Functional neural circuits for mental timekeeping

The Interactions of Temporal and Sensory Representations in the Basal Ganglia

In rodents and primates, interval estimation has been associated with a complex network of cortical and subcortical structures where the dorsal striatum plays a paramount role. Diverse evidence ranging from individual neurons to population activity has demonstrated that this area hosts temporal-related neural representations that may be instrumental for the perception and production of time intervals. However, little is known about how temporal representations interact with other well-known striatal representations, such as kinematic parameters of movements or somatosensory representations. An attractive hypothesis suggests that somatosensory representations may serve as the scaffold for complex representations such as elapsed time. Alternatively, these representations may coexist as independent streams of information that could be integrated into downstream nuclei, such as the substantia nigra or the globus pallidus. In this review, we will revise the available information suggesting an instrumental role of sensory representations in the construction of temporal representations at population and single-neuron levels throughout the basal ganglia.

Syncopation as Probabilistic Expectation: Conceptual, Computational, and Experimental Evidence

Definitions of syncopation share two characteristics: the presence of a meter or analogous hierarchical rhythmic structure and a displacement or contradiction of that structure. These attributes are translated in terms of a Bayesian theory of syncopation, where the syncopation of a rhythm is inferred based on a hierarchical structure that is, in turn, learned from the ongoing musical stimulus. Several experiments tested its simplest possible implementation, with equally weighted priors associated with different meters and independence of auditory events, which can be decomposed into two terms representing note density and deviation from a metric hierarchy. A computational simulation demonstrated that extant measures of syncopation fall into two distinct factors analogous to the terms in the simple Bayesian model. Next, a series of behavioral experiments found that perceived syncopation is significantly related to both terms, offering support for the general Bayesian construction of syncopation. However, we also found that the prior expectations associated with different metric structures are not equal across meters and that there is an interaction between density and hierarchical deviation, implying that auditory events are not independent from each other. Together, these findings provide evidence that syncopation is a manifestation of a form of temporal expectation that can be directly represented in Bayesian terms and offer a complementary, feature-driven approach to recent Bayesian models of temporal prediction.

Melatonin secretion patterns are associated with cognitive vulnerability and brain structure in bipolar depression

Circadian rhythm disruption is a core symptom of bipolar disorder (BD), also reflected in altered patterns of melatonin release. Reductions of grey matter (GM) volumes are well documented in BD. We hypothesized that levels and timing of melatonin secretion in bipolar depression could be associated with depressive psychopathology and brain GM integrity. The onset of melatonin secretion under dim light conditions (DLMO) and the amount of time between DLMO and midsleep (i.e. phase angle difference; PAD) were used as circadian rhythm markers. To study the time course of melatonin secretion, an exponential curve fitting the melatonin values was calculated, and the slope coefficients (SLP) were obtained for each participant. Significant differences were found between HC and BD in PAD measures and melatonin profiles. Correlations between PAD and depressive psychopathology were identified. Melatonin secretion patterns were found to be associated with GM volumes in the Striatum and Supramarginal Gyrus in BD. Our findings emphasized the role of melatonin secretion role as a biological marker of circadian synchronization in bipolar depression and provided a novel insight for a link between melatonin release and brain structure.

Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study

Introduction

Over the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort.

Methods

We designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference.

Results

We defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them.

Discussion

We conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia.

Temporal judgments of actions following unilateral brain damage

Sense of time is a complex construct, and its neural correlates remain to date in most part unknown. To complicate the frame, physical attributes of the stimulus, such as its intensity or movement, influence temporal perception. Although previous studies have shown that time perception can be compromised after a brain lesion, the evidence on the role of the left and right hemispheres are meager. In two experiments, the study explores the ability of temporal estimation of multi-second actions and non-biological movements in 33 patients suffering from unilateral brain lesion. Furthermore, the modulatory role of induced embodiment processes is investigated. The results reveal a joint contribution of the two hemispheres depending not only on different durations but also on the presence of actions. Indeed, the left hemisphere damaged patients find it difficult to estimate 4500 ms or longer durations, while the right hemisphere damaged patients fail in 3000 ms durations. Furthermore, the former fail when a biological action is shown, while the latter fail in non-biological movement. Embodiment processes have a modulatory effect only after right hemisphere lesions. Among neuropsychological variables, only spatial neglect influences estimation of non-biological movement.

The neural bases for timing of durations

Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.

Perceiving your hand moving: BOLD suppression in sensory cortices and the role of the cerebellum in the detection of feedback delays

Sensory consequences of self-generated as opposed to externally generated movements are perceived as less intense and lead to less neural activity in corresponding sensory cortices, presumably due to predictive mechanisms. Self-generated sensory inputs have been mostly studied in a single modality, using abstract feedback, with control conditions not differentiating efferent from reafferent feedback. Here we investigated the neural processing of (a) naturalistic action-feedback associations of (b) self-generated versus externally generated movements, and (c) how an additional (auditory) modality influences neural processing and detection of delays. Participants executed wrist movements using a passive movement device (PMD) as they watched their movements in real time or with variable delays (0-417 ms). The task was to judge whether there was a delay between the movement and its visual feedback. In the externally generated condition, movements were induced by the PMD to disentangle efferent from reafferent feedback. Half of the trials involved auditory beeps coupled to the onset of the visual feedback. We found reduced BOLD activity in visual, auditory, and somatosensory areas during self-generated compared with externally generated movements in unimodal and bimodal conditions. Anterior and posterior cerebellar areas were engaged for trials in which action-feedback delays were detected for self-generated movements. Specifically, the left cerebellar lobule IX was functionally connected with the right superior occipital gyrus. The results indicate efference copy-based predictive mechanisms specific to self-generated movements, leading to BOLD suppression in sensory areas. In addition, our results support the cerebellum's role in the detection of temporal prediction errors during our actions and their consequences.

