Role of the Default Mode Network in Cognitive Transitions

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia

PURPOSE

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia.

METHODS

The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods.

RESULTS

The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups.

CONCLUSIONS

Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Task and stimulus coding in the multiple-demand network

In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala et al, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns. In each parcel, we compared multivertex patterns for every combination of three tasks (working memory, task-switching, and stop-signal) and two stimulus classes (faces and buildings). Though both task and stimulus category were discriminated in every cortical parcel, the strength of discrimination varied strongly across parcels. The different cognitive operations of the three tasks were strongly discriminated in MD regions. Stimulus categories, in contrast, were most strongly discriminated in a large region of primary and higher visual cortex, and intriguingly, in both parietal and frontal lobe regions adjacent to core MD regions. In the monkey, frontal neurons show a strong pattern of nonlinear mixed selectivity, with activity reflecting specific conjunctions of task events. In our data, however, there was limited evidence for mixed selectivity; throughout the brain, discriminations of task and stimulus combined largely linearly, with a small nonlinear component. In MD regions, human fMRI data recapitulate some but not all aspects of electrophysiological data from nonhuman primates.

Differential spatial working memory-related functional network reconfiguration in young and older adults

Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.

Silence between words: Is solitude important for relatedness?

Chronic loneliness is a risk factor for physical and health problems, in part due to dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system. In contrast, temporary moments of positive solitude (passing good times alone and not feeling lonely) appear to have positive effects on mental health, social life, and creativity, and seems to be a buffer against loneliness. Herein, three ways of how solitude may have positive effects on health and relatedness are discussed, namely effects on enhancement of mind-wandering, interoceptive awareness, and spirituality. Solitude may facilitate (1) activation of the default mode network (DMN) underlying mind-wandering including daydreaming about other people; (2) activation of brain areas supporting interoceptive awareness; (3) deactivation of prefrontal cortex, or deactivation and decreased connectivity of the DMN, giving raise to susceptibility to spiritual experiences. The capacity to handle and enjoy solitude is a developmental process that may be difficult for many persons. Craving for social connections and external stimulation with digital technologies (e.g., internet, smartphones, social media) might be interfering with the development of the capacity for solitude and thereby increasing loneliness; this might be partly due to impaired interoceptive awareness and impaired functional mind-wandering (common in solitude). Congruently, overuse of digital technologies was associated with reduced activity, and reduced gray matter volume and density, in brain areas supporting interoceptive awareness, as well as with decreased connectivity of the DMN supporting creative insights. Solitude has been a relatively dismissed topic in neuroscience and health sciences, but a growing number of studies is highlighting its importance for well-being.

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Comparing mouse and human cingulate cortex organization using functional connectivity

The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingulate cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse 'gold standard' tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data. We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address between-species brain organization and aim to improve the translation from preclinical to human results.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which, in turn, modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (n = 149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Advancing Alzheimer's research: Radiomics visualization of the default mode network in cerebral perfusion imaging

OBJECTIVE

Alzheimer's disease, an irreversible neurological condition, demands timely diagnosis for effective clinical intervention. This study employs radiomics analysis to assess image features in default mode network cerebral perfusion imaging among individuals with cognitive impairment.

METHODS

A radiomics analysis of cerebral perfusion imaging was conducted on 117 patients with cognitive impairment. They were divided into training and validation sets in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were employed to select and model image features, followed by logistic regression analysis of LASSO and Random Forest results. Diagnostic performance was assessed by calculating the area under the curve (AUC).

RESULTS

In the training set, LASSO achieved AUC of 0.978, Random Forest had an AUC of 0.933. In the validation set, LASSO had AUC of 0.859, Random Forest had AUC of 0.986. By conducting Logistic Regression analysis in combination with LASSO and Random Forest, we identified a total of five radiomics features, with four related to morphology and one to textural features, originating from the medial prefrontal cortex and middle temporal gyrus. In the training set, Logistic Regression achieved AUC of 0.911, while in the validation set, it attained AUC of 0.925.

CONCLUSION

The medial prefrontal cortex and middle temporal gyrus are the two brain regions within the default mode network that hold the highest significance for Alzheimer's disease diagnosis. Radiomics analysis contributes to the clinical assessment of Alzheimer's disease by delving into image data to extract deeper layers of information.

Correlations between developmental trajectories of brain functional connectivity, neurocognitive functions, and clinical symptoms in patients with attention-deficit hyperactivity disorder

Several studies on attention-deficit hyperactivity disorder (ADHD) have suggested a developmental sequence of brain changes: subcortico-subcortical connectivity in children, evolving to subcortico-cortical in adolescence, and culminating in cortico-cortical connectivity in young adulthood. This study hypothesized that children with ADHD would exhibit decreased functional connectivity (FC) between the cortex and striatum compared to adults with ADHD, who may show increased FC in these regions. Seventy-six patients with ADHD (26 children, 26 adolescents, and 24 adults) and 74 healthy controls (25 children, 24 adolescents, and 25 adults) participated in the study. Resting state magnetic resonance images were acquired using a 3.0 T Philips Achieva scanner. The results indicated a gradual decrease in the number of subcategories representing intelligence quotient deficits in the ADHD group with age. In adulthood, the ADHD group exhibited lower working memory compared to the healthy control group. The number of regions showing decreased FC from the cortex to striatum between the ADHD and control groups reduced with age, while regions with increased FC from the default mode network and attention network in the ADHD group increased with age. In adolescents and adults, working memory was positively associated with brain activity in the postcentral gyrus and negatively correlated with ADHD clinical symptoms. In conclusion, the findings suggest that intelligence deficits in certain IQ subcategories may diminish as individuals with ADHD age. Additionally, the study indicates an increasing anticorrelation between cortical and subcortical regions with age in individuals with ADHD.

