Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players.

Background: Exposure to thousands of head and body impacts during a career in contact and collision sports may contribute to current or later life issues related to brain health. Wearable technology enables the measurement of impact exposure. The validation of impact detection is required for accurate exposure monitoring. In this study, we present a method of automatic identification (classification) of head and body impacts using an instrumented mouthguard, video-verified impacts, and machine-learning algorithms. Methods: Time series data were collected via the Nexus A9 mouthguard from 60 elite level men (mean age = 26.33; SD = 3.79) and four women (mean age = 25.50; SD = 5.91) from the Australian Rules Football players from eight clubs, participating in 119 games during the 2020 season. Ground truth data labeling on the captures used in this machine learning study was performed through the analysis of game footage by two expert video reviewers using SportCode and Catapult Vision. The visual labeling process occurred independently of the mouthguard time series data. True positive captures (captures where the reviewer directly observed contact between the mouthguard wearer and another player, the ball, or the ground) were defined as hits. Spectral and convolutional kernel based features were extracted from time series data. Performances of untuned classification algorithms from scikit-learn in addition to XGBoost were assessed to select the best performing baseline method for tuning. Results: Based on performance, XGBoost was selected as the classifier algorithm for tuning. A total of 13,712 video verified captures were collected and used to train and validate the classifier. True positive detection ranged from 94.67% in the Test set to 100% in the hold out set. True negatives ranged from 95.65 to 96.83% in the test and rest sets, respectively. Discussion and conclusion: This study suggests the potential for high performing impact classification models to be used for Australian Rules Football and highlights the importance of frequencies <150 Hz for the identification of these impacts.

Predicting Post-Stroke Somatosensory Function from Resting-State Functional Connectivity: A Feasibility Study.

Accumulating evidence shows that brain functional deficits may be impacted by damage to remote brain regions. Recent advances in neuroimaging suggest that stroke impairment can be better predicted based on disruption to brain networks rather than from lesion locations or volumes only. Our aim was to explore the feasibility of predicting post-stroke somatosensory function from brain functional connectivity through the application of machine learning techniques. Somatosensory impairment was measured using the Tactile Discrimination Test. Functional connectivity was employed to model the global brain function. Behavioral measures and MRI were collected at the same timepoint. Two machine learning models (linear regression and support vector regression) were chosen to predict somatosensory impairment from disrupted networks. Along with two feature pools (i.e., low-order and high-order functional connectivity, or low-order functional connectivity only) engineered, four predictive models were built and evaluated in the present study. Forty-three chronic stroke survivors participated this study. Results showed that the regression model employing both low-order and high-order functional connectivity can predict outcomes based on correlation coefficient of r = 0.54 (p = 0.0002). A machine learning predictive approach, involving high- and low-order modelling, is feasible for the prediction of residual somatosensory function in stroke patients using functional brain networks.

Altered Functional Connectivity and Cognition Persists 4 Years After a Transient Ischemic Attack or Minor Stroke.

Background and Purpose: Altered executive functions and resting-state functional connectivity (rsFC) are common following a minor stroke or transient ischemic attack (TIA). However, the long-term persistence of these abnormalities is not well-studied. We investigated whether there were cognitive and rsFC differences between (a) controls and minor cerebrovascular event (CVE) patients and (b) between CVE patients with and without an imaging confirmed infarct (i.e., minor stroke and TIA, respectively) at an average of 3.8 years following their event. Methods: Structural and resting-state imaging and cognitive assessments including the Montreal Cognitive Assessment, the Trail Making Task and the National Institute of Health (NIH) Cognition Toolbox were conducted on 42 patients (minor stroke = 17, TIA = 25) and 20 healthy controls (total N = 62). Results: Controls performed better than patients on two measures of executive functioning (both p < 0.046) and had reduced rsFC between the frontoparietal and default mode networks (FPN and DMN, respectively; p = 0.035). No cognitive differences were found between minor stroke and TIA patients, however, rsFC differences were found within the FPN and the DMN (both p < 0.013). Specifically, increased connectivity within the FPN was associated with faster performance in the minor stroke group but not the TIA group (p = 0.047). Conclusions: These findings suggest that transient or relatively minor cerebrovascular events are associated with persistent disruption of functional connectivity of neural networks and cognitive performance. These findings suggest a need for novel interventions beyond secondary prevention to reduce the risk of persistent cognitive deficits.

Correlated Resting-State Functional MRI Activity of Frontostriatal, Thalamic, Temporal, and Cerebellar Brain Regions Differentiates Stroke Survivors with High Compared to Low Depressive Symptom Scores.