Altered Time Awareness in Dementia

Our awareness of time, specifically of longer intervals spanning hours, days, months, and years, is critical for ensuring our sense of self-continuity. Disrupted time awareness over such intervals is a clinical feature in a number of frontotemporal dementia syndromes and Alzheimer's disease, but has not been studied and compared systematically in these diseases. We used a semi-structured caregiver survey to capture time-related behavioral alterations in 71 patients representing all major sporadic and genetic syndromes of frontotemporal dementia, in comparison to 28 patients with typical Alzheimer's disease and nine with logopenic aphasia, and 32 healthy older individuals. Survey items pertained to apparent difficulties ordering past personal events or estimating time intervals between events, temporal rigidity and clockwatching, and propensity to relive past events. We used a logistic regression model including diagnosis, age, gender, and disease severity as regressors to compare the proportions of individuals exhibiting each temporal awareness symptom between diagnostic groups. Gray matter associations of altered time awareness were assessed using voxel-based morphometry. All patient groups were significantly more prone to exhibit temporal awareness symptoms than healthy older individuals. Clinical syndromic signatures were identified. While patients with typical and logopenic Alzheimer's disease most frequently exhibited disturbed event ordering or interval estimation, patients with semantic dementia were most prone to temporal rigidity and clockwatching and those with behavioral variant frontotemporal dementia commonly exhibited all these temporal symptoms as well as a propensity to relive past events. On voxel-based morphometry, the tendency to relive past events was associated with relative preservation of a distributed left-sided temporo-parietal gray matter network including hippocampus. These findings reveal a rich and complex picture of disturbed temporal awareness in major dementia syndromes, with stratification of frontotemporal dementia syndromes from Alzheimer's disease. This is the first study to assess symptoms of altered temporal awareness across frontotemporal dementia syndromes and provides a motivation for future work directed to the development of validated clinical questionnaires, analysis of underlying neurobiological mechanisms and design of interventions.

Alcohol effects on globus pallidus connectivity: Role of impulsivity and binge drinking

Despite the harm caused by binge drinking, the neural mechanisms leading to risky and disinhibited intoxication-related behaviors are not well understood. Evidence suggests that the globus pallidus externus (GPe), a substructure within the basal ganglia, participates in inhibitory control processes, as examined in stop-signaling tasks. In fact, studies in rodents have revealed that alcohol can change GPe activity by decreasing neuronal firing rates, suggesting that the GPe may have a central role in explaining impulsive behaviors and failures of inhibition that occur during binge drinking. In this study, twenty-five healthy volunteers underwent intravenous alcohol infusion to achieve a blood alcohol level of 0.08 g/dl, which is equivalent to a binge drinking episode. A resting state functional magnetic resonance imaging scan was collected prior to the infusion and at binge-level exposure. Functional connectivity analysis was used to investigate the association between alcohol-induced changes in GPe connectivity, drinking behaviors, and impulsivity traits. We found that individuals with greater number of drinks or heavy drinking days in the recent past had greater alcohol-induced deficits in GPe connectivity, particularly to the striatum. Our data also indicated an association between impulsivity and alcohol-induced deficits in GPe-frontal/precentral connectivity. Moreover, alcohol induced changes in GPe-amygdala circuitry suggested greater vulnerabilities to stress-related drinking in some individuals. Taken together, these findings suggest that alcohol may interact with impulsive personality traits and drinking patterns to drive alterations in GPe circuitry associated with behavioral inhibition, possibly indicating a neural mechanism by which binge drinking could lead to impulsive behaviors.

The Neural Correlates of Time: A Meta-analysis of Neuroimaging Studies

During the last two decades, our inner sense of time has been repeatedly studied with the help of neuroimaging techniques. These investigations have suggested the specific involvement of different brain areas in temporal processing. At least two distinct neural systems are likely to play a role in measuring time: One is mainly constituted of subcortical structures and is supposed to be more related to the estimation of time intervals below the 1-sec range (subsecond timing tasks), and the other is mainly constituted of cortical areas and is supposed to be more related to the estimation of time intervals above the 1-sec range (suprasecond timing tasks). Tasks can then be performed in motor or nonmotor (perceptual) conditions, thus providing four different categories of time processing. Our meta-analytical investigation partly confirms the findings of previous meta-analytical works. Both sub- and suprasecond tasks recruit cortical and subcortical areas, but subcortical areas are more intensely activated in subsecond tasks than in suprasecond tasks, which instead receive more contributions from cortical activations. All the conditions, however, show strong activations in the SMA, whose rostral and caudal parts have an important role not only in the discrimination of different time intervals but also in relation to the nature of the task conditions. This area, along with the striatum (especially the putamen) and the claustrum, is supposed to be an essential node in the different networks engaged when the brain creates our sense of time.

Brain activity during time to contact estimation: an EEG study

Understanding the neural mechanisms associated with time to contact (TTC) estimation is an intriguing but challenging task. Despite the importance of TTC estimation in our everyday life, few studies have been conducted on it, and there are still a lot of unanswered questions and unknown aspects of this issue. In this study, we intended to address one of these unknown aspects. We used independent component analysis to systematically assess EEG substrates associated with TTC estimation using two experiments: (1) transversal motion experiment (when a moving object passes transversally in the frontoparallel plane from side to side in front of the observer), and (2) head-on motion experiment (when the observer is on the motion path of the moving object). We also studied the energy of all EEG sources in these two experiments. The results showed that brain regions involved in the transversal and head-on motion experiments were the same. However, the energy used by some brain regions in the head-on motion experiment, including some regions in left parietotemporal and left frontal lobes, was significantly higher than the energy used by those regions in the transversal motion experiment. These brain regions are dominantly associated with different kinds of visual attention, integration of visual information, and responding to visual motion.

Differential cortical activation during the perception of moving objects along different trajectories

Detection of 3D object-motion trajectories depends on the integration of two distinct visual cues: translational displacement and looming. Electrophysiological studies have identified distinct neuronal populations, whose activity depends on the precise motion cues present in the stimulus. This distinction, however, has been less clear in humans, and it is confounded by differences in the behavioral task being performed. We analyzed whole-brain fMRI, while subjects performed a common time-to-arrival task for objects moving along three trajectories: moving directly towards the observer (collision course), with trajectories parallel to the line of sight (passage course), and with trajectories perpendicular to the line of sight (gap closure). We found that there was substantial overlap in the pattern of activation associated with each of the three tasks, with differences among conditions limited to the human motion area (hMT+), which showed greater activation extent in the gap closure condition than for either collision or passage courses. These results support a common substrate for temporal judgments of an object's time-to-arrival, wherein the special cases of object motion directly toward, or perpendicular to, the observer represent two extremes within the broader continuum of 3D passage trajectories relative to the observer.

