Dorsal Attention Network Research Articles

Resting-state MRI functional connectivity as a neural correlate of multidomain lifestyle adherence in older adults at risk for Alzheimer’s disease

Prior research has demonstrated the importance of a healthy lifestyle to protect brain health and diminish dementia risk in later life. While a multidomain lifestyle provides an ecological perspective to voluntary engagement, its association with brain health is still under-investigated. Therefore, understanding the neural mechanisms underlying multidomain lifestyle engagement, particularly in older adults at risk for Alzheimer’s disease (AD), gives valuable insights into providing lifestyle advice and intervention for those in need. The current study included 139 healthy older adults with familial risk for AD from the Prevent-AD longitudinal aging cohort. Self-reported exercise engagement, cognitive activity engagement, healthy diet adherence, and social activity engagement were included to examine potential phenotypes of an individual’s lifestyle adherence. Two adherence profiles were discovered using data-driven clustering methodology [i.e., Adherence to healthy lifestyle (AL) group and Non-adherence to healthy lifestyle group]. Resting-state functional connectivity matrices and grey matter brain features obtained from magnetic resonance imaging were used to classify the two groups using a support vector machine (SVM). The SVM classifier was 75% accurate in separating groups. The features that show consistently high importance to the classification model were functional connectivity mainly between nodes located in different prior-defined functional networks. Most nodes were located in the default mode network, dorsal attention network, and visual network. Our results provide preliminary evidence of neurobiological characteristics underlying multidomain healthy lifestyle choices.

Dynamic brain states in spatial neglect after stroke.

Previous studies indicated that spatial neglect is characterized by widespread alteration of resting-state functional connectivity and changes in the functional topology of large-scale brain systems. However, whether such network modulations exhibit temporal fluctuations related to spatial neglect is still largely unknown. This study investigated the association between brain states and spatial neglect after the onset of focal brain lesions. A cohort of right-hemisphere stroke patients (n = 20) underwent neuropsychological assessment of neglect as well as structural and resting-state functional MRI sessions within 2 weeks from stroke onset. Brain states were identified using dynamic functional connectivity as estimated by the sliding window approach followed by clustering of seven resting state networks. The networks included visual, dorsal attention, sensorimotor, cingulo-opercular, language, fronto-parietal, and default mode networks. The analyses on the whole cohort of patients, i.e., with and without neglect, identified two distinct brain states characterized by different degrees of brain modularity and system segregation. Compared to non-neglect patients, neglect subjects spent more time in less modular and segregated state characterized by weak intra-network coupling and sparse inter-network interactions. By contrast, patients without neglect dwelt mainly in more modular and segregated states, which displayed robust intra-network connectivity and anti-correlations among task-positive and task-negative systems. Notably, correlational analyses indicated that patients exhibiting more severe neglect spent more time and dwelt more often in the state featuring low brain modularity and system segregation and vice versa. Furthermore, separate analyses on neglect vs. non-neglect patients yielded two distinct brain states for each sub-cohort. A state featuring widespread strong connections within and between networks and low modularity and system segregation was detected only in the neglect group. Such a connectivity profile blurred the distinction among functional systems. Finally, a state exhibiting a clear separation among modules with strong positive intra-network and negative inter-network connectivity was found only in the non-neglect group. Overall, our results indicate that stroke yielding spatial attention deficits affects the time-varying properties of functional interactions among large-scale networks. These findings provide further insights into the pathophysiology of spatial neglect and its treatment.

Widespread Intra- and Inter-Network Dysconnectivity among Large-Scale Resting State Networks in Schizophrenia.

