The resting human brain and motor learning

Expertise modulates local regional homogeneity of spontaneous brain activity in the resting brain: an fMRI study using the model of skilled acupuncturists

Studies on training/expertise-related effects on human brain in context of neuroplasticity have revealed that plastic changes modulate not only task activations but also patterns and strength of internetworks and intranetworks functional connectivity in the resting state. Much has known about plastic changes in resting state on global level; however, how training/expertise-related effect affects patterns of local spontaneous activity in resting brain remains elusive. We investigated the homogeneity of local blood oxygen level-dependent fluctuations in the resting state using a regional homogeneity (ReHo) analysis among 16 acupuncturists and 16 matched nonacupuncturists (NA). To prove acupuncturists' expertise, we used a series of psychophysical tests. Our results demonstrated that, acupuncturists significantly outperformed NA in tactile-motor and emotional regulation domain and the acupuncturist group showed increased coherence in local BOLD signal fluctuations in the left primary motor cortex (MI), the left primary somatosensory cortex (SI) and the left ventral medial prefrontal cortex/orbitofrontal cortex (VMPFC/OFC). Regression analysis displayed that, in the acupuncturists group, ReHo of VMPFC/OFC could predict behavioral outcomes, evidenced by negative correlation between unpleasantness ratings and ReHo of VMPFC/OFC and ReHo of SI and MI positively correlated with the duration of acupuncture practice. We suggest that expertise could modulate patterns of local resting state activity by increasing regional clustering strength, which is likely to contribute to advanced local information processing efficiency. Our study completes the understanding of neuroplasticity changes by adding the evidence of local resting state activity alterations, which is helpful for elucidating in what manner training effect extends beyond resting state.

Alterations in resting functional connectivity due to recent motor task

The impact of recent experiences of task performance on resting functional connectivity MRI (fcMRI) has important implications for the design of many neuroimaging studies, because, if an effect is present, the fcMRI scan then must be performed before any evoked fMRI or after a time gap to allow it to dissipate. The present study aims to determine the effect of simple button presses, which are used in many cognitive fMRI tasks as a response recording method, on later acquired fcMRI data. Human volunteers were subject to a 23-minute button press motor task. Their resting-state brain activity before and after the task was assessed with fcMRI. It was found that, compared to the pre-task resting period, the post-task resting fcMRI revealed a significantly higher (p=0.002, N=24) cross correlation coefficient (CC) between left and right motor cortices. These changes were not present in sham control studies that matched the paradigm timing but had no actual task. The amplitude of fcMRI signal fluctuation (AF) also demonstrated an increase in the post-task period compared to pre-task. These changes were observed using both the right-hand-only task and the two-hand task. Study of the recovery time course of these effects revealed that the CC changes lasted for about 5 min while the AF change lasted for at least 15 min. Finally, voxelwise analysis revealed that the pre/post-task differences were also observed in several other brain regions, including the auditory cortex, visual areas, and the thalamus. Our data suggest that the recent performance of the simple button press task can result in elevated fcMRI CC and AF in relevant brain networks and that fcMRI scan should be performed either before evoked fMRI or after a sufficient time gap following fMRI.

Changes of inter-hemispheric functional connectivity between motor cortices after brachial plexuses injury: a resting-state fMRI study

OBJECT

The aim of this study is to explore the changes of inter-hemispheric functional connectivity in patients with unilateral brachial plexus injury.

METHODS

Nine patients with five roots of unilateral brachial plexus avulsion injury and 11 healthy controls were recruited in this study. Resting-state functional connectivity magnetic resonance image was used to study the differences of inter-hemispheric functional connectivity between patients and healthy controls. Four areas were defined as regions of interest (ROI): the two primary motor areas (M1 areas) and two supplementary motor areas (SMAs) in the two hemispheres activated when the healthy controls performed unilateral hand grasping movement of the two hands, respectively. Functional connectivity maps were generated by correlating the regional time course of each ROI with that of every voxel in the whole brain. Then, functional connectivity was calculated by correlating the functional magnetic resonance image signal time courses of every two ROIs.

RESULTS

Resting-state inter-hemispheric functional connectivity of the primary motor areas was reduced following brachial plexus avulsion injury. The correlation coefficients of the SMAs showed no difference between the brachial plexus patients and healthy volunteers.

CONCLUSIONS

Our results indicate that brachial plexus injury decreases resting-state inter-hemispheric functional connectivity of the two primary motor areas. These results provide new insight into functional reorganization of the cerebral cortex after brachial plexus injury.

Early visual learning induces long-lasting connectivity changes during rest in the human brain

Spontaneous fluctuations in resting state activity can change in response to experience-dependent plasticity and learning. Visual learning is fast and can be elicited in an MRI scanner. Here, we showed that a random dot motion coherence task can be learned within one training session. While the task activated primarily visual and parietal brain areas, learning related changes in neural activity were observed in the hippocampus. Crucially, even this rapid learning affected resting state dynamics both immediately after the learning and 24 h later. Specifically, the hippocampus changed its coupling with the striatum, in a way that was best explained as a consolidation of early learning related changes. Our findings suggest that long-lasting changes in neuronal coupling are accompanied by changes in resting state activity.

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Early learning of sensory task changes hippocampal activity.

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Coupling changes between hippocampus and striatum.

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Resting-state changes are consolidated during sleep.

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Stochastic DCM is a tool for resting state analysis.

