Scale-free functional brain dynamics during recovery from sport-related concussion

A Self-Similarity Logic May Shape the Organization of the Nervous System

From the morphological point of view, the nervous system exhibits a fractal, self-similar geometry at various levels of observations, from single cells up to cell networks. From the functional point of view, it is characterized by a hierarchical organization in which self-similar structures (networks) of different miniaturizations are nested within each other. In particular, neuronal networks, interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks, mainly having proteins as components that via protein-protein interactions can be assembled in multimeric complexes working as micro-devices. On this basis, the term "self-similarity logic" was introduced to describe a nested organization where, at the various levels, almost the same rules (logic) to perform operations are used. Self-similarity and self-similarity logic both appear to be intimately linked to the biophysical evidence for the nervous system being a pattern-forming system that can flexibly switch from one coherent state to another. Thus, they can represent the key concepts to describe its complexity and its concerted, holistic behavior.

Multifractal Analysis in Neuroimaging

The characteristics of biomedical signals are not captured by conventional measures like the average amplitude of the signal. The methodologies derived from fractal geometry have been a very useful approach to study the degree of irregularity of a signal. The monofractal analysis of a signal is defined by a single power-law exponent in assuming a scale invariance in time and space. However, temporal and spatial variation in the scale-invariant structure of the biomedical signal often appears. In this case, multifractal analysis is well-suited because it is defined by a multifractal spectrum of power-law exponents. There are several approaches to the implementation of this analysis, and there are numerous ways to present these.In this chapter, we review the use of multifractal analysis for the purpose of characterizing signals in neuroimaging. After describing the tenets of multifractal analysis, we present several approaches to estimating the multifractal spectrum. Finally, we describe the applications of this spectrum on biomedical signals in the characterization of several diseases in neurosciences.

Persistent post-COVID headache is associated with suppression of scale-free functional brain dynamics in non-hospitalized individuals

INTRODUCTION

Post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) is a growing concern, with headache being a particularly debilitating symptom with high prevalence. The long-term effects of COVID-19 and post-COVID headache on brain function remain poorly understood, particularly among non-hospitalized individuals. This study focused on the power-law scaling behavior of functional brain dynamics, indexed by the Hurst exponent (H). This measure is suppressed during physiological and psychological distress and was thus hypothesized to be reduced in individuals with post-COVID syndrome, with greatest reductions among those with persistent headache.

METHODS

Resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging data were collected for 57 individuals who had COVID-19 (32 with no headache, 14 with ongoing headache, 11 recovered) and 17 controls who had cold and flu-like symptoms but  tested negative for COVID-19. Individuals were assessed an average of 4-5 months after COVID testing, in a cross-sectional, observational study design.

RESULTS

No significant differences in H values were found between non-headache COVID-19 and control groups., while those with ongoing headache had significantly reduced H values, and those who had recovered from headache had elevated H values, relative to non-headache groups. Effects were greatest in temporal, sensorimotor, and insular brain regions. Reduced H in these regions was also associated with decreased BOLD activity and local functional connectivity.

CONCLUSIONS

These findings provide new insights into the neurophysiological mechanisms that underlie persistent post-COVID headache, with reduced BOLD scaling as a potential biomarker that is specific to this debilitating condition.

Improvements in task performance after practice are associated with scale-free dynamics of brain activity

Although practicing a task generally benefits later performance on that same task, there are individual differences in practice effects. One avenue to model such differences comes from research showing that brain networks extract functional advantages from operating in the vicinity of criticality, a state in which brain network activity is more scale-free. We hypothesized that higher scale-free signal from fMRI data, measured with the Hurst exponent (H), indicates closer proximity to critical states. We tested whether individuals with higher H during repeated task performance would show greater practice effects. In Study 1, participants performed a dual-n-back task (DNB) twice during MRI (n = 56). In Study 2, we used two runs of n-back task (NBK) data from the Human Connectome Project sample (n = 599). In Study 3, participants performed a word completion task (CAST) across six runs (n = 44). In all three studies, multivariate analysis was used to test whether higher H was related to greater practice-related performance improvement. Supporting our hypothesis, we found patterns of higher H that reliably correlated with greater performance improvement across participants in all three studies. However, the predictive brain regions were distinct, suggesting that the specific spatial H↑ patterns are not task-general.

