EEG Complexity Analysis of Brain States, Tasks and ASD Risk.

Autism spectrum disorder is an increasingly prevalent and debilitating neurodevelopmental condition and an electroencephalogram (EEG) diagnostic challenge. Despite large amounts of electrophysiological research over many decades, an EEG biomarker for autism spectrum disorder (ASD) has not been found. We hypothesized that reductions in complex dynamical system behaviour in the human central nervous system as part of the macroscale neuronal function during cognitive processes might be detectable in whole EEG for higher-risk ASD adults. In three studies, we compared the medians of correlation dimension, largest Lyapunov exponent, Higuchi's fractal dimension, multiscale entropy, multifractal detrended fluctuation analysis and Kolmogorov complexity during resting, cognitive and social skill tasks in 20 EEG channels of 39 adults over a range of ASD risk. We found heterogeneous complexity distribution with clusters of hierarchical sequences pointing to potential cognitive processing differences, but no clear distinction based on ASD risk. We suggest that there is indication of statistically significant differences between complexity measures of brain states and tasks. Though replication of our studies is needed with a larger sample, we believe that our electrophysiological and analytic approach has potential as a biomarker for earlier ASD diagnosis.

Acute exercise as a modifier of neocortical plasticity and aperiodic activity in the visual cortex.

Long-term potentiation (LTP) is a form of neuroplasticity commonly implicated in mechanistic models of learning and memory. Acute exercise can boost LTP in the motor cortex, and is associated with a shift in excitation/inhibition (E:I) balance, but whether this extends to other regions such as the visual cortex is unknown. We investigated the effect of a preceding bout of exercise on LTP induction and the E:I balance in the visual cortex using electroencephalography (EEG). Young adults (N = 20, mean age = 24.20) engaged in 20 min of high-intensity interval training (HIIT) exercise and rest across two counterbalanced sessions. LTP was induced using a high frequency presentation of a visual stimulus; a "visual tetanus". Established EEG markers of visual LTP, the N1b and P2 component of the visual evoked potential, and an EEG-derived measure of the E:I balance, the aperiodic exponent, were measured before and after the visual tetanus. As expected, there was a potentiation of the N1b following the visual tetanus, with specificity to the tetanised stimulus, and a non-specific potentiation of the P2. These effects were not sensitive to a preceding bout of exercise. However, the E:I balance showed a late shift towards inhibition following the visual tetanus. A preceding bout of exercise resulted in specificity of this E:I balance shift to the tetanised stimulus, that was not seen following rest. This novel finding suggests a possible exercise-induced tuning of the visual cortex to stimulus details following LTP induction.

Altered structural connectome of children with auditory processing disorder: a diffusion MRI study.

Auditory processing disorder (APD) is a listening impairment that some school-aged children may experience despite having normal peripheral hearing. Recent resting-state functional magnetic resonance imaging (MRI) has revealed an alteration in regional functional brain topology in children with APD. However, little is known about the structural organization in APD. We used diffusion MRI data to investigate the structural connectome of 58 children from 8 to 14 years old diagnosed with APD (n = 29) and children without hearing complaints (healthy controls, HC; n = 29). We investigated the rich-club organization and structural connection differences between groups. The APD group showed similar rich-club organization and edge-wise connection compared with the HC group. However, at the regional level, we observed increased average path length (APL) and betweenness centrality in the right inferior parietal lobule and inferior precentral gyrus, respectively, in the APD group. Only HCs demonstrated a positive association between APL and the listening-in-spatialized-noise-sentences task in the left orbital gyrus. In line with previous findings, the current results provide evidence for altered structural networks at the regional level in the APD group, suggesting the involvement of multimodal deficits and a role for structure-function alteration in the listening difficulties of children with APD.

Altered brain network topology in children with auditory processing disorder: A resting-state multi-echo fMRI study.

Children with auditory processing disorder (APD) experience hearing difficulties, particularly in the presence of competing sounds, despite having normal audiograms. There is considerable debate on whether APD symptoms originate from bottom-up (e.g., auditory sensory processing) and/or top-down processing (e.g., cognitive, language, memory). A related issue is that little is known about whether functional brain network topology is altered in APD. Therefore, we used resting-state functional magnetic resonance imaging data to investigate the functional brain network organization of 57 children from 8 to 14 years old, diagnosed with APD (n = 28) and without hearing difficulties (healthy control, HC; n = 29). We applied complex network analysis using graph theory to assess the whole-brain integration and segregation of functional networks and brain hub architecture. Our results showed children with APD and HC have similar global network properties -i.e., an average of all brain regions- and modular organization. Still, the APD group showed different hub architecture in default mode-ventral attention, somatomotor and frontoparietal-dorsal attention modules. At the nodal level -i.e., single-brain regions-, we observed decreased participation coefficient (PC - a measure quantifying the diversity of between-network connectivity) in auditory cortical regions in APD, including bilateral superior temporal gyrus and left middle temporal gyrus. Beyond auditory regions, PC was also decreased in APD in bilateral posterior temporo-occipital cortices, left intraparietal sulcus, and right posterior insular cortex. Correlation analysis suggested a positive association between PC in the left parahippocampal gyrus and the listening-in-spatialized-noise -sentences task where APD children were engaged in auditory perception. In conclusion, our findings provide evidence of altered brain network organization in children with APD, specific to auditory networks, and shed new light on the neural systems underlying children's listening difficulties.