Amygdala functional connectivity with medial prefrontal cortex at rest predicts the positivity effect in older adults' memory

As people get older, they tend to remember more positive than negative information. This age-by-valence interaction has been called "positivity effect." The current study addressed the hypotheses that baseline functional connectivity at rest is predictive of older adults' brain activity when learning emotional information and their positivity effect in memory. Using fMRI, we examined the relationship among resting-state functional connectivity, subsequent brain activity when learning emotional faces, and individual differences in the positivity effect (the relative tendency to remember faces expressing positive vs. negative emotions). Consistent with our hypothesis, older adults with a stronger positivity effect had increased functional coupling between amygdala and medial PFC (MPFC) during rest. In contrast, younger adults did not show the association between resting connectivity and memory positivity. A similar age-by-memory positivity interaction was also found when learning emotional faces. That is, memory positivity in older adults was associated with (a) enhanced MPFC activity when learning emotional faces and (b) increased negative functional coupling between amygdala and MPFC when learning negative faces. In contrast, memory positivity in younger adults was related to neither enhanced MPFC activity to emotional faces, nor MPFC-amygdala connectivity to negative faces. Furthermore, stronger MPFC-amygdala connectivity during rest was predictive of subsequent greater MPFC activity when learning emotional faces. Thus, emotion-memory interaction in older adults depends not only on the task-related brain activity but also on the baseline functional connectivity.

Increased local synchronization of resting-state fMRI signal after episodic memory encoding reflects off-line memory consolidation

The changes of spontaneous activity from before and after a memory or learning task had been considered to be related to off-line memory consolidation process in human brain by using resting-state functional connectivity (RSFC) MRI (fMRI). However, RSFC reflects temporal synchronization of timecourses of spatially distinct brain regions and therefore could not determine which specific brain region is involved in the memory consolidation process. Here we used regional homogeneity (ReHo), a method for measuring local synchronization, to link the local spontaneous activity change to off-line episodic memory consolidation. We hypothesized that the spontaneous activity change would be different between people with better memory performance and those with worse performance in memory-related regions. All participants completed two resting-state sessions, that is, before (REST-1) and after (REST-2) an episodic memory encoding task (picture indoor or outdoor judgment). Then, based on the d' of a later surprise memory retrieval test, a high-performance group and a low-performance group, each consisting of 16 participants, were chosen from whole 58 participants. We defined a ReHo ratio, that is, ReHo of REST-2 divided by ReHo of REST-1, as a change induced by memory consolidation. The high-performance group showed a significant higher ReHo ratio than low-performance group in medial temporal lobe (MTL) including parahippocampal and anterior temporal regions. The current results provide neuroimaging evidence supporting that the MTL is involved in off-line memory consolidation of episodic memory. Moreover, this study may provide a paradigm for understanding of episodic memory deficit in Alzheimer's disease.

Altered resting brain function and structure in professional badminton players

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

Functional brain connectivity at rest changes after working memory training

Networks of functional connectivity are highly consistent across participants, suggesting that functional connectivity is for a large part predetermined. However, several studies have shown that functional connectivity may change depending on instructions or previous experience. In the present study, we investigated whether 6 weeks of practice with a working memory task changes functional connectivity during a resting period preceding the task. We focused on two task-relevant networks, the frontoparietal network and the default network, using seed regions in the right middle frontal gyrus (MFG) and the medial prefrontal cortex (PFC), respectively. After practice, young adults showed increased functional connectivity between the right MFG and other regions of the frontoparietal network, including bilateral superior frontal gyrus, paracingulate gyrus, and anterior cingulate cortex. In addition, they showed reduced functional connectivity between the medial PFC and right posterior middle temporal gyrus. Moreover, a regression with performance changes revealed a positive relation between performance increases and changes of frontoparietal connectivity, and a negative relation between performance increases and changes of default network connectivity. Next, to study whether experience-dependent effects would be different during development, we also examined practice effects in a pilot sample of 12-year-old children. No practice effects were found in this group, suggesting that practice-related changes of functional connectivity are age-dependent. Nevertheless, future studies with larger samples are necessary to confirm this hypothesis.

Resting-state functional connectivity in normal brain aging

The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.

Neural plasticity and its contribution to functional recovery

In this chapter we address the phenomena of neural plasticity, operationally defined as the ability of the central nervous system to adapt in response to changes in the environment or lesions. At the cellular level, we discuss basic changes in membrane excitability, synaptic plasticity as well as structural changes in dendritic and axonal anatomy that support behavioral expressions of plasticity and functional recovery. We consider the different levels at which these changes can occur and possible links with modification of cognitive strategies, recruitment of new/different neural networks, or changes in strength of such connections or specific brain areas in charge of carrying out a particular task (i.e., movement, language, vision, hearing). The study of neuroplasticity has wide-reaching implications for understanding reorganization of action and cognition in the healthy and lesioned brain.

Working memory-related changes in functional connectivity persist beyond task disengagement

We examined whether altered connectivity in functional networks during working memory performance persists following conclusion of that performance, into a subsequent resting state. We conducted functional magnetic resonance imaging (fMRI) in 50 young adults during an initial resting state, followed by an N-back working memory task and a subsequent resting state, in order to examine changes in functional connectivity within and between the default-mode network (DMN) and the task-positive network (TPN) across the three states. We found that alterations in connectivity observed during the N-back task persisted into the subsequent resting state within the TPN and between the DMN and TPN, but not within the DMN. Further, both speed of working memory performance and TPN connectivity strength during the N-back task predicted connectivity strength in the subsequent resting state. Finally, DMN connectivity measured before and during the N-back task predicted individual differences in self-reported inattentiveness, but this association was not found during the post-task resting state. Together, these findings have important implications for models of how the brain recovers following effortful cognition, as well as for experimental designs using resting and task scans.

