A growth chart of brain function from infancy to adolescence based on EEG.

BACKGROUND: In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. METHODS: We developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15-min segment of 18-channel EEG recorded during light sleep (N1 and N2 states). FINDINGS: The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028). INTERPRETATION: A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts. FUNDING: This research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.

Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures.

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

Optimization of time series features to estimate brain age in children from electroencephalography.

Functional brain age measures in children, derived from the electroencephalogram (EEG), offer direct and objective measures in assessing neurodevelopmental status. Here we explored the effectiveness of 32 preselected 'handcrafted' EEG features in predicting brain age in children. These features were benchmarked against a large library of highly comparative multivariate time series features (>7000 features). Results showed that age predictors based on handcrafted EEG features consistently outperformed a generic set of time series features. These findings suggest that optimization of brain age estimation in children benefits from careful preselection of EEG features that are related to age and neurodevelopmental trajectory. This approach shows potential for clinical translation in the future.Clinical Relevance-Handcrafted EEG features provide an accurate functional neurodevelopmental biomarker that tracks brain function maturity in children.

Mechanisms underlying pathological cortical bursts during metabolic depletion.

Cortical activity depends upon a continuous supply of oxygen and other metabolic resources. Perinatal disruption of oxygen availability is a common clinical scenario in neonatal intensive care units, and a leading cause of lifelong disability. Pathological patterns of brain activity including burst suppression and seizures are a hallmark of the recovery period, yet the mechanisms by which these patterns arise remain poorly understood. Here, we use computational modeling of coupled metabolic-neuronal activity to explore the mechanisms by which oxygen depletion generates pathological brain activity. We find that restricting oxygen supply drives transitions from normal activity to several pathological activity patterns (isoelectric, burst suppression, and seizures), depending on the potassium supply. Trajectories through parameter space track key features of clinical electrophysiology recordings and reveal how infants with good recovery outcomes track toward normal parameter values, whereas the parameter values for infants with poor outcomes dwell around the pathological values. These findings open avenues for studying and monitoring the metabolically challenged infant brain, and deepen our understanding of the link between neuronal and metabolic activity.

Modulations of right hemisphere connectivity in young children relates to the perception of spoken words.

The early school years shape a young brain's capability to comprehend and contextualize words within milliseconds of exposure. Parsing word sounds (phonological interpretation) and word recognition (enabling semantic interpretation) are integral to this process. Yet little is known about the causal mechanisms of cortical activity during these early developmental stages. In this study, we aimed to explore these causal mechanisms via dynamic causal modelling of event-related potentials (ERPs) acquired from 30 typically developing children (ages 6-8 years) as they completed a spoken word-picture matching task. Source reconstruction of high-density electroencephalography (128 channels) was used to ascertain differences in whole-brain cortical activity during semantically "congruent" and "incongruent" conditions. Source activations analyzed during the N400 ERP window identified significant regions-of-interest (pFWE<.05) localized primarily in the right hemisphere when contrasting congruent and incongruent word-picture stimuli. Dynamic causal models (DCMs) were tested on source activations in the fusiform gyrus (rFusi), inferior parietal lobule (rIPL), inferior temporal gyrus (rITG) and superior frontal gyrus (rSFG). DCM results indicated that a fully connected bidirectional model with self-(inhibiting) connections over rFusi, rIPL and rSFG provided the highest model evidence, based on exceedance probabilities derived from Bayesian statistical inferences. Connectivity parameters of rITG and rSFG regions from the winning DCM were negatively correlated with behavioural measures of receptive vocabulary and phonological memory (pFDR<.05), such that lower scores on these assessments corresponded with increased connectivity between temporal pole and anterior frontal regions. The findings suggest that children with lower language processing skills required increased recruitment of right hemisphere frontal/temporal areas during task performance.

Bedside tracking of functional autonomic age in preterm infants.