Age-Related Atrophy and Compensatory Neural Networks in Reading Comprehension

OBJECTIVES

Despite changes to brain integrity with aging, some functions like basic language processes remain remarkably preserved. One theory for the maintenance of function in light of age-related brain atrophy is the engagement of compensatory brain networks. This study examined age-related changes in the neural networks recruited for simple language comprehension.

METHODS

Sixty-five adults (native English-speaking, right-handed, and cognitively normal) aged 17-85 years underwent a functional magnetic resonance imaging (fMRI) reading paradigm and structural scanning. The fMRI data were analyzed using independent component analysis to derive brain networks associated with reading comprehension.

RESULTS

Two typical frontotemporal language networks were identified, and these networks remained relatively stable across the wide age range. In contrast, three attention-related networks showed increased activation with increasing age. Furthermore, the increased recruitment of a dorsal attention network was negatively correlated to gray matter thickness in temporal regions, whereas an anterior frontoparietal network was positively correlated to gray matter thickness in insular regions.

CONCLUSIONS

We found evidence that older adults can exert increased effort and recruit additional attentional resources to maintain their reading abilities in light of increased cortical atrophy.

"Average is good, extremes are bad" - Non-linear inverted U-shaped relationship between neural mechanisms and functionality of mental features

Traditionally, studies emphasize differences in neural measures between pathological and healthy groups, assuming a binary distinction between the groups, and a linear relationship between neural measures and symptoms. Here, we present four examples that show a continuous relation across the divide of normal and pathological states between neural measures and mental functions. This relation can be characterized by a non-linear inverted-U shaped curve. Along this curve, mid-range or average expression of a neural measure is associated with optimal function of a mental feature (in healthy states), whereas extreme expression, either high or low, is associated with sub-optimal function, and occurs in different neural disorders. Neural expression between the optimal or intermediate and pathological or extreme values is associated with sub-optimal function and at-risk mental states. Thus, this model of neuro-mental relationship can be summarized as "average is good, extremes are bad". By focussing on neuro-mental relationships, this model can facilitate the transition of psychiatry from a categorical to a dimensional and individualized approach needed in the era of precision medicine.

Common and distinct neural correlates of dual-tasking and task-switching: a meta-analytic review and a neuro-cognitive processing model of human multitasking

Although there are well-known limitations of the human cognitive system in performing two tasks simultaneously (dual-tasking) or alternatingly (task-switching), the question for a common vs. distinct neural basis of these multitasking limitations is still open. We performed two Activation Likelihood Estimation meta-analyses of neuroimaging studies on dual-tasking or task-switching and tested for commonalities and differences in the brain regions associated with either domain. We found a common core network related to multitasking comprising bilateral intraparietal sulcus (IPS), left dorsal premotor cortex (dPMC), and right anterior insula. Meta-analytic contrasts revealed eight fronto-parietal clusters more consistently activated in dual-tasking (bilateral frontal operculum, dPMC, and anterior IPS, left inferior frontal sulcus and left inferior frontal gyrus) and, conversely, four clusters (left inferior frontal junction, posterior IPS, and precuneus as well as frontomedial cortex) more consistently activated in task-switching. Together with sub-analyses of preparation effects in task-switching, our results argue against purely passive structural processing limitations in multitasking. Based on these findings and drawing on current theorizing, we present a neuro-cognitive processing model of multitasking.

Adolescent sex differences in cortico-subcortical functional connectivity during response inhibition

Numerous lines of evidence have shown that cognitive processes engaged during response inhibition tasks are associated with structure and functional integration of regions within fronto-parietal networks. However, while prior studies have started to characterize how intrinsic connectivity during resting state differs between boys and girls, comparatively less is known about how functional connectivity differs between males and females when brain function is exogenously driven by the processing demands of typical Go/No-Go tasks that assess both response inhibition and error processing. The purpose of this study was to characterize adolescent sex differences and possible changes in sexually dimorphic regional functional connectivity across adolescent development in both cortical and subcortical brain connectivity elicited during a visual Go/No-Go task. A total of 130 healthy adolescents (ages 12-25 years) performed a Go/No-Go task during functional magnetic resonance imaging. High model-order group independent component analysis was used to characterize whole-brain network functional connectivity during response inhibition and then a univariate technique used to evaluate differences related to sex and age. As predicted and similar to previously described findings from non-task-driven resting state connectivity studies, functional connectivity sex differences were observed in several subcortical regions, including the amygdala, caudate, thalamus, and cortical regions, including inferior frontal gyrus engaged most strongly during successful response inhibition and/or error processing. Importantly, adolescent boys and girls exhibited different normative profiles of age-related changes in several default mode networks of regions and anterior cingulate cortex. These results suggest that cortical-subcortical functional networks supporting response inhibition operate differently between sexes during adolescence.

Unbalanced Occlusion Modifies the Pattern of Brain Activity During Execution of a Finger to Thumb Motor Task

In order to assess possible influences of occlusion on motor performance, we studied by functional magnetic resonance imaging (fMRI) the changes in the blood oxygenation level dependent (BOLD) signal induced at brain level by a finger to thumb motor task in a population of subjects characterized by an asymmetric activation of jaw muscles during clenching (malocclusion). In these subjects, appropriate occlusal correction by an oral orthotic (bite) reduced the masticatory asymmetry. The finger to thumb task was performed while the subject's dental arches were touching, in two conditions: (a) with the teeth in direct contact (Bite OFF) and (b) with the bite interposed between the arches (Bite ON). Both conditions required only a very slight activation of masticatory muscles. Maps of the BOLD signal recorded during the movement were contrasted with the resting condition (activation maps). Between conditions comparison of the activation maps (Bite OFF/Bite ON) showed that, in Bite OFF, the BOLD signal was significantly higher in the trigeminal sensorimotor region, the premotor cortex, the cerebellum, the inferior temporal and occipital cortex, the calcarine cortex, the precuneus on both sides, as well as in the right posterior cingulate cortex. These data are consistent with the hypothesis that malocclusion makes movement performance more difficult, leading to a stronger activation of (a) sensorimotor areas not dealing with the control of the involved body part, (b) regions planning the motor sequence, and (c) the cerebellum, which is essential in motor coordination. Moreover, the findings of a higher activation of temporo-occipital cortex and precuneus/cingulus, respectively, suggest that, during malocclusion, the movement occurs with an increased visual imagery activity, and requires a stronger attentive effort.