Effects of apolipoprotein E genotype on the off-line memory consolidation

Spontaneous brain activity or off-line activity after memory encoding is associated with memory consolidation. A few recent resting-state functional magnetic resonance imaging (RS-fMRI) studies indicate that the RS-fMRI could map off-line memory consolidation effects. However, the gene effects on memory consolidation process remain largely unknown. Here we collected two RS-fMRI sessions, one before and another after an episodic memory encoding task, from two groups of healthy young adults, one with apolipoprotein E (APOE) ε2/ε3 and the other with APOE ε3/ε4. The ratio of regional homogeneity (ReHo), a measure of local synchronization of spontaneous RS-fMRI signal, of the two sessions was used as an index of memory-consolidation. APOE ε3/ε4 group showed greater ReHo ratio within the medial temporal lobe (MTL). The ReHo ratio in MTL was significantly correlated with the recognition memory performance in the APOE ε3/ε4 group but not in ε2/ε3 group. Additionally, APOE ε3/ε4 group showed lower ReHo ratio in the occipital and parietal picture-encoding areas. Our results indicate that APOE ε3/ε4 group may have a different off-line memory consolidation process compared to ε2/ε3 group. These results may help generate future hypotheses that the off-line memory consolidation might be impaired in Alzheimer's disease.

Functional alteration of the DMN by learned regulation of the PCC using real-time fMRI

The default mode network (DMN) is a network of brain regions that are active during rest and suppressed during a cognitively demanding task. Previous studies have shown that the DMN can be altered by development, aging, disorder, cognitive tasks and offline training. However, it's unclear whether activity in the DMN can be altered by real-time training. Recently, real-time functional magnetic resonance imaging (rtfMRI), as a novel neurofeedback technique, has been applied to train subjects to voluntarily control activities in specific brain regions. In the current study, it was found that by using rtfMRI to guide training, subjects were able to learn to decrease activity in the posterior cingulate cortex (PCC), which is a "key hub" in the DMN, using motor imagery strategy. After the real-time training, activity in the medial prefrontral cortex/ anterior cingulate cortex (MPFC/ACC) of the resting state DMN was decreased. By contrast, the control group without neurofeedback produced increased activity in the MPFC/ACC of the DMN during the post-training resting state. These findings suggest that this rtfMRI technique has great potential to be used in the regulation of the DMN and may be a novel approach for studying functional plasticity of the cortex.

Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS)

Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include using resting state fcMRI to guide target selection for TMS and using TMS to modulate pathological network interactions identified with resting state fcMRI. The combination of TMS and resting state fcMRI has the potential to accelerate the translation of both techniques into the clinical realm and promises a new approach to the diagnosis and treatment of neurological and psychiatric diseases that demonstrate network pathology.

Why use a connectivity-based approach to study stroke and recovery of function?

The brain is organized into a set of widely distributed networks. Therefore, although structural damage from stroke is focal, remote dysfunction can occur in regions connected to the area of lesion. Historically, neuroscience has focused on local processing due in part to the absence of tools to study the function of distributed networks. In this article we discuss how a more comprehensive understanding of the effects of stroke can be attained using resting state functional connectivity BOLD magnetic resonance imaging (resting state fcMRI). Resting state fcMRI has a number of advantages over task-evoked fMRI for studying brain network reorganization in response to stroke, including the ability to image subjects with a broad range of impairments and the ability to study multiple networks simultaneously. We describe our rationale for using resting state connectivity as a tool for investigating the neural substrates of stroke recovery in a heterogeneous population of stroke patients and discuss the main questions we hope to answer, in particular whether resting state fcMRI measures in the acute phase of stroke can predict subsequent recovery. Early results suggest that disruption of inter-hemispheric connectivity in the somatomotor network and the dorsal attention network is more strongly associated with behavioral impairment in those domains than is intra-hemispheric connectivity within either the lesioned or unaffected hemisphere. We also observe in the somatomotor network an interesting interaction between corticospinal tract damage and decreased inter-hemispheric connectivity that suggests that both processes combine to contribute to neuromotor impairment after stroke. A connectivity-based approach will provide greater insight into network reorganization in the acute and chronic phases after stroke and will contribute to improving prognostic ability and the development of therapeutic interventions.

Prefrontal and limbic resting state brain network functional connectivity differs between nicotine-dependent smokers and non-smoking controls

BACKGROUND

Brain dysfunction in prefrontal cortex (PFC) and dorsal striatum (DS) contributes to habitual drug use. These regions are constituents of brain networks thought to be involved in drug addiction. To investigate whether networks containing these regions differ between nicotine dependent female smokers and age-matched female non-smokers, we employed functional MRI (fMRI) at rest.

METHODS

Data were processed with independent component analysis (ICA) to identify resting state networks (RSNs). We identified a subcortical limbic network and three discrete PFC networks: a medial prefrontal cortex (mPFC) network and right and left lateralized fronto-parietal networks common to all subjects. We then compared these RSNs between smokers and non-smokers using a dual regression approach.

RESULTS

Smokers had greater coupling versus non-smokers between left fronto-parietal and mPFC networks. Smokers with the greatest mPFC-left fronto-parietal coupling had the most DS smoking cue reactivity as measured during an fMRI smoking cue reactivity paradigm. This may be important because the DS plays a critical role in maintaining drug-cue associations. Furthermore, subcortical limbic network amplitude was greater in smokers.

CONCLUSIONS

Our results suggest that prefrontal brain networks are more strongly coupled in smokers, which could facilitate drug-cue responding. Our data also are the first to document greater reward-related network fMRI amplitude in smokers. Our findings suggest that resting state PFC network interactions and limbic network amplitude can differentiate nicotine-dependent smokers from controls, and may serve as biomarkers for nicotine dependence severity and treatment efficacy.