BACKGROUND: Preterm birth predisposes infants to adverse outcomes that, without early intervention, impacts their long-term health. To assist bedside monitoring, we developed a tool to track the autonomic maturation of the preterm by assessing heart rate variability (HRV) changes during intensive care. METHODS: Electrocardiogram (ECG) recordings were longitudinally recorded in 67 infants (26-38 weeks postmenstrual age (PMA)). Supervised machine learning was used to generate a functional autonomic age (FAA), by combining 50 computed HRV features from successive 5-minute ECG epochs (median of 23 epochs per infant). Performance of the FAA was assessed by correlation to PMA, clinical outcomes and the infant's functional brain age (FBA), an index of maturation derived from the electroencephalogram. RESULTS: The FAA was strongly correlated to PMA (r = 0.86, 95% CI: 0.83-0.93) with a mean absolute error (MAE) of 1.66 weeks and also accurately estimated FBA (MAE = 1.58 weeks, n = 54 infants). The relationship between PMA and FAA was not confounded by neurodevelopmental outcome (p = 0.18, n = 45), sex (p = 0.88, n = 56), patent ductus arteriosus (p = 0.08, n = 56), IVH (p = 0.63, n = 56) or body weight at birth (p = 0.95, n = 56). CONCLUSIONS: The FAA, an index derived from the ubiquitous ECG signal, offers direct avenues towards estimating autonomic maturation at the bedside during intensive care monitoring. IMPACT: The development of a tool to track functional autonomic age in preterm infants based on heart rate variability features in the electrocardiogram provides a rapid and specialized view of autonomic maturation at the bedside. Functional autonomic age is linked closely to postmenstrual age and central nervous system function response, as determined by its relationship to functional brain age from the electroencephalogram. Tracking functional autonomic age during neonatal intensive care unit monitoring offers a unique insight into cardiovascular health in infants born extremely preterm and their maturational trajectories to term age.

Focal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance.

The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain's low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

Dorsal and Ventral Cortical Connectivity Is Mediated by the Inferior Frontal Gyrus During Facilitated Naming of Pictures.

Background: It is well recognized that semantic processing and auditory repetition facilitate subsequent naming of pictures. However, the neurocognitive mechanisms that underpin these facilitation effects remain unclear. Materials and Methods: The current study utilized a dynamic causal modeling (DCM) approach to examine high-density electroencephalographic (128-channel EEG) recordings and investigate connectivity modulations during facilitated naming of pictures in 18 healthy older adults (mean age 61.50 years). Source reconstruction of event-related potentials was performed in two specific time windows, (1) 150-250 msec and (2) 300-500 msec, to establish the timescale of significant cortical activations present during participation of semantic and phonological tasks. Hypothesis-driven DCM of source-activated regions was tested to ascertain which model most likely explained the semantic and phonological conditions, respectively. Results: DCM results indicated that a common cortical network comprising dorsal and ventral cortical connections best explained EEG task data derived from repetition and semantic tasks. For repetition (phonological) tasks, this model featured long feedback, bidirectional connections from inferior frontal gyrus (IFG) to occipitotemporal areas. Semantic tasks were most plausibly explained by a model that featured a self-inhibiting connection over the IFG only. Conclusions: Findings from this study reveal that a common cortical model comprising pathways that include dorsal and ventral regions is appropriate for characterizing EEG naming facilitation data, and that distinct cortical connections explain differences between semantic and auditory repetition processes. These models could be repurposed for naming facilitation paradigms in patients with language difficulties to optimize prediction and responsiveness to such paradigms. Impact statement The combination of semantic (word-level) and phonological (sound-level) processing in the cortex facilitates one of the most robust responses-the naming of pictures. Here, dynamic causal modeling of high-density electroencephalography during facilitated naming tasks revealed a model consisting of common dorsal and ventral connections that best explained response to semantic and phonological stimuli. Within this cortical network, phonological facilitation involved a long-range connection from inferior frontal gyrus (IFG) to occipitotemporal regions, whereas semantic facilitation contributed to self-inhibition of the IFG. The IFG is therefore a key region mediating cortical activity when switching between phonological and semantic conditions.