Reproducibility and repeatability of magnetic resonance imaging in dementia.

PURPOSE: Individualised predictive models of cognitive decline require disease-monitoring markers that are repeatable. For wide-spread adoption, such markers also need to be reproducible at different locations. This study assessed the repeatability and reproducibility of MRI markers derived from a dementia protocol. METHODS: Six participants were scanned at three different sites with a 3T MRI scanner. The protocol employed: T1-weighted (T1w) imaging, resting state functional MRI (rsfMRI), arterial spin labelling (ASL), diffusion-weighted imaging (DWI), T2-weighted fluid attenuation inversion recovery (FLAIR), T2-weighted (T2w) imaging, and susceptibility weighted imaging (SWI). Participants were scanned repeatedly, up to six times over a maximum period of five years. One participant was also scanned a further three times on sequential days on one scanner. Fifteen derived metrics were computed from the seven different modalities. RESULTS: Reproducibility (coefficient of variation; CoV, across sites) was best for T1w derived grey matter, white matter and hippocampal volume (CoV < 1.5%), compared to rsfMRI and SWI derived metrics (CoV, 19% and 21%). For a given metric, long-term repeatability (CoV across time) was comparable to reproducibility, with short-term repeatability considerably better. CONCLUSIONS: Reproducibility and repeatability were assessed for a suite of markers calculated from a dementia MRI protocol. In general, structural markers were less variable than functional MRI markers. Variability over time on the same scanner was comparable to variability measured across different scanners. Overall, the results support the viability of multi-site longitudinal studies for monitoring cognitive decline.

Task-Modulated Oscillation Differences in Auditory and Spoken Chinese-English Bilingual Processing: An Electroencephalography Study.

Neurophysiological research on the bilingual activity of interpretation or interpreting has been very fruitful in understanding the bilingual brain and has gained increasing popularity recently. Issues like word interpreting and the directionality of interpreting have been attended to by many researchers, mainly with localizing techniques. Brain structures such as the dorsolateral prefrontal cortex have been repeatedly identified during interpreting. However, little is known about the oscillation and synchronization features of interpreting, especially sentence-level overt interpreting. In this study we implemented a Chinese-English sentence-level overt interpreting experiment with electroencephalography on 43 Chinese-English bilinguals and compared the oscillation and synchronization features of interpreting with those of listening, speaking and shadowing. We found significant time-frequency power differences in the delta-theta (1-7 Hz) and gamma band (above 30 Hz) between motor and silent tasks. Further theta-gamma coupling analysis revealed different synchronization networks in between speaking, shadowing and interpreting, indicating an idea-formulation dependent mechanism. Moreover, interpreting incurred robust right frontotemporal gamma coactivation network compared with speaking and shadowing, which we think may reflect the language conversion process inherent in interpreting.

A callosal biomarker of behavioral intervention outcomes for autism spectrum disorder? A case-control feasibility study with diffusion tensor imaging.

Tentative results from feasibility analyses are critical for planning future randomized control trials (RCTs) in the emerging field of neural biomarkers of behavioral interventions. The current feasibility study used MRI-derived diffusion imaging data to investigate whether it would be possible to identify neural biomarkers of a behavioral intervention among people diagnosed with autism spectrum disorder (ASD). The corpus callosum has been linked to cognitive processing and callosal abnormalities have been previously found in people diagnosed with ASD. We used a case-control design to evaluate the association between the type of intervention people diagnosed with ASD had previously received and their current white matter integrity in the corpus callosum. Twenty-six children and adolescents with ASD, with and without a history of parent-managed behavioral intervention, underwent an MRI scan with a diffusion data acquisition sequence. We conducted tract-based spatial statistics and a region of interest analysis. The fractional anisotropy values (believed to indicate white matter integrity) in the posterior corpus callosum was significantly different across cases (exposed to parent-managed behavioral intervention) and controls (not exposed to parent-managed behavioral intervention). The effect was modulated by the intensity of the behavioral intervention according to a dose-response relationship. The current feasibility case-control study provides the basis for estimating the statistical power required for future RCTs in this field. In addition, the study demonstrated the effectiveness of purposely-developed motion control protocols and helped to identify regions of interest candidates. Potential clinical applications of diffusion tensor imaging in the evaluation of treatment outcomes in ASD are discussed.

Spatial variation of perfusion MRI reflects cognitive decline in mild cognitive impairment and early dementia.

Cerebral blood flow (CBF) measured with arterial spin labelling (ASL) magnetic resonance imaging (MRI) reflects cerebral perfusion, related to metabolism, and arterial transit time (ATT), related to vascular health. Our aim was to investigate the spatial coefficient of variation (sCoV) of CBF maps as a surrogate for ATT, in volunteers meeting criteria for subjective cognitive decline (SCD), amnestic mild cognitive impairment (MCI) and probable Alzheimer's dementia (AD). Whole-brain pseudo continuous ASL MRI was performed at 3 T in 122 participants (controls = 20, SCD = 44, MCI = 45 and AD = 13) across three sites in New Zealand. From CBF maps that included all grey matter, sCoV progressively increased across each group with increased cognitive deficit. A similar overall trend was found when examining sCoV solely in the temporal lobe. We conclude that sCoV, a simple to compute imaging metric derived from ASL MRI, is sensitive to varying degrees of cognitive changes and supports the view that vascular health contributes to cognitive decline associated with Alzheimer's disease.

Right frontal anxiolytic-sensitive EEG 'theta' rhythