Characterizations of resting-state modulatory interactions in the human brain

Explorations of using a convolutional neural network to understand brain activations during movie watching

Neuroimaging studies increasingly use naturalistic stimuli like video clips to trigger complex brain activations, but the complexity of such stimuli makes it difficult to assign specific functions to the resulting brain activations, particularly for higher-level content like social interactions. To address this challenge, researchers have turned to deep neural networks, e.g., convolutional neural networks (CNNs). CNNs have shown success in image recognition due to their different levels of features enabling high performance. In this study, we used pre-trained VGG-16, a popular CNN model, to analyze video data and extract hierarchical features from low-level shallow layers to high-level deeper layers, linking these activations to different levels of activation of the human brain. We hypothesized that activations in different layers of VGG-16 would be associated with different levels of brain activation and visual processing hierarchy in the brain. We were also curious about which brain regions would be associated with deeper convolutional layers in VGG-16. The study analyzed a functional MRI (fMRI) dataset where participants watched the cartoon movie Partly Cloudy. Frames of the videos were fed into VGG-16, and activation maps from different kernels and layers were extracted. Time series of the average activation patterns for each kernel were created and fed into a voxel-wise model to study brain activations. Results showed that lower convolutional layers (1st convolutional layer) were mostly associated with lower visual regions, but some kernels (6, 19, 24, 42, 55, and 58) surprisingly showed associations with activations in the posterior cingulate cortex, part of the default mode network. Deeper convolutional layers were associated with more anterior and lateral portions of the visual cortex (e.g., the lateral occipital complex) and the supramarginal gyrus. Analyzing activation features associated with different brain regions showed the promise and limitations of using CNNs to link video content to brain functions.

Functional reorganization of brain activity in children with attention-deficit/hyperactivity disorder: Evidence from the modulatory effect of cognitive demand during visuospatial attention task

Previous studies reported that the inferior parietal lobule (IPL) had lower activation during visuospatial attention in children with attention-deficit/hyperactivity disorder (ADHD), while the functional connectivity (FC) between the IPL and other brain regions and how cognitive demand might modulate IPL's FC remain unclear. We performed a functional magnetic resonance imaging experiment recruiting two task conditions with relatively low and high cognitive demand of visuospatial attention. Forty-four children with ADHD and 36 age- and sex-matched healthy controls were included. IPL's regional activation and FC intensities were compared between groups and correlated with clinical measurements. We found that the IPL had significantly reduced activation in children with ADHD compared to healthy controls and this abnormal activation was not modulated by the cognitive demand of visuospatial attention. Importantly, further analysis revealed that the functional connectivity between IPL and inferior frontal gyrus was modulated by the cognitive demand of visuospatial attention in children with ADHD. These results revealed a modulatory effect of cognitive demand of visuospatial attention on IPL's functional connectivity but not IPL's activation in children with ADHD. More generally, these results highlight the functional reorganization of the brain activity as a possible compensatory strategy in response to the symptoms of ADHD.

Neurofunctional underpinnings of individual differences in visual episodic memory performance

Episodic memory, the ability to consciously recollect information and its context, varies substantially among individuals. While prior fMRI studies have identified certain brain regions linked to successful memory encoding at a group level, their role in explaining individual memory differences remains largely unexplored. Here, we analyze fMRI data of 1,498 adults participating in a picture encoding task in a single MRI scanner. We find that individual differences in responsivity of the hippocampus, orbitofrontal cortex, and posterior cingulate cortex account for individual variability in episodic memory performance. While these regions also emerge in our group-level analysis, other regions, predominantly within the lateral occipital cortex, are related to successful memory encoding but not to individual memory variation. Furthermore, our network-based approach reveals a link between the responsivity of nine functional connectivity networks and individual memory variability. Our work provides insights into the neurofunctional correlates of individual differences in visual episodic memory performance.

Fine-scale dynamics of functional connectivity in the face-processing network during movie watching

Mapping the human face-processing network is typically done during rest or using isolated, static face images, overlooking widespread cortical interactions obtained in response to naturalistic face dynamics and context. To determine how inter-subject functional correlation (ISFC) relates to face recognition scores, we measure cortical connectivity patterns in response to a dynamic movie in typical adults (N = 517). We find a positive correlation with recognition scores in edges connecting the occipital visual and anterior temporal regions and a negative correlation in edges connecting the attentional dorsal, frontal default, and occipital visual regions. We measure the inter-subject stimulus-evoked response at a single TR resolution and demonstrate that co-fluctuations in face-selective edges are related to activity in core face-selective regions and that the ISFC patterns peak during boundaries between movie segments rather than during the presence of faces. Our approach demonstrates how face processing is linked to fine-scale dynamics in attentional, memory, and perceptual neural circuitry.

A functional MRI pre-processing and quality control protocol based on statistical parametric mapping (SPM) and MATLAB

Functional MRI (fMRI) has become a popular technique to study brain functions and their alterations in psychiatric and neurological conditions. The sample sizes for fMRI studies have been increasing steadily, and growing studies are sourced from open-access brain imaging repositories. Quality control becomes critical to ensure successful data processing and valid statistical results. Here, we outline a simple protocol for fMRI data pre-processing and quality control based on statistical parametric mapping (SPM) and MATLAB. The focus of this protocol is not only to identify and remove data with artifacts and anomalies, but also to ensure the processing has been performed properly. We apply this protocol to the data from fMRI Open quality control (QC) Project, and illustrate how each quality control step can help to identify potential issues. We also show that simple steps such as skull stripping can improve coregistration between the functional and anatomical images.

Dynamic and stationary brain connectivity during movie watching as revealed by functional MRI

Spatially remote brain regions show synchronized activity as typically revealed by correlated functional MRI (fMRI) signals. An emerging line of research has focused on the temporal fluctuations of connectivity; however, its relationships with stationary connectivity have not been clearly illustrated. We examined dynamic and stationary connectivity when the participants watched four different movie clips. We calculated point-by-point multiplication between two regional time series to estimate the time-resolved dynamic connectivity, and estimated the inter-individual consistency of the dynamic connectivity time series. Widespread consistent dynamic connectivity was observed for each movie clip, which also showed differences between the clips. For example, a cartoon movie clip, Wall-E, showed more consistent of dynamic connectivity with the posterior cingulate cortex and supramarginal gyrus, while a court drama clip, A Few Good Men, showed more consistent of dynamic connectivity with the auditory cortex and temporoparietal junction, which might suggest the involvement of specific brain processing for different movie contents. In contrast, the stationary connectivity as measured by the correlations between regional time series was highly similar among the movie clips, and showed fewer statistically significant differences. The patterns of consistent dynamic connectivity could be used to classify different movie clips with higher accuracy than the stationary connectivity and regional activity. These results support the functional significance of dynamic connectivity in reflecting functional brain changes, which could provide more functionally relevant information than stationary connectivity.

Principal component analysis reveals multiple consistent responses to naturalistic stimuli in children and adults

Functional MRI (fMRI) study of naturalistic conditions, for example, movie watching, usually focuses on shared responses across subjects. However, individual differences have been attracting increasing attention in search of group differences or associations with behavioral outcomes. Individual differences are typically studied by directly modeling the pair‐wise intersubject correlation matrix or projecting the relations onto a single dimension. We contend that it is critical to examine whether there are one or more consistent responses underlying the whole sample, because multiple components, if exist, may undermine the intersubject relations using the previous methods. We propose to use principal component analysis (PCA) to examine the heterogeneity of brain responses across subjects and project the individual variability into higher dimensions. By analyzing an fMRI dataset of children and adults watching a cartoon movie, we showed evidence of two consistent responses in the supramarginal gyrus and other regions. While the first components in many regions represented a response pattern mostly in older children and adults, the second components mainly represented the younger children. The second components in the supramarginal network resembled a delayed version of the first PCs for 4 s (2 TR), indicating slower responses in the younger children than the older children and adults. The analyses highlight the importance of identifying multiple consistent responses in responses to naturalistic stimuli. This PCA‐based approach could be complementary to the commonly used intersubject correlation to analyze movie‐watching data.

Estimations of the weather effects on brain functions using functional MRI: A cautionary note

The influences of environmental factors such as weather on the human brain are still largely unknown. A few neuroimaging studies have demonstrated seasonal effects, but were limited by their cross‐sectional design or sample sizes. Most importantly, the stability of the MRI scanner has not been taken into account, which may also be affected by environments. In the current study, we analyzed longitudinal resting‐state functional MRI (fMRI) data from eight individuals, where they were scanned over months to years. We applied machine learning regression to use different resting‐state parameters, including the amplitude of low‐frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity matrix, to predict different weather and environmental parameters. For careful control, the raw EPI and the anatomical images were also used for predictions. We first found that daylight length and air temperatures could be reliably predicted with cross‐validation using the resting‐state parameters. However, similar prediction accuracies could also be achieved by using one frame of EPI image, and even higher accuracies could be achieved by using the segmented or raw anatomical images. Finally, the signals outside of the brain in the anatomical images and signals in phantom scans could also achieve higher prediction accuracies, suggesting that the predictability may be due to the baseline signals of the MRI scanner. After all, we did not identify detectable influences of weather on brain functions other than the influences on the baseline signals of MRI scanners. The results highlight the difficulty of studying long‐term effects using MRI.

