Reliability of energy landscape analysis of resting-state functional MRI data.

Energy landscape analysis is a data-driven method to analyse multidimensional time series, including functional magnetic resonance imaging (fMRI) data. It has been shown to be a useful characterization of fMRI data in health and disease. It fits an Ising model to the data and captures the dynamics of the data as movement of a noisy ball constrained on the energy landscape derived from the estimated Ising model. In the present study, we examine test-retest reliability of the energy landscape analysis. To this end, we construct a permutation test that assesses whether or not indices characterizing the energy landscape are more consistent across different sets of scanning sessions from the same participant (i.e. within-participant reliability) than across different sets of sessions from different participants (i.e. between-participant reliability). We show that the energy landscape analysis has significantly higher within-participant than between-participant test-retest reliability with respect to four commonly used indices. We also show that a variational Bayesian method, which enables us to estimate energy landscapes tailored to each participant, displays comparable test-retest reliability to that using the conventional likelihood maximization method. The proposed methodology paves the way to perform individual-level energy landscape analysis for given data sets with a statistically controlled reliability.

State-transition dynamics of resting-state functional magnetic resonance imaging data: model comparison and test-to-retest analysis.

Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior. While microstate analysis has been widely employed to analyze EEG data, its use remains less prevalent in functional magnetic resonance imaging (fMRI) data, largely due to the slower timescale of such data. In the present study, we extend various data clustering methods used in EEG microstate analysis to resting-state fMRI data from healthy humans to extract their state-transition dynamics. We show that the quality of clustering is on par with that for various microstate analyses of EEG data. We then develop a method for examining test-retest reliability of the discrete-state transition dynamics between fMRI sessions and show that the within-participant test-retest reliability is higher than between-participant test-retest reliability for different indices of state-transition dynamics, different networks, and different data sets. This result suggests that state-transition dynamics analysis of fMRI data could discriminate between different individuals and is a promising tool for performing fingerprinting analysis of individuals.

Neurochemical evidence for differential effects of acute and repeated oxytocin administration.

A discrepancy in oxytocin's behavioral effects between acute and repeated administrations indicates distinct underlying neurobiological mechanisms. The current study employed a combination of human clinical trial and animal study to compare neurochemical changes induced by acute and repeated oxytocin administrations. Human study analyzed medial prefrontal metabolite levels by using 1H-magnetic resonance spectroscopy, a secondary outcome in our randomized, double-blind, placebo-controlled crossover trial of 6 weeks intranasal administrations of oxytocin (48 IU/day) and placebo within-subject design in 17 psychotropic-free high-functioning men with autism spectrum disorder. Medial prefrontal transcript expression levels were analyzed in adult male C57BL/6J mice after intraperitoneal injection of oxytocin or saline either once (200 ng/100 µL/mouse, n = 12) or for 14 consecutive days (200 ng/100 µL/mouse/day, n = 16). As the results, repeated administration of oxytocin significantly decreased the medial prefrontal N-acetylaspartate (NAA; p = 0.043) and glutamate-glutamine levels (Glx; p = 0.001), unlike the acute oxytocin. The decreases were inversely and specifically associated (r = 0.680, p = 0.004 for NAA; r = 0.491, p = 0.053 for Glx) with oxytocin-induced improvements of medial prefrontal functional MRI activity during a social judgment task not with changes during placebo administrations. In wild-type mice, we found that repeated oxytocin administration reduced medial frontal transcript expression of N-methyl-D-aspartate receptor type 2B (p = 0.018), unlike the acute oxytocin, which instead changed the transcript expression associated with oxytocin (p = 0.0004) and neural activity (p = 0.0002). The present findings suggest that the unique sensitivity of the glutamatergic system to repeated oxytocin administration may explain the differential behavioral effects of oxytocin between acute and repeated administration.

Modelling state-transition dynamics in resting-state brain signals by the hidden Markov and Gaussian mixture models.