Graded and sharp transitions in semantic function in left temporal lobe

Recent work has focussed on how patterns of functional change within the temporal lobe relate to whole-brain dimensions of intrinsic connectivity variation (Margulies et al., 2016). We examined two such 'connectivity gradients' reflecting the separation of (i) unimodal versus heteromodal and (ii) visual versus auditory-motor cortex, examining visually presented verbal associative and feature judgments, plus picture-based context and emotion generation. Functional responses along the first dimension sometimes showed graded change between modality-tuned and heteromodal cortex (in the verbal matching task), and other times showed sharp functional transitions, with deactivation at the extremes and activation in the middle of this gradient (internal generation). The second gradient revealed more visual than auditory-motor activation, regardless of content (associative, feature, context, emotion) or task process (matching/generation). We also uncovered subtle differences across each gradient for content type, which predominantly manifested as differences in relative magnitude of activation or deactivation.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which in turn modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (N=149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Concussion-Related Disruptions to Hub Connectivity in the Default Mode Network Are Related to Symptoms and Cognition

Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three time points: baseline (before beginning their athletic season), acute post-injury (approximately 48h after a diagnosed concussion), and recovery (after starting return-to-play progression, but before returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar time points to link these functional connectivity changes to clinical outcomes. Concussion resulted in increased connectivity between regions within the DMN compared with baseline and recovery, and this post-injury connectivity was more positively related to symptoms and more negatively related to visual memory performance compared with baseline and recovery. Further, concussion led to decreased connectivity between DMN hubs and visual network non-hubs relative to baseline and recovery, and this post-injury connectivity was more negatively related to somatic symptoms and more positively related to visual memory performance compared with baseline and recovery. Relationships between functional connectivity, symptoms, and cognition were not significantly different at baseline versus recovery. These results highlight a unique relationship between self-reported symptoms, visual memory performance, and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.

Transcranial direct current stimulation over the left posterior temporal lobe modulates semantic control: Evidence from episodic memory distortions

Evidence accumulates to show that semantic cognition requires, in addition to semantic representations, control processes that regulate the accessibility and use of semantic knowledge in a task- and time-appropriate fashion. Semantic control has been recently proposed to rely on a distributed network that includes the posterior temporal cortex. Along these lines, recent meta-analyses of neuroimaging data and studies with patients suffering from semantic aphasia have suggested that the left posterior middle temporal gyrus (pMTG) is critically involved whenever situational context must constrain semantic retrieval. In the present experiment, we used transcranial direct current stimulation over the left posterior temporal lobe in an attempt to interfere with semantic control while participants performed a DRM task, a procedure for inducing conceptually-based false recognition that is contingent on both activation and control processes. Paralleling findings with patients suffering from brain damage restricted to the temporoparietal cortex, anodal stimulation (relative to sham stimulation) resulted in increased false recognition but intact true recognition. These findings fit well with the idea that the left pMTG is a key component of a semantic control network, the alteration of which results in memory performance that is affected by the intrusion of contextually-inappropriate semantic information.

Altered task-related decoupling of the rostral anterior cingulate cortex in depression

Dysfunctional activity of the rostral anterior cingulate cortex (rACC) - an extensively connected hub region of the default mode network - has been broadly linked to cognitive and affective impairments in depression. However, the nature of aberrant task-related rACC suppression in depression is incompletely understood. In this study, we sought to characterize functional connectivity of rACC activity suppression ('deactivation') - an essential feature of rACC function - during external task engagement in depression. Specifically, we aimed to explore neural patterns of functional decoupling and coupling with the rACC during its task-driven suppression. We enrolled 81 15- to 25-year-old young people with moderate-to-severe major depressive disorder (MDD) before they commenced a 12-week clinical trial that assessed the effectiveness of cognitive behavioral therapy plus either fluoxetine or placebo. Ninety-four matched healthy controls were also recruited. Participants completed a functional magnetic resonance imaging face matching task known to elicit rACC suppression. To identify brain regions associated with the rACC during its task-driven suppression, we employed a seed-based functional connectivity analysis. We found MDD participants, compared to controls, showed significantly reduced 'decoupling' of the rACC with extended task-specific regions during task performance. Specifically, less decoupling was observed in the occipital and fusiform gyrus, dorsal ACC, medial prefrontal cortex, cuneus, amygdala, thalamus, and hippocampus. Notably, impaired decoupling was apparent in participants who did not remit to treatment, but not treatment remitters. Further, we found MDD participants showed significant increased coupling with the anterior insula cortex during task engagement. Our findings indicate that aberrant task-related rACC suppression is associated with disruptions in adaptive neural communication and dynamic switching between internal and external cognitive modes that may underpin maladaptive cognitions and biased emotional processing in depression.

Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study

Cognitive flexibility is an executive functioning skill that develops in childhood, and when impaired, has transdiagnostic implications for psychiatric disorders. To identify how intrinsic neural architecture at rest is linked to cognitive flexibility performance, we used the data-driven method of independent component analysis (ICA) to investigate resting state networks (RSNs) and their whole-brain connectivity associated with levels of cognitive flexibility performance in children. We hypothesized differences by cognitive flexibility performance in RSN connectivity strength in cortico-striatal circuitry, which would manifest via the executive control network, right and left frontoparietal networks (FPN), salience network, default mode network (DMN), and basal ganglia network. We selected participants from the Adolescent Brain Cognitive Development (ABCD) Study who scored at the 25th, ("CF-Low"), 50th ("CF-Average"), or 75th percentiles ("CF-High") on a cognitive flexibility task, were early to middle puberty, and did not exhibit significant psychopathology (n = 967, 47.9% female; ages 9-10). We conducted whole-brain ICA, identifying 14 well-characterized RSNs. Groups differed in connectivity strength in the right FPN, anterior DMN, and posterior DMN. Planned comparisons indicated CF-High had stronger connectivity between right FPN and supplementary motor/anterior cingulate than CF-Low. CF-High had more anti-correlated connectivity between anterior DMN and precuneus than CF-Average. CF-Low had stronger connectivity between posterior DMN and supplementary motor/anterior cingulate than CF-Average. Post-hoc correlations with reaction time by trial type demonstrated significant associations with connectivity. In sum, our results suggest childhood cognitive flexibility performance is associated with DMN and FPN connectivity strength at rest, and that there may be optimal levels of connectivity associated with task performance that vary by network.

Functional connectivity of cognition-related brain networks in adults with fetal alcohol syndrome

BACKGROUND

Fetal alcohol syndrome (FAS) can result in cognitive dysfunction. Cognitive functions affected are subserved by few functional brain networks. Functional connectivity (FC) in these networks can be assessed with resting-state functional MRI (rs-fMRI). Alterations of FC have been reported in children and adolescents prenatally exposed to alcohol. Previous reports varied substantially regarding the exact nature of findings. The purpose of this study was to assess FC of cognition-related networks in young adults with FAS.

METHODS

Cross-sectional rs-fMRI study in participants with FAS (n = 39, age: 20.9 ± 3.4 years) and healthy participants without prenatal alcohol exposure (n = 44, age: 22.2 ± 3.4 years). FC was calculated as correlation between cortical regions in ten cognition-related sub-networks. Subsequent modelling of overall FC was based on linear models comparing FC between FAS and controls. Results were subjected to a hierarchical statistical testing approach, first determining whether there is any alteration of FC in FAS in the full cognitive connectome, subsequently resolving these findings to the level of either FC within each network or between networks based on the Higher Criticism (HC) approach for detecting rare and weak effects in high-dimensional data. Finally, group differences in single connections were assessed using conventional multiple-comparison correction. In an additional exploratory analysis, dynamic FC states were assessed.

RESULTS

Comparing FAS participants with controls, we observed altered FC of cognition-related brain regions globally, within 7 out of 10 networks, and between networks employing the HC statistic. This was most obvious in attention-related network components. Findings also spanned across subcomponents of the fronto-parietal control and default mode networks. None of the single FC alterations within these networks yielded statistical significance in the conventional high-resolution analysis. The exploratory time-resolved FC analysis did not show significant group differences of dynamic FC states.

CONCLUSIONS

FC in cognition-related networks was altered in adults with FAS. Effects were widely distributed across networks, potentially reflecting the diversity of cognitive deficits in FAS. However, no altered single connections could be determined in the most detailed analysis level. Findings were pronounced in networks in line with attentional deficits previously reported.

Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network

In healthy subjects, activity in the default mode network (DMN) and the frontoparietal network (FPN) has consistently been associated with working memory (WM). In particular, the dorsolateral prefrontal cortex (DLPFC) is important for WM. The functional-anatomical basis of WM impairment in glioma patients is, however, still poorly understood. We investigated whether WM performance of glioma patients is reflected in resting-state functional connectivity (FC) between the DMN and FPN, additionally focusing on the DLPFC. Resting-state functional MRI data were acquired from 45 glioma patients prior to surgery. WM performance was derived from a pre-operative N-back task. Scans were parcellated into ROIs using both the Gordon and Yeo atlas. FC was calculated as the average Pearson correlation between functional time series. The FC between right DLPFC and DMN was inversely related to WM performance for both the Gordon and Yeo atlas (p = .010). No association was found for FC between left DLPFC and DMN, nor between the whole FPN and DMN. The results are robust and not dependent on atlas choice or tumor location, as they hold for both the Gordon and Yeo atlases, and independently of location variables. Our findings show that WM performance of glioma patients can be quantified in terms of interactions between regions and large-scale networks that can be measured with resting-state fMRI. These group-based results are a necessary step toward development of biomarkers for clinical management of glioma patients, and provide additional evidence that global disruption of the DMN relates to cognitive impairment in glioma patients.

Planning ahead: Predictable switching recruits task-active and resting-state networks

Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

Alterations in intra- and inter-network connectivity associated with cognition impairment in insulinoma patients

Objective

Cognitive dysfunction is common in insulinoma patients, but the underlying neural mechanisms are less well understood. This study aimed to explore the alterations of intra- and inter-network connectivity patterns associated with patients with insulinoma.

Methods

Resting-state fMRI were acquired from 13 insulinoma patients and 13 matched healthy controls (HCs). Group Independent component analysis (ICA) was employed to capture the resting-state networks (RSNs), then the intra- and inter-network connectivity patterns, were calculated and compared. Montreal Cognitive Assessment (MoCA) was used to assess the cognitive function. The relationship between connectivity patterns and MoCA scores was also examined.

Results

Insulinoma patients performed significantly worse on MoCA compared to HCs. The intra-network connectivity analysis revealed that patients with insulinoma showed decreased connectivity in the left medial superior frontal gyrus within anterior default mode network (aDMN), and decreased connectivity in right lingual gyrus within the visual network (VN). The intra-network connectivity analysis showed that patients with insulinoma had an increased connectivity between the inferior-posterior default mode network (ipDMN) and right frontoparietal network (rFPN) and decreased connectivity between the ipDMN and auditory network (AUN). There was a significant negative correlation between the ipDMN-rFPN connectivity and MoCA score.

Conclusion

This study demonstrated significant abnormalities in the intra- and inter-network connectivity in patients with insulinoma, which may represent the neural mechanisms underlying the cognitive impairment in insulinoma patients.

Hippocampal Connectivity with the Default Mode Network is Linked to Hippocampal Volume in the Clinical High Risk for Psychosis Syndrome and Healthy Individuals

Reduced hippocampal volume (HV) is an established brain morphological feature of psychiatric conditions. HV is associated with brain connectivity in humans and non-human animals and altered connectivity is associated with risk for psychiatric illness. Associations between HV and connectivity remain poorly characterized in humans, and especially in phases of psychiatric illness that precede disease onset. This study examined associations between HV and hippocampal functional connectivity (FC) during rest in 141 healthy controls and 248 individuals at-risk for psychosis. Significant inverse associations between HV and hippocampal FC with the inferior parietal lobe (IPL) and thalamus were observed. Select associations between hippocampal FC and HV were moderated by diagnostic group. Significant moderation results shifted from implicating the IPL to the temporal pole after excluding participants on antipsychotic medication. Considered together, this work implicates hippocampal FC with the temporoparietal junction, within a specialized subsystem of the default mode network, as sensitive to HV.

The Involvement of the Multiple Demand and Default Mode Networks in a Trial-by-Trial Cognitive Control

Adaptive behavior in the environment requires a high level of cognitive control to bias limited processing resources to behaviorally significant stimuli. Such control has been associated with a set of brain regions located in the fronto-parietal cortex (multiple demand network), whose activity was found to increase as the control demand for a task increases. In contrast, another set of regions, default mode network regions, were found to be deactivated during top-down processing of task stimuli. Despite this dissociation in their activation amplitudes, it is possible that activation patterns of these regions commonly encode specific task features. In two independent neuroimaging datasets, involving a total of 40 human samples, we found that the performance of an attentional task evoked positive activity of the MDN and deactivation of the DMN. Consistent with previous studies, task features could be decoded from the fronto-parietal cognitive regions. Importantly, the regions of the DMN also encoded task features when the task set had to be rapidly reconfigured in a transient, trial-by-trial manner, along with the MDN regions. These results suggest that the two separate brain networks ultimately co-ordinate for the effective establishment of top-down cognitive control.

20 years of the default mode network: A review and synthesis

The discovery of the default mode network (DMN) has revolutionized our understanding of the workings of the human brain. Here, I review developments that led to the discovery of the DMN, offer a personal reflection, and consider how our ideas of DMN function have evolved over the past two decades. I summarize literature examining the role of the DMN in self-reference, social cognition, episodic and autobiographical memory, language and semantic memory, and mind wandering. I identify unifying themes and propose new perspectives on the DMN's role in human cognition. I argue that the DMN integrates and broadcasts memory, language, and semantic representations to create a coherent "internal narrative" reflecting our individual experiences. This narrative is central to the construction of a sense of self, shapes how we perceive ourselves and interact with others, may have ontogenetic origins in self-directed speech during childhood, and forms a vital component of human consciousness.