Atypical resting state functional connectivity in mild traumatic brain injury

OBJECTIVES

This study aimed to investigate changes in three intrinsic functional connectivity networks (IFCNs; default mode network [DMN], salience network [SN], and task-positive network [TPN]) in individuals who had sustained a mild traumatic brain injury (mTBI).

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 27 mTBI patients with persistent postconcussive symptoms, along with 26 age- and sex-matched controls. These individuals were recruited from a Level-1 trauma center, at least 3 months after a traumatic episode. IFCNs were established based on seed-to-voxel, region-of-interest (ROI) to ROI, and independent component analyses (ICA). Subsequently, we analyzed the relationship between functional connectivity and postconcussive symptoms.

RESULTS

Seed-to-voxel analysis of rs-fMRI demonstrated decreased functional connectivity in the right lateral parietal lobe, part of the DMN, and increased functional connectivity in the supramarginal gyrus, part of the SN. Our TPN showed both hypo- and hyperconnectivity dependent on seed location. Within network hypoconnectivity was observed in the visual network also using group comparison. Using an ICA, we identified altered network functional connectivity in regions within four IFCNs (sensorimotor, visual, DMN, and dorsal attentional). A significant negative correlation between dorsal attentional network connectivity and behavioral symptoms score was also found.

CONCLUSIONS

Our findings indicate that rs-fMRI may be of use clinically in order to assess disrupted functional connectivity among IFCNs in mTBI patients. Improved mTBI diagnostic and prognostic information could be especially relevant for athletes looking to safely return to play, as well for individuals from the general population with persistent postconcussive symptoms months after injury, who hope to resume activity.

Reproducible coactivation patterns of functional brain networks reveal the aberrant dynamic state transition in schizophrenia

It is well documented that massive dynamic information is contained in the resting-state fMRI. Recent studies have identified recurring states dominated by similar coactivation patterns (CAPs) and revealed their temporal dynamics. However, the reproducibility and generalizability of the CAP analysis are unclear. To address this question, the effects of methodological pipelines on CAP are comprehensively evaluated in this study, including the preprocessing, network construction, cluster number and three independent cohorts. The CAP state dynamics are characterized by the fraction of time, persistence, counts, and transition probability. Results demonstrate six reliable CAP states and their dynamic characteristics are also reproducible. The state transition probability is found to be positively associated with the spatial similarity. Furthermore, the aberrant CAP states in schizophrenia have been investigated by using the reproducible method on three cohorts. Schizophrenia patients spend less time in CAP states that involve the fronto-parietal network, but more time in CAP states that involve the default mode and salience network. The aberrant dynamic characteristics of CAP states are correlated with the symptom severity. These results reveal the reproducibility and generalizability of the CAP analysis, which can provide novel insights into the neuropathological mechanism associated with aberrant brain network dynamics of schizophrenia.

Altered dynamic parahippocampus functional connectivity in patients with post-traumatic stress disorder

OBJECTIVES

This study investigated dynamic brain functional alterations in post-traumatic stress disorder (PTSD) patients with resting state functional magnetic resonance imaging.

METHODS

Degree centrality (DC) and seed-based functional connectivity (FC) analyses were conducted among typhoon survivours with (n = 27) and without PTSD (n = 33) and healthy controls (HC) (n = 30) to assess the intrinsic dysconnectivity pattern and network-level brain function.

RESULTS

Both the PTSD group and the trauma-exposed control (TEC) group had increased DC in the left parahippocampal gyrus relative to the HC group. More increased DC in the left parahippocampal gyrus was found in the PTSD group. Both traumatised groups exhibited decreased left parahippocampal gyrus dynamic FC with the bilateral middle frontal gyrus and superior frontal gyrus relative to the HC group. The Checklist-Civilian Version score was positively correlated with dynamic FC between the parahippocampal gyrus and left superior frontal gyrus but was negatively correlated with dynamic FC between the parahippocampal gyrus and right middle frontal gyrus.

CONCLUSIONS

Trauma exposure may lead to an altered dynamic FC in individuals with or without PTSD. An altered DC in the parahippocampal gyrus may be an important risk factor for PTSD development following trauma exposure. A more prominently increased DC in the parahippocampal gyrus might be a common trait in the PTSD group.