Recent studies have proposed that one can summarize brain activity into dynamics among a relatively small number of hidden states and that such an approach is a promising tool for revealing brain function. Hidden Markov models (HMMs) are a prevalent approach to inferring such neural dynamics among discrete brain states. However, the impact of assuming Markovian structure in neural time series data has not been sufficiently examined. Here, to address this situation and examine the performance of the HMM, we compare the model with the Gaussian mixture model (GMM), which is with no temporal regularization and thus a statistically simpler model than the HMM, by applying both models to synthetic time series generated from empirical resting-state functional magnetic resonance imaging (fMRI) data. We compared the GMM and HMM for various sampling frequencies, lengths of recording per participant, numbers of participants and numbers of independent component signals. We find that the HMM attains a better accuracy of estimating the hidden state than the GMM in a majority of cases. However, we also find that the accuracy of the GMM is comparable to that of the HMM under the condition that the sampling frequency is reasonably low (e.g., TR = 2.88 or 3.60 s) or the data are relatively short. These results suggest that the GMM can be a viable alternative to the HMM for investigating hidden-state dynamics under this condition.

A Neuroanatomical Substrate Linking Perceptual Stability to Cognitive Rigidity in Autism.

Overly stable visual perception seen in individuals with autism spectrum disorder (ASD) is related to higher-order core symptoms of the condition. However, the neural basis by which these seemingly different symptoms are simultaneously observed in individuals with ASD remains unclear. Here, we aimed to identify such a neuroanatomical substrate linking perceptual stability to autistic cognitive rigidity, a part of core restricted, repetitive behaviors (RRBs). First, using a bistable visual perception test, we measured the perceptual stability of 22 high-functioning adults with ASD and 22 age-, IQ-, and sex-matched typically developing human individuals and confirmed overstable visual perception in autism. Next, using a spontaneous task-switching (TS) test, we showed that the individuals with ASD were more likely to repeat the same task voluntarily and spontaneously, and such rigid TS behavior was associated with the severity of their RRB symptoms. We then compared these perceptual and cognitive behaviors and found a significant correlation between them for individuals with ASD. Finally, we found that this behavioral link was supported by a smaller gray matter volume (GMV) of the posterior superior parietal lobule (pSPL) in individuals with ASD. Moreover, this smaller GMV in the pSPL was also associated with the RRB symptoms and replicated in two independent datasets. Our findings suggest that the pSPL could be one of the neuroanatomical mediators of cognitive and perceptual inflexibility in autism, which could help a unified biological understanding of the mechanisms underpinning diverse symptoms of this developmental disorder.SIGNIFICANCE STATEMENT Behavioral studies show perceptual overstability in autism spectrum disorder (ASD). However, the neural mechanisms by which such sensory symptoms can coexist and often correlate with seemingly separate core symptoms remain unknown. Here, we have identified such a key neuroanatomical substrate. We have revealed that overstable sensory perception of individuals with ASD is linked with their cognitive rigidity, a part of core restricted, repetitive behavior symptoms, and such a behavioral link is underpinned by a smaller gray matter volume in the posterior superior parietal lobule in autism. These findings uncover a key neuroanatomical mediator of autistic perceptual and cognitive inflexibility and would ignite future studies on how the core symptoms of ASD interact with its unique sensory perception.

Age-related changes in the ease of dynamical transitions in human brain activity.

Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks.

Meta-analytic evaluation of the association between head injury and risk of amyotrophic lateral sclerosis.

Head injury is considered as a potential risk factor for amyotrophic lateral sclerosis (ALS). However, several recent studies have suggested that head injury is not a cause, but a consequence of latent ALS. We aimed to evaluate such a possibility of reverse causation with meta-analyses considering time lags between the incidence of head injuries and the occurrence of ALS. We searched Medline and Web of Science for case-control, cross-sectional, or cohort studies that quantitatively investigated the head-injury-related risk of ALS and were published until 1 December 2016. After selecting appropriate publications based on PRISMA statement, we performed random-effects meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CI). Sixteen of 825 studies fulfilled the eligibility criteria. The association between head injuries and ALS was statistically significant when the meta-analysis included all the 16 studies (OR 1.45, 95% CI 1.21-1.74). However, in the meta-analyses considering the time lags between the experience of head injuries and diagnosis of ALS, the association was weaker (OR 1.21, 95% CI 1.01-1.46, time lag ≥ 1 year) or not significant (e.g. OR 1.16, 95% CI 0.84-1.59, time lag ≥ 3 years). Although it did not deny associations between head injuries and ALS, the current study suggests a possibility that such a head-injury-oriented risk of ALS has been somewhat overestimated. For more accurate evaluation, it would be necessary to conduct more epidemiological studies that consider the time lags between the occurrence of head injuries and the diagnosis of ALS.