Acute evaluation of sport-related concussion and implications for the Sport Concussion Assessment Tool (SCAT6) for adults, adolescents and children: a systematic review

OBJECTIVES

To systematically review the scientific literature regarding the acute assessment of sport-related concussion (SRC) and provide recommendations for improving the Sport Concussion Assessment Tool (SCAT6).

DATA SOURCES

Systematic searches of seven databases from 2001 to 2022 using key words and controlled vocabulary relevant to concussion, sports, SCAT, and acute evaluation.

ELIGIBILITY CRITERIA

(1) Original research articles, cohort studies, case-control studies, and case series with a sample of >10; (2) ≥80% SRC; and (3) studies using a screening tool/technology to assess SRC acutely (<7 days), and/or studies containing psychometric/normative data for common tools used to assess SRC.

DATA EXTRACTION

Separate reviews were conducted involving six subdomains: Cognition, Balance/Postural Stability, Oculomotor/Cervical/Vestibular, Emerging Technologies, and Neurological Examination/Autonomic Dysfunction. Paediatric/Child studies were included in each subdomain. Risk of Bias and study quality were rated by coauthors using a modified SIGN (Scottish Intercollegiate Guidelines Network) tool.

RESULTS

Out of 12 192 articles screened, 612 were included (189 normative data and 423 SRC assessment studies). Of these, 183 focused on cognition, 126 balance/postural stability, 76 oculomotor/cervical/vestibular, 142 emerging technologies, 13 neurological examination/autonomic dysfunction, and 23 paediatric/child SCAT. The SCAT discriminates between concussed and non-concussed athletes within 72 hours of injury with diminishing utility up to 7 days post injury. Ceiling effects were apparent on the 5-word list learning and concentration subtests. More challenging tests, including the 10-word list, were recommended. Test-retest data revealed limitations in temporal stability. Studies primarily originated in North America with scant data on children.

CONCLUSION

Support exists for using the SCAT within the acute phase of injury. Maximal utility occurs within the first 72 hours and then diminishes up to 7 days after injury. The SCAT has limited utility as a return to play tool beyond 7 days. Empirical data are limited in pre-adolescents, women, sport type, geographical and culturally diverse populations and para athletes.

PROSPERO REGISTRATION NUMBER

CRD42020154787.

The Current State of Functional MR Imaging for Trauma Prognostication

In this review, we discuss the basics of functional MRI (fMRI) techniques including task-based and resting state fMRI, and overview the major findings in patients with traumatic brain injury. We summarize the studies that have longitudinally evaluated the changes in brain connectivity and task-related activation in trauma patients during different phases of trauma. We discuss how these data may potentially be used for prognostication, treatment planning, or monitoring and management of trauma patients.

Clinical Outcome Following Concussion Among College Athletes with a History of Prior Concussion: A Systematic Review

BACKGROUND

There is long-standing interest in, and concern about, whether collegiate athletes with a history of concussion will experience worse clinical outcomes, or prolonged recovery, should they sustain a subsequent concussion.

OBJECTIVES

This systematic review examined the association between prior concussion history and clinical outcomes following a subsequent sport-related concussion among college-age student athletes.

STUDY DESIGN

Systematic review.

METHODS

We screened 5,118 abstracts and 619 full-text articles that were appraised to determine whether they met inclusion criteria. We utilized a likelihood heuristic to assess the probability of observing a specific number of statistically significant and nonsignificant studies reporting an association between concussion history and clinical outcomes. We conducted a narrative synthesis of the study findings.

RESULTS

Sixteen studies met the inclusion criteria. Thirteen studies reported the number of participants with a history of prior concussions (≥ 1), which totaled 1690 of 4573 total participants (on average 37.0% of study participants; median = 46.0%, range 5.6-63.8%). On the Newcastle-Ottawa Quality Assessment Scale, the risk of bias ratings ranged from 3 to 9 (mean = 5.4, SD = 1.4). Across all studies, 43.8% (k = 7/16) reported at least one statistically significant result among primary analyses showing an association between concussion history and worse clinical outcome. A minority of studies reporting on symptom duration (4/13, 30.8%) and time to return to play (2/7, 28.6%) found an association between concussion history and worse outcome. Studies included in the review reported limited information pertaining to the characteristics of prior concussions, such as presence or duration of loss of consciousness or posttraumatic amnesia, age at first lifetime concussion, time since most recent past concussion, or length of recovery from prior concussions.