The default mode network is affected in the early stage of simian immunodeficiency virus infection: a longitudinal study

Acquired immune deficiency syndrome infection can lead to cognitive dysfunction represented by changes in the default mode network. Most recent studies have been cross-sectional and thus have not revealed dynamic changes in the default mode network following acquired immune deficiency syndrome infection and antiretroviral therapy. Specifically, when brain imaging data at only one time point are analyzed, determining the duration at which the default mode network is the most effective following antiretroviral therapy after the occurrence of acquired immune deficiency syndrome. However, because infection times and other factors are often uncertain, longitudinal studies cannot be conducted directly in the clinic. Therefore, in this study, we performed a longitudinal study on the dynamic changes in the default mode network over time in a rhesus monkey model of simian immunodeficiency virus infection. We found marked changes in default mode network connectivity in 11 pairs of regions of interest at baseline and 10 days and 4 weeks after virus inoculation. Significant interactions between treatment and time were observed in the default mode network connectivity of regions of interest pairs area 31/V6.R and area 8/frontal eye field (FEF). L, area 8/FEF.L and caudal temporal parietal occipital area (TPOC).R, and area 31/V6.R and TPOC.L. ART administered 4 weeks after infection not only interrupted the progress of simian immunodeficiency virus infection but also preserved brain function to a large extent. These findings suggest that the default mode network is affected in the early stage of simian immunodeficiency virus infection and that it may serve as a potential biomarker for early changes in brain function and an objective indicator for making early clinical intervention decisions.

Accumulation of network redundancy marks the early stage of Alzheimer's disease

Brain wiring redundancy counteracts aging-related cognitive decline by reserving additional communication channels as a neuroprotective mechanism. Such a mechanism plays a potentially important role in maintaining cognitive function during the early stages of neurodegenerative disorders such as Alzheimer's disease (AD). AD is characterized by severe cognitive decline and involves a long prodromal stage of mild cognitive impairment (MCI). Since MCI subjects are at high risk of converting to AD, identifying MCI individuals is essential for early intervention. To delineate the redundancy profile during AD progression and enable better MCI diagnosis, we define a metric that reflects redundant disjoint connections between brain regions and extract redundancy features in three high-order brain networks-medial frontal, frontoparietal, and default mode networks-based on dynamic functional connectivity (dFC) captured by resting-state functional magnetic resonance imaging (rs-fMRI). We show that redundancy increases significantly from normal control (NC) to MCI individuals and decreases slightly from MCI to AD individuals. We further demonstrate that statistical features of redundancy are highly discriminative and yield state-of-the-art accuracy of up to 96.8 ± 1.0% in support vector machine (SVM) classification between NC and MCI individuals. This study provides evidence supporting the notion that redundancy serves as a crucial neuroprotective mechanism in MCI.

Responsiveness variability during anaesthesia relates to inherent differences in brain structure and function of the frontoparietal networks

Anaesthesia combined with functional neuroimaging provides a powerful approach for understanding the brain mechanisms of consciousness. Although propofol is used ubiquitously in clinical interventions that reversibly suppress consciousness, it shows large inter-individual variability, and the brain bases of this variability remain poorly understood. We asked whether three networks key to conscious cognition-the dorsal attention (DAN), executive control (ECN), and default mode (DMN)-underlie responsiveness variability under anaesthesia. Healthy participants (N = 17) were moderately anaesthetized during narrative understanding and resting-state conditions inside the Magnetic Resonance Imaging scanner. A target detection task measured behavioural responsiveness. An independent behavioural study (N = 25) qualified the attention demands of narrative understanding. Then, 30% of participants were unaffected in their response times, thus thwarting a key aim of anaesthesia-the suppression of behavioural responsiveness. Individuals with stronger functional connectivity within the DAN and ECN, between them, and to the DMN, and with larger grey matter volume in frontal regions were more resilient to anaesthesia. For the first time, we show that responsiveness variability during propofol anaesthesia relates to inherent differences in brain structure and function of the frontoparietal networks, which can be predicted prior to sedation. Results highlight novel markers for improving awareness monitoring during clinical anaesthesia.

F = ma. Is the macaque brain Newtonian?

Intuitive Physics, the ability to anticipate how the physical events involving mass objects unfold in time and space, is a central component of intelligent systems. Intuitive physics is a promising tool for gaining insight into mechanisms that generalize across species because both humans and non-human primates are subject to the same physical constraints when engaging with the environment. Physical reasoning abilities are widely present within the animal kingdom, but monkeys, with acute 3D vision and a high level of dexterity, appreciate and manipulate the physical world in much the same way humans do.

A distinct intra-individual suppression subnetwork in the brain's default mode network across cognitive tasks

Suppression of the brain's default mode network (DMN) during external goal-directed cognitive tasks has been consistently observed in neuroimaging studies. However, emerging insights suggest the DMN is not a monolithic "task-negative" network but is comprised of subsystems that show functional heterogeneity. Despite considerable research interest, no study has investigated the consistency of DMN activity suppression across multiple cognitive tasks within the same individuals. In this study, 85 healthy 15- to 25-year-olds completed three functional magnetic resonance imaging tasks that were designed to reliably map DMN suppression from a resting baseline. Our findings revealed a distinct suppression subnetwork across the three tasks that comprised traditional DMN and adjacent regions. Specifically, common suppression was observed in the medial prefrontal cortex, the dorsal-to-mid posterior cingulate cortex extending to the precuneus, and the posterior insular cortex and parietal operculum. Further, we found the magnitude of suppression of these regions were significantly correlated within participants across tasks. Overall, our findings indicate that externally oriented cognitive tasks elicit common suppression of a distinct subnetwork of the broader DMN. The consistency to which the DMN is suppressed within individuals suggests a domain-general mechanism that may reflect a stable feature of cognitive function that optimizes external goal-directed behavior.