Two distinct neural mechanisms underlying indirect reciprocity.

Cooperation is a hallmark of human society. Humans often cooperate with strangers even if they will not meet each other again. This so-called indirect reciprocity enables large-scale cooperation among nonkin and can occur based on a reputation mechanism or as a succession of pay-it-forward behavior. Here, we provide the functional and anatomical neural evidence for two distinct mechanisms governing the two types of indirect reciprocity. Cooperation occurring as reputation-based reciprocity specifically recruited the precuneus, a region associated with self-centered cognition. During such cooperative behavior, the precuneus was functionally connected with the caudate, a region linking rewards to behavior. Furthermore, the precuneus of a cooperative subject had a strong resting-state functional connectivity (rsFC) with the caudate and a large gray matter volume. In contrast, pay-it-forward reciprocity recruited the anterior insula (AI), a brain region associated with affective empathy. The AI was functionally connected with the caudate during cooperation occurring as pay-it-forward reciprocity, and its gray matter volume and rsFC with the caudate predicted the tendency of such cooperation. The revealed difference is consistent with the existing results of evolutionary game theory: although reputation-based indirect reciprocity robustly evolves as a self-interested behavior in theory, pay-it-forward indirect reciprocity does not on its own. The present study provides neural mechanisms underlying indirect reciprocity and suggests that pay-it-forward reciprocity may not occur as myopic profit maximization but elicit emotional rewards.

Effects of rTMS of pre-supplementary motor area on fronto basal ganglia network activity during stop-signal task.

Stop-signal task (SST) has been a key paradigm for probing human brain mechanisms underlying response inhibition, and the inhibition observed in SST is now considered to largely depend on a fronto basal ganglia network consisting mainly of right inferior frontal cortex, pre-supplementary motor area (pre-SMA), and basal ganglia, including subthalamic nucleus, striatum (STR), and globus pallidus pars interna (GPi). However, causal relationships between these frontal regions and basal ganglia are not fully understood in humans. Here, we partly examined these causal links by measuring human fMRI activity during SST before and after excitatory/inhibitory repetitive transcranial magnetic stimulation (rTMS) of pre-SMA. We first confirmed that the behavioral performance of SST was improved by excitatory rTMS and impaired by inhibitory rTMS. Afterward, we found that these behavioral changes were well predicted by rTMS-induced modulation of brain activity in pre-SMA, STR, and GPi during SST. Moreover, by examining the effects of the rTMS on resting-state functional connectivity between these three regions, we showed that the magnetic stimulation of pre-SMA significantly affected intrinsic connectivity between pre-SMA and STR, and between STR and GPi. Furthermore, the magnitudes of changes in resting-state connectivity were also correlated with the behavioral changes seen in SST. These results suggest a causal relationship between pre-SMA and GPi via STR during response inhibition, and add direct evidence that the fronto basal ganglia network for response inhibition consists of multiple top-down regulation pathways in humans.

Clinical and neural effects of six-week administration of oxytocin on core symptoms of autism.

Autism spectrum disorder is a prevalent neurodevelopmental disorder with no established pharmacological treatment for its core symptoms. Although previous literature has shown that single-dose administration of oxytocin temporally mitigates autistic social behaviours in experimental settings, it remains in dispute whether such potentially beneficial responses in laboratories can result in clinically positive effects in daily life situations, which are measurable only in long-term observations of individuals with the developmental disorder undergoing continual oxytocin administration. Here, to address this issue, we performed an exploratory, randomized, double-blind, placebo-controlled, crossover trial including 20 high-functional adult males with autism spectrum disorder. Data obtained from 18 participants who completed the trial showed that 6-week intranasal administration of oxytocin significantly reduced autism core symptoms specific to social reciprocity, which was clinically evaluated by Autism Diagnostic Observation Scale (P = 0.034, PFDR < 0.05, Cohen's d = 0.78). Critically, the improvement of this clinical score was accompanied by oxytocin-induced enhancement of task-independent resting-state functional connectivity between anterior cingulate cortex and dorso-medial prefrontal cortex (rho = -0.60, P = 0.011), which was measured by functional magnetic resonance imaging. Moreover, using the same social-judgement task as used in our previous single-dose oxytocin trial, we confirmed that the current continual administration also significantly mitigated behavioural and neural responses during the task, both of which were originally impaired in autistic individuals (judgement tendency: P = 0.019, d = 0.62; eye-gaze effect: P = 0.03, d = 0.56; anterior cingulate activity: P = 0.00069, d = 0.97; dorso-medial prefrontal activity: P = 0.0014, d = 0.92; all, PFDR < 0.05). Furthermore, despite its longer administration, these effect sizes of the 6-week intervention were not larger than those seen in our previous single-dose intervention. These findings not only provide the evidence for clinically beneficial effects of continual oxytocin administration on the core social symptoms of autism spectrum disorder with suggesting its underlying biological mechanisms, but also highlight the necessity to seek optimal regimens of continual oxytocin treatment in future studies.

