, which were restored by analgesic treatment. These findings provide a novel interpretation for altered cortical sensory processing in chronic neuropathic pain and give insights into the effects of systemic analgesic treatment in the cortex.

Functional integration of anterior insula related to meaning in life and loneliness

BackgroundMeaning in life (MIL), defined as people's feelings of life's meaningfulness, plays a vital role in buffering loneliness - an important indicator of depression and other psychological disorders. Considerable evidence shows that MIL arises from widely distributed brain activity; however, how such activity is functionally integrated and how it influences loneliness is still understudied. MethodsWe here examined how the functional integration of brain regions is related to individual MIL based on resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 970). ResultsWe found that the global brain connectivity (GBC) of the right anterior insula (rAI) can significantly predict individual MIL. Moreover, mediation analyses were conducted to investigate how the brain influences loneliness with MIL's mediation, which revealed that MIL fully mediates the effect of this hub on loneliness. ConclusionsThese findings suggest that the rAI is a key hub for MIL and loneliness. Its functional integration can be used as a biomarker to predict individual MIL and loneliness.

Time-resolved correlation of distributed brain activity tracks E-I balance and accounts for diverse scale-free phenomena

Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.

The pericontused cortex can support function early after TBI but it remains functionally isolated from normal afferent input

Traumatically injured brain functional connectivity (FC) is altered in a region-dependent manner with some regions functionally disconnected while others are hyperconnected after experimental TBI. Remote, homotopic cortical regions become hyperexcitable after injury, and we hypothesize that this results in increased trans-hemispheric cortical inhibition, preventing reorganization of the primary injured hemisphere. Previously we have shown that temporary silencing the contralesional cortex at 1wk normalizes affected forelimb behavioral use, but not at 4wks. To investigate the potential mechanism for this and to determine whether this occurs due to restoration of afferent pathway FC, and/or reorganization of brain circuits, we probed forelimb circuit function with sensorimotor task-evoked-fMRI, resting state fMRI seed-based analysis, and exploratory structural equation modelling (SEM) of directed causal connections due to forelimb task at 1 and 4wks post-injury after temporary, contralateral silencing with intraparenchymal injection of muscimol versus vehicle, as well as from sham rats. As predicted, silencing at 1wk and 4wks post-injury decimated the contralesional cortical forelimb map evoked by stimulation of the opposite, unaffected forelimb compared to vehicle-injected injured rats indicating the success of the intervention. Surprisingly however, this also resulted in activation of the pericontused cortex ipsilateral to the stimulated forelimb at 1wk, yet this same region could not be activated by directly stimulating the opposite, injury-affected forelimb. Underpinning this were significant increases in interhemispheric FC at the level of the cortex but decreases within subcortical regions. Causal SEM analysis confirmed increased corticothalamic connectivity and suggested changes from and to bilateral thalamus are important for the effect. At 4wks post-injury only cortical increases in FC were found in response to silencing indicating a less flexible brain, and ipsilesional cortex evoked activity was mostly absent. The absence of a reinstatement of ipsilesional evoked activity through normal pathways by temporary neuromodulation despite prior data showing behavioral improvements under the same conditions, indicates that while the pericontused cortex does retain function initially after injury, it is too functionally disconnected to be controlled by normal afferent input. More significant alterations in cross-brain FC during neuromodulation at 1wk compared to 4wk post-injury, suggest that more distributed brain activity accounts for prior behavior improvements in sensorimotor function, and that hemispheric imbalance in function is causally involved in early loss of sensorimotor function in this TBI model.

Time-Resolved Smoothness of Distributed Brain Activity Tracks Conscious States and Unifies Emergent Neural Phenomena

Time-Resolved Smoothness of Distributed Brain Activity Tracks Conscious States and Unifies Emergent Neural Phenomena

Integrated Intelligence from Distributed Brain Activity.

How does organized cognition arise from distributed brain activity? Recent analyses of fluid intelligence suggest a core process of cognitive focus and integration, organizing the components of a cognitive operation into the required computational structure. A cortical 'multiple-demand' (MD) system is closely linked to fluid intelligence, and recent imaging data define nine specific MD patches distributed across frontal, parietal, and occipitotemporal cortex. Wide cortical distribution, relative functional specialization, and strong connectivity suggest a basis for cognitive integration, matching electrophysiological evidence for binding of cognitive operations to their contents. Though still only in broad outline, these data suggest how distributed brain activity can build complex, organized cognition.