Neural substrates of internally-based and externally-cued timing: An activation likelihood estimation (ALE) meta-analysis of fMRI studies

A dynamic interplay exists between Internally-Based (IBT) and Externally-Cued (ECT) time processing. While IBT processes support the self-generation of context-independent temporal representations, ECT mechanisms allow constructing temporal representations primarily derived from the structure of the sensory environment. We performed an activation likelihood estimation (ALE) meta-analysis on 177 fMRI experiments, from 79 articles, to identify brain areas involved in timing; two individual ALEs tested the hypothesis of a neural segregation between IBT and ECT. The general ALE highlighted a network involving supplementary motor area (SMA), intraparietal sulcus, inferior frontal gyrus (IFG), insula (INS) and basal ganglia. We found evidence of a partial dissociation between IBT and ECT. IBT relies on a subset of areas also involved in ECT, however ECT tasks activate SMA, right IFG, left precentral gyrus and INS in a significantly stronger way. Present results suggest that ECT involves the detection of environmental temporal regularities and their integration with the output of the IBT processing, to generate a representation of time which reflects the temporal metric of the environment.

Group independent component analysis reveals alternation of right executive control network in Internet gaming disorder

OBJECTIVE

Previous studies have demonstrated that individuals with Internet gaming disorder (IGD) showed attentional bias toward gaming-related cues and exhibited impaired executive functions. The purpose of this study was to explore the alternations in related functional brain networks underlying attentional bias in IGD subjects.

METHODS

Eighteen IGD subjects and 19 healthy controls (HC) were scanned with functional magnetic resonance imaging while they were performing an addiction Stroop task. Networks of functional connectivity were identified using group independent component analysis (ICA).

RESULTS

ICA identified 4 functional networks that showed differences between the 2 groups, which were related to the right executive control network and visual related networks in our study. Within the right executive control network, in contrast to controls, IGD subjects showed increased functional connectivity in the temporal gyrus and frontal gyrus, and reduced functional connectivity in the posterior cingulate cortex, temporal gyrus, and frontal gyrus.

CONCLUSION

These findings suggest that IGD is related to abnormal functional connectivity of the right executive control network, and may be described as addiction-related abnormally increased cognitive control processing and diminished response inhibition during an addiction Stroop task. The results suggest that IGD subjects show increased susceptibility towards gaming-related cues but weakened strength of inhibitory control.

Functional brain networks for learning predictive statistics

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics.

Too Fast or Too Slow? Time and Neuronal Variability in Bipolar Disorder-A Combined Theoretical and Empirical Investigation

Time is an essential feature in bipolar disorder (BP). Manic and depressed BP patients perceive the speed of time as either too fast or too slow. The present article combines theoretical and empirical approaches to integrate phenomenological, psychological, and neuroscientific accounts of abnormal time perception in BP. Phenomenology distinguishes between perception of inner time, ie, self-time, and outer time, ie, world-time, that desynchronize or dissociate from each other in BP: inner time speed is abnormally slow (as in depression) or fast (as in mania) and, by taking on the role as default-mode function, impacts and modulates the perception of outer time speed in an opposite way, ie, as too fast in depression and too slow in mania. Complementing, psychological investigation show opposite results in time perception, ie, time estimation and reproduction, in manic and depressed BP. Neuronally, time speed can be indexed by neuronal variability, ie, SD. Our own empirical data show opposite changes in manic and depressed BP (and major depressive disorder [MDD]) with abnormal SD balance, ie, SD ratio, between somatomotor and sensory networks that can be associated with inner and outer time. Taken together, our combined theoretical-empirical approach demonstrates that desynchronization or dissociation between inner and outer time in BP can be traced to opposite neuronal variability patterns in somatomotor and sensory networks. This opens the door for individualized therapeutic "normalization" of neuronal variability pattern in somatomotor and sensory networks by stimulation with TMS and/or tDCS.

Ten Key Observations on the Analysis of Resting-state Functional MR Imaging Data Using Independent Component Analysis

For more than 20 years, the powerful, flexible family of independent component analysis (ICA) techniques has been used to examine spatial, temporal, and subject variation in functional magnetic resonance (fMR) imaging data. This article provides an overview of 10 key principles in the basic and advanced application of ICA to resting-state fMR imaging. ICA's core advantages include robustness to artifact; false-positives and autocorrelation; adaptability to variant study designs; agnosticism to the temporal evolution of fMR imaging signals; and ability to extract, identify, and analyze neural networks. ICA remains in the vanguard of fMRI methods development.

Ten Key Observations on the Analysis of Resting-state Functional MR Imaging Data Using Independent Component Analysis

For more than 20 years, the powerful, flexible family of independent component analysis (ICA) techniques has been used to examine spatial, temporal, and subject variation in functional magnetic resonance (fMR) imaging data. This article provides an overview of 10 key principles in the basic and advanced application of ICA to resting-state fMR imaging. ICA's core advantages include robustness to artifact; false-positives and autocorrelation; adaptability to variant study designs; agnosticism to the temporal evolution of fMR imaging signals; and ability to extract, identify, and analyze neural networks. ICA remains in the vanguard of fMRI methods development.

Functional network connectivity alterations in schizophrenia and depression

There is a high degree of overlap between the symptoms of major depressive disorder (MDD) and schizophrenia, but it remains unclear whether the similar symptoms are derived from convergent alterations in functional network connectivity. In this study, we performed a group independent component analysis on resting-state functional MRI data from 20 MDD patients, 24 schizophrenia patients, and 43 matched healthy controls. The functional network connectivity analysis revealed that, compared to healthy controls, the MDD and schizophrenia patients exhibited convergent decreased positive connectivity between the left and right fronto-parietal control network and decreased negative connectivity between the left control and medial visual networks. Furthermore, the MDD patients showed decreased negative connectivity between the left control and auditory networks, and the schizophrenia patients showed decreased positive connectivity between the bilateral control and language networks and decreased negative connectivity between the right control and dorsal attention networks. The convergent network connectivity alterations may underlie the common primary control and regulation disorders, and the divergent connectivity alterations may enable the distinction between the two disorders. All of the convergent and divergent network connectivity alterations were relevant to the control network, suggesting an important role of the network in the pathophysiology of MDD and schizophrenia.