Microbiota links to neural dynamics supporting threat processing.

There is growing recognition that the composition of the gut microbiota influences behaviour, including responses to threat. The cognitive-interoceptive appraisal of threat-related stimuli relies on dynamic neural computations between the anterior insular (AIC) and the dorsal anterior cingulate (dACC) cortices. If, to what extent, and how microbial consortia influence the activity of this cortical threat processing circuitry is unclear. We addressed this question by combining a threat processing task, neuroimaging, 16S rRNA profiling and computational modelling in healthy participants. Results showed interactions between high-level ecological indices with threat-related AIC-dACC neural dynamics. At finer taxonomic resolutions, the abundance of Ruminococcus was differentially linked to connectivity between, and activity within the AIC and dACC during threat updating. Functional inference analysis provides a strong rationale to motivate future investigations of microbiota-derived metabolites in the observed relationship with threat-related brain processes.

Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease.

BACKGROUND: The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response. METHODS: 70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups. RESULTS: A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age. LIMITATIONS: This study only reports on optimal dosage of dopaminergic treatment ('on' state) in PD and did not investigate at "off" medication". CONCLUSIONS: Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.

Neural Correlates of Sleep Recovery following Melatonin Treatment for Pediatric Concussion: A Randomized Controlled Trial.

Evidence-based treatments for children with persistent post-concussion symptoms (PPCS) are few and limited. Common PPCS complaints such as sleep disturbance and fatigue could be ameliorated via the supplementation of melatonin, which has significant neuroprotective and anti-inflammatory properties. This study aims to identify neural correlates of melatonin treatment with changes in sleep disturbances and clinical recovery in a pediatric cohort with PPCS. We examined structural and functional neuroimaging (fMRI) in 62 children with PPCS in a randomized, double-blind, placebo-controlled trial of 3 mg or 10 mg of melatonin (NCT01874847). The primary outcome was the total youth self-report Post-Concussion Symptom Inventory (PCSI) score after 28 days of treatment. Secondary outcomes included the change in the sleep domain PCSI score and sleep-wake behavior (assessed using wrist-worn actigraphy). Whole-brain analyses of (1) functional connectivity (FC) of resting-state fMRI, and (2) structural gray matter volumes via voxel-based morphometry were assessed immediately before and after melatonin treatment and compared with placebo to identify neural effects of melatonin treatment. Increased FC of posterior default mode network (DMN) regions with visual, somatosensory, and dorsal networks was detected in the melatonin groups over time. The FC increases also corresponded with reduced wake periods (r = -0.27, p = 0.01). Children who did not recover (n = 39) demonstrated significant FC increases within anterior DMN and limbic regions compared with those who did recover (i.e., PCSI scores returned to pre-injury level, n = 23) over time, (p = 0.026). Increases in GM volume within the posterior cingulate cortex were found to correlate with reduced wakefulness after sleep onset (r = -0.32, p = 0.001) and sleep symptom improvement (r = 0.29, p = 0.02). Although the melatonin treatment trial was negative and did not result in PPCS recovery (with or without sleep problems), the relationship between melatonin and improvement in sleep parameters was linked to changes in function-structure within and between brain regions interacting with the DMN.

Alterations to dual stream connectivity predicts response to aphasia therapy following stroke.