CONCLUSION

The question of whether college athletes with a prior history of concussion have worse clinical outcome from their next sport-related concussion remains unresolved. The published results are mixed and in aggregate show modest evidence for an association. Many studies have small samples, and only three studies were designed specifically to address this research question. Important outcomes, such as time to return to academics, have not been adequately studied. Larger hypothesis-driven studies considering the number of prior concussions (e.g., 3 or more) are needed.

TRIAL REGISTRATION

PROSPERO CRD42016041479, CRD42019128300.

Long-Known Music Exposure Effects on Brain Imaging and Cognition in Early-Stage Cognitive Decline: A Pilot Study

BACKGROUND

Repeated exposure to long-known music has been shown to have a beneficial effect on cognitive performance in patients with AD. However, the brain mechanisms underlying improvement in cognitive performance are not yet clear.

OBJECTIVE

In this pilot study we propose to examine the effect of repeated long-known music exposure on imaging indices and corresponding changes in cognitive function in patients with early-stage cognitive decline.

METHODS

Participants with early-stage cognitive decline were assigned to three weeks of daily long-known music listening, lasting one hour in duration. A cognitive battery was administered, and brain activity was measured before and after intervention. Paired-measures tests evaluated the longitudinal changes in brain structure, function, and cognition associated with the intervention.

RESULTS

Fourteen participants completed the music-based intervention, including 6 musicians and 8 non-musicians. Post-baseline there was a reduction in brain activity in key nodes of a music-related network, including the bilateral basal ganglia and right inferior frontal gyrus, and declines in fronto-temporal functional connectivity and radial diffusivity of dorsal white matter. Musician status also significantly modified longitudinal changes in functional and structural brain measures. There was also a significant improvement in the memory subdomain of the Montreal Cognitive Assessment.

CONCLUSION

These preliminary results suggest that neuroplastic mechanisms may mediate improvements in cognitive functioning associated with exposure to long-known music listening and that these mechanisms may be different in musicians compared to non-musicians.

Mild traumatic brain injury impairs the coordination of intrinsic and motor-related neural dynamics

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MTBI is poorly understood and lacks objective diagnostic and prognostic tools.

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Abnormal neural oscillations are found in subjects with a history of mTBI.

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We identify transient bursts in MEG data using a Hidden Markov Model.

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We explain a deficit in beta connectivity and power in terms of transient bursts.

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Data-driven feature selection identifies symptom-relevant functional connections.

Mild traumatic brain injury (mTBI) poses a considerable burden on healthcare systems. Whilst most patients recover quickly, a significant number suffer from sequelae that are not accompanied by measurable structural damage. Understanding the neural underpinnings of these debilitating effects and developing a means to detect injury, would address an important unmet clinical need. It could inform interventions and help predict prognosis. Magnetoencephalography (MEG) affords excellent sensitivity in probing neural function and presents significant promise for assessing mTBI, with abnormal neural oscillations being a potential specific biomarker. However, growing evidence suggests that neural dynamics are (at least in part) driven by transient, pan-spectral bursting and in this paper, we employ this model to investigate mTBI. We applied a Hidden Markov Model to MEG data recorded during resting state and a motor task and show that previous findings of diminished intrinsic beta amplitude in individuals with mTBI are largely due to the reduced beta band spectral content of bursts, and that diminished beta connectivity results from a loss in the temporal coincidence of burst states. In a motor task, mTBI results in diminished burst amplitude, altered modulation of burst probability during movement, and a loss in connectivity in motor networks. These results suggest that, mechanistically, mTBI disrupts the structural framework underlying neural synchrony, which impairs network function. Whilst the damage may be too subtle for structural imaging to see, the functional consequences are detectable and persist after injury. Our work shows that mTBI impairs the dynamic coordination of neural network activity and proposes a potent new method for understanding mTBI.