Maladaptive brain organization at 1 month into abstinence as an indicator for future relapse in patients with alcohol use disorder

Abstinence is a lifelong endeavor, and the risk of a relapse is always present for patients with Alcohol Use Disorder (AUD). The aim of the study was to better understand specific characteristics of the intrinsic whole-brain-network architecture of 34 AUD patients that may support abstinence or relapse. We used Graph Theory Analysis (GTA) of resting-state fMRI data from treatment seekers at 1 month of abstinence and their follow-up data as abstainers or relapsers 3 months later, together with data from 30 light/non-drinking controls scanned at the same interval. We determined the group-specific intrinsic community configurations at both timepoints as well as the corresponding modularity Q, a GTA measure that quantifies how well individual network communities are separated from each other. Both AUD groups at both timepoints had community configurations significantly different from those of controls, but the three groups did not significantly differ in their Q values. However, relapsers showed a maladaptive community configuration at baseline, which became more similar to the controls' community organization after the relapsers had started consuming alcohol again during the study interval. Additionally, successful recovery from AUD was not associated with re-gaining the intrinsic brain organization found in light/non-drinkers, but with a re-configuration resulting in a new brain organization distinctly different from that of healthy controls. Resting-state fMRI provides useful measures reflecting neuroplastic adaptations related to AUD treatment outcome.

The laminar pattern of resting state in human cerebral cortex

Resting state functional Magnetic Resonance Imaging (RS-fMRI) provides the means to measure neuronal activity. One of the most commonly used methods to explore the RS-fMRI signal is the Probabilistic Independent Component Analysis (PICA). PICA allows to depict brain functional connectivity (FC) networks. Yet most of the IC maps obtained with this method do not represent any particular FC network. Consequently, those IC maps are classified as artifacts or noise of an unknown source. We hypothesized that the unexplained RS-fMRI signal patterns that are picked up by the PICA can be related to the differences in oxygen metabolism and blood flow in cortical layers. This study aimed at (1) providing preliminary evidence to the effects of laminar organization of neocortex on the RS-fMRI signal, and (2) evaluating the application of laminar maps to aid the classification of IC maps. We created laminar maps 1-4 that depict relative cortical thickness of layers IV and VI. Our data show that the RS-fMRI signal is significantly related to the relative thickness of the cortical layer VI but not layer IV. Importantly, the laminar maps 1-4 overlap with four separate IC maps. Thus, the laminar maps 1-4 improve classification and interpretation of the IC maps. Moreover, the laminar maps 1-4 may be considered as FC networks that are the bridging piece between particular cognitive functions. Together, these data provide preliminary evidence to the fundamental questions about the role of cortical layering in the RS-fMRI signal and brain FC networks.

Non-classical behavior of the default mode network regions during an information processing task

The default mode network (DMN) efficient deactivation and suppressed functional connectivity (FC) during goal-directed tasks, which require attentional resources, have been considered essential to healthy brain cognition. However, recent studies have shown that DMN regions do not always show the expected behavior. Then, we aimed to investigate the functional activation and connectivity of DMN nodes in young, healthy controls during a goal-directed task. We used an adaptation of the symbol digit modalities test (SDMT) to evaluate the information processing speed (IPS). Twenty-four subjects (10 women, age: 29 ± 7 years) underwent two functional Magnetic Resonance Imaging experiments: one during resting-state and one during a block-designed SDMT paradigm. We superimposed the templates of the DMN on the group activation map and observed the reorganization of the network. For the posterior cingulate cortex (PCC) node of the DMN, which is spatially extensive, comprising the precuneus (dorsal portion) and the posterior cingulate gyrus (PCG, ventral portion), the extent of each region was different between conditions, suggesting different functional roles for them. Therefore, for the functional connectivity (FC) analysis, we split the DMN-PCC region into two regions: left precuneus (BA 7) and PCG. The left precuneus (BA 7) was positively correlated with the left lingual gyrus (BA 17), a task-positive region, and negatively associated with the DMN nodes when comparing task performance with the resting-state condition. The other DMN regions presented the classical antagonistic role during the attentional task. In conclusion, we found that the activation and functional connectivity of the DMN is, in general, suppressed during the information processing. However, the left precuneus BA 7 presented a context-dependent modulatory behavior, working as a transient in-between hub connecting the DMN to task-positive areas. Such findings support studies that show increased activation and excitatory functional connectivity of DMN portions during goal-directed tasks. Moreover, our results may contribute to defining more precise functional correlates of IPS deficits in a wide range of clinical and neurological diseases.