BACKGROUND: Predicting aphasia recovery is difficult due to a high variability in treatment response. Detailed measures of treatment response are compounded by a dearth of information that examine brain connections that contribute to clinical improvement. In this study we measure alterations to cortical connectivity pathways during a therapy paradigm to detect whether key brain connections that contribute to language recovery can be detected prior to therapy. METHODS: We conducted a case-control trial with twenty-three adults including eight adults with chronic, post-stroke aphasia. Aphasia patients underwent 12 naming therapy sessions over 4 weeks, consisting of semantic and phonological treatment approaches. High-density electroencephalography (128 channel EEG) was measured prior to therapy and immediately following treatment in patients with aphasia. Analysis via a dynamic causal modelling (DCM) was used to assess which cortical connections significantly correlated with therapy response. RESULTS: Altered cortical responses in aphasia patients measured bilaterally in a dual stream DCM connectivity model were predictive of treatment-induced improvement in naming. Pre-treatment DCM coupling (i.e., strength of cortical connections) significant correlated with naming improvement for items treated with semantic therapy, as indicated by increased connection strengths between left inferior parietal lobule (LIPL) and inferior frontal gyrus (LIFG, r = .63, pFDR = .016). In particular, the mediating role of contralateral regions significantly influences overall treatment improvement in the latter stages of stroke recovery. CONCLUSIONS: Our findings identify a potential means to stratify larger cohorts of patients in neurorehabilitation settings into distinct treatments that are tailored to their individual language deficit.

Default mode network anatomy and function is linked to pediatric concussion recovery.

OBJECTIVE: To determine whether anatomical and functional brain features relate to key persistent post-concussion symptoms (PPCS) in children recovering from mild traumatic brain injuries (mTBI), and whether such brain indices can predict individual recovery from PPCS. METHODS: One hundred and ten children with mixed recovery following mTBI were seen at the concussion clinic at Neurology department Alberta Children's Hospital. The primary outcome was the Post-Concussion Symptom Inventory (PCSI, parent proxy). Sleep disturbance scores (PCSI subdomain) and the Neurocognition Index (CNS Vital Signs) were also measured longitudinally. PPCS was assessed at 4 weeks postinjury and 8-10 weeks postinjury. Gray matter volumes were assessed using magnetic resonance imaging (MRI) and voxel-based morphometry at 4 weeks postinjury. Functional connectivity was estimated at the same timepoint using resting-state MRI. Two complementary machine learning methods were used to assess if the combination of gray matter and functional connectivity indices carried meaningful prognostic information. RESULTS: Higher scores on a composite index of sleep disturbance, including fatigue, were associated with converging decreases in gray matter volume and local functional connectivity in two key nodes of the default mode network: the posterior cingulate cortex and the medial prefrontal cortex. Sleep-related disturbances also significantly correlated with reductions in functional connectivity between these brain regions. The combination of structural and functional brain indices associated to individual variations in the default mode network accurately predicted clinical outcomes at follow-up (area under the curve = 0.86). INTERPRETATION: These results highlight that the function-structure profile of core default mode regions underpins sleep-related problems following mTBI and carries meaningful prognostic information for pediatric concussion recovery.

Source activity during emotion processing and its relationship to cognitive impairment in Parkinson's disease.

BACKGROUND: Neural mechanisms contributing to an underlying cognitive impairment in Parkinson's disease (PD) are poorly understood. An effective method to probe cognitive processing deficits in PD is the examination of brain activity during emotional processes, particularly in explicit language emotion recognition contexts. METHODS: The present study utilised cortical source imaging of event related potentials (ERP) from electroencephalography (EEG) to evaluate valence judgements on negative and neutral target words in an automatic affective priming paradigm. Fifty non-demented PD patients, unmedicated for depression or anxiety, completed affective priming tasks during EEG monitoring. Cognitive impairment was measured using the validated Parkinson's Disease-Cognitive Rating Scale (PD-CRS). RESULTS: Results reveal that compared to healthy age-matched controls, PD patients demonstrate a reduced N400 activation during affective priming tasks in bilateral regions of the middle frontal gyrus (MFG), inferior parietal lobule (IPL) and, notably, have a late wave ERP component (LPP) in left MFG, present between 600 and 800 ms, following family-wise error correction (pFWE < 0.05). LPP in PD patients were significantly associated with PD-CRS scores. LIMITATIONS: Although affective priming paradigms are an effective means for various domains of cognition, it is not a focused cognitive behavioural test for cognitive dysfunction. Our study is thus limited to a surrogate measure of cognitive dysfunction via examination of emotional word processing cues. CONCLUSIONS: These findings suggest that source imaging methods with ERP paradigms in PD are effective in identifying delayed cognitive processes in PD.