Recurrent neural network-based acute concussion classifier using raw resting state EEG data

Concussion is a global health concern. Despite its high prevalence, a sound understanding of the mechanisms underlying this type of diffuse brain injury remains elusive. It is, however, well established that concussions cause significant functional deficits; that children and youths are disproportionately affected and have longer recovery time than adults; and that individuals suffering from a concussion are more prone to experience additional concussions, with each successive injury increasing the risk of long term neurological and mental health complications. Currently, the most significant challenge in concussion management is the lack of objective, clinically- accepted, brain-based approaches for determining whether an athlete has suffered a concussion. Here, we report on our efforts to address this challenge. Specifically, we introduce a deep learning long short-term memory (LSTM)-based recurrent neural network that is able to distinguish between non-concussed and acute post-concussed adolescent athletes using only short (i.e. 90 s long) samples of resting state EEG data as input. The athletes were neither required to perform a specific task nor expected to respond to a stimulus during data collection. The acquired EEG data were neither filtered, cleaned of artefacts, nor subjected to explicit feature extraction. The LSTM network was trained and validated using data from 27 male, adolescent athletes with sports related concussion, benchmarked against 35 non-concussed adolescent athletes. During rigorous testing, the classifier consistently identified concussions with an accuracy of > 90% and achieved an ensemble median Area Under the Receiver Operating Characteristic Curve (ROC/AUC) equal to 0.971. This is the first instance of a high-performing classifier that relies only on easy-to-acquire resting state, raw EEG data. Our concussion classifier represents a promising first step towards the development of an easy-to-use, objective, brain-based, automatic classification of concussion at an individual level.

Insular Connectivity Is Associated With Self-Appraisal of Cognitive Function After a Concussion

Concussion is associated with acute cognitive impairments, with declines in processing speed and reaction time being common. In the clinical setting, these issues are identified via symptom assessments and neurocognitive test (NCT) batteries. Practice guidelines recommend integrating both symptoms and NCTs into clinical decision-making, but correlations between these measures are often poor. This suggests that many patients experience difficulties in the self-appraisal of cognitive issues. It is presently unclear what neural mechanisms give rise to appraisal mismatch after a concussion. One promising target is the insula, which regulates aspects of cognition, particularly interoception and self-monitoring. The present study tested the hypothesis that appraisal mismatch is due to altered functional connectivity of the insula to frontal and midline structures, with hypo-connectivity leading to under-reporting of cognitive issues and hyper-connectivity leading to over-reporting. Data were collected from 59 acutely concussed individuals and 136 normative controls, including symptom assessments, NCTs and magnetic resonance imaging (MRI) data. Analysis of resting-state functional MRI supported the hypothesis, identifying insular networks that were associated with appraisal mismatch in concussed athletes that included frontal, sensorimotor, and cingulate connections. Subsequent analysis of diffusion tensor imaging also determined that symptom over-reporting was associated with reduced fractional anisotropy and increased mean diffusivity of posterior white matter. These findings provide new insights into the mechanisms of cognitive appraisal mismatch after a concussion. They are of particular interest given the central role of symptom assessments in the diagnosis and clinical management of concussion.

Long-term changes in the small-world organization of brain networks after concussion

There is a growing body of literature using functional MRI to study the acute and long-term effects of concussion on functional brain networks. To date, studies have largely focused on changes in pairwise connectivity strength between brain regions. Less is known about how concussion affects whole-brain network topology, particularly the “small-world” organization which facilitates efficient communication at both local and global scales. The present study addressed this knowledge gap by measuring local and global efficiency of 26 concussed athletes at acute injury, return to play (RTP) and one year post-RTP, along with a cohort of 167 athletic controls. On average, concussed athletes showed no alterations in local efficiency but had elevated global efficiency at acute injury, which had resolved by RTP. Athletes with atypically long recovery, however, had reduced global efficiency at 1 year post-RTP, suggesting long-term functional abnormalities for this subgroup. Analyses of nodal efficiency further indicated that global network changes were driven by high-efficiency visual and sensorimotor regions and low-efficiency frontal and subcortical regions. This study provides evidence that concussion causes subtle acute and long-term changes in the small-world organization of the brain, with effects that are related to the clinical profile of recovery.