Schizophrenia is characterized by the distributed dysconnectivity of resting-state multiple brain networks. However, the abnormalities of intra- and inter-network functional connectivity (FC) in schizophrenia and its relationship to symptoms remain unknown. The aim of the present study is to compare the intra- and inter-connectivity of the intrinsic networks between a large sample of patients with schizophrenia and healthy controls. Using the Region of interest (ROI) to ROI FC analyses, the intra- and inter-network FC of the eight resting state networks [default mode network (DMN); salience network (SN); frontoparietal network (FPN); dorsal attention network (DAN); language network (LN); visual network (VN); sensorimotor network (SMN); and cerebellar network (CN)] were investigated in 196 schizophrenia and 169-healthy controls. Compared to the healthy control group, the schizophrenia group exhibited increased intra-network FC in the DMN and decreased intra-network FC in the CN. Additionally, the schizophrenia group showed the decreased inter-network FC mainly involved the SN-DMN, SN-LN and SN-CN while increased inter-network FC in the SN-SMN and SN-DAN (p < 0.05, FDR-corrected). Our study suggests widespread intra- and inter-network dysconnectivity among large-scale RSNs in schizophrenia, mainly involving the DMN, SN and SMN, which may further contribute to the dysconnectivity hypothesis of schizophrenia.

The Cerebellum’s Orchestra: Understanding the Functional Connectivity of Its Lobes and Deep Nuclei in Coordination and Integration of Brain Networks

The cerebellum, a crucial brain region, significantly contributes to various brain functions. Although it occupies a small portion of the brain, it houses nearly half of the neurons in the nervous system. Previously thought to be solely involved in motor activities, the cerebellum has since been found to play a role in cognitive, sensory, and associative functions. To further elucidate the intricate neurophysiological characteristics of the cerebellum, we investigated the functional connectivity of cerebellar lobules and deep nuclei with 8 major functional brain networks in 198 healthy subjects. Our findings revealed both similarities and differences in the functional connectivity of key cerebellar lobules and nuclei. Despite robust functional connectivity among these lobules, our results demonstrated that they exhibit heterogeneous functional integration with different functional networks. For instance, lobules 4, 5, 6, and 8 were linked to sensorimotor networks, while lobules 1, 2, and 7 were associated with higher-order, non-motor, and complex functional networks. Notably, our study uncovered a lack of functional connectivity in lobule 3, strong connections between lobules 4 and 5 with the default mode networks, and connections between lobules 6 and 8 with the salience, dorsal attention, and visual networks. Additionally, we found that cerebellar nuclei, particularly the dentate cerebellar nuclei, were connected to sensorimotor, salience, language, and default-mode networks. This study provides valuable insights into the diverse functional roles of the cerebellum in cognitive processing.

Disrupted resting-sate brain network dynamics in children born extremely preterm.

The developing brain has to adapt to environmental and intrinsic insults after extremely preterm (EPT) birth. Ongoing maturational processes maximize their fit to the environment and this can provide a substrate for neurodevelopmental failures. Resting-state functional magnetic resonance imaging was used to scan 33 children born EPT, at < 27weeks of gestational age, and 26 full-term controls at 10years of age. We studied the capability of a brain area to propagate neural information (intrinsic ignition) and its variability across time (node-metastability). This framework was computed for the dorsal attention network (DAN), frontoparietal, default-mode network (DMN), and the salience, limbic, visual, and somatosensory networks. The EPT group showed reduced intrinsic ignition in the DMN and DAN, compared with the controls, and reduced node-metastability in the DMN, DAN, and salience networks. Intrinsic ignition and node-metastability values correlated with cognitive performance at 12years of age in both groups, but only survived in the term group after adjustment. Preterm birth disturbed the signatures of functional brain organization at rest in 3 core high-order networks: DMN, salience, and DAN. Identifying vulnerable resting-state networks after EPT birth may lead to interventions that aim to rebalance brain function.

Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis.