Intersubject consistent dynamic connectivity during natural vision revealed by functional MRI

The functional communications between brain regions are thought to be dynamic. However, it is usually difficult to elucidate whether the observed dynamic connectivity is functionally meaningful or simply due to noise during unconstrained task conditions such as resting-state. During naturalistic conditions, such as watching a movie, it has been shown that local brain activities, e.g. in the visual cortex, are consistent across subjects. Following similar logic, we propose to study intersubject correlations of the time courses of dynamic connectivity during naturalistic conditions to extract functionally meaningful dynamic connectivity patterns. We analyzed a functional MRI (fMRI) dataset when the subjects watched a short animated movie. We calculated dynamic connectivity by using sliding window technique, and quantified the intersubject correlations of the time courses of dynamic connectivity. Although the time courses of dynamic connectivity are thought to be noisier than the original signals, we found similar level of intersubject correlations of dynamic connectivity to those of regional activity. Most importantly, highly consistent dynamic connectivity could occur between regions that did not show high intersubject correlations of regional activity, and between regions with little stable functional connectivity. The analysis highlighted higher order brain regions such as the default mode network that dynamically interacted with posterior visual regions during the movie watching, which may be associated with the understanding of the movie.

Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains

Human brain anatomical and resting-state functional connectivity have been comprehensively portrayed using MRI, which are termed anatomical and functional connectomes. A systematic examination of tasks modulated whole brain functional connectivity, which we term as task connectome, is still lacking. We analyzed 6 block-designed and 1 event-related designed functional MRI data, and examined whole-brain task modulated connectivity in various task domains, including emotion, reward, language, relation, social cognition, working memory, and inhibition. By using psychophysiological interaction between pairs of regions from the whole brain, we identified statistically significant task modulated connectivity in 4 tasks between their experimental and respective control conditions. Task modulated connectivity was found not only between regions that were activated during the task but also regions that were not activated or deactivated, suggesting a broader involvement of brain regions in a task than indicated by simple regional activations. Decreased functional connectivity was observed in all the 4 tasks and sometimes reduced connectivity was even between regions that were both activated during the task. This suggests that brain regions that are activated together do not necessarily work together. The current study demonstrates the comprehensive task connectomes of 4 tasks, and suggested complex relationships between regional activations and connectivity changes.

Anterior cingulate cortex differently modulates frontoparietal functional connectivity between resting-state and working memory tasks

The brain frontoparietal regions and the functional communications between them are critical in supporting working memory and other executive functions. The functional connectivity between frontoparietal regions are modulated by working memory loads, and are shown to be modulated by a third brain region in resting-state. However, it is largely unknown whether the third-region modulations remain the same during working memory tasks or were largely modulated by task demands. In the current study, we collected functional MRI (fMRI) data when the subjects were performing n-back tasks and in resting-state. We first used a block-designed localizer to define the frontoparietal regions that showed higher activations in the 2-back than the 1-back condition. Next, we performed physiophysiological interaction (PPI) analysis using left and right middle frontal gyrus (MFG) and superior parietal lobule (SPL) regions, respectively, in three continuous-designed runs of resting-state, 1-back, and 2-back conditions. No regions showed consistent modulatory interactions with the seed pairs in the three conditions. Instead, the anterior cingulate cortex (ACC) showed different modulatory interactions with the right MFG and SPL among the three conditions. While the increased activity of the ACC was associated with decreased functional coupling between the right MFG and SPL in resting-state, it was associated with increased functional coupling in the 2-back condition. The observed task modulations support the functional significance of the modulations of the ACC on frontoparietal connectivity.

Psychoanalysis and Neuroscience: The Bridge Between Mind and Brain

In 1895 in the Project for a Scientific Psychology, Freud tried to integrate psychology and neurology in order to develop a neuroscientific psychology. Since 1880, Freud made no distinction between psychology and physiology. His papers from the end of the 1880s to 1890 were very clear on this scientific overlap: as with many of his contemporaries, Freud thought about psychology essentially as the physiology of the brain. Years later he had to surrender, realizing a technological delay, not capable of pursuing its ambitious aim, and until that moment psychoanalysis would have to use its more suitable clinical method. Also, he seemed skeptical about phrenology drift, typical of that time, in which any psychological function needed to be located in its neuroanatomical area. He could not see the progresses of neuroscience and its fruitful dialogue with psychoanalysis, which occurred also thanks to the improvements in the field of neuroimaging, which has made possible a remarkable advance in the knowledge of the mind-brain system and a better observation of the psychoanalytical theories. After years of investigations, deriving from research and clinical work of the last century, the discovery of neural networks, together with the free energy principle, we are observing under a new light psychodynamic neuroscience in its exploration of the mind-brain system. In this manuscript, we summarize the important developments of psychodynamic neuroscience, with particular regard to the free energy principle, the resting state networks, especially the Default Mode Network in its link with the Self, emphasizing our view of a bridge between psychoanalysis and neuroscience. Finally, we suggest a discussion by approaching the concept of Alpha Function, proposed by the psychoanalyst Wilfred Ruprecht Bion, continuing the association with neuroscience.

Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks

Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, interactions among multiple (e.g., triple and quadruple) areas cannot be reduced to pairwise interactions. Such higher order interactions (HOIs), e.g., exclusive-or (XOR) operation, are widely implemented in computation systems and are crucial for effective information processing. However, it is currently unclear whether any HOIs are present in large-scale brain functional networks when subjects are executing specific tasks. Here we analyzed functional magnetic resonance imaging (fMRI) data collected from human subjects executing various perceptual, motor, and cognitive tasks. We found that HOI strength in the macroscopic functional networks was very weak for all tasks, suggesting that major brain activities do not rely on HOIs on the macroscopic level at the timescale of hundreds of milliseconds. These weak HOIs during tasks were further investigated with a neural network model activated by external inputs, which suggested that weak pairwise interactions among brain areas organized the system without involving HOIs. Taken together, these results demonstrated the dominance of pairwise interactions in organizing coordinated activities among different brain areas to support various brain functions.

The dynamic contribution of the high-level visual cortex to imagery and perception

Mental imagery and visual perception rely on the same content-dependent brain areas in the high-level visual cortex (HVC). However, little is known about dynamic mechanisms in these areas during imagery and perception. Here we disentangled local and inter-regional dynamic mechanisms underlying imagery and perception in the HVC and the hippocampus (HC), a key region for memory retrieval during imagery. Nineteen healthy participants watched or imagined a familiar scene or face during fMRI acquisition. The neural code for familiar landmarks and faces was distributed across the HVC and the HC, although with a different representational structure, and generalized across imagery and perception. However, different regional adaptation effects and inter-regional functional couplings were detected for faces and landmarks during imagery and perception. The left PPA showed opposite adaptation effects, with activity suppression following repeated observation of landmarks, but enhancement following repeated imagery of landmarks. Also, functional coupling between content-dependent brain areas of the HVC and HC changed as a function of task and content. These findings provide important information about the dynamic networks underlying imagery and perception in the HVC and shed some light upon the thin line between imagery and perception which has characterized the neuropsychological debates on mental imagery.

HIV infection across aging: Synergistic effects on intrinsic functional connectivity of the brain

The objective of the study was to examine additive and synergistic effects of age and HIV infection on resting state (RS) intra- and inter-network functional connectivity (FC) of the brain. We also aimed to assess relationships with neurocognition and determine clinical-, treatment-, and health-related factors moderating intrinsic brain activity in aging HIV-positive (HIV+) individuals. The current report presents data on 54 HIV+ individuals (age M = 41, SD = 12 years) stabilized on cART and 54 socio-demographically matched healthy (HIV-) comparators (age M = 43, SD = 12 years), with cohort education mean of 16 years (SD = 12). Age at seroconversion ranged 20-55 years old. ANOVA assessed additive and synergistic effects of age and HIV in 133 ROIs. Bivariate statistics examined relationships of FC indices vulnerable to age-HIV interactions and neurocognitive domains T-scores (attention, executive, memory, psychomotor, semantic skills). Multivariate logistic models determined covariates of FC. This study found no statistically significant age-HIV effects on RS-FC after correcting for multiple comparisons except for synergistic effects on connectivity within cingulo-opercular network (CON) at the trending level. However, for uncorrected RS connectivity analyses, we observed HIV-related strengthening between regions of fronto-parietal network (FPN) and default mode network (DMN), and particular DMN regions and sensorimotor network (SMN). Simultaneously, FC weakening was observed within FPN and between other regions of DMN-SMN, in HIV+ vs. HIV- individuals. Ten ROI pairs revealed age-HIV interactions, with FC decreasing with age in HIV+, while increasing in controls. FC correlated with particular cognitive domains positively in HIV+ vs. negatively in HIV- group. Proportion of life prior-to-after HIV-seroconversion, post-infection years, and treatment determined within-FPN and SMN-DMN FC. In sum, highly functioning HIV+/cART+ patients do not reveal significantly altered RS-FC from healthy comparators. Nonetheless, the current findings uncorrected for multiple comparisons suggest that HIV infection may lead to simultaneous increases and decreases in FC in distinct brain regions even in patients successfully stabilized on cART. Moreover, RS-fMRI ROI-based analysis can be sensitive to age-HIV interactions, which are especially pronounced for inter-network FC in relation to neurocognition. Aging and treatment-related factors partially explain RS-FC in aging HIV+ patients.