Relating Cognition to both Brain Structure and Function: A Systematic Review of Methods

Introduction: Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Many studies have combined structural and functional neuroimaging techniques to uncover the complex relationship between them. In this study, we report the first systematic review that assesses how information from structural and functional neuroimaging methods can be integrated to investigate the brain substrates of cognition. Procedure: Web of Science and Scopus databases were searched for studies of healthy young adult populations that collected cognitive data and structural and functional neuroimaging data. Results: Five percent of screened studies met all inclusion criteria. Next, 50% of included studies related cognitive performance to brain structure and function without quantitative analysis of the relationship. Finally, 31% of studies formally integrated structural and functional brain data. Overall, many studies consider either structural or functional neural correlates of cognition, and of those that consider both, they have rarely been integrated. We identified four emergent approaches to the characterization of the relationship between brain structure, function, and cognition; comparative, predictive, fusion, and complementary. Discussion: We discuss the insights provided in each approach about the relationship between brain structure and function and how it impacts cognitive performance. In addition, we discuss how authors can select approaches to suit their research questions. Impact statement The relationship between structural and functional brain networks and their relationship to cognition is a matter of current investigations. This work surveys how researchers have studied the relationship between brain structure and function and its impact on cognitive function in healthy adult populations. We review four emergent approaches of quantitative analysis of this multivariate problem; comparative, predictive, fusion, and complementary. We explain the characteristics of each approach, discuss the insights provided in each approach, and how authors can combine approaches to suit their research questions.

Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli

The default mode network (DMN) is critical for self-referential mental processes, and its dysfunction is implicated in many neuropsychiatric disorders. However, the neurophysiological properties and task-based functional organization of the rodent DMN are poorly understood, limiting its translational utility. Here, we combine fiber photometry with functional magnetic resonance imaging (fMRI) and computational modeling to characterize dynamics of putative rat DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. Our analysis revealed neuronal activity changes in AI and DMN nodes preceding fMRI-derived DMN activations and cyclical transitions between brain network states. Furthermore, we demonstrate that salient oddball stimuli suppress the DMN and enhance AI neuronal activity and that the AI causally inhibits the retrosplenial cortex, a prominent DMN node. These findings elucidate the neurophysiological foundations of the rodent DMN, its spatiotemporal dynamical properties, and modulation by salient stimuli, paving the way for future translational studies.

A true response of the brain network during electroacupuncture stimulation at scalp acupoints: An fMRI with simultaneous EAS study

OBJECTIVES

The aim of this study was to explore simultaneous brain network responses to electroacupuncture stimulation (EAS) at scalp acupoints by accounting for placebo effects.

MATERIALS AND METHODS

Sixty healthy subjects were recruited and randomly divided into two groups: Group 1 and Group 2. Functional magnetic resonance imaging (fMRI) was performed in Group 1 with sham acupuncture stimulation at acupoints Shenting (GV24) and Touwei (ST8) without EAS. Group 2 underwent verum EAS at the same acupoints during fMRI. Independent component analysis was used to analyze the fMRI data. Full-factor statistical analysis was used to compare the differences in fMRI data between the two groups and evaluate the changes in functional connectivity in brain networks after verum electrical stimulation (Group 1 [after sham electrical current stimulation - before sham electrical current stimulation] - Group 2 [after verum electrical current stimulation - before verum electrical current stimulation]) (p <.001, extent threshold k = 20 voxels).

RESULTS

Six brain networks were identified. Significant increased functional connectivity was observed in the right and left executive control networks, sensorimotor network, and attention network, while decreased functional connectivity was mainly found in the default mode network. There were no statistically significant differences in the salience network.

CONCLUSIONS

fMRI with simultaneous EAS provides a method to explore brain network responses due to EAS at scalp acupoints. The networks responsible for cognition are differentially activated by EAS in a coordinated manner.

Context-independent scaling of neural responses to task difficulty in the multiple-demand network

The multiple-demand (MD) network is sensitive to many aspects of cognitive demand, showing increased activation with more difficult tasks. However, it is currently unknown whether the MD network is modulated by the context in which task difficulty is experienced. Using functional magnetic resonance imaging, we examined MD network responses to low, medium, and high difficulty arithmetic problems within 2 cued contexts, an easy versus a hard set. The results showed that MD activity varied reliably with the absolute difficulty of a problem, independent of the context in which the problem was presented. Similarly, MD activity during task execution was independent of the difficulty of the previous trial. Representational similarity analysis further supported that representational distances in the MD network were consistent with a context-independent code. Finally, we identified several regions outside the MD network that showed context-dependent coding, including the inferior parietal lobule, paracentral lobule, posterior insula, and large areas of the visual cortex. In sum, a cognitive effort is processed by the MD network in a context-independent manner. We suggest that this absolute coding of cognitive demand in the MD network reflects the limited range of task difficulty that can be supported by the cognitive apparatus.

Resting state fMRI brain mapping in pediatric supratentorial brain tumors

Background

Functional mapping of eloquent brain areas is crucial for preoperative planning in patients with brain tumors. Resting state functional MRI (rs-fMRI) allows the localization of functional brain areas without the need for task performance, making it well-suited for the pediatric population. In this study the independent component analysis (ICA) rs-fMRI functional mapping results are reported in a group of 22 pediatric patients with supratentorial brain tumors. Additionally, the functional connectivity (FC) maps of the sensori-motor network (SMN) obtained using ICA and seed-based analysis (SBA) are compared.

Results

Different resting state networks (RSNs) were extracted using ICA with varying levels of sensitivity, notably, the SMN was identified in 100% of patients, followed by the Default mode network (DMN) (91%) and Language networks (80%). Additionally, FC maps of the SMN extracted by SBA were more extensive (mean volume = 25,288.36 mm3, standard deviation = 13,364.36 mm3) than those found on ICA (mean volume = 13,403.27 mm3, standard deviation = 9755.661 mm3). This was confirmed by statistical analysis using a Wilcoxon signed rank t test at p < 0.01.

Conclusions

Results clearly demonstrate the successful applicability of rs-fMRI for localizing different functional brain networks in the preoperative assessment of brain areas, and thus represent a further step in the integration of computational radiology research in a clinical setting.

EEG analysis of the visual motion activated vection network in left- and right-handers

Visually-induced self-motion perception (vection) relies on interaction of the visual and vestibular systems. Neuroimaging studies have identified a lateralization of the thalamo-cortical multisensory vestibular network, with left-handers exhibiting a dominance of the left hemisphere and right-handers exhibiting a dominance of the right hemisphere. Using electroencephalography (EEG), we compare the early processing of a vection-consistent visual motion stimulus against a vection-inconsistent stimulus, to investigate the temporal activation of the vection network by visual motion stimulation and the lateralization of these processes in left- versus right-handers. In both groups, vection-consistent stimulation evoked attenuated central event-related potentials (ERPs) in an early (160-220 ms) and a late (260-300 ms) time window. Differences in estimated source activity were found across visual, sensorimotor, and multisensory vestibular cortex in the early window, and were observed primarily in the posterior cingulate, retrosplenial cortex, and precuneus in the late window. Group comparisons revealed a larger ERP condition difference (i.e. vection-consistent stimulation minus vection-inconsistent stimulation) in left-handers, which was accompanied by group differences in the cingulate sulcus visual (CSv) area. Together, these results suggest that handedness may influence ERP responses and activity in area CSv during vection-consistent and vection-inconsistent visual motion stimulation.