Epilepsy is considered as a neural network disorder. Seizure activity in epilepsy may disturb brain networks and damage brain functions. We propose using resting-state functional magnetic resonance imaging (rs-fMRI) data to characterize connectivity patterns in drug-resistant epilepsy. This study enrolled 47 participants, including 28 with drug-resistant epilepsy and 19 healthy controls. Functional and effective connectivity was employed to assess drug-resistant epilepsy patients within resting state networks. The resting state functional connectivity (FC) analysis was performed to assess connectivity between each patient and healthy controls within the default mode network (DMN) and the dorsal attention network (DAN). In addition, dynamic causal modeling was used to compute effective connectivity (EC). Finally, a statistical analysis was performed to evaluate our findings. The FC analysis revealed significant connectivity changes in patients giving 64.3% (18/28) and 78.6% (22/28) for DMN and DAN, respectively. Statistical analysis of FC was significant between the medial prefrontal cortex, posterior cingulate cortex, and bilateral inferior parietal cortex for DMN. For DAN, it was significant between the left and the right intraparietal sulcus and the frontal eye field. For the DMN, the patient group showed significant EC connectivity in the right inferior parietal cortex and the medial prefrontal cortex for the DMN. There was also bilateral connectivity between the medial prefrontal cortex and the posterior cingulate cortex, as well as between the left and right inferior parietal cortex. For DAN, patients showed significant connectivity in the right frontal eye field and the right intraparietal sulcus. Bilateral connectivity was also found between the left frontal eye field and the left intraparietal sulcus, as well as between the right frontal eye field and the right intraparietal sulcus. The statistical analysis of the EC revealed a significant result in the medial prefrontal cortex and the right intraparietal cortex for the DMN. The DAN was found significant in the left frontal eye field, as well as the left and right intraparietal sulcus. Our results provide preliminary evidence to support that the combination of functional and effective connectivity analysis of rs-fMRI can aid in diagnosing epilepsy in the DMN and DAN networks.

Oscillatory dynamics serving visual selective attention during a Simon task.

Selective attention is an important component of cognitive control and is essential for day-to-day functioning. The Simon task is a common test of visual selective attention that has been widely used to probe response selection, inhibition and cognitive control. However, to date, there is a dearth of literature that has focused on the oscillatory dynamics serving task performance in the selective attention component of this task. In this study, 32 healthy adults (mean age: 33.09 years, SD: 7.27 years) successfully completed a modified version of the Simon task during magnetoencephalography. All magnetoencephalographic data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and peak task-related neural activity was extracted to examine the temporal dynamics. Across both congruent and Simon conditions, our results indicated robust decreases in alpha (8-12 Hz) activity in the bilateral occipital regions and cuneus during task performance, while increases in theta (3-6 Hz) oscillatory activity were detected in regions of the dorsal frontoparietal attention network, including the dorsolateral prefrontal cortex, frontal eye fields and insula. Lastly, whole-brain condition-wise analyses showed Simon interference effects in the theta range in the superior parietal region and the alpha range in the posterior cingulate and inferior frontal cortices. These findings provide network-specific insights into the oscillatory dynamics serving visual selective attention.

Visuo-spatial attention and semantic memory competition in the parietal cortex

Neuroimaging studies associate specific functional roles to distinct brain regions investigating separate cognitive processes using dedicated tasks. For example, using both correlative (i.e., fMRI) and causal (i.e., TMS) approaches it has been shown the involvement of intra-parietal sulcus (IPS), as part of the dorsal attention network, in spatial attentional tasks as well as the importance of the angular gyrus (AG), as part of the default mode network, during the selection of relevant information in semantic memory. Nonetheless, in our daily life attention and semantic memory are rarely needed in isolation. In the present TMS study we investigate how the brain combines attentional and semantic memory demands in a single task. Results showed that, compared to a pseudo-TMS, stimulation of IPS, but not AG, affects behavioral performance, thus suggesting its preponderant role in such a combined task. Moreover, the lack of difference between the effect of IPS and AG stimulations seems to suggest that the two regions may be coactivated or that a third-party source might indirectly mediate the interaction between the two networks.

Brain Connectivity-Based Prediction of Combining Remote Semantic Associates for Creative Thinking

ABSTRACT Associative thinking plays a major role in creativity, as it involves the ability to link distant concepts. Yet, the neural mechanisms allowing to combine distant associates in creative thinking tasks remain poorly understood. We investigated the whole-brain functional connectivity patterns related to combining remote associations for creative thinking. Using a connectome predictive modeling approach, we examined whole-brain functional connectivity patterns related to connecting close and distant remote associates in the Combination Association Task (CAT). Brain connectivity networks predicting CAT performance showed contributions from brain functional connectivity mostly related to the Default Mode Network, likely related to associative processes required in all trials of the task. Besides, the functional connectivity pattern of associative remoteness linked to CAT trials also largely involved the Executive Control Network, Dorsal Attention Network and Somatomotor networks, suggesting that more controlled processes played an important role in trials with higher associative remoteness. Critically, the functional connectivity patterns related to higher creative demands of the task share similarities with functional connectivity patterns previously found to predict divergent thinking. Thus, our work potentially offers insights into neural mechanisms that play a role in both convergent and divergent remote thinking.