Dissociable memory traces within the macaque medial temporal lobe predict subsequent recognition performance.

Functional magnetic resonance imaging (fMRI) studies have revealed that activity in the medial temporal lobe (MTL) predicts subsequent memory performance in humans. Because of limited knowledge on cytoarchitecture and axonal projections of the human MTL, precise localization and characterization of the areas that can predict subsequent memory performance are benefited by the use of nonhuman primates in which integrated approach of the MRI- and cytoarchiture-based boundary delineation is available. However, neural correlates of this subsequent memory effect have not yet been identified in monkeys. Here, we used fMRI to examine activity in the MTL during memory encoding of events that monkeys later remembered or forgot. Application of both multivoxel pattern analysis and conventional univariate analysis to high-resolution fMRI data allowed us to identify memory traces within the caudal entorhinal cortex (cERC) and perirhinal cortex (PRC), as well as within the hippocampus proper. Furthermore, activity in the cERC and the hippocampus, which are directly connected, was responsible for encoding the initial items of sequentially presented pictures, which may reflect recollection-like recognition, whereas activity in the PRC was not. These results suggest that two qualitatively distinct encoding processes work in the monkey MTL and that recollection-based memory is formed by the interplay of the hippocampus with the cERC, a focal cortical area anatomically closer to the hippocampus and hierarchically higher than previously believed. These findings will advance the understanding of common memory system between humans and monkeys and accelerate fine electrophysiological characterization of these dissociable memory traces in the monkey MTL.

Oxytocin improves behavioural and neural deficits in inferring others' social emotions in autism.

Recent studies have suggested oxytocin's therapeutic effects on deficits in social communication and interaction in autism spectrum disorder through improvement of emotion recognition with direct emotional cues, such as facial expression and voice prosody. Although difficulty in understanding of others' social emotions and beliefs under conditions without direct emotional cues also plays an important role in autism spectrum disorder, no study has examined the potential effect of oxytocin on this difficulty. Here, we sequentially conducted both a case-control study and a clinical trial to investigate the potential effects of oxytocin on this difficulty at behavioural and neural levels measured using functional magnetic resonance imaging during a psychological task. This task was modified from the Sally-Anne Task, a well-known first-order false belief task. The task was optimized for investigation of the abilities to infer another person's social emotions and beliefs distinctively so as to test the hypothesis that oxytocin improves deficit in inferring others' social emotions rather than beliefs, under conditions without direct emotional cues. In the case-control study, 17 males with autism spectrum disorder showed significant behavioural deficits in inferring others' social emotions (P = 0.018) but not in inferring others' beliefs (P = 0.064) compared with 17 typically developing demographically-matched male participants. They also showed significantly less activity in the right anterior insula and posterior superior temporal sulcus during inferring others' social emotions, and in the dorsomedial prefrontal cortex during inferring others' beliefs compared with the typically developing participants (P < 0.001 and cluster size > 10 voxels). Then, to investigate potential effects of oxytocin on these behavioural and neural deficits, we conducted a double-blind placebo-controlled crossover within-subject trial for single-dose intranasal administration of 24 IU oxytocin in an independent group of 20 males with autism spectrum disorder. Behaviourally, oxytocin significantly increased the correct rate in inferring others' social emotions (P = 0.043, one-tail). At the neural level, the peptide significantly enhanced the originally-diminished brain activity in the right anterior insula during inferring others' social emotions (P = 0.004), but not in the dorsomedial prefrontal cortex during inferring others' beliefs (P = 0.858). The present findings suggest that oxytocin enhances the ability to understand others' social emotions that have also required second-order false belief rather than first-order false beliefs under conditions without direct emotional cues in autism spectrum disorder at both the behaviour and neural levels.