Effects of working memory training on functional connectivity and cerebral blood flow during rest

Working memory (WM) training (WMT) alters the task-related brain activity and structure of the external attention system (EAS). We investigated whether WMT also alters resting-state brain mechanisms, which are assumed to reflect intrinsic brain activity and connectivity. Our study subjects were subjected to a 4-week WMT program and brain scans before and after the intervention for determining changes of functional connectivity and regional cerebral blood flow during rest (resting-FC/resting-rCBF). Compared with no-intervention, WMT (a) increased resting-FC between the medial prefrontal cortex (mPFC) and precuneus, which are key nodes of the default mode network (DMN), (b) decreased resting-FC between mPFC and the right posterior parietal cortex/right lateral prefrontal cortex (LPFC), which are key nodes of the EAS, and (c) increased resting-rCBF in the right LPFC. However, the training-related decreases in resting-FC between the key DMN node and the nodes of EAS were only observed when the whole brain signal was regressed out in individual analyses, and these changes were not observed when the whole brain signal was not regressed out in individual analyses. Further analyses indicated that these differences may be mediated by a weak but a widespread increase in resting-FC between the nodes of EAS and activity of multiple bilateral areas across the brain. These results showed that WMT induces plasticity in neural mechanisms involving DMN and the EAS during rest and indicated that intrinsic brain activity and connectivity can be affected by cognitive training.

Shared and specific independent components analysis for between-group comparison

Independent component analysis (ICA) has been extensively used in individual and within-group data sets in real-world applications, but how can it be employed in a between-groups or conditions design? Here, we propose a new method to embed group membership information into the FastICA algorithm so as to extract components that are either shared between groups or specific to one or a subset of groups. The proposed algorithm is designed to automatically extract the pattern of differences between different experimental groups or conditions. A new constraint is added to the FastICA algorithm to simultaneously deal with the data of multiple groups in a single ICA run. This cost function restricts the specific components of one group to be orthogonal to the subspace spanned by the data of the other groups. As a result of performing a single ICA on the aggregate data of several experimental groups, the entire variability of data sets is used to extract the shared components. The results of simulations show that the proposed algorithm performs better than the regular method in both the reconstruction of the source signals and classification of shared and specific components. Also, the sensitivity to detect variations in the amplitude of shared components across groups is enhanced. A rigorous proof of convergence is provided for the proposed iterative algorithm. Thus, this algorithm is guaranteed to extract and classify shared and specific independent components across different experimental groups and conditions in a systematic way.

A brief history of the resting state: the Washington University perspective

We present a history of the concepts and developments that have led us to focus on the resting state as an object of study. We then discuss resting state research performed in our laboratory since 2005 with an emphasis on papers of particular interest.

Changes in resting-state functionally connected parietofrontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Clustering of resting state networks

Background

The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm.

Methodology/Principal Findings

The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization.

Conclusions/Significance

The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually

A better understanding of how behavioral performance emerges from interacting brain systems may come from analysis of functional networks using functional magnetic resonance imaging. Recent studies comparing such networks with human behavior have begun to identify these relationships, but few have used a time scale small enough to relate their findings to variation within a single individual's behavior. In the present experiment we examined the relationship between a psychomotor vigilance task and the interacting default mode and task positive networks. Two time-localized comparative metrics were calculated: difference between the two networks' signals at various time points around each instance of the stimulus (peristimulus times) and correlation within a 12.3-s window centered at each peristimulus time. Correlation between networks was also calculated within entire resting-state functional imaging runs from the same individuals. These metrics were compared with response speed on both an intraindividual and an interindividual basis. In most cases, a greater difference or more anticorrelation between networks was significantly related to faster performance. While interindividual analysis showed this result generally, using intraindividual analysis it was isolated to peristimulus times 4 to 8 s before the detected target. Within that peristimulus time span, the effect was stronger for individuals who tended to have faster response times. These results suggest that the relationship between functional networks and behavior can be better understood by using shorter time windows and also by considering both intraindividual and interindividual variability.

The effects of sustained cognitive task performance on subsequent resting state functional connectivity in healthy young and middle-aged male schoolteachers

Previous studies showed that functional connectivity (FC) within resting state (RS) networks is modulated by previous experience. In this study the effects of sustained cognitive performance on subsequent RS FC were investigated in healthy young (25-30 years; n=15) and middle-aged (50-60 years; n=14) male schoolteachers. Participants were scanned (functional magnetic resonance imaging [MRI]) after a cognitively demanding and a control intervention (randomized tester-blind within-subject design). Independent component analysis (ICA) was used to decompose the data into spatially independent networks. This study focused on the executive control (ExN), the left and right frontoparietal (FPN), and the default mode network (DMN). The effects of cognitive performance and age were calculated with a full-factorial analysis of variance (ANOVA). A main effect of age was found in the left inferior frontal gyrus for the ExN and in the middle frontal gyrus for the DMN with middle-aged teachers having reduced RS FC. Sustained cognitive performance increased subsequent RS FC between the ExN and a lingual/parahippocampal cluster, and between the left FPN and a right calcarine/precuneus cluster. In these clusters, FC strength correlated positively with the perceived amount of effort during the intervention. Further, sustained cognitive performance affected subsequent RS FC between the ExN and the right temporal superior gyrus differently in young and middle-aged men. The results suggest that effects of age on RS FC are already present at middle age. Sustained cognitive performance increased RS FC between task-positive networks and other brain regions, although a change in RS FC within the networks was not found.

Independent component analysis of resting brain activity reveals transient modulation of local cortical processing by transcranial direct current stimulation

Neuroplasticity induced by transcranial direct current stimulation (tDCS) contributes to motor learning although the underlying mechanisms are incompletely understood. Here, we investigated the effects of tDCS on resting brain dynamics recorded by whole-head magnetoencephalography (MEG) pre- and up to 35 minutes post-tDCS or sham over the left primary motor cortex (M1) in healthy adults. Owing to superior temporal and spatial resolution of MEG, we sought to apply a robust, blind and data-driven analytic approach such as independent component analysis (ICA) and statistical clustering to these data to investigate potential neuroplastic effects of tDCS during resting state conditions. We found decreased alpha and increased gamma band power that outlasted the real tDCS stimulation period in a fronto-parietal motor network relative to sham. However, this method could not find differences between anodal and cathodal polarities of tDCS. These results suggest that tDCS over M1 modulates resting brain dynamics in a fronto-parietal motor network (that includes the stimulated location), indicative of within-network enhanced localized cortical processing.