Establishing a predictive model for unsafe driving in the elderly using artificial intelligence and elucidating the neural basis

In Japan, there is a social issue associated with accidents caused by elderly drivers. Although mandatory cognitive function tests when renewing driving lessons screen for dementia, they cannot account for risk of unsafe driving due to the natural ageing process. In his work, Associate Professor Bun Yamagata, Department of Neuropsychiatry, Keio University School of Medicine, has been using imaging techniques such as MRI and NIRS and combining the data obtained with neuropsychological evaluations and artificial intelligence (AI) technology to better understand brain function and structural abnormalities within the brain. In partnership with ergonomics and mechanical engineering specialist Associate Professor Motoki Shino, from The University of Tokyo, he is conducting an innovative study on driving behaviours and brain atrophy patterns. By combining engineering and neuropsychology techniques the researchers will develop algorithms that predict the risk of dangerous driving behaviours in elderly drivers. In research exploring the relationship between the structural connectivity of white matter in the brain and the driving ability of healthy older people Yamagata found that changes in the white matter within the dorsal attention network may contribute to a higher risk of unsafe driving behaviours in healthy elderly people. The researchers have used machine learning to develop a model that predicts the risk of unsafe driving in healthy older people with high accuracy from neuropsychological tests and practical visual acuity.

Reversible large-scale network disruption correlates with neurocognitive improvement in HIV-associated minor neurocognitive disorder with combined anti-retroviral therapy intensification: a prospective longitudinal resting-state functional magnetic resonance imaging study.

HIV-associated neurocognitive disorder (HAND) affects multiple cognitive domains and currently, the neuropsychological testing is the gold standard to identify these deficits. The aim of this longitudinal 12-month pilot study is to determine the effect of intensified combination antiretroviral therapy (cART) on rs-fMRI in virally suppressed (both in CSF and blood) patients with active HAND (those who have progressive neurocognitive impairment) and correlated with neurocognitive function tests. In this pilot study, we have evaluated sixteen patients with active HAND with viral suppression in both blood and CSF to study the effect of cART on functional connectivity. Participants underwent rs-fMRI at the baseline (time point-1 (TP-1) and 12-month visits (time point-2 (TP-2)). Connectivity in the five major networks was measured at TP-1 and TP-2 using the seed-based approach. All the participants underwent a five-domain neuropsychological battery at TP-1 and TP-2. Neurocognitive scores (NC) as well as blood and CSF markers were correlated with functional connectivity (FC). There was a significant increase in the FC between the two time points within the executive, salience, default mode, dorsal attention, and visual networks at voxel level threshold of p < 0.001 and cluster level threshold of p < 0.05 and corrected for false detection rate (FDR). The neurocognitive scores were positively correlated with all the networks at similar cluster and voxel level thresholds. These results indicate that rs-fMRI can be potentially used as one of the biomarkers for treatment efficacy in HAND.

Associations of bullying perpetration and peer victimization subtypes with preadolescent’s suicidality, non-suicidal self-injury, neurocognition, and brain development