The effect of large deformation on Poisson's ratio of brain white matter: An experimental study

A more Accurate description of the mechanical behavior of brain tissue could improve the results of computational models. While most studies have assumed brain tissue as an incompressible material with constant Poisson's ratio of almost 0.5 and constructed their modeling approach according to this assumption, the relationship between this ratio and levels of applied strains has not yet been studied. Since the mechanical response of the tissue is highly sensitive to the value of Poisson's ratio, this study was designed to investigate the characteristics of the Poisson's ratio of brain tissue at different levels of applied strains. Samples were extracted from bovine brain tissue and tested under unconfined compression at strain values of 5%, 10%, and 30%. Using an image processing method, the axial and transverse strains were measured over a 60-s period to calculate the Poisson's ratio for each sample. The results of this study showed that the Poisson's ratio of brain tissue at strain levels of 5% and 10% was close to 0.5, and assuming brain tissue as an incompressible material is a valid assumption at these levels of strain. For samples under 30% compression, this ratio was higher than 0.5, which could suggest that under strains higher than the brain injury threshold (approximately 18%), tissue integrity was impaired. Based on these observations, it could be concluded that for strain levels higher than the injury threshold, brain tissue could not be assumed as an incompressible material, and new material models need to be proposed to predict the material behavior of the tissue. In addition, the results showed that brain tissue under unconfined compression uniformly stretched in the transverse direction, and the bulging in the samples is negligible.

Microstructural changes in the brain after long-term post-concussion symptoms: A randomized trial

A recent randomized controlled trial in young patients with long-term post-concussion symptoms showed that a novel behavioral intervention "Get going After concussIoN" is superior to enhanced usual care in terms of symptom reduction. It is unknown whether these interventional effects are associated with microstructural brain changes. The aim of this study was to examine whether diffusion-weighted MRI indices, which are sensitive to the interactions between cellular structures and water molecules' Brownian motion, respond differently to the interventions of the above-mentioned trial and whether such differences correlate with the improvement of post-concussion symptoms. Twenty-three patients from the intervention group (mean age 22.8, 18 females) and 19 patients from the control group (enhanced usual care) (mean age 23.9, 14 females) were enrolled. The primary outcome measure was the mean kurtosis tensor, which is sensitive to the microscopic complexity of brain tissue. The mean kurtosis tensor was significantly increased in the intervention group (p = 0.003) in the corpus callosum but not in the thalamus (p = 0.78) and the hippocampus (p = 0.34). An increase in mean kurtosis tensor in the corpus callosum tended to be associated with a reduction in symptoms, but this association did not reach significance (p = 0.059). Changes in diffusion tensor imaging metrics did not differ between intervention groups and were not associated with symptoms. The current study found different diffusion-weighted MRI responses from the microscopic cellular structures of the corpus callosum between patients receiving a novel behavioral intervention and patients receiving enhanced usual care. Correlations with improvement of post-concussion symptoms were not evident.

Scale-free functional brain dynamics during recovery from sport-related concussion

Studies using blood‐oxygenation‐level‐dependent functional magnetic resonance imaging (BOLD fMRI) have characterized how the resting brain is affected by concussion. The literature to date, however, has largely focused on measuring changes in the spatial organization of functional brain networks. In the present study, changes in the temporal dynamics of BOLD signals are examined throughout concussion recovery using scaling (or fractal) analysis. Imaging data were collected for 228 university‐level athletes, 61 with concussion and 167 athletic controls. Concussed athletes were scanned at the acute phase of injury (1–7 days postinjury), the subacute phase (8–14 days postinjury), medical clearance to return to sport (RTS), 1 month post‐RTS and 1 year post‐RTS. The wavelet leader multifractal approach was used to assess scaling (c₁) and multifractal (c₂) behavior. Significant longitudinal changes were identified for c₁, which was lowest at acute injury, became significantly elevated at RTS, and returned near control levels by 1 year post‐RTS. No longitudinal changes were identified for c₂. Secondary analyses showed that clinical measures of acute symptom severity and time to RTP were related to longitudinal changes in c₁. Athletes with both higher symptoms and prolonged recovery had elevated c₁ values at RTS, while athletes with higher symptoms but rapid recovery had reduced c₁ at acute injury. This study provides the first evidence for long‐term recovery of BOLD scale‐free brain dynamics after a concussion.