Brain activations underlying different patterns of performance improvement during early motor skill learning

BACKGROUND/INTRODUCTION

Motor learning plays a central role in daily life and in neurorehabilitation. Several forms of motor learning have been described, among which motor skill learning, i.e. reaching a superior level of performance (a skill) through a shift of the speed/accuracy trade-off. During the first stage of learning a visuomotor skill, we observed differential patterns of evolution of the speed/accuracy trade-off in normal subjects. Half of the subjects rapidly achieved successful motor skill learning with an early shift of the speed/accuracy trade-off leading to a superior level of performance (shift pattern). The other subjects attained only minimal global improvement due to a converse evolution of speed and accuracy (i.e. a respect of the speed/accuracy trade-off: fit pattern). Functional magnetic resonance imaging (fMRI) was used to explore the neural substrates underlying these differential patterns during the first stage of motor skill learning in normal subjects.

METHODS

Twenty right-handed normal subjects performed an implicit visuomotor learning task with their non-dominant hand. The task ("circuit game") consisted in learning to navigate a pointer along a circuit as quickly and accurately as possible using a fMRI-compatible mouse. Velocity, accuracy, and performance indexes were used to characterise the motor learning pattern (shift/fit) and to perform fMRI correlation analysis in order to find the neural substrate associated with the shift and fit patterns during early motor skill learning.

RESULTS

Nine subjects showed a fit pattern (fitters), and eleven, a shift pattern ("shifters"). fMRI analyses at whole group level (ANOVA) and at sub-group level demonstrated that the supplementary motor area (SMA) was more activated in "shifters" than in the "fitters" groups and that the BOLD activation within the SMA correlated significantly with the on-line shift of the speed/accuracy trade-off in the "shifters" group.

CONCLUSION

Despite identical instructions and experimental conditions, during the first stage of motor skill learning normal subjects spontaneously adopted different patterns that can be differentiated based on distinct fMRI activation patterns. In this implicit visuomotor task, the SMA proper was the key area underlying the achievement of early successful motor skill learning, i.e. on-line shift of the speed/accuracy trade-off.

Changes in the brain intrinsic organization in both on-task state and post-task resting state

The dynamic and robust characteristics of intrinsic functional connectivity of coherent spontaneous activity are critical for the brain functional stability and flexibility. Studies have demonstrated modulation of intrinsic connectivity within local spatial patterns during or after task performance, such as the default mode network (DMN) and task-specific networks. Moreover, recent studies have compared the global spatial pattern in different tasks or over time. However, it is still unclear how the large-scale intrinsic connectivity varies during and after a task. To better understand this issue, we conducted a functional MRI experiment over three sequential periods: an active semantic-matching task period and two rest periods, before and after the task respectively (namely, on-task state and pre-/post-task resting states), to detect task-driven effect on the dynamic large-scale intrinsic organization in both on-task state and post-task resting state. Three hierarchical levels were investigated, including (a) the whole brain small-world topology, (b) the whole pairwise functional connectivity patterns both within the DMN and between the DMN and other regions (i.e., the global/full DMN topography), and (c) the DMN nodal graph properties. The major findings are: (1) The large-scale small-world configuration of brain functional organization is robust, regardless of the behavioral state changing, while it varies adaptively with significantly higher local efficiency and lower global efficiency during the on-task state (P<0.05, Monte-Carlo corrected); (2) The DMN may be essentially engaged during both task and post-task processes with adaptively varied spatial patterns and nodal graph properties. The present study provides further insights into the robustness and plasticity of the brain intrinsic organization over states, which may be the basis of memory and learning in the brain.

Training the developing brain: a neurocognitive perspective

Developmental training studies are important to increase our understanding of the potential of the developing brain by providing answers to questions such as: “Which functions can and which functions cannot be improved as a result of practice?,” “Is there a specific period during which training has more impact?,” and “Is it always advantageous to train a particular function?”In addition, neuroimaging methods provide valuable information about the underlying mechanisms that drive cognitive plasticity. In this review, we describe how neuroscientific studies of training effects inform us about the possibilities of the developing brain, pointing out that childhood is a special period during which training may have different effects. We conclude that there is much complexity in interpreting training effects in children. Depending on the type of training and the level of maturation of the individual, training may influence developmental trajectories in different ways. We propose that the immature brain structure might set limits on how much can be achieved with training, but that the immaturity can also have advantages, in terms of flexibility for learning.

Perceptual plasticity is mediated by connectivity changes of the medial thalamic nucleus

It is well known that the threshold for somatosensory perception may adapt to different inputs. Recent studies suggest the presence of a modulating effect of somatosensory inputs on the spinal dorsal horn. However, the effects of somatosensory inputs on cerebral processing and, in particular, on the functional and effective connectivity of the somatosensory brain network, are poorly understood. In this study, we investigated the longitudinal impact of somatosensory stimuli on the resting-state functional connectivity and effective connectivity of the somatosensory brain network. We performed resting-state functional magnetic resonance imaging (fMRI) in 12 healthy subjects before and after unilateral electrical median nerve stimulation. We combined this analysis with a psychophysiological examination of changes of the perception threshold. We found that the unilateral median nerve stimulation increased the perception thresholds bilaterally and increased the resting-state functional and effective connectivity between most cortical areas of the somatosensory network. The major finding, however, was a decreased resting-state functional connectivity between both secondary somatosensory cortices and the bilateral medial nuclear complex of the thalamus. This decreased connectivity was correlated with increased perception thresholds. These findings emphasize the importance of the medial thalamic nucleus for the perceptual awareness of somatosensory stimuli.