White Matter Microstructure Predicts Focal and Broad Functional Brain Dedifferentiation in Normal Aging.

Ventral visual cortex exhibits highly organized and selective patterns of functional activity associated with visual processing. However, this specialization decreases in normal aging, with functional responses to different visual stimuli becoming more similar with age, a phenomenon termed "dedifferentiation." The current study tested the hypothesis that age-related degradation of the inferior longitudinal fasciculus (ILF), a white matter pathway involved in visual perception, could account for dedifferentiation of both localized and distributed brain activity in ventral visual cortex. Participants included 281 adults, ages 20-89 years, from the Dallas Lifespan Brain Study who underwent diffusion-weighted imaging to measure white matter diffusivity, as well as fMRI to measure functional selectivity to viewing photographs from different categories (e.g., faces, houses). In general, decreased ILF anisotropy significantly predicted both focal and broad functional dedifferentiation. Specifically, there was a localized effect of structure on function, such that decreased anisotropy in a smaller mid-fusiform region of ILF predicted less selective (i.e., more dedifferentiated) response to viewing faces in a proximal face-responsive region of fusiform. On the other hand, the whole ILF predicted less selective response across broader ventral visual cortex for viewing animate (e.g., human faces, animals) versus inanimate (e.g., houses, chairs) images. This structure-function relationship became weaker with age and was no longer significant after the age of 70 years. These findings indicate that decreased white matter anisotropy is associated with maladaptive differences in proximal brain function and is an important variable to consider when interpreting age differences in functional selectivity.

Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review.

Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI‐NF studies. We found: (a) that less than a third of the studies reported implementing standard real‐time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI‐NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI‐NF studies: (a) report implementation of a set of standard real‐time fMRI denoising steps according to a proposed COBIDAS‐style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community‐informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open‐source rtfMRI‐NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality‐and‐denoising‐in‐rtfmri‐nf.

Affective brain patterns as multivariate neural correlates of cardiovascular disease risk.

This study tested whether brain activity patterns evoked by affective stimuli relate to individual differences in an indicator of pre-clinical atherosclerosis: carotid artery intima-media thickness (CA-IMT). Adults (aged 30–54 years) completed functional magnetic resonance imaging (fMRI) tasks that involved viewing three sets of affective stimuli. Two sets included facial expressions of emotion, and one set included neutral and unpleasant images from the International Affective Picture System (IAPS). Cross-validated, multivariate and machine learning models showed that individual differences in CA-IMT were partially predicted by brain activity patterns evoked by unpleasant IAPS images, even after accounting for age, sex and known cardiovascular disease risk factors. CA-IMT was also predicted by brain activity patterns evoked by angry and fearful faces from one of the two stimulus sets of facial expressions, but this predictive association did not persist after accounting for known cardiovascular risk factors. The reliability (internal consistency) of brain activity patterns evoked by affective stimuli may have constrained their prediction of CA-IMT. Distributed brain activity patterns could comprise affective neural correlates of pre-clinical atherosclerosis; however, the interpretation of such correlates may depend on their psychometric properties, as well as the influence of other cardiovascular risk factors and specific affective cues.

Effects of age, sex, and puberty on neural efficiency of cognitive and motor control in adolescents.

Critical changes in adolescence involve brain cognitive maturation of inhibitory control processes that are essential for a myriad of adult functions. Cognitive control advances into adulthood as there is more flexible integration of component processes, including inhibitory control of conflicting information, overwriting inappropriate response tendencies, and amplifying relevant responses for accurate execution. Using a modified Stroop task with fMRI, we investigated the effects of age, sex, and puberty on brain functional correlates of cognitive and motor control in 87 boys and 91 girls across the adolescent age range. Results revealed dissociable brain systems for cognitive and motor control processes, whereby adolescents flexibly adapted neural responses to control demands. Specifically, when response repetitions facilitated planning-based action selection, frontoparietal-insular regions associated with cognitive control operations were less activated, whereas cortical-pallidal-cerebellar motor regions associated with motor skill acquisition, were more activated. Attenuated middle cingulate cortex activation occurred with older adolescent age for both motor control and cognitive control with automaticity from repetition learning. Sexual dimorphism for control operations occurred in extrastriate cortices involved in visuo-attentional selection: While boys enhanced extrastriate selection processes for motor control, girls activated these regions more for cognitive control. These sex differences were attenuated with more advanced pubertal stage. Together, our findings show that brain cognitive and motor control processes are segregated, demand-specific, more efficient in older adolescents, and differ between sexes relative to pubertal development. Our findings advance our understanding of how distributed brain activity and the neurodevelopment of automaticity enhances cognitive and motor control ability in adolescence.