Background: One in three survivors of stroke experience poststroke depression (PSD). PSD has been linked with poorer recovery of function and cognition, yet our understanding of potential mechanisms is currently limited. Alterations in resting-state functional MRI have been investigated to a limited extent. Fluctuations in low frequency signal are reported, but it is unknown if interactions are present between the level of depressive symptom score and intrinsic brain activity in varying brain regions. Objective: To investigate potential interaction effects between whole-brain resting-state activity and depressive symptoms in stroke survivors with low and high levels of depressive symptoms. Methods: A cross-sectional analysis of 63 stroke survivors who were assessed at 3 months poststroke for depression, using the Montgomery-Åsberg Depression Rating Scale (MÅDRS-SIGMA), and for brain activity using fMRI. A MÅDRS-SIGMA score of >8 was classified as high depressive symptoms. Fractional amplitude of frequency fluctuations (fALFF) data across three frequency bands (broadband, i.e., ~0.01-0.08; subbands, i.e., slow-5: ~0.01-0.027 Hz, slow-4: 0.027-0.07) was examined. Results: Of the 63 stroke survivors, 38 were classified as "low-depressive symptoms" and 25 as "high depressive symptoms." Six had a past history of depression. We found interaction effects across frequency bands in several brain regions that differentiated the two groups. The broadband analysis revealed interaction effects in the left insula and the left superior temporal lobe. The subband analysis showed contrasting fALFF response between the two groups in the left thalamus, right caudate, and left cerebellum. Across the three frequency bands, we found contrasting fALFF response in areas within the fronto-limbic-thalamic network and cerebellum. Conclusions: We provide evidence that fALFF is sensitive to changes in poststroke depressive symptom severity and implicates frontostriatal and cerebellar regions, consistent with previous studies. The use of multiband analysis could be an effective method to examine neural correlates of depression after stroke. The START-PrePARE trial is registered with the Australian New Zealand Clinical Trial Registry, number ACTRN12610000987066.

Modafinil treatment modulates functional connectivity in stroke survivors with severe fatigue.

Post-stroke fatigue has a significant impact on stroke survivors' mental and physical well-being. Our recent clinical trial showed significant reduction of post-stroke fatigue with modafinil treatment, however functional connectivity changes in response to modafinil have not yet been explored in stroke survivors with post-stroke fatigue. Twenty-eight participants (multidimensional fatigue inventory-20 ≥ 60) had MRI scans at baseline, and during modafinil and placebo treatment. Resting-state functional MRI data were obtained, and independent component analysis was used to extract functional networks. Resting-state functional connectivity (rsFC) was examined between baseline, modafinil and placebo treatment using permutation testing with threshold-free cluster enhancement. Overall twenty-eight participants (mean age: 62 ± 14.3, mean baseline MFI-20: 72.3 ± 9.24) were included. During modafinil treatment, increased rsFC was observed in the right hippocampus (p = 0.004, 11 voxels) compared to placebo. This coincided with lower rsFC in the left frontoparietal (inferior parietal lobule, p = 0.023, 13 voxels), somatosensory (primary somatosensory cortex; p = 0.009, 32 voxels) and mesolimbic network (temporal pole, p = 0.016, 35 voxels). In conclusion, modafinil treatment induces significant changes in rsFC in post-stroke fatigue. This modulation of rsFC may relate to a reduction of post-stroke fatigue; however, the relationship between sensory processing, neurotransmitter expression and fatigue requires further exploration.

Finding the Intersection of Neuroplasticity, Stroke Recovery, and Learning: Scope and Contributions to Stroke Rehabilitation.

Aim: Neural plastic changes are experience and learning dependent, yet exploiting this knowledge to enhance clinical outcomes after stroke is in its infancy. Our aim was to search the available evidence for the core concepts of neuroplasticity, stroke recovery, and learning; identify links between these concepts; and identify and review the themes that best characterise the intersection of these three concepts. Methods: We developed a novel approach to identify the common research topics among the three areas: neuroplasticity, stroke recovery, and learning. A concept map was created a priori, and separate searches were conducted for each concept. The methodology involved three main phases: data collection and filtering, development of a clinical vocabulary, and the development of an automatic clinical text processing engine to aid the process and identify the unique and common topics. The common themes from the intersection of the three concepts were identified. These were then reviewed, with particular reference to the top 30 articles identified as intersecting these concepts. Results: The search of the three concepts separately yielded 405,636 publications. Publications were filtered to include only human studies, generating 263,751 publications related to the concepts of neuroplasticity (n = 6,498), stroke recovery (n = 79,060), and learning (n = 178,193). A cluster concept map (network graph) was generated from the results; indicating the concept nodes, strength of link between nodes, and the intersection between all three concepts. We identified 23 common themes (topics) and the top 30 articles that best represent the intersecting themes. A time-linked pattern emerged. Discussion and Conclusions: Our novel approach developed for this review allowed the identification of the common themes/topics that intersect the concepts of neuroplasticity, stroke recovery, and learning. These may be synthesised to advance a neuroscience-informed approach to stroke rehabilitation. We also identified gaps in available literature using this approach. These may help guide future targeted research.