Schizophrenia, neuroimaging and connectomics

Schizophrenia is frequently characterized as a disorder of brain connectivity. Neuroimaging has played a central role in supporting this view, with nearly two decades of research providing abundant evidence of structural and functional connectivity abnormalities in the disorder. In recent years, our understanding of how schizophrenia affects brain networks has been greatly advanced by attempts to map the complete set of inter-regional interactions comprising the brain's intricate web of connectivity; i.e., the human connectome. Imaging connectomics refers to the use of neuroimaging techniques to generate these maps which, combined with the application of graph theoretic methods, has enabled relatively comprehensive mapping of brain network connectivity and topology in unprecedented detail. Here, we review the application of these techniques to the study of schizophrenia, focusing principally on magnetic resonance imaging (MRI) research, while drawing attention to key methodological issues in the field. The published findings suggest that schizophrenia is associated with a widespread and possibly context-independent functional connectivity deficit, upon which are superimposed more circumscribed, context-dependent alterations associated with transient states of hyper- and/or hypo-connectivity. In some cases, these changes in inter-regional functional coupling dynamics can be related to measures of intra-regional dysfunction. Topological disturbances of functional brain networks in schizophrenia point to reduced local network connectivity and modular structure, as well as increased global integration and network robustness. Some, but not all, of these functional abnormalities appear to have an anatomical basis, though the relationship between the two is complex. By comprehensively mapping connectomic disturbances in patients with schizophrenia across the entire brain, this work has provided important insights into the highly distributed character of neural abnormalities in the disorder, and the potential functional consequences that these disturbances entail.

Functional connectivity-based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI

This study aimed to identify subunits of the basal ganglia and thalamus and to investigate the functional connectivity among these anatomically segregated subdivisions and the cerebral cortex in healthy subjects. For this purpose, we introduced multilevel independent component analysis (ICA) of the resting-state functional magnetic resonance imaging (fMRI). After applying ICA to the whole brain gray matter, we applied second-level ICA restrictively to the basal ganglia and the thalamus area to identify discrete functional subunits of those regions. As a result, the basal ganglia and the thalamus were parcelled into 31 functional subdivisions according to their temporal activity patterns. The extracted parcels showed functional network connectivity between hemispheres, between subdivisions of the basal ganglia and thalamus, and between the extracted subdivisions and cerebral functional components. Grossly, these findings correspond to cortico-striato-thalamo-cortical circuits in the brain. This study also showed the utility of multilevel ICA of resting state fMRI in brain network research.

Functionally specific changes in resting-state sensorimotor networks after motor learning

Motor learning changes the activity of cortical motor and subcortical areas of the brain, but does learning affect sensory systems as well? We examined in humans the effects of motor learning using fMRI measures of functional connectivity under resting conditions and found persistent changes in networks involving both motor and somatosensory areas of the brain. We developed a technique that allows us to distinguish changes in functional connectivity that can be attributed to motor learning from those that are related to perceptual changes that occur in conjunction with learning. Using this technique, we identified a new network in motor learning involving second somatosensory cortex, ventral premotor cortex, and supplementary motor cortex whose activation is specifically related to perceptual changes that occur in conjunction with motor learning. We also found changes in a network comprising cerebellar cortex, primary motor cortex, and dorsal premotor cortex that were linked to the motor aspects of learning. In each network, we observed highly reliable linear relationships between neuroplastic changes and behavioral measures of either motor learning or perceptual function. Motor learning thus results in functionally specific changes to distinct resting-state networks in the brain.

Does the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunction

The insular cortex is one of the brain regions that show consistent abnormalities in both structural and functional neuroimaging studies of schizophrenia. In healthy individuals, the insula has been implicated in a myriad of physiologic functions. The anterior cingulate cortex (ACC) and insula together constitute the salience network, an intrinsic large-scale network showing strong functional connectivity. Considering the insula as a functional unit along with the ACC provides an integrated understanding of the role of the insula in information processing. In this review, we bring together evidence from imaging studies to understand the role of the salience network in schizophrenia and propose a model of insular dysfunction in psychosis.

Neural Encoding of Objects Relevant for Navigation and Resting State Correlations with Navigational Ability

Objects along a route can help us to successfully navigate through our surroundings. Previous neuroimaging research has shown that the parahippocampal gyrus (PHG) distinguishes between objects that were previously encountered at navigationally relevant locations (decision points) and irrelevant locations (nondecision points) during simple object recognition. This study aimed at unraveling how this neural marking of objects relevant for navigation is established during learning and postlearning rest. Twenty-four participants were scanned using fMRI while they were viewing a route through a virtual environment. Eye movements were measured, and brain responses were time-locked to viewing each object. The PHG showed increased responses to decision point objects compared with nondecision point objects during route learning. We compared functional connectivity between the PHG and the rest of the brain in a resting state scan postlearning with such a scan prelearning. Results show that functional connectivity between the PHG and the hippocampus is positively related to participants' self-reported navigational ability. On the other hand, connectivity with the caudate nucleus correlated negatively with navigational ability. These results are in line with a distinction between egocentric and allocentric spatial representations in the caudate nucleus and the hippocampus, respectively. Our results thus suggest a relation between navigational ability and a neural preference for a specific type of spatial representation. Together, these results show that the PHG is immediately involved in the encoding of navigationally relevant object information. Furthermore, they provide insight into the neural correlates of individual differences in spatial ability.

Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis

Correlations in spontaneous brain activity provide powerful access to large-scale organizational principles of the CNS. However, making inferences about cognitive processes requires a detailed understanding of the link between these couplings and the structural integrity of the CNS. We studied the impact of multiple sclerosis, which leads to the severe disintegration of the central white matter, on functional connectivity patterns in spontaneous cortical activity. Using a data driven approach based on the strength of a salient pattern of cognitive pathology, we identified distinct networks that exhibit increases in functional connectivity despite the presence of strong and diffuse reductions of the central white-matter integrity. The default mode network emerged as a core target of these connectivity modulations, showing enhanced functional coupling in bilateral inferior parietal cortex, posterior cingulate, and medial prefrontal cortex. These findings imply a complex and diverging relation of anatomical and functional connectivity in early multiple sclerosis and, thus, add an important observation for understanding how cognitive abilities and CNS integrity may be reflected in the intrinsic covariance of functional signals.