Mindfulness-based training with transcranial direct current stimulation modulates neuronal resource allocation in working memory: A randomized pilot study with a nonequivalent control group

Mindfulness-based training (MBT) and transcranial electrical stimulation (TES) methods such as direct current stimulation (tDCS) have demonstrated promise for the augmentation of cognitive abilities. The current study investigated the potential compatibility of concurrent “electrical” MBT and tDCS (or eMBT) by testing its combined effects on behavioral and neurophysiological indices of working memory (WM) and attentional resource allocation. Thirty-four healthy participants were randomly assigned to either a MBT task with tDCS group (eMBT) or an active control training task with sham tDCS (Control) group. Training lasted 4-weeks, with up to twenty MBT sessions and with up to eight of those sessions that were eMBT sessions. Electroencephalography was acquired during varying WM load conditions using the n-back task (1-, 2-, 3-back), along with performance on complex WM span tasks (operation and symmetry span) and fluid intelligence measures (Ravens and Shipley) before and after training. Improved performance was observed only on the 3-back and spatial span tasks for eMBT but not the Control group. During 3-back performance in the eMBT group, an increase in P3 amplitude and theta power at electrode site Pz was also observed, along with a simultaneous decrease in frontal midline P3 amplitude and theta power compared to the Control group. These results are consistent with the neural efficiency hypothesis, where higher cognitive capacity was associated with more distributed brain activity (i.e., increase in parietal and decrease in frontal amplitudes). Future longitudinal studies are called upon to further examine the direct contributions of tDCS on MBT by assessing the differential effects of electrode montage, polarity, current strength and a direct contrast between the eMBT and MBT conditions on performance and neuroimaging outcome data. While preliminary, the current results provided evidence for the potential compatibility of using eMBT to modulate WM capacity through the allocation of attention and its neurophysiological correlates.

Heritability of the human connectome: A connectotyping study.

Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks.

The evolution of cognitive models: From neuropsychology to neuroimaging and back

This paper provides a historical and future perspective on how neuropsychology and neuroimaging can be used to develop cognitive models of human brain functions. Section 1 focuses on the emergence of cognitive modelling from neuropsychology, why lesion location was considered to be unimportant and the challenges faced when mapping symptoms to impaired cognitive processes. Section 2 describes how established cognitive models based on behavioural data alone cannot explain the complex patterns of distributed brain activity that are observed in functional neuroimaging studies. This has led to proposals for new cognitive processes, new cognitive strategies and new functional ontologies for cognition. Section 3 considers how the integration of data from lesion, behavioural and functional neuroimaging studies of large cohorts of brain damaged patients can be used to determine whether inter-patient variability in behaviour is due to differences in the premorbid function of each brain region, lesion site or cognitive strategy. This combination of neuroimaging and neuropsychology is providing a deeper understanding of how cognitive functions can be lost and re-learnt after brain damage – an understanding that will transform our ability to generate and validate cognitive models that are both physiologically plausible and clinically useful.

Have Standard Tests of Cognitive Function Been Misappropriated in the Study of Cognitive Enhancement?

In the past decade, there has emerged a vast research literature dealing with attempts to harness brain plasticity in older adults, with a view to improving cognitive function. Since cognitive training (CT) has shown restricted utility in this regard, attention has increasingly turned to interventions that use adjunct procedures such as motor training or physical activity (PA). As evidence builds that these have some efficacy, it becomes necessary to ensure that the outcome measures being used to infer causal influence upon cognitive function are subjected to appropriate critical appraisal. It has been highlighted previously that the choice of specific tasks used to demonstrate transfer to the cognitive domain is of critical importance. In the context of most intervention studies, standardized tests and batteries of cognitive function are de rigueur. The argument presented here is that the latent constructs to which these tests relate are not usually subject to a sufficient level of analytic scrutiny. We present the historical origins of some exemplar tests, and give particular consideration to the limits on explanatory scope that are implied by their composition and the nature of their deployment. In addition to surveying the validity of these tests when used to appraise intervention-related changes in cognitive function, we also consider their neurophysiological correlates. In particular, we argue that the broadly distributed brain activity associated with the performance of many tests of cognitive function, extending to the classical motor networks, permits the impact of interventions based on motor training or PA to be better understood.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning

BackgroundThe use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. New methodTo facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. ResultsOur experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. Comparison with existing methodsWe compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. ConclusionsThese results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models.