Evaluating the reliability, validity, and utility of overlapping networks: Implications for network theories of cognition

Brain network definitions typically assume nonoverlap or minimal overlap, ignoring regions' connections to multiple networks. However, new methods are emerging that emphasize network overlap. Here, we investigated the reliability and validity of one assignment method, the mixed membership algorithm, and explored its potential utility for identifying gaps in existing network models of cognition. We first assessed between-sample reliability of overlapping assignments with a split-half design; a bootstrapped Dice similarity analysis demonstrated good agreement between the networks from the two subgroups. Next, we assessed whether overlapping networks captured expected nonoverlapping topographies; overlapping networks captured portions of one to three nonoverlapping topographies, which aligned with canonical network definitions. Following this, a relative entropy analysis showed that a majority of regions participated in more than one network, as is seen biologically, and many regions did not show preferential connection to any one network. Finally, we explored overlapping network membership in regions of the dual-networks model of cognitive control, showing that almost every region was a member of multiple networks. Thus, the mixed membership algorithm produces consistent and biologically plausible networks, which presumably will allow for the development of more complete network models of cognition.

Abnormalities of the Default Mode Network Functional Connectivity in Patients with Insomnia Disorder

Objective

This paper aimed to probe changes in the default mode network (DMN) functional connectivity (DMNFC) of the brain of patients with insomnia disorder (ID) under the resting state.

Methods

A total of 67 patients with ID and 67 graphically matched healthy controls were selected. Then, their general information was collected, followed by a psychological scale valuation. Resting state functional magnetic resonance imaging (rs-fMRI) scanning was conducted. Subsequently, collected statistics were processed, bilateral precuneus and medial superior frontal gyrus were defined as regions of interest (ROI), and the difference in intensity between these two groups was compared.

Results

Compared with the healthy control group, the patients in the ID group were observed with abnormalities of DMNFC. Specifically, a significant increase in the functional connectivity (FC) could be observed between the left medial superior frontal gyrus and left central anterior gyrus, the left medial superior frontal gyrus and anterior cingulate gyrus, the right medial superior frontal gyrus and left central anterior gyrus, the left anterior cuneiform and left central anterior/posterior gyrus, the left anterior cuneiform and left superior occipital gyrus, as well as the right anterior cuneiform and left central posterior gyrus. However, the FC between the left anterior cuneiform and the right middle frontal gyrus was weakened, as well as between the left anterior cuneiform and the right angle gyrus and between the right precuneus and the left inferior temporal gyrus.

Conclusion

ID patients may suffer changes in FC. The decline of FC in DMN may be one of the underlying causes of ID; the enhancement of FC between DMN and the visual-spatial attention network may play a key role in the mechanisms of impaired brain functional networks of ID.

Cortical excitatory and inhibitory correlates of the fronto-limbic circuit in major depression and differential effects of left frontal brain stimulation in a randomized sham-controlled trial

BACKGROUND

Major depressive disorder (MDD), particularly treatment-resistant ones, is associated with abnormal fronto-limbic glucose metabolism. 10-Hz repetitive transcranial magnetic stimulation (rTMS) over left prefrontal cortex (PFC) is believed to normalize the abnormal metabolism to treat depression. However, the exact molecular mechanisms underlying the mood circuit of depressed brains and whether brain stimulation techniques regulate the underlying molecules remain elusive.

METHODS

Whole-brain glucose metabolism and cortical excitatory and inhibitory markers including P30, N45, P60, N100, and LICI (long-interval cortical inhibition) of TMS-evoked potentials from left DLPFC were measured in 40 subjects with MDD patients. The neurophysiological markers were repeated immediately after 1st session of left PFC rTMS, intermittent theta-burst stimulation (iTBS), and sham (randomly assigned).

RESULTS

Brain glucose metabolism in the limbic structures significantly correlated with left PFC P30 (mainly GABA-A and glutamate receptor mediated) and with LICI (mainly GABA-B receptor mediated inhibition) (FWE-corrected p < 0.001). Correlations between other neurophysiological markers (left PFC N45, P60, and N100) and posterior cingulate cortex, a key region in the default mode network, were also noted. One session of rTMS significantly decreased left PFC P60 (mainly glutamate receptor mediated), while a significant group effect was found for LICI (iTBS < sham).

CONCLUSION

The first study showed that the underlying molecular mechanisms of fronto-limbic circuit of MDD brains involved glutamatergic excitation and GABAergic inhibition at specific time points. In addition, one session of rTMS mainly modulated glutamatergic neurotransmission at left PFC, while the mechanisms of iTBS might involve GABA-B receptor mediated inhibition.

CLINICAL TRIALS REGISTRY NUMBER

UMIN000044951.

Exploring the relationship between resting state intra-network connectivity and accelerometer-measured physical activity in pediatric concussion: A cohort study

Our objective was to explore the association between resting state functional connectivity and accelerometer-measured physical activity in pediatric concussion. Fourteen children with concussion (aged 14.54 ± 2.39 years, 8 female) were included in this secondary data analysis of a larger study. Participants had neuroimaging at 15.3 ± 6.7 days post-injury and subsequently a mean of 11.1 ± 5.0 days of accelerometer data. Intra-network connectivity of the default mode network (DMN), sensorimotor network (SMN), salience network (SN), and fronto-parietal network (FPN) was computed using resting state functional MRI. We found that per general linear models, only intra-network connectivity of the DMN was associated with physical activity levels. More specifically, increased intra-network connectivity of the DMN was significantly associated with higher levels of subsequent accelerometer-measured light physical activity (F(2, 11) = 7.053, p = 0.011, Ra2 = 0.562; β = 0.469), moderate physical activity (F(2, 11) = 7.053, p = 0.011, Ra2 = 0.562; β = 0.725), and vigorous physical activity (F(2, 11) = 10.855, p = 0.002, Ra2 = 0.664; β = 0.79). Intra-network connectivity of the DMN did not significantly predict sedentary time. Therefore, these preliminary findings suggest that there is a positive association between the intra-network connectivity of the DMN and device-measured physical activity in children with concussion.