Neuroplasticity subserving motor skill learning

Recent years have seen significant progress in our understanding of the neural substrates of motor skill learning. Advances in neuroimaging provide new insight into functional reorganization associated with the acquisition, consolidation, and retention of motor skills. Plastic changes involving structural reorganization in gray and white matter architecture that occur over shorter time periods than previously thought have been documented as well. Data from experimental animals provided crucial information on plausible cellular and molecular substrates contributing to brain reorganization underlying skill acquisition in humans. Here, we review findings demonstrating functional and structural plasticity across different spatial and temporal scales that mediate motor skill learning while identifying converging areas of interest and possible avenues for future research.

Learning-related gray and white matter changes in humans: an update

In contrast to a long-held view that structural brain plasticity is restricted to critical periods during ontogenesis, it is now well established that the adult human brain preserves its capacity for functional and structural changes throughout life. Although early experimental studies were mainly performed in animals, technical developments especially in the field of MRI enabled the non-invasive observation of functional and structural reorganization in the human brain. This article reports recent insights in human brain plasticity with particular emphasis on (dynamic) learning-related structural gray and white matter changes and its behavioral correlates.

Hemispheric asymmetry of visual scene processing in the human brain: evidence from repetition priming and intrinsic activity

Asymmetrical specialization of cognitive processes across the cerebral hemispheres is a hallmark of healthy brain development and an important evolutionary trait underlying higher cognition in humans. While previous research, including studies of priming, divided visual field presentation, and split-brain patients, demonstrates a general pattern of right/left asymmetry of form-specific versus form-abstract visual processing, little is known about brain organization underlying this dissociation. Here, using repetition priming of complex visual scenes and high-resolution functional magnetic resonance imaging (MRI), we demonstrate asymmetrical form specificity of visual processing between the right and left hemispheres within a region known to be critical for processing of visual spatial scenes (parahippocampal place area [PPA]). Next, we use resting-state functional connectivity MRI analyses to demonstrate that this functional asymmetry is associated with differential intrinsic activity correlations of the right versus left PPA with regions critically involved in perceptual versus conceptual processing, respectively. Our results demonstrate that the PPA comprises lateralized subregions across the cerebral hemispheres that are engaged in functionally dissociable yet complementary components of visual scene analysis. Furthermore, this functional asymmetry is associated with differential intrinsic functional connectivity of the PPA with distinct brain areas known to mediate dissociable cognitive processes.

Modulation of large-scale brain networks by transcranial direct current stimulation evidenced by resting-state functional MRI

BACKGROUND

Brain areas interact mutually to perform particular complex brain functions such as memory or language. Furthermore, under resting-state conditions several spatial patterns have been identified that resemble functional systems involved in cognitive functions. Among these, the default-mode network (DMN), which is consistently deactivated during task periods and is related to a variety of cognitive functions, has attracted most attention. In addition, in resting-state conditions some brain areas engaged in focused attention (such as the anticorrelated network, AN) show a strong negative correlation with DMN; as task demand increases, AN activity rises, and DMN activity falls.

OBJECTIVE

We combined transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) to investigate these brain network dynamics.

METHODS

Ten healthy young volunteers underwent four blocks of resting-state fMRI (10-minutes), each of them immediately after 20 minutes of sham or active tDCS (2 mA), on two different days. On the first day the anodal electrode was placed over the left dorsolateral prefrontal cortex (DLPFC) (part of the AN) with the cathode over the contralateral supraorbital area, and on the second day, the electrode arrangement was reversed (anode right-DLPFC, cathode left-supraorbital).

RESULTS

After active stimulation, functional network connectivity revealed increased synchrony within the AN components and reduced synchrony in the DMN components.

CONCLUSIONS

Our study reveals a reconfiguration of intrinsic brain activity networks after active tDCS. These effects may help to explain earlier reports of improvements in cognitive functions after anodal-tDCS, where increasing cortical excitability may have facilitated reconfiguration of functional brain networks to address upcoming cognitive demands.

Time Course of Cortical Plasticity After Facial Nerve Palsy

Background. Functional connectivity is defined as the temporal correlation between spatially remote neurophysiological events. This method has become particularly useful for studying neuroplasticity to detect changes in the collaboration of brain areas during cortical reorganization. Methods. In this article, the authors longitudinally studied voxel-based morphometry and resting state functional magnetic resonance imaging 10 times in 1 patient during the course of Bell palsy (idiopathic facial nerve palsy) up to complete clinical recovery. Results. Morphometric analysis revealed a significant alteration in the face area of the primary motor cortex (M1) contralateral to the paretic face, with an initial increase in gray matter concentration. Functional connectivity analysis between the M1 and other parts of the facial motor network revealed acutely disrupted intrahemispheric connectivity but unaltered interhemispheric connectivity. The disrupted functional connectivity was most pronounced on the day of the onset of symptoms, with a subsequent return toward normal during the course of recovery. This time course was found to differ between the selected parts of the facial motor network. However, the increase in functional connectivity strength preceded clinical recovery in all areas and reached a stable level before the patient fully recovered. Conclusion. These results demonstrate that recovery from facial nerve palsy is complemented by cortical reorganization, with pronounced changes of functional connectivity that precede clinical recovery.