BackgroundAlthough both peer victimization and bullying perpetration negatively impact preadolescents’ development, the underlying neurobiological mechanism of this adverse relationship remains unclear. Besides, the specific psycho-cognitive patterns of different bullying subtypes also need further exploration, warranting large-scale studies on both general bullying and specific bullying subtypes.MethodsWe adopted a retrospective methodology by utilizing the data from the Adolescent Brain and Cognitive DevelopmentSM Study (ABCD Study®) cohort collected between July 2018 and January 2021. Participants were preadolescents aged from 10 to 13 years. The main purpose of our study is to examine the associations of general and specific peer victimization/bullying perpetration with preadolescents’ (1) suicidality and non-suicidal self-injury; (2) executive function and memory, including attention inhibition, processing speed, emotion working memory, and episodic memory; (3) brain structure abnormalities; and (4) brain network disturbances. Age, sex, race/ethnicity, body mass index (BMI), socioeconomic status (SES), and data acquisition site were included as covariates.ResultsA total of 5819 participants aged from 10 to 13 years were included in this study. Higher risks of suicide ideation, suicide attempt, and non-suicidal self-injury were found to be associated with both bullying perpetration/peer victimization and their subtypes (i.e., overt, relational, and reputational). Meanwhile, poor episodic memory was shown to be associated with general victimization. As for perpetration, across all four tasks, significant positive associations of relational perpetration with executive function and episodic memory consistently manifested, yet opposite patterns were shown in overt perpetration. Notably, distinct psycho-cognitive patterns were shown among different subtypes. Additionally, victimization was associated with structural brain abnormalities in the bilateral paracentral and posterior cingulate cortex. Furthermore, victimization was associated with brain network disturbances between default mode network and dorsal attention network, between default mode network and fronto-parietal network, and ventral attention network related connectivities, including default mode network, dorsal attention network, cingulo-opercular network, cingulo-parietal network, and sensorimotor hand network. Perpetration was also associated with brain network disturbances between the attention network and the sensorimotor hand network.ConclusionsOur findings offered new evidence for the literature landscape by emphasizing the associations of bullying experiences with preadolescents’ clinical characteristics and cognitive functions, while distinctive psycho-cognitive patterns were shown among different subtypes. Additionally, there is evidence that these associations are related to neurocognitive brain networks involved in attention control and episodic retrieval. Given our findings, future interventions targeting ameliorating the deleterious effect of bullying experiences on preadolescents should consider their subtypes and utilize an ecosystemic approach involving all responsible parties.

Fast changes in default and control network activity underlying intraindividual response time variability in childhood: Does age and sex matter?

Intraindividual response time variability (RTV) is considered as a general marker of neurological health. In adults, the central executive and salience networks (task-positive networks, TPN) and the default mode network (DMN) are critical for RTV. Given that RTV decreases with growing up, and that boys are likely somewhat behind girls with respect to the network development, we aimed to clarify age and sex effects. Electroencephalogram was recorded during Stroop-like test performance in 124 typically developing children aged 5-12 years. Network fluctuations were calculated as changes of current source density (CSD) in regions of interest (ROIs) from pretest to 1-s test interval. In boys, TPN activation (CSD increase in ROIs included in the TPN) was associated with lower RTV, suggesting a greater engagement of attentional control. In children younger than 9.5 years, higher response stability was associated with the predominance of TPN activation over DMN activation (CSD increase in ROIs included in the TPN>that in the DMN); this predominance increased with age, suggesting that variability among younger children may be due to network immaturity. These findings suggest that the TPN and DMN may play different roles within the network mechanisms of RTV in boys and girls and at different developmental stages.

358. Default Mode and Dorsal Attention Network Connectivity as a Predictor and Mechanism of Clinical Improvement During Cognitive Behavioral Therapy in a Transdiagnostic Sample

358. Default Mode and Dorsal Attention Network Connectivity as a Predictor and Mechanism of Clinical Improvement During Cognitive Behavioral Therapy in a Transdiagnostic Sample