Neurocognitive Mechanisms Underlying Internet/Smartphone Addiction: A Preliminary fMRI Study

The present study investigated the neurocognitive mechanisms underlying smartphone/internet addiction. We tested a specific hypothesis that the excessive, uncontrolled use of smartphones should be related to the ability of controlling attention in a purely endogenous and self-regulatory manner. In an fMRI experiment, in which 43 adults participated, we had participants detect and identify specified target stimuli among non-targets. In some trials, 10 s oddball movies were presented as distractors. While the participants try to filter out the distractors and focus their attention on the main task, the activation profiles of the frontoparietal brain regions were examined. The results showed that the people with a higher risk of being addicted to smartphone use failed to filter out distractors via the endogenous control of attention. The neuroimaging data showed that the high-risk group showed significantly lower levels of activation in the frontopolar cortex (FPC). We conclude that people at a high risk of smartphone addiction have difficulty endogenously shifting their attention from distracting stimuli toward goal-directed behavior, and FPC plays a critical role in this self-regulatory control of attention.

A voice without a mouth no more: The neurobiology of language and consciousness

Most research on the neurobiology of language ignores consciousness and vice versa. Here, language, with an emphasis on inner speech, is hypothesised to generate and sustain self-awareness, i.e., higher-order consciousness. Converging evidence supporting this hypothesis is reviewed. To account for these findings, a 'HOLISTIC' model of neurobiology of language, inner speech, and consciousness is proposed. It involves a 'core' set of inner speech production regions that initiate the experience of feeling and hearing words. These take on affective qualities, deriving from activation of associated sensory, motor, and emotional representations, involving a largely unconscious dynamic 'periphery', distributed throughout the whole brain. Responding to those words forms the basis for sustained network activity, involving 'default mode' activation and prefrontal and thalamic/brainstem selection of contextually relevant responses. Evidence for the model is reviewed, supporting neuroimaging meta-analyses conducted, and comparisons with other theories of consciousness made. The HOLISTIC model constitutes a more parsimonious and complete account of the 'neural correlates of consciousness' that has implications for a mechanistic account of mental health and wellbeing.

A generalized cortical activity pattern at internally generated mental context boundaries during unguided narrative recall

Current theory and empirical studies suggest that humans segment continuous experiences into events based on the mismatch between predicted and actual sensory inputs; detection of these ‘event boundaries’ evokes transient neural responses. However, boundaries can also occur at transitions between internal mental states, without relevant external input changes. To what extent do such ‘internal boundaries’ share neural response properties with externally driven boundaries? We conducted an fMRI experiment where subjects watched a series of short movies and then verbally recalled the movies, unprompted, in the order of their choosing. During recall, transitions between movies thus constituted major boundaries between internal mental contexts, generated purely by subjects’ unguided thoughts. Following the offset of each recalled movie, we observed stereotyped spatial activation patterns in the default mode network, especially the posterior medial cortex, consistent across different movie contents and even across the different tasks of movie watching and recall. Surprisingly, the between-movie boundary patterns did not resemble patterns at boundaries between events within a movie. Thus, major transitions between mental contexts elicit neural phenomena shared across internal and external modes and distinct from within-context event boundary detection, potentially reflecting a cognitive state related to the flushing and reconfiguration of situation models.

Retrieval context determines whether event boundaries impair or enhance temporal order memory

Meaningful changes in context create "event boundaries", segmenting continuous experience into distinct episodes in memory. A foundational finding in this literature is that event boundaries impair memory for the temporal order of stimuli spanning a boundary compared to equally spaced stimuli within an event. This seems surprising in light of intuitions about memory in everyday life, where the order of within-event experiences (did I have coffee before the first bite of bagel?) often seems more difficult to recall than the order of events per se (did I have breakfast or do the dishes first?). Here, we aimed to resolve this discrepancy by manipulating whether stimuli carried information about their encoding context during retrieval, as they often do in everyday life (e.g., bagel-breakfast). In Experiments 1 and 2, we show that stimuli inherently associated with a unique encoding context produce a "flipped" order memory effect, whereby temporal memory was superior for cross-boundary than within-event item pairs. In Experiments 3 and 4, we added context information at retrieval to a standard laboratory event memory protocol where stimuli were encoded in the presence of arbitrary context cues (colored frames). We found that whether temporal order memory for cross-boundary stimuli was enhanced or impaired relative to within-event items depended on whether the context was present or absent during the memory test. Taken together, we demonstrate that the effect of event boundaries on temporal memory is malleable, and determined by the availability of context information at retrieval.

Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition

Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

How general anesthetics work: from the perspective of reorganized connections within the brain

General anesthesia is critical for various procedures and surgeries. Despite the widespread use of anesthetics, their precise mechanisms remain poorly understood. Anesthetics inevitably act on the brain, primarily through the modulation of target receptors. Even if the action is specific to an individual neuron, however, long-range effects can occur due to the tremendous interconnectedness of neuronal activity. The strength of this connectivity can be understood using mathematical models that allow for the study of neuronal connectivity dynamics. These models also allow researchers to develop hypotheses on the candidate mechanisms of action of different types of anesthesia. This review highlights the theoretical background associated with the study of the mechanisms of action of anesthetics. We propose a candidate framework that describes how anesthetics act on the brain and consciousness in general.

Weak Task Synchronization of Default Mode Network in Task Based Paradigms

The brains Default mode network (DMN) is generally characterized by brain areas that gets deactivated upon the presentation of a wide variety of externally focused, attention demanding tasks. These areas also exhibit significant intra-DMN functional connectivity and significant negative functional connectivity with other brain areas, especially with attention networks, in both resting state and task conditions. Therefore, the DMN has been hypothesized to be involved in internally directed cognitive activities such as autobiographical recall of the past, future planning and mind wandering. Recent research has discovered the role of bottom-up attention in modulating the behaviour of DMN. We hypothesize that the de-engagement of the DMN regions upon the presentation of an externally-focused attention-demanding stimulus may not be strictly stimulus locked and may exhibit significant trial-to-trial as well as subject-to-subject variability. Due to the involvement of frontoparietal control network in modulating the anticorrelations between DMN and dorsal attention network (DAN), we expect the DMN regions to have lower inter-trial and inter-subject synchronization in their fMRI BOLD responses as compared to the bottom-up early-sensory task-positive regions. To test this hypothesis, we designed new statistical methods called Inter Trial Temporal Synchronization Analysis (IT-TSA) and Inter Subject TSA (IS-TSA) to analyse variability across trials and subjects respectively. We analysed four publicly available datasets (total 223 subjects) across seven tasks related to different cognitive modalities and found out that there is significantly low stimulus-locked synchronization across trials and subjects in the DMN regions as compared to early sensory task positive regions. Our study challenges the understanding of DMN as a strictly task-negative region and supports the recent findings that DMN acts as an active component associated with intrinsic processing which deactivates differentially and non-linearly across trials and subjects in the presence of extrinsic processes.