Network-dependent modulation of brain activity during sleep.

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks.

Bidirectional effects on interhemispheric resting-state functional connectivity induced by excitatory and inhibitory repetitive transcranial magnetic stimulation.

Several recent studies using functional magnetic resonance imaging (fMRI) have shown that repetitive transcranial magnetic stimulation (rTMS) affects not only brain activity in stimulated regions but also resting-state functional connectivity (RSFC) between the stimulated region and other remote regions. However, these studies have only demonstrated an effect of either excitatory or inhibitory rTMS on RSFC, and have not clearly shown the bidirectional effects of both types of rTMS. Here, we addressed this issue by performing excitatory and inhibitory quadripulse TMS (QPS), which is considered to exert relatively large and long-lasting effects on cortical excitability. We found that excitatory rTMS (QPS with interstimulus intervals of 5 ms) decreased interhemispheric RSFC between bilateral primary motor cortices, whereas inhibitory rTMS (QPS with interstimulus intervals of 50 ms) increased interhemispheric RSFC. The magnitude of these effects on RSFC was significantly correlated with that of rTMS-induced effects on motor evoked potential from the corresponding muscle. The bidirectional effects of QPS were also observed in the stimulation over prefrontal and parietal association areas. These findings provide evidence for the robust bidirectional effects of excitatory and inhibitory rTMSs on RSFC, and raise a possibility that QPS can be a powerful tool to modulate RSFC.

Functional relevance of micromodules in the human association cortex delineated with high-resolution FMRI.

Recent advancement of resting-state functional connectivity magnetic resonance imaging (MRI) has provided a method for drawing boundaries of brain areas. However, it remains to be elucidated how the parcellated areas in the association cortex relate to the spatial extent of the brain activation which ought to reflect a functional unit in the neural network supporting that particular function. To address this issue, in the present study, we first mapped boundaries and 2 adjacent activations in the human inferior frontal cortex, and then examined the spatial relationship between the boundaries and the 2 activations. The boundaries mapped with high-resolution functional magnetic resonance imaging revealed a collection of micromodules, the size of which was approximately only 12 mm on average, much smaller than the Brodmann areas. Each of the 2 activations associated with 2 functions, response inhibition and feedback processing, was smaller in size than the micromodules. By comparing the spatial patterns between the boundaries and the 2 activations, it was revealed that the brain activations were less likely to be located on the boundaries. These results suggest the functional relevance of the areas in the association cortex delineated by the boundary mapping method based on resting-state functional connectivity MRI.

Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease.

Alzheimer's disease is characterized by cognitive impairment and progressive brain atrophy. Recent human neuroimaging studies reported atypical anatomical and functional changes in some regions in the default mode network in patients with Alzheimer's disease, but which brain area of the default mode network is the key region whose atrophy disturbs the entire network activity and consequently contributes to the symptoms of the disease remains unidentified. Here, in this case-control study, we aimed to identify crucial neural regions that mediated the phenotype of Alzheimer's disease, and as such, we examined the intrinsic neural timescales-a functional metric to evaluate the capacity to integrate diverse neural information-and grey matter volume of the regions in the default mode network using resting-state functional MRI images and structural MRI data obtained from individuals with Alzheimer's disease and cognitively typical people. After confirming the atypically short neural timescale of the entire default mode network in Alzheimer's disease and its link with the symptoms of the disease, we found that the shortened neural timescale of the default mode network was associated with the aberrantly short neural timescale of the left angular gyrus. Moreover, we revealed that the shortened neural timescale of the angular gyrus was correlated with the atypically reduced grey matter volume of this parietal region. Furthermore, we identified an association between the neural structure, brain function and symptoms and proposed a model in which the reduced grey matter volume of the left angular gyrus shortened the intrinsic neural time of the region, which then destabilized the entire neural timescale of the default mode network and resultantly contributed to cognitive decline in Alzheimer's disease. These findings highlight the key role of the left angular gyrus in the anatomical and functional aetiology of Alzheimer's disease.