Alterations of Resting-State Static and Dynamic Functional Connectivity of the Dorsolateral Prefrontal Cortex in Subjects with Internet Gaming Disorder

Internet gaming disorder (IGD), a major behavior disorder, has gained increasing attention. Recent studies indicate altered resting-state static functional connectivity (FC) of the dorsolateral prefrontal cortex (DLPFC) in subjects with IGD. Whereas static FC often provides information on functional changes in subjects with IGD, investigations of temporal changes in FC between the DLPFC and the other brain regions may shed light on the dynamic characteristics of brain function associated with IGD. Thirty subjects with IGD and 30 healthy controls (HCs) matched for age, gender and education status were recruited. Using the bilateral DLPFC as seeds, static FC and dynamic FC maps were calculated and compared between groups. Correlations between alterations in static FC and dynamic FC and clinical variables were also investigated within the IGD group. The IGD group showed significantly lower static FC between the right DLPFC and the left rolandic operculum while higher static FC between the right DLPFC and the left pars triangularis when compared to HCs. The IGD group also had significantly decreased dynamic FC between the right DLPFC and the left insula, right putamen and left precentral gyrus, and increased dynamic FC in the left precuneus. Moreover, the dynamic FC between the right DLPFC and the left insula was negatively correlated with the severity of IGD. Dynamic FC can be used as a powerful supplement to static FC, helping us obtain a more comprehensive understanding of large-scale brain network activity in IGD and put forward new ideas for behavioral intervention therapy for it.

Age and HIV effects on resting state of the brain in relationship to neurocognitive functioning

This study examined the effects of age and HIV infection on the resting state (RS) functional connectivity (FC) of the brain and cognitive functioning. The objective was to evaluate the moderating role of age and HIV on the relationship between RS-FC and cognition. To examine RS-FC we implemented the Independent Component Analysis (ICA) and Regional Homogeneity (ReHo). Neurocognition was evaluated with comprehensive battery of standardized neuropsychological tests. Age and HIV were entered as the independent variables. The independent effects of age, HIV, and interaction effects of age-HIV on RS-fMRI measures (ICA, ReHo) were tested in 108 participants (age M = 42). RS-FC indices that exhibited age-HIV interactions were entered into further analysis. Bivariate correlation analysis was performed between the retained RS-FC indices and T-scores of neurocognitive domains (Attention, Executive, Memory, Psychomotor, Semantic Skills). Multivariate regression modeling determined the impact of age and HIV on these relationships. We found that in the ICA measures, HIV-seropositivity was decreasing RS-FC in the left middle occipital gyrus (p < .001). Age-HIV interaction was observed in the left superior frontal gyrus (LSupFrontG), where FC was decreasing with age in HIV+ (p < .001) and increasing in HIV- (p = .031). ReHo indices did not reveal significant effects. HIV strengthened the relationship between RS-FC in LSupFrontG, Memory and Psychomotor Factor scores. Aging weakened those relationships only in control group. In sum, age-HIV interaction effects are prominent rather in remote than local RS-FC. Seroconversion strengthens relationships between intrinsic brain activity and neurocognition, but no acceleration with years of age was noted in HIV+ individuals.

Psychophysiological Interactions in a Visual Checkerboard Task: Reproducibility, Reliability, and the Effects of Deconvolution

Psychophysiological interaction (PPI) is a regression based method to study task modulated brain connectivity. Despite its popularity in functional MRI (fMRI) studies, its reliability and reproducibility have not been evaluated. We investigated reproducibility and reliability of PPI effects during a simple visual task, and examined the effect of deconvolution on the PPI results. A large open-access dataset was analyzed (n = 138), where a visual task was scanned twice with repetition times (TRs) of 645 and 1,400 ms, respectively. We first replicated our previous results by using the left and right middle occipital gyrus as seeds. Then regions of interest (ROI)-wise analysis was performed among 20 visual-related thalamic and cortical regions, and negative PPI effects were found between many ROIs with the posterior fusiform gyrus as a hub region. Both the seed-based and ROI-wise results were similar between the two runs and between the two PPI methods with and without deconvolution. The non-deconvolution method and the short TR run in general had larger effect sizes and greater extents. However, the deconvolution method performed worse in the 645 ms TR run than the 1,400 ms TR run in the voxel-wise analysis. Given the general similar results between the two methods and the uncertainty of deconvolution, we suggest that deconvolution may be not necessary for PPI analysis on block-designed data. Lastly, intraclass correlations (ICC) between the two runs were much lower for the PPI effects than the activation main effects, which raise cautions on performing inter-subject correlations and group comparisons on PPI effects.

Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis

Normal aging is typically characterized by abnormal resting-state functional connectivity (FC), including decreasing connectivity within networks and increasing connectivity between networks, under the assumption that the FC over the scan time was stationary. In fact, the resting-state FC has been shown in recent years to vary over time even within minutes, thus showing the great potential of intrinsic interactions and organization of the brain. In this article, we assumed that the dynamic FC consisted of an intrinsic dynamic balance in the resting brain and was altered with increasing age. Two groups of individuals (N = 36, ages 20–25 for the young group; N = 32, ages 60–85 for the senior group) were recruited from the public data of the Nathan Kline Institute. Phase randomization was first used to examine the reliability of the dynamic FC. Next, the variation in the dynamic FC and the energy ratio of the dynamic FC fluctuations within a higher frequency band were calculated and further checked for differences between groups by non-parametric permutation tests. The results robustly showed modularization of the dynamic FC variation, which declined with aging; moreover, the FC variation of the inter-network connections, which mainly consisted of the frontal-parietal network-associated and occipital-associated connections, decreased. In addition, a higher energy ratio in the higher FC fluctuation frequency band was observed in the senior group, which indicated the frequency interactions in the FC fluctuations. These results highly supported the basis of abnormality and compensation in the aging brain and might provide new insights into both aging and relevant compensatory mechanisms.

Resting-State Functional Connectivity Alterations Associated with Six-Month Outcomes in Mild Traumatic Brain Injury

Brain lesions are subtle or absent in most patients with mild traumatic brain injury (mTBI) and the standard clinical criteria are not reliable for predicting long-term outcome. This study investigates resting-state functional MRI (rsfMRI) to assess semiacute alterations in brain connectivity and its relationship with outcome measures assessed 6 months after injury. Seventy-five mTBI patients were recruited as part of the prospective multicenter Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) pilot study and compared with matched 47 healthy subjects. Patients were classified following radiological criteria: CT/MRI positive, evidence of lesions; CT/MRI negative, without evidence of brain lesions. rsfMRI data were acquired and then processed using probabilistic independent component analysis. We compared the functional connectivity of the resting-state networks (RSNs) between patients and controls, as well as group differences in the interactions between RSNs, and related both to cognitive and behavioral performance at 6 months post-injury. Alterations were found in the spatial maps of the RSNs between mTBI patients and healthy controls in networks involved in behavioral and cognition processes. These alterations were predictive of mTBI patients' outcomes at 6 months post-injury. Moreover, different patterns of reduced network interactions were found between the CT/MRI positive and CT/MRI negative patients and the control group. These rsfMRI results demonstrate that even mTBI patients not showing brain lesions on conventional CT/MRI scans can have alterations of functional connectivity at the semiacute stage that help explain their outcomes. These results suggest rsfMRI as a sensitive biomarker both for early diagnosis and for prediction of the cognitive and behavioral performance of these patients.

Aberrant intra-salience network dynamic functional connectivity impairs large-scale network interactions in schizophrenia

Aberrant functional interactions between several large-scale networks, especially the central executive network (CEN), the default mode network (DMN) and the salience network (SN), have been postulated as core pathophysiologic features of schizophrenia; however, the attributing factors of which remain unclear. The study employed resting-state fMRI with 77 participants (42 patients and 35 controls). We performed dynamic functional connectivity (DFC) and functional connectivity (FC) analyses to explore the connectivity patterns of these networks. Furthermore, we performed a structural equation model (SEM) analysis to explore the possible role of the SN in modulating network interactions. The results were as follows: (1) The inter-network connectivity showed decreased connectivity strength and increased time-varying instability in schizophrenia; (2) The SN manifested schizophrenic intra-network dysfunctions in both the FC and DFC patterns; (3) The connectivity properties of the SN were effective in discriminating controls from patients; (4) In patients, the dynamic intra-SN connectivity negatively predicted the inter-network FC, and this effect was mediated by intra-SN connectivity strength. These findings suggest that schizophrenia show systematic deficits in temporal stability of large-scale network connectivity. Furthermore, aberrant network interactions in schizophrenia could be attributed to instable intra-SN connectivity and the dysfunction of the SN may be an intrinsic biomarker of the disease.