Flavor pleasantness processing in the ventral emotion network

The ventral emotion network-encompassing the amygdala, insula, ventral striatum, and ventral regions of the prefrontal cortex-has been associated with the identification of emotional significance of perceived external stimuli and the production of affective states. Functional magnetic resonance imaging (fMRI) studies investigating chemosensory stimuli have associated parts of this network with pleasantness coding. In the current study, we independently analyzed two datasets in which we measured brain responses to flavor stimuli in young adult men. In the first dataset, participants evaluated eight regular off the shelf drinking products while participants evaluated six less familiar oral nutritional supplements (ONS) in the second dataset. Participants provided pleasantness ratings 20 seconds after tasting. Using independent component analysis (ICA) and mixed effect models, we identified one brain network in the regular products dataset that was associated with flavor pleasantness. This network was very similar to the ventral emotion network. Although we identified an identical network in the ONS dataset using ICA, we found no linear relation between activation of any network and pleasantness scores within this dataset. Our results indicate that flavor pleasantness is processed in a network encompassing amygdala, ventral prefrontal, insular, striatal and parahippocampal regions for familiar drinking products. For more unfamiliar ONS products the association is not obvious, which could be related to the unfamiliarity of these products.

Increased frontal functional networks in adult survivors of childhood brain tumors

Childhood brain tumors and associated treatment have been shown to affect brain development and cognitive outcomes. Understanding the functional connectivity of brain many years after diagnosis and treatment may inform the development of interventions to improve the long-term outcomes of adult survivors of childhood brain tumors. This work investigated the frontal region functional connectivity of 16 adult survivors of childhood cerebellar tumors after an average of 14.9 years from diagnosis and 16 demographically-matched controls using resting state functional MRI (rs-fMRI). Independent component analysis (ICA) was applied to identify the resting state activity from rs-fMRI data and to select the specific regions associated with executive functions, followed by the secondary analysis of the functional networks connecting these regions. It was found that survivors exhibited differences in the functional connectivity in executive control network (ECN), default mode network (DMN) and salience network (SN) compared to demographically-matched controls. More specifically, the number of functional connectivity observed in the survivors is higher than that in the controls, and with increased strength, or stronger correlation coefficient between paired seeds, in survivors compared to the controls. Observed hyperconnectivity in the selected frontal functional network thus is consistent with findings in patients with other neurological injuries and diseases.

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rs-fMRI and ICA analysis were used to investigate functional connectivity of adult survivors of childhood brain tumors.

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Survivors exhibited changes in connectivity in executive function, default mode and salience networks compared to controls.

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Observed increased number and strength of functional connectivity suggest adaption of hyperconnectivity by survivors.

Ecstatic Epileptic Seizures: A Glimpse into the Multiple Roles of the Insula

Ecstatic epileptic seizures are a rare but compelling epileptic entity. During the first seconds of these seizures, ecstatic auras provoke feelings of well-being, intense serenity, bliss, and "enhanced self-awareness." They are associated with the impression of time dilation, and can be described as a mystic experience by some patients. The functional neuroanatomy of ecstatic seizures is still debated. During recent years several patients presenting with ecstatic auras have been reported by others and us (in total n = 52); a few of them in the setting of presurgical evaluation including electrical brain stimulation. According to the recently recognized functions of the insula, and the results of nuclear brain imaging and electrical stimulation, the ecstatic symptoms in these patients seem to localize to a functional network centered around the anterior insular cortex, where we thus propose to locate this rare ictal phenomenon. Here we summarize the role of the multiple sensory, autonomic, affective, and cognitive functions of the insular cortex, which are integrated into the creation of self-awareness, and we suggest how this system may become dysfunctional on several levels during ecstatic aura.

Disrupted Frontoparietal Network Mediates White Matter Structure Dysfunction Associated with Cognitive Decline in Hypertension Patients

Some previous reports have suggested that hypertension is a risk factor for dementia and cognitive impairments. Using behavioral data from 1007 elderly human subjects (405 hypertensive patients) of Han ethnicity from Beijing, China, the present study aimed to assess the effects of hypertension on cognitive performance and explore related neuronal changes via advanced resting-state functional magnetic resonance imaging and diffusion tensor imaging data from 84 of these subjects (44 hypertensive patients). Cognitively, we found that patients with hypertension showed decreased executive functions and attention compared with those with normotension in the large sample. In magnetic resonance imaging scan sample, using independent component analysis to examine the functional connectivity difference between the two groups, we found that the frontoparietal networks in the hypertensive group exhibited altered patterns compared with the control group, mainly in the inferior parietal lobe, left inferior frontal lobe, and precuneus. Using tract-based spatial statistics to investigate the between-group structural difference, we found that the hypertensive group showed significantly reduced integrity of white matter in the bilateral superior longitudinal fasciculus. Importantly, using the mediation analysis, we found that the functional connectivity of the frontoparietal networks mediates the impact of white matter on executive function in the hypertensive group. The results demonstrate that hypertension targets a specific pattern of cognitive decline, possibly due to deficits in the white matter and functional connectivity in frontal and parietal lobes. Our findings highlight the importance of brain protection in hypertension.

SIGNIFICANCE STATEMENT

Hypertension is a risk factor for cognitive decline and dementia. However, the neural mechanism underlying cognitive decline in hypertension is largely unknown. We studied the relationship among cognitive decline, brain functional, and structural changes in hypertensive patients via advanced resting-state functional magnetic resonance imaging and diffusion tensor imaging data in a Chinese cohort. Hypertensive patients showed executive dysfunction, along with disrupted functional connectivity in frontoparietal (FP) networks and reduced integrity of white matter in the bilateral superior longitudinal fasciculus. Importantly, the functional connectivity changes mediate the impact of white matter alterations on cognitive decline in the hypertensive group. Our findings provide a better understanding of the mechanism of cognitive decline in hypertension and highlight the importance of brain protection in hypertension.