Relating brain connectivity with persistent symptoms in pediatric concussion.

Persistent post-concussion symptoms (PCS) in children following a mild traumatic brain injury (mTBI) are a growing public health concern. There is a pressing need to understand the neural underpinning of PCS. Here, we examined whole-brain functional connectivity from resting-state fMRI with behavioral assessments in a cohort of 110 children with mTBI. Children with mTBI and controls had similar levels of connectivity. PCS symptoms and behaviors including poor cognition and sleep were associated with connectivity within functional brain networks. The identification of a single "positive-negative" dimension linking connectivity with behaviors enables better prognosis and stratification toward personalized therapeutic interventions.

Depression symptomatology correlates with event-related potentials in Parkinson's disease: An affective priming study.

BACKGROUND: Depression is a predominant non-motor symptom of Parkinson's disease (PD), which is often under recognised and undertreated. To improve identification of depression in PD it is imperative to examine objective brain-related markers. The present study addresses this gap by using electroencephalography (EEG) to evaluate the processing of emotionally valanced words in PD. METHODS: Fifty non-demented PD patients, unmedicated for depression or anxiety, completed an affective priming task while EEG was simultaneously recorded. Prime and target word pairs of negative or neutral valence were presented at a short 250 ms stimulus onset asynchrony. Participants were asked to evaluate the valence of the target word by button press. Depression was measured using an established rating scale. Repeated measures analysis of covariance and correlational analyses were performed to examine whether event-related potentials (ERP) varied as a function of depression scores. RESULTS: Key ERP findings reveal reduced responses in parietal midline P300, N400 and Late Positive Potential (LPP) difference waves between congruent and incongruent neutral targets in patients with higher depression scores. LIMITATIONS: Comparisons of ERPs were limited by insufficient classification of participants with and without clinical depression. A majority of PD patients who had high depression scores were excluded from the analysis as they were receiving antidepressant and/or anxiolytic medications which could interfere with ERP sensitivity. CONCLUSIONS: The present study suggests that the Pz-P300, N400 and LPP are ERP markers relates to emotional dysfunction in PD. These findings thus advance current knowledge regarding the neurophysiological markers of a common neuropsychiatric deficit in PD.

Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review.

Response inhibition, the ability to withhold a dominant and prepotent response following a change in circumstance or sensory stimuli, declines with advancing age. While non-invasive brain stimulation (NiBS) has shown promise in alleviating some cognitive and motor functions in healthy older individuals, NiBS research focusing on response inhibition has mostly been conducted on younger adults. These extant studies have primarily focused on modulating the activity of distinct neural regions known to be critical for response inhibition, including the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA). However, given that changes in structural and functional connectivity have been associated with healthy aging, this review proposes that NiBS protocols aimed at modulating the functional connectivity between the rIFG and pre-SMA may be the most efficacious approach to investigate-and perhaps even alleviate-age-related deficits in inhibitory control.

Mechanisms of facial emotion recognition in autism spectrum disorders: Insights from eye tracking and electroencephalography.

While behavioural difficulties in facial emotion recognition (FER) have been observed in individuals with Autism Spectrum Disorder (ASD), behavioural studies alone are not suited to elucidate the specific nature of FER challenges in ASD. Eye tracking (ET) and electroencephalography (EEG) provide insights in to the attentional and neurological correlates of performance, and may therefore provide insight in to the mechanisms underpinning FER in ASD. Given that these processes develop over the course of the developmental trajectory, there is a need to synthesise findings in regard to the developmental stages to determine how the maturation of these systems may impact FER in ASD. We conducted a systematic review of fifty-four studies investigating ET or EEG meeting inclusion criteria. Findings indicate divergence of visual processing pathways in individuals with ASD. Altered function of the social brain in ASD impacts the processing of facial emotion across the developmental trajectory, resulting in observable differences in ET and EEG outcomes.