Decreased Response to Positive Facial Affect in a Depressed Cohort in the Dorsal Striatum During a Working Memory Task-A Preliminary fMRI Study.

People with depression have shown alterations in processing emotional information and working memory functionality. There is some evidence that emotional content may interact with working memory update processes, however neurological correlates are current unknown. In this preliminary study we utilized a novel version of the emotional variant of the n-back working memory task in fMRI. We examined BOLD response of 14 healthy controls and 13 depressed participants in response to happy, sad, and neutral displays of facial affect. No accuracy or reaction time differences were found between the two groups. The depressed group showed significantly decreased BOLD response to happy faces compared to the control group areas of the dorsal striatum and anterior cingulate. Significant, moderate, positive associations were found between right caudate activation with anxiety score and anterior cingulate activation with depression score in those with depression. Our novel task was able to elicit group level differences in emotional processing during working memory update. These results suggest those with depression fail to differentiate between positive emotional stimuli and stimuli with no emotional content.

Predicting Modafinil-Treatment Response in Poststroke Fatigue Using Brain Morphometry and Functional Connectivity.

Background and Purpose- Poststroke fatigue affects a large proportion of stroke survivors and is associated with a poor quality of life. In a recent trial, modafinil was shown to be an effective agent in reducing poststroke fatigue; however, not all patients reported a significant decrease in fatigue with therapy. We sought to investigate clinical and radiological predictors of fatigue reduction with modafinil therapy in a stroke survivor cohort. Methods- Twenty-six participants with severe fatigue (multidimensional fatigue inventory-20 ≥60) underwent magnetic resonance imaging at baseline and during the last week of a 6-week treatment period of 200 mg modafinil taken daily. Resting-state functional magnetic resonance imaging and high-resolution structural imaging data were obtained, and functional connectivity and regional brain volumes within the fronto-striato-thalamic network were obtained. Linear regression analysis was used to identify predictors of modafinil-induced fatigue reduction. Results- Multiple regression analysis showed that baseline multidimensional fatigue inventory-20 score (ß=0.576, P=0.006) and functional connectivity between the dorsolateral prefrontal cortex and the caudate nucleus (ß=-0.424, P=0.008) were significant predictors of modafinil-associated decreases in poststroke fatigue (adjusted r2=0.52, area under the receiver operator characteristic curve=0.939). Conclusions- Fronto-striato-thalamic functional connectivity predicted modafinil response for poststroke fatigue. Fatigue in other neurological disease has been attributed to altered function of the fronto-striato-thalamic network and may indicate that poststroke fatigue has a similar mechanism to other neurological injury related fatigue. Self-reported fatigue in patients with normal fronto-striato-thalamic functional connectivity may have a different mechanism and require alternate therapeutic approaches. Clinical Trial Registration- URL: https://www.clinicaltrials.gov . Unique identifier: ACTRN12615000350527.

Altered functional connectivity differs in stroke survivors with impaired touch sensation following left and right hemisphere lesions.

One in two survivors experience impairment in touch sensation after stroke. The nature of this impairment is likely associated with changes associated with the functional somatosensory network of the brain; however few studies have examined this. In particular, the impact of lesioned hemisphere has not been investigated. We examined resting state functional connectivity in 28 stroke survivors, 14 with left hemisphere and 14 with right hemisphere lesion, and 14 healthy controls. Contra-lesional hands showed significantly decreased touch discrimination. Whole brain functional connectivity (FC) data was extracted from four seed regions, i.e. primary (S1) and secondary (S2) somatosensory cortices in both hemispheres. Whole brain FC maps and Laterality Indices (LI) were calculated for subgroups. Inter-hemispheric FC was greater in healthy controls compared to the combined stroke cohort from the left S1 seed and bilateral S2 seeds. The left lesion subgroup showed decreased FC, relative to controls, from left ipsi-lesional S1 to contra-lesional S1 and to distributed temporal, occipital and parietal regions. In comparison, the right lesion group showed decreased connectivity from contra-lesional left S1 and bilateral S2 to ipsi-lesional parietal operculum (S2), and to occipital and temporal regions. The right lesion group also showed increased intra-hemispheric FC from ipsi-lesional right S1 to inferior parietal regions compared to controls. In comparison to the left lesion group, those with right lesion showed greater intra-hemispheric connectivity from left S1 to left parietal and occipital regions and from right S1 to right angular and parietal regions. Laterality Indices were significantly greater for stroke subgroups relative to matched controls for contra-lesional S1 (left lesion group) and contra-lesional S2 (both groups). We provide evidence of altered functional connectivity within the somatosensory network, across both hemispheres, and to other networks in stroke survivors with impaired touch sensation. Hemisphere of lesion was associated with different patterns of altered functional connectivity within the somatosensory network and with related function was associated with different patterns of altered functional connectivity within the somatosensory network and with related functional networks.