Animal-oriented virtual environments: illusion, dilation, and discovery

As a research tool, virtual environments (VEs) hold immense promise for brain scientists. Yet to fully realize this potential in non-human systems, theoretical and conceptual perspectives must be developed. When selectively coupled to nervous systems, virtual environments can help us better understand the functional architecture of animals’ brains during naturalistic behaviors. While this will no doubt allow us to further our understanding of the neural basis of behavior, there is also an opportunity to uncover the diversity inherent in brain activity and behavior. This is due to two properties of virtual environments: the ability to create sensory illusions, and the ability to dilate space and/or time. These and other potential manipulations will be characterized as the effects of virtuality. In addition, the systems-level outcomes of virtual environment enhanced perception will be discussed in the context of the uncanny valley and other expected relationships between emotional valence, cognition, and training. These effects and their usefulness for brain science will be understood in the context of three types of neurobehavioral phenomena: sensorimotor integration, spatial navigation, and interactivity. For each of these behaviors, a combination of illusory and space/time dilation examples will be reviewed. Once these examples are presented, the implications for improving upon virtual models for more directly inducing the mental phenomena of illusion and space/time dilation will be considered. To conclude, future directions for integrating the use of VEs into a strategy of broader biological inquiry will be presented.

Investing in the future: stimulation of the medial prefrontal cortex reduces discounting of delayed rewards

Generally, rewards that are received sooner are often preferred over future rewards, and the time between the choice and the reception of the reward is an important factor that influences our decisions, a phenomenon called delay discounting (DD). In DD, the medial prefrontal cortex (MePFC) and striatal dopamine neurotransmission both play an important role. We used repetitive transcranial magnetic stimulation (rTMS) to transiently activate the MePFC to evaluate its behavioral effect on the DD paradigm, and subsequently to measure its effect on striatal dopamine. Twenty-four right-handed young healthy subjects (11 females; age: 22.1±2.9 years) underwent DD following 10 Hz-rTMS of the MePFC and vertex stimulation (control condition). Thereafter, 11 subjects (5 females; age: 22.2±2.87 years) completed the PET study at rest using [(11)C]-(+)-PHNO following 10 Hz-rTMS of the MePFC and vertex. Modulation of the MePFC excitability influenced the subjective level of DD for delayed rewards and interfered with synaptic dopamine level in the striatum. The present study yielded findings that might reconcile the role of these areas in inter-temporal decision making and dopamine modulation, suggesting that the subjective sense of time and value of reward are critically controlled by these important regions.

Everywhere and everything: The power and ubiquity of time

Anticipatory timing plays a critical role in many aspects of human and non-human animal behavior. Timing has been consistently observed in the range of milliseconds to hours, and demonstrates a powerful influence on the organization of behavior. Anticipatory timing is acquired early in associative learning and appears to guide association formation in important ways. Importantly, timing participates in regulating goal-directed behaviors in many schedules of reinforcements, and plays a critical role in value-based decision making under concurrent schedules. In addition to playing a key role in fundamental learning processes, timing often dominates when temporal cues are available concurrently with other stimulus dimensions. Such control by the passage of time has even been observed when other cues provide more accurate information and can lead to sub-optimal behaviors. The dominance of temporal cues in governing anticipatory behavior suggests that time may be inherently more salient than many other stimulus dimensions. Discussions of the interface of the timing system with other cognitive processes are provided to demonstrate the powerful and primitive nature of time as a stimulus dimension.

Neural correlates of intentional switching from ternary to binary meter in a musical hemiola pattern

Musical rhythms are often perceived and interpreted within a metrical framework that integrates timing information hierarchically based on interval ratios. Endogenous timing processes facilitate this metrical integration and allow us using the sensory context for predicting when an expected sensory event will happen (“predictive timing”). Previously, we showed that listening to metronomes and subjectively imagining the two different meters of march and waltz modulated the resulting auditory evoked responses in the temporal lobe and motor-related brain areas such as the motor cortex, basal ganglia, and cerebellum. Here we further explored the intentional transitions between the two metrical contexts, known as hemiola in the Western classical music dating back to the sixteenth century. We examined MEG from 12 musicians while they repeatedly listened to a sequence of 12 unaccented clicks with an interval of 390 ms, and tapped to them with the right hand according to a 3 + 3 + 2 + 2 + 2 hemiola accent pattern. While participants listened to the same metronome sequence and imagined the accents, their pattern of brain responses significantly changed just before the “pivot” point of metric transition from ternary to binary meter. Until 100 ms before the pivot point, brain activities were more similar to those in the simple ternary meter than those in the simple binary meter, but the pattern was reversed afterwards. A similar transition was also observed at the downbeat after the pivot. Brain areas related to the metric transition were identified from source reconstruction of the MEG using a beamformer and included auditory cortices, sensorimotor and premotor cortices, cerebellum, inferior/middle frontal gyrus, parahippocampal gyrus, inferior parietal lobule, cingulate cortex, and precuneus. The results strongly support that predictive timing processes related to auditory-motor, fronto-parietal, and medial limbic systems underlie metrical representation and its transitions.

Oscillatory multiplexing of neural population codes for interval timing and working memory

Interval timing and working memory are critical components of cognition that are supported by neural oscillations in prefrontal-striatal-hippocampal circuits. In this review, the properties of interval timing and working memory are explored in terms of behavioral, anatomical, pharmacological, and neurophysiological findings. We then describe the various neurobiological theories that have been developed to explain these cognitive processes - largely independent of each other. Following this, a coupled excitatory - inhibitory oscillation (EIO) model of temporal processing is proposed to address the shared oscillatory properties of interval timing and working memory. Using this integrative approach, we describe a hybrid model explaining how interval timing and working memory can originate from the same oscillatory processes, but differ in terms of which dimension of the neural oscillation is utilized for the extraction of item, temporal order, and duration information. This extension of the striatal beat-frequency (SBF) model of interval timing (Matell and Meck, 2000, 2004) is based on prefrontal-striatal-hippocampal circuit dynamics and has direct relevance to the pathophysiological distortions observed in time perception and working memory in a variety of psychiatric and neurological conditions.