Causal dynamics and information flow in parietal-temporal-hippocampal circuits during mental arithmetic revealed by high-temporal resolution human intracranial EEG

Mental arithmetic involves distributed brain regions spanning parietal and temporal cortices, yet little is known about the neural dynamics of causal functional circuits that link them. Here we use high-temporal resolution (1000 Hz sampling rate) intracranial EEG from 35 participants, 362 electrodes, and 1727 electrode pairs, to investigate dynamic causal circuits linking posterior parietal cortex (PPC) with ventral temporal-occipital cortex and hippocampal regions which constitute the perceptual, visuospatial, and mnemonic building blocks of mental arithmetic. Nonlinear phase transfer entropy measures capable of capturing information flow identified dorsal PPC as a causal inflow hub during mental arithmetic, with strong causal influences from fusiform gyrus in ventral temporal-occipital cortex as well as the hippocampus. Net causal inflow into dorsal PPC was significantly higher during mental arithmetic, compared to both resting-state and verbal memory recall. Our analysis also revealed functional heterogeneity of casual signaling in the PPC, with greater net causal inflow into the dorsal PCC, compared to ventral PPC. Additionally, the strength of causal influences was significantly higher on dorsal, compared to ventral, PPC from the hippocampus, and ventral temporal-occipital cortex during mental arithmetic, when compared to both resting-state and verbal memory recall. Our findings provide novel insights into dynamic neural circuits and hubs underlying numerical problem solving and reveal neurophysiological circuit mechanisms by which both the visual number form processing and declarative memory systems dynamically engage the PPC during mental arithmetic.

Cognitive Implications of Correlated Structural Network Changes in Schizophrenia

Background

Schizophrenia is a brain disorder characterized by diffuse, diverse, and wide-spread changes in gray matter volume (GM) and white matter structure (fractional anisotropy, FA), as well as cognitive impairments that greatly impact an individual’s quality of life. While the relationship of each of these image modalities and their links to schizophrenia status and cognitive impairment has been investigated separately, a multimodal fusion via parallel independent component analysis (pICA) affords the opportunity to explore the relationships between the changes in GM and FA, and the implications these network changes have on cognitive performance.

Methods

Images from 73 subjects with schizophrenia (SZ) and 82 healthy controls (HC) were drawn from an existing dataset. We investigated 12 components from each feature (FA and GM). Loading coefficients from the images were used to identify pairs of features that were significantly correlated and showed significant group differences between HC and SZ. MANCOVA analysis uncovered the relationships the identified spatial maps had with age, gender, and a global cognitive performance score.

Results

Three component pairs showed significant group differences (HC > SZ) in both gray and white matter measurements. Two of the component pairs identified networks of gray matter that drove significant relationships with cognition (HC > SZ) after accounting for age and gender. The gray and white matter structural networks identified in these three component pairs pull broadly from many regions, including the right and left thalamus, lateral occipital cortex, multiple regions of the middle temporal gyrus, precuneus cortex, postcentral gyrus, cingulate gyrus/cingulum, lingual gyrus, and brain stem.

Conclusion

The results of this multimodal analysis adds to our understanding of how the relationship between GM, FA, and cognition differs between HC and SZ by highlighting the correlated intermodal covariance of these structural networks and their differential relationships with cognitive performance. Previous unimodal research has found similar areas of GM and FA differences between these groups, and the cognitive deficits associated with SZ have been well documented. This study allowed us to evaluate the intercorrelated covariance of these structural networks and how these networks are involved the differences in cognitive performance between HC and SZ.

OUP accepted manuscript

One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks—the dorsal attention and executive control network—is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22–36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.

Dynamic Subcortical Modulators of Human Default Mode Network Function

The brain’s “default mode network” (DMN) enables flexible switching between internally and externally focused cognition. Precisely how this modulation occurs is not well understood, although it may involve key subcortical mechanisms, including hypothesized influences from the basal forebrain (BF) and mediodorsal thalamus (MD). Here, we used ultra-high field (7 T) functional magnetic resonance imaging to examine the involvement of the BF and MD across states of task-induced DMN activity modulation. Specifically, we mapped DMN activity suppression (“deactivation”) when participants transitioned between rest and externally focused task performance, as well as DMN activity engagement (“activation”) when task performance was internally (i.e., self) focused. Consistent with recent rodent studies, the BF showed overall activity suppression with DMN cortical regions when comparing the rest to external task conditions. Further analyses, including dynamic causal modeling, confirmed that the BF drove changes in DMN cortical activity during these rest-to-task transitions. The MD, by comparison, was specifically engaged during internally focused cognition and demonstrated a broad excitatory influence on DMN cortical activation. These results provide the first direct evidence in humans of distinct BF and thalamic circuit influences on the control of DMN function and suggest novel mechanistic avenues for ongoing translational research.

Fluid intelligence and naturalistic task impairments after focal brain lesions

Classical executive tasks, such as Wisconsin card-sorting and verbal fluency, are widely used as tests of frontal lobe control functions. Since the pioneering work of Shallice and Burgess (1991), it has been known that complex, naturalistic tasks can capture deficits that are missed in these classical tests. Matching this finding, deficits in several classical tasks are predicted by loss of fluid intelligence, linked to damage in a specific cortical "multiple-demand" (MD) network, while deficits in a more naturalistic task are not. To expand on these previous results, we examined the effect of focal brain lesions on three new tests-a modification of the previously-used Hotel task, a new test of task switching after extended delays, and a test of decision-making in imagined real-life scenarios. As potential predictors of impairment we measured volume of damage to a priori MD and default mode (DMN) networks, as well as cortical damage outside these networks. Deficits in the three new tasks were substantial, but were not explained by loss of fluid intelligence, or by volume of damage to either MD or DMN networks. Instead, deficits were associated with diverse lesions, and not strongly correlated with one another. The results confirm that naturalistic tasks capture cognitive deficits beyond those measured by fluid intelligence. We suggest, however, that these deficits may not arise from specific control operations required by complex behaviour. Instead, like everyday activities, complex tasks combine a rich variety of interacting cognitive components, bringing many opportunities for processing to be disturbed.