Anticorrelated resting-state functional connectivity in awake rat brain

Resting-state functional connectivity (RSFC) measured by functional magnetic resonance imaging has played an essential role in understanding neural circuitry and brain diseases. The vast majority of RSFC studies have been focused on positive RSFC, whereas our understanding about its conceptual counterpart - negative RSFC (i.e. anticorrelation) - remains elusive. To date, anticorrelated RSFC has yet been observed without the commonly used preprocessing step of global signal correction. However, this step can induce artifactual anticorrelation (Murphy et al., 2009), making it difficult to determine whether the observed anticorrelation in humans is a processing artifact (Fox et al., 2005). In this report we demonstrated robust anticorrelated RSFC in a well characterized frontolimbic circuit between the infralimbic cortex (IL) and amygdala in the awake rat. This anticorrelation was anatomically specific, highly reproducible and independent of preprocessing methods. Interestingly, this anticorrelated relationship was absent in anesthetized rats even with global signal correction, further supporting its functional significance. Establishing negative RSFC independent of data preprocessing methods will significantly enhance the applicability of RSFC in better understanding neural circuitries and brain networks. In addition, combining the neurobiological data of the IL-amygdala circuit in rodents, the finding of the present study will enable further investigation of the neurobiological basis underlying anticorrelation.

Upstream dysfunction of somatomotor functional connectivity after corticospinal damage in stroke

BACKGROUND

Recent studies have shown that focal injuries can have remote effects on network function that affect behavior, but these network-wide repercussions are poorly understood.

OBJECTIVE

This study tested the hypothesis that lesions specifically to the outflow tract of a distributed network can result in upstream dysfunction in structurally intact portions of the network. In the somatomotor system, this upstream dysfunction hypothesis predicted that lesions of the corticospinal tract might be associated with functional disruption within the system. Motor impairment might then reflect the dual contribution of corticospinal damage and altered network functional connectivity.

METHODS

A total of 23 subacute stroke patients and 13 healthy controls participated in the study. Corticospinal tract damage was quantified using a template of the tract generated from diffusion tensor imaging in healthy controls. Somatomotor network functional integrity was determined by resting state functional connectivity magnetic resonance imaging.

RESULTS

The extent of corticospinal damage was negatively correlated with interhemispheric resting functional connectivity, in particular with connectivity between the left and right central sulcus. Although corticospinal damage accounted for much of the variance in motor performance, the behavioral impact of resting connectivity was greater in subjects with mild or moderate corticospinal damage and less in those with severe corticospinal damage.

CONCLUSIONS

Our results demonstrated that dysfunction of cortical functional connectivity can occur after interruption of corticospinal outflow tracts and can contribute to impaired motor performance. Recognition of these secondary effects from a focal lesion is essential for understanding brain-behavior relationships after injury, and they may have important implications for neurorehabilitation.

Graph theoretical analysis of functional brain networks: test-retest evaluation on short- and long-term resting-state functional MRI data

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest.

Can resting-state functional MRI serve as a complement to task-based mapping of sensorimotor function? A test-retest reliability study in healthy volunteers

PURPOSE

To investigate if resting-state functional MRI (fMRI) reliably can serve as a complement to task-based fMRI for presurgical mapping of the sensorimotor cortex.

MATERIALS AND METHODS

Functional data were obtained in 10 healthy volunteers using a 3 Tesla MRI system. Each subject performed five bilateral finger tapping experiments interleaved with five resting-state experiments. Following preprocessing, data from eight volunteers were further analyzed with the general linear model (finger tapping data) and independent component analysis (rest data). Test-retest reliability estimates (hit rate and false alarm rate) for resting-state fMRI activation of the sensorimotor network were compared with the reliability estimates for task-evoked activation of the sensorimotor cortex. The reliability estimates constituted a receiver operating characteristics curve from which the area under the curve (AUC) was calculated. Statistical testing was performed to compare the two groups with respect to reliability.

RESULTS

The AUC was generally higher for the task experiments, although median AUC was not significantly different on a group level. Also, the two groups showed comparable levels of within-group variance.

CONCLUSION

Test-retest reliability was comparable between resting-state measurements and task-based fMRI, suggesting that presurgical mapping of functional networks can be a supplement to task-based fMRI in cases where patient status excludes task-based fMRI.

Concepts and principles in the analysis of brain networks

The brain is a large-scale network, operating at multiple levels of information processing ranging from neurons, to local circuits, to systems of brain areas. Recent advances in the mathematics of graph theory have provided tools with which to study networks. These tools can be employed to understand how the brain's behavioral repertoire is mediated by the interactions of objects of information processing. Within the graph-theoretic framework, networks are defined by independent objects (nodes) and the relationships shared between them (edges). Importantly, the accurate incorporation of graph theory into the study of brain networks mandates careful consideration of the assumptions, constraints, and principles of both the mathematics and the underlying neurobiology. This review focuses on understanding these principles and how they guide what constitutes a brain network and its elements, specifically focusing on resting-state correlations in humans. We argue that approaches that fail to take the principles of graph theory into consideration and do not reflect the underlying neurobiological properties of the brain will likely mischaracterize brain network structure and function.

Changes occur in resting state network of motor system during 4 weeks of motor skill learning

We tested whether the resting state functional connectivity of the motor system changed during 4 weeks of motor skill learning using functional magnetic resonance imaging (fMRI). Ten healthy volunteers learned to produce a sequential finger movement by daily practice of the task over a 4 week period. Changes in the resting state motor network were examined before training (Week 0), two weeks after the onset of training (Week 2), and immediately at the end of the training (Week 4). The resting state motor system was analyzed using group independent component analysis (ICA). Statistical Parametric Mapping (SPM) second-level analysis was conducted on independent z-maps generated by the group ICA. Three regions, namely right postcentral gyrus, and bilateral supramarginal gyri were found to be sensitive to the training duration. Specifically, the strength of resting state functional connectivity in the right postcentral gyrus and right supramarginal gyrus increased from Week 0 to Week 2, during which the behavioral performance improved significantly, and decreased from Week 2 to Week 4, during which there was no more significant improvement in behavioral performance. The strength of resting state functional connectivity in left supramarginal gyrus increased throughout the training. These results confirm changes in the resting state network during slow-learning stage of motor skill learning, and support the premise that the resting state networks play a role in improving performance.