De-noising with a SOCK can improve the performance of event-related ICA

Event-related ICA (eICA) is a partially data-driven analysis method for event-related fMRI that is particularly suited to analysis of simultaneous EEG-fMRI of patients with epilepsy. EEG-fMRI studies in epileptic patients are typically analyzed using the general linear model (GLM), often with assumption that the onset and offset of neuronal activity match EEG event onset and offset, the neuronal activation is sustained at a constant level throughout the epileptiform event and that associated fMRI signal changes follow the canonical HRF. The eICA method allows for less constrained analyses capable of detecting early, non-canonical responses. A key step of eICA is the initial deconvolution which can be confounded by various sources of structured noise present in the fMRI signal. To help overcome this, we have extend the eICA procedure by utilizing a fully standalone and automated fMRI de-noising procedure to process the fMRI data from an EEG-fMRI acquisition prior to running eICA. Specifically we first apply ICA to the entire fMRI time-series and use a classifier to remove noise-related components. The automated objective de-noiser, “Spatially Organized Component Klassificator” (SOCK) is used; it has previously been shown to distinguish a substantial fraction of noise from true activation, without rejecting the latter, in resting-state fMRI. A second ICA is then performed, this time on the event-related response estimates derived from the denoised data (according to the usual eICA procedure). We hypothesize that SOCK + eICA has the potential to be more sensitive than eICA alone. We test the effectiveness of SOCK by comparing activation obtained in an eICA analysis of EEG-fMRI data with and without the use of SOCK for 14 patients with rolandic epilepsy who exhibited stereotypical IEDs arising from a focus in the rolandic fissure.

The role of top-down control in different phases of a sensorimotor timing task: a DCM study of adults and adolescents

The ability to precisely coordinate motor control to regularly-paced sensory stimuli requires an ability often called 'mental timekeeping', a distinct form of cognitive function. A consistent feature among conceptual models of the internal clock mechanism is an element of 'top-down' cognitive control. Although lesion and fMRI studies have provided indirect evidence supporting the role of the prefrontal cortex in exerting top-down influence over lower-level sensory and motor regions, little direct evidence exists. We investigated changes in Dynamic Causal Modeling (DCM)-measured top-down control of sensorimotor timing during different phases of a unimanual, auditory-paced finger-tapping task in a cohort of healthy adults and adolescents. The brain regions examined were organized into a network of excitatory connections between bilateral dorso- and ventrolateral prefrontal cortices and motor and auditory cortices. This baseline connectivity changed depending on whether participants listened passively to the pacing cue, synchronized their regular interval finger tapping with the cue, or continued tapping in absence of the cue. Subjects who performed better at maintaining the prescribed tapping pace in the absence of the auditory cue relied more on top-down control of the motor and sensory regions, while those with less accurate performance relied more on sensory driven, bottom-up control of the motor cortex. No significant maturational effects were observed in either the behavioral or DCM path weight data. Both right and left prefrontal cortex were found to exert control over timing behavioral accuracy, but there were distinctly lateralized roles with respect to optimal performance.

Spatial variability of functional brain networks in early-blind and sighted subjects

To further the understanding how the human brain adapts to early-onset blindness, we searched in early-blind and normally-sighted subjects for functional brain networks showing the most and least spatial variabilities across subjects. We hypothesized that the functional networks compensating for early-onset blindness undergo cortical reorganization. To determine whether reorganization of functional networks affects spatial variability, we used functional magnetic resonance imaging to compare brain networks, derived by independent component analysis, of 7 early-blind and 7 sighted subjects while they rested or listened to an audio drama. In both conditions, the blind compared with sighted subjects showed more spatial variability in a bilateral parietal network (comprising the inferior parietal and angular gyri and precuneus) and in a bilateral auditory network (comprising the superior temporal gyri). In contrast, a vision-related left-hemisphere-lateralized occipital network (comprising the superior, middle and inferior occipital gyri, fusiform and lingual gyri, and the calcarine sulcus) was less variable in blind than sighted subjects. Another visual network and a tactile network were spatially more variable in the blind than sighted subjects in one condition. We contemplate whether our results on inter-subject spatial variability of brain networks are related to experience-dependent brain plasticity, and we suggest that auditory and parietal networks undergo a stronger experience-dependent reorganization in the early-blind than sighted subjects while the opposite is true for the vision-related occipital network.

What is all the noise about in interval timing?

Cognitive processes such as decision-making, rate calculation and planning require an accurate estimation of durations in the supra-second range-interval timing. In addition to being accurate, interval timing is scale invariant: the time-estimation errors are proportional to the estimated duration. The origin and mechanisms of this fundamental property are unknown. We discuss the computational properties of a circuit consisting of a large number of (input) neural oscillators projecting on a small number of (output) coincidence detector neurons, which allows time to be coded by the pattern of coincidental activation of its inputs. We showed analytically and checked numerically that time-scale invariance emerges from the neural noise. In particular, we found that errors or noise during storing or retrieving information regarding the memorized criterion time produce symmetric, Gaussian-like output whose width increases linearly with the criterion time. In contrast, frequency variability produces an asymmetric, long-tailed Gaussian-like output, that also obeys scale invariant property. In this architecture, time-scale invariance depends neither on the details of the input population, nor on the distribution probability of noise.

A meta-analysis of cerebellar contributions to higher cognition from PET and fMRI studies

A growing interest in cerebellar function and its involvement in higher cognition have prompted much research in recent years. Cerebellar presence in a wide range of cognitive functions examined within an increasing body of neuroimaging literature has been observed. We applied a meta-analytic approach, which employed the activation likelihood estimate method, to consolidate results of cerebellar involvement accumulated in different cognitive tasks of interest and systematically identified similarities among the studies. The current analysis included 88 neuroimaging studies demonstrating cerebellar activations in higher cognitive domains involving emotion, executive function, language, music, timing and working memory. While largely consistent with a prior meta-analysis by Stoodley and Schmahmann ([2009]: Neuroimage 44:489-501), our results extended their findings to include music and timing domains to provide further insights into cerebellar involvement and elucidate its role in higher cognition. In addition, we conducted inter- and intradomain comparisons for the cognitive domains of emotion, language, and working memory. We also considered task differences within the domain of verbal working memory by conducting a comparison of the Sternberg with the n-back task, as well as an analysis of the differential components within the Sternberg task. Results showed a consistent cerebellar presence in the timing domain, providing evidence for a role in time keeping. Unique clusters identified within the domain further refine the topographic organization of the cerebellum.

Probing interval timing with scalp-recorded electroencephalography (EEG)

Humans, and other animals, are able to easily learn the durations of events and the temporal relationships among them in spite of the absence of a dedicated sensory organ for time. This chapter summarizes the investigation of timing and time perception using scalp-recorded electroencephalography (EEG), a non-invasive technique that measures brain electrical potentials on a millisecond time scale. Over the past several decades, much has been learned about interval timing through the examination of the characteristic features of averaged EEG signals (i.e., event-related potentials, ERPs) elicited in timing paradigms. For example, the mismatch negativity (MMN) and omission potential (OP) have been used to study implicit and explicit timing, respectively, the P300 has been used to investigate temporal memory updating, and the contingent negative variation (CNV) has been used as an index of temporal decision making. In sum, EEG measures provide biomarkers of temporal processing that allow researchers to probe the cognitive and neural substrates underlying time perception.