Brain-Based Predictions of Psychiatric Illness–Linked Behaviors Across the Sexes

BackgroundIndividual differences in functional brain connectivity can be used to predict both the presence of psychiatric illness and variability in associated behaviors. However, despite evidence for sex differences in functional network connectivity and in the prevalence, presentation, and trajectory of psychiatric illnesses, the extent to which disorder-relevant aspects of network connectivity are shared or unique across the sexes remains to be determined. MethodsIn this work, we used predictive modeling approaches to evaluate whether shared or unique functional connectivity correlates underlie the expression of psychiatric illness–linked behaviors in males and females in data from the Adolescent Brain Cognitive Development Study (N = 5260; 2571 females). ResultsWe demonstrate that functional connectivity profiles predict individual differences in externalizing behaviors in males and females but predict internalizing behaviors only in females. Furthermore, models trained to predict externalizing behaviors in males generalize to predict internalizing behaviors in females, and models trained to predict internalizing behaviors in females generalize to predict externalizing behaviors in males. Finally, the neurobiological correlates of many behaviors are largely shared within and across sexes: functional connections within and between heteromodal association networks, including default, limbic, control, and dorsal attention networks, are associated with internalizing and externalizing behaviors. ConclusionsTaken together, these findings suggest that shared neurobiological patterns may manifest as distinct behaviors across the sexes. Based on these results, we recommend that both clinicians and researchers carefully consider how sex may influence the presentation of psychiatric illnesses, especially those along the internalizing-externalizing spectrum.

A Residual Marker of Cognitive Reserve Is Associated with Resting-State Intrinsic Functional Connectivity Along the Alzheimer's Disease Continuum.

Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored. To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN). Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-β)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models. CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+. Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.

Excess BMI in early adolescence adversely impacts maturating functional circuits supporting high-level cognition and their structural correlates.

Adverse effects of excess BMI (affecting 1 in 5 children in the US) on brain circuits during neurodevelopmentally vulnerable periods are incompletely understood. This study investigated BMI-related alterations in maturating functional networks and their underlying brain structures, and high-level cognition in early adolescence. Cross-sectional resting-state fMRI, structural sMRI, neurocognitive task scores, and BMI from 4922 youth [median (IQR) age = 120.0 (13.0) months, 2572 females (52.25%)] from the Adolescent Brain Cognitive Development (ABCD) cohort were analyzed. Comprehensive topological and morphometric network properties were estimated from fMRI and sMRI, respectively. Cross-validated linear regression models assessed correlations with BMI. Results were reproduced across multiple fMRI datasets. Almost 30% of youth had excess BMI, including 736 (15.0%) with overweight and 672 (13.7%) with obesity, and statistically more Black and Hispanic compared to white, Asian and non-Hispanic youth (p < 0.01). Those with obesity or overweight were less physically active, slept less than recommended, snored more frequently, and spent more time using an electronic device (p < 0.01). They also had lower topological efficiency, resilience, connectivity, connectedness and clustering in Default-Mode, dorsal attention, salience, control, limbic, and reward networks (p ≤ 0.04, Cohen's d: 0.07-0.39). Lower cortico-thalamic efficiency and connectivity were estimated only in youth with obesity (p < 0.01, Cohen's d: 0.09-0.19). Both groups had lower cortical thickness, volume and white matter intensity in these networks' constituent structures, particularly anterior cingulate, entorhinal, prefrontal, and lateral occipital cortices (p < 0.01, Cohen's d: 0.12-0.30), which also mediated inverse relationships between BMI and regional functional topologies. Youth with obesity or overweight had lower scores in a task measuring fluid reasoning - a core aspect of cognitive function, which were partially correlated with topological changes (p ≤ 0.04). Excess BMI in early adolescence may be associated with profound aberrant topological alterations in maturating functional circuits and underdeveloped brain structures that adversely impact core aspects of cognitive function.