Efficiency of go/no-go task performance implemented in the left hemisphere.

It is well known that the efficiency of response inhibition differs from person to person, but the neural mechanism that implements the efficiency is less understood. In the present fMRI study, we devised an index to evaluate the efficiency of response inhibition in the go/no-go task, and investigated the neural correlates of the efficiency of response inhibition. The human subjects who perform the go/no-go task with a shorter reaction time in go trials (Go-RT) and with a higher percentage of correct no-go trials (Nogo-PC) are thought to have the ability to conduct response inhibition more efficiently. To quantify the efficiency, we defined an efficiency index as the difference in the Nogo-PC between each subject and an ordinarily efficient subject, under the same Go-RT. An across-subject correlation analysis revealed that the brain activity in multiple regions in the left frontal and parietal cortex positively correlated with the efficiency index. Moreover, a test of hemispheric asymmetry with regard to the across-subject correlation revealed left-hemispheric dominance. The significant correlation in the left frontal and parietal regions complements the results of previous studies that used the stop-signal reaction time (SSRT), a well known index to evaluate the efficiency of response inhibition used in the stop-signal task. Our results also indicate that, although it is well known that the neural substrates for response inhibition common in a subject group exist dominantly in the right hemisphere, the neural substrates for efficiency exist dominantly in the left hemisphere.

Functional dissociation between anterior and posterior temporal cortical regions during retrieval of remote memory.

Retrieval of remote memory is considered to differentially involve the anterior and posterior temporal neocortices. Previous neuropsychological studies suggest that the different posterior temporal cortical regions are involved in the retrieval of remote memory of different categories of stimuli, whereas the anterior region is involved more generally in remote memory retrieval. In the present study, using functional magnetic resonance imaging of human brains, we tested this dissociation by examining the more precise characteristics of the anterior and posterior temporal cortical regions. Two categories of stimuli, faces and scenes, were used for paired stimuli to be retrieved, and the brain activity during retrieval of paired stimuli that were learned immediately before the scanning was compared with that during retrieval of paired stimuli that were learned ∼8 weeks earlier. We found that the different posterior temporal cortical regions were activated during retrieval of different categories of remote memory in a category-specific manner, whereas the anterior temporal cortical region was activated during retrieval of remote memory in a category-general manner. Furthermore, by applying a multivariate pattern analysis to psychophysiological interactions during retrieval of remote memory relative to recent memory, we revealed the significant interaction from the category-specific posterior temporal cortical regions to the category-general anterior temporal region. These results suggest that the posterior temporal cortical regions are involved in representation and retrieval of category-specific remote memory, whereas the anterior cortical temporal region is involved in category-general retrieval process of remote memory.

Functional connectivity between anatomically unconnected areas is shaped by collective network-level effects in the macaque cortex.

Coherent spontaneous blood oxygen level-dependent (BOLD) fluctuations have been intensely investigated as a measure of functional connectivity (FC) in the primate neocortex. BOLD-FC is commonly assumed to be constrained by the underlying anatomical connectivity (AC); however, cortical area pairs with no direct AC can also have strong BOLD-FC. On the mechanism generating FC in the absence of direct AC, there are 2 possibilities: 1) FC is determined by signal flows via short connection patterns, such as serial relays and common afferents mediated by a third area; 2) FC is shaped by collective effects governed by network properties of the cortex. In this study, we conducted functional magnetic resonance imaging in anesthetized macaque monkeys and found that BOLD-FC between unconnected areas depends less on serial relays through a third area than on common afferents and, unexpectedly, common efferents, which does not match the first possibility. By utilizing a computational model for interareal BOLD-FC network, we show that the empirically detected AC-FC relationships reflect the configuration of network building blocks (motifs) in the cortical anatomical network, which supports the second possibility. Our findings indicate that FC is not determined solely by interareal short connection patterns but instead is substantially influenced by the network-level cortical architecture.

[Autism spectrum disorder and brain state dynamics].

In this review, I will present that focusing on global brain state dynamics could bring unique insights into the biological understanding of autism. To this end, I will first introduce energy landscape analysis and a novel brain stimulation method called brain-state-driven neural stimulation. Then, this article will discuss the results of the applications of these methods to autism. Finally, I will also state what such an approach reveals about the brain mechanisms underpinning ADHD.