Serotonergic hallucinogens as translational models relevant to schizophrenia

One of the oldest models of schizophrenia is based on the effects of serotonergic hallucinogens such as mescaline, psilocybin, and (+)-lysergic acid diethylamide (LSD), which act through the serotonin 5-HT(2A) receptor. These compounds produce a 'model psychosis' in normal individuals that resembles at least some of the positive symptoms of schizophrenia. Based on these similarities, and because evidence has emerged that the serotonergic system plays a role in the pathogenesis of schizophrenia in some patients, animal models relevant to schizophrenia have been developed based on hallucinogen effects. Here we review the behavioural effects of hallucinogens in four of those models, the receptor and neurochemical mechanisms for the effects and their translational relevance. Despite the difficulty of modelling hallucinogen effects in nonverbal species, animal models of schizophrenia based on hallucinogens have yielded important insights into the linkage between 5-HT and schizophrenia and have helped to identify receptor targets and interactions that could be exploited in the development of new therapeutic agents.

The pattern of striatal dopaminergic denervation explains sensorimotor synchronization accuracy in Parkinson's disease

The basal ganglia are thought to play a critical role in duration perception and production. However, experimental evidence for impaired temporal processing in Parkinson's disease (PD) patients is mixed. This study examined the association between striatal dopaminergic denervation in PD patients and sensorimotor synchronization. Twenty-eight mild-to-moderate stage PD patients synchronized finger taps to tone sequences of either 500 ms, 1000 ms or 1500 ms time intervals while ON levodopa (l-DOPA) or placebo pill (on separate test days) with the index finger of their more and less affected hands. We measured the accuracy and variability of synchronization. In a separate session, patients underwent (11)C-dihydrotetrabenazine ((11)C-DTBZ) PET scanning to measure in vivo striatal dopaminergic denervation. Patients were less accurate synchronizing to the 500 ms target time interval, compared to the 1000 ms and 1500 ms time intervals, but neither medication state nor hand affected accuracy; medication state, hand nor the target time interval affected synchronization variability. Regression analyses revealed no strong relationships between synchronization accuracy or variability and striatal dopaminergic denervation. We performed a cluster analysis on the degree of dopaminergic denervation to determine whether patient subgroup differences underlie our results. Three patient subgroups showed behavioral differences in synchronization accuracy, but not variability, paralleling their pattern of denervation. These findings provide further evidence for the role of the basal ganglia and dopamine in duration production and suggest that the degree of striatal dopaminergic denervation may explain the heterogeneity of performance between PD patients on the sensorimotor synchronization task.

Changes in resting-state fMRI in vestibular neuritis

Vestibular neuritis (VN) is a sudden peripheral unilateral vestibular failure with often persistent head movement-related dizziness and unsteadiness. Compensation of asymmetrical activity in the primary peripheral vestibular afferents is accomplished by restoration of impaired brainstem vestibulo-ocular and vestibulo-spinal reflexes, but presumably also by changing cortical vestibular tone imbalance subserving, e.g., spatial perception and orientation. The aim of this study was to elucidate (i) whether there are changes of cerebral resting-state networks with respect to functional interregional connectivity (resting-state activity) in VN patients and (ii) whether these are related to neurophysiological, perceptual and functional parameters of vestibular-induced disability. Using independent component analysis (ICA), we compared resting-state networks between 20 patients with unilateral VN and 20 age- and gender-matched healthy control subjects. Patients were examined in the acute VN stage and after 3 months. A neural network (component 50) comprising the parietal lobe, medial aspect of the superior parietal lobule, posterior cingulate cortex, middle frontal gyrus, middle temporal gyrus, parahippocampal gyrus, anterior cingulate cortex, insular cortex, caudate nucleus, thalamus and midbrain was modulated between acute VN patients and healthy controls and in patients over time. Within this network, acute VN patients showed decreased resting-state activity (ICA) in the contralateral intraparietal sulcus (IPS), in close vicinity to the supramarginal gyrus (SMG), which increased after 3 months. Resting-state activity in IPS tended to increase over 3 months in VN patients who improved with respect to functional parameters of vestibular-induced disability (VADL). Resting-state activity in the IPS was not related to perceptual (subjective visual vertical) or neurophysiological parameters of vestibular-induced disability (e.g., gain of vestibulo-ocular reflex, caloric responsiveness, postural sway). VN leads to a change in resting-state activity of the contralateral IPS adjacent to the SMG, which reverses during vestibular compensation over 3 months. The ventral intraparietal area in the IPS contains multimodal regions with directionally selective responses to vestibular stimuli making them suitable for participating in spatial orientation and multisensory integration. The clinical importance is indicated by the fact that the increase in resting-state activity tended to be larger in those patients with only little disability at the follow-up examination. This may indicate powerful restitution-related or compensatory cortical changes in resting-state activity.

Exploring the effective connectivity of resting state networks in mild cognitive impairment: an fMRI study combining ICA and multivariate Granger causality analysis

Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent neuroimaging studies have shown that the cognitive and memory decline in AD and MCI patients is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses of small-world attributes. However, the causal interactions among the spatially isolated but function-related resting state networks (RSNs) are still largely unexplored in MCI patients. In this study, we first identified eight RSNs by independent components analysis (ICA) from resting state functional MRI data of 16 MCI patients and 18 age-matched healthy subjects respectively. Then, we performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that MCI patients exhibited decreased causal interactions among the RSNs in both intensity and quantity compared with normal controls. Results from mGCA indicated that the causal interactions involving the default mode network (DMN) became weaker in MCI patients, while stronger causal connectivity emerged related to the memory network and executive control network. Our findings suggested that the DMN played a less important role in MCI patients. Increased causal connectivity of the memory network and executive control network may elucidate the dysfunctional and compensatory processes in the brain networks of MCI patients. These preliminary findings may be helpful for further understanding the pathological mechanisms of MCI and provide a new clue to explore the neurophysiological mechanisms of MCI.

An automated method for identifying artifact in independent component analysis of resting-state FMRI

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.