451 Posterior Cingulate Theta Power as a Novel Biomarker of Mood

INTRODUCTION: One third of patients with major depressive disorder (MDD) are refractory to standard therapies. Progress in therapeutic neuromodulation for depression has been challenging because of the widespread, network basis of mood and lack of neurophysiologic biomarkers. Neuroimaging studies of depression demonstrate increased connectivity within the default mode network (DMN), which subserves internal processes such as self-reflection, mind wandering, and memory. Invasive electrophysiology in the resting state has demonstrated that DMN connectivity corresponds to correlations in theta-band power. DMN activity is anti-correlated with the dorsal attention network (DAN) which, in contrast, subserves externally oriented cognition (i.e., top-down attention), and demonstrates alpha-specific resting-state correlations. METHODS: We used hourly, self-reported measures of mood and video facial affect recognition to estimate mood valence in six epilepsy patients undergoing invasive stereotactic electroencephalography monitoring. We analyzed power spectra and functional connectivity (band-limited power correlations) in epochs corresponding to mood estimates. Patients without substantial inpatient mood variability (n=3) were excluded. RESULTS: Depressed mood was correlated with increased theta power. This was most significant in electrodes within posterior cingulate cortex (DMN region; r = -0.58; p = 0.0007). Conversely, alpha power was increased during elevated mood, most significantly in the intraparietal sulcus (DAN region; r = 0.55, p = 0.0013). Theta connectivity was correlated with depressed mood (r = -0.53, p = 0.003) whereas alpha connectivity was correlated with elevated mood (r = 0.56, p = 0.002). CONCLUSIONS: Our results recapitulate the frequency specificity of resting-state physiology and encourage a network-based perspective of depression neurophysiology. Theta and alpha power within DMN and DAN networks, respectively, represent important biomarkers of mood and may guide neuromodulatory therapies. Posterior cingulate/precuneus cortex is a major DMN hub and should be sampled in future studies of neural correlates of mood.

377 Evaluating Large-Scale Brain Networks Patients With Brain Tumors: A Machine Learning Analysis of 100 Consecutive Patients

INTRODUCTION: Large-scale brain networks and higher cognitive functions are frequently altered in neuro-oncology patients, but comprehensive non-invasive brain mapping is difficult to achieve in the clinical setting. METHODS: We retrospectively included patients who underwent surgery for brain tumor resection at our Institution. Preoperative MRI with T1-weighted and DTI sequences were uploaded into the Quicktome platform. We categorized the integrity of nine large-scale brain networks: language, sensorimotor, visual, ventral attention, central executive, default mode, dorsal attention, salience and limbic. Networks were correlated with preoperative clinical data. RESULTS: One-hundred patients were included in the study. The most affected network was the central executive network (49%), followed by the default mode network (42%) and dorsal attention network (33%). Patients with preoperative deficits showed a significantly higher number of altered networks before the surgery (3.44 vs 2.16, p &lt; .001), compared to patients without deficits. Furthermore, we found that patients without neurologic deficits had an average 2.16 networks affected and 1.56 networks at risk, with most of them being related to non-traditional eloquent areas (p = .014). CONCLUSIONS: Our results show that large-scale brain networks are frequently affected in patients with brain tumors, even when presenting without evident neurologic deficits. In our study, the most commonly affected brain networks were related to non-traditional eloquent areas. Integrating non-invasive brain mapping machine-learning techniques into the clinical setting may help elucidate how to preserve higher-order cognitive functions associated with those networks.

Rethinking recovery in adolescent concussions: Network-level functional connectivity alterations associated with motor deficits.

Adolescents who are clinically recovered from concussion continue to show subtle motor impairment on neurophysiological and behavioral measures. However, there is limited information on brain-behavior relationships of persistent motor impairment following clinical recovery from concussion. We examined the relationship between subtle motor performance and functional connectivity of the brain in adolescents with a history of concussion, status post-symptom resolution, and subjective return to baseline. Participants included 27 adolescents who were clinically recovered from concussion and 29 never-concussed, typically developing controls (10-17 years); all participants were examined using the Physical and Neurologic Examination of Subtle Signs (PANESS). Functional connectivity between the default mode network (DMN) or dorsal attention network (DAN) and regions of interest within the motor network was assessed using resting-state functional magnetic resonance imaging (rsfMRI). Compared to controls, adolescents clinically recovered from concussion showed greater subtle motor deficits as evaluated by the PANESS and increased connectivity between the DMN and left lateral premotor cortex. DMN to left lateral premotor cortex connectivity was significantly correlated with the total PANESS score, with more atypical connectivity associated with more motor abnormalities. This suggests that altered functional connectivity of the brain may underlie subtle motor deficits in adolescents who have clinically recovered from concussion. More investigation is required to understand the persistence and longer-term clinical relevance of altered functional connectivity and associated subtle motor deficits to inform whether functional connectivity may serve as an important biomarker related to longer-term outcomes after clinical recovery from concussion.