Cooperation in mind: Motor imagery of joint and single actions is represented in different brain areas

In this study brain activity during motor imagery (MI) of joint actions, compared to single actions and rest conditions, was investigated using functional magnetic resonance imaging (fMRI). To the best of our knowledge, this is the first neuroimaging study which directly investigated the neural correlates of joint action motor imagery. Twenty-one healthy participants imagined three different motor tasks (dancing, carrying a box, wiping). Each imagery task was performed at two kinds: alone (single action MI) or with a partner (joint action MI). We hypothesized that to imagine a cooperative task would lead to a stronger cortical activation in motor related areas due to a higher vividness and intensification of the imagery. This would be elicited by the integration of the action simulation of the virtual partner to one’s own action. Comparing the joint action and the single action condition with the rest condition, we found significant activation in the precentral gyrus and precuneus respectively. Furthermore the joint action MI showed higher activation patterns in the premotor cortex (inferior and middle frontal gyrus) compared to the single action MI. The imagery of a more vivid and engaging task, like our joint action imagery, could improve rehabilitation processes since a more distributed brain activity is found. Furthermore, the joint action imagery compared to single action imagery might be an appropriate BCI task due to its clear spatial distinction of activation.

Influences of High-Level Features, Gaze, and Scene Transitions on the Reliability of BOLD Responses to Natural Movie Stimuli.

Complex, sustained, dynamic, and naturalistic visual stimulation can evoke distributed brain activities that are highly reproducible within and across individuals. However, the precise origins of such reproducible responses remain incompletely understood. Here, we employed concurrent functional magnetic resonance imaging (fMRI) and eye tracking to investigate the experimental and behavioral factors that influence fMRI activity and its intra- and inter-subject reproducibility during repeated movie stimuli. We found that widely distributed and highly reproducible fMRI responses were attributed primarily to the high-level natural content in the movie. In the absence of such natural content, low-level visual features alone in a spatiotemporally scrambled control stimulus evoked significantly reduced degree and extent of reproducible responses, which were mostly confined to the primary visual cortex (V1). We also found that the varying gaze behavior affected the cortical response at the peripheral part of V1 and in the oculomotor network, with minor effects on the response reproducibility over the extrastriate visual areas. Lastly, scene transitions in the movie stimulus due to film editing partly caused the reproducible fMRI responses at widespread cortical areas, especially along the ventral visual pathway. Therefore, the naturalistic nature of a movie stimulus is necessary for driving highly reliable visual activations. In a movie-stimulation paradigm, scene transitions and individuals’ gaze behavior should be taken as potential confounding factors in order to properly interpret cortical activity that supports natural vision.

Investigating the Role of Alpha and Beta Rhythms in Functional Motor Networks

It is recognized that lower electroencephalography (EEG) frequencies correspond to distributed brain activity over larger spatial regions than higher frequencies and are associated with coordination. In motor processes it has been suggested that this is not always the case. Our objective was to explore this contradiction. In our study, seven healthy subjects performed four motor tasks (execution and imagery of right hand and foot) under EEG recording. Two cortical source models were defined, model «A» with 16 regions of interest (ROIs) and model «B» with 20 ROIs over the sensorimotor cortex. Functional connectivity was calculated by Directed Transfer Function for alpha and beta rhythm networks. Four graph properties were calculated for each network: characteristic path length (CPL), clustering coefficient (CC), density (D) and small-world-ness (SW). Different network modules and in-degrees of nodes were also calculated and depicted in connectivity maps. Analysis of variance was used to determine statistical significance of observed differences in the network properties between tasks, between rhythms and between ROI models. Consistently on both models, CPL and CC were lower and D was higher in beta rhythm networks. No statistically significant difference was observed for SW between rhythms or for any property between tasks on any model. Comparing the models we observed lower CPL for both rhythms, lower CC in alpha and higher CC in beta when the number of ROIs increased. Also, denser networks with higher SW were correlated with higher number of ROIs. We propose a non-exclusive model where alpha rhythm uses greater wiring costs to engage in local information progression while beta rhythm coordinates the neurophysiological processes in sensorimotor tasks.