Activation of Bilateral Secondary Somatosensory Cortex With Right Hand Touch Stimulation: A Meta-Analysis of Functional Neuroimaging Studies.

Background: Brain regions involved in processing somatosensory information have been well documented through lesion, post-mortem, animal, and more recently, structural and functional neuroimaging studies. Functional neuroimaging studies characterize brain activation related to somatosensory processing; yet a meta-analysis synthesis of these findings is currently lacking and in-depth knowledge of the regions involved in somatosensory-related tasks may also be confounded by motor influences. Objectives: Our Activation Likelihood Estimate (ALE) meta-analysis sought to quantify brain regions that are involved in the tactile processing of the right (RH) and left hands (LH) separately, with the exclusion of motor related activity. Methods: The majority of studies (n = 41) measured activation associated with RH tactile stimulation. RH activation studies were grouped into those which conducted whole-brain analyses (n = 29) and those which examined specific regions of interest (ROI; n = 12). Few studies examined LH activation, though all were whole-brain studies (N = 7). Results: Meta-analysis of brain activation associated with RH tactile stimulation (whole-brain studies) revealed large clusters of activation in the left primary somatosensory cortex (S1) and bilaterally in the secondary somatosensory cortex (S2; including parietal operculum) and supramarginal gyrus (SMG), as well as the left anterior cingulate. Comparison between findings from RH whole-brain and ROI studies revealed activation as expected, but restricted primarily to S1 and S2 regions. Further, preliminary analyses of LH stimulation studies only, revealed two small clusters within the right S1 and S2 regions, likely limited due to the small number of studies. Contrast analyses revealed the one area of overlap for RH and LH, was right secondary somatosensory region. Conclusions: Findings from the whole-brain meta-analysis of right hand tactile stimulation emphasize the importance of taking into consideration bilateral activation, particularly in secondary somatosensory cortex. Further, the right parietal operculum/S2 region was commonly activated for right and left hand tactile stimulation, suggesting a lateralized pattern of somatosensory activation in right secondary somatosensory region. Implications for further research and for possible differences in right and left hemispheric stroke lesions are discussed.

Examining the N400m in affectively negative sentences: A magnetoencephalography study.

Magnetoencephalography was used to examine the effect on the N400m of reading words that create emotional violations in sentences. The beginnings of the sentences were affectively negative and were completed with either a negative congruous, positive incongruous, or neutral incongruous adjective (e.g., "My mother was killed and I felt bad/great/normal"). The task conditions were also manipulated to favor semantic over affective processing. Compared to the sentences with the congruous negative adjectives, the results of sensor space analysis showed that there was an N400m effect with the sentences with the neutral but not positive adjectives, despite both types of sentences containing an emotional violation. Source localization results showed a similar pattern where the sentences with the incongruous positive versus congruous negative adjectives showed no significant N400m effect in the temporal and frontal areas examined, but the sentences with the incongruous neutral versus incongruous positive adjectives in the temporal areas did, particularly the left middle temporal gyrus. These results suggest that (a) the N400m effect was likely to be caused by the incongruous neutral adjectives being comparatively harder to integrate into a negative emotional context than the incongruous positive ones, (b) emotional context created by the negative sentence stems caused deeper semantic processing of the incongruous positive adjectives to be bypassed, and (c) negative affective context was generated from reading the sentences even in task conditions where it has not been generated with isolated words.

A high-density EEG investigation into steady state binaural beat stimulation.

Binaural beats are an auditory phenomenon that has been suggested to alter physiological and cognitive processes including vigilance and brainwave entrainment. Some personality traits measured by the NEO Five Factor Model have been found to alter entrainment using pulsing light stimuli, but as yet no studies have examined if this occurs using steady state presentation of binaural beats for a relatively short presentation of two minutes. This study aimed to examine if binaural beat stimulation altered vigilance or cortical frequencies and if personality traits were involved. Thirty-one participants were played binaural beat stimuli designed to elicit a response at either the Theta (7 Hz) or Beta (16 Hz) frequency bands while undertaking a zero-back vigilance task. EEG was recorded from a high-density electrode cap. No significant differences were found in vigilance or cortical frequency power during binaural beat stimulation compared to a white noise control period. Furthermore, no significant relationships were detected between the above and the Big Five personality traits. This suggests a short presentation of steady state binaural beats are not sufficient to alter vigilance or entrain cortical frequencies at the two bands examined and that certain personality traits were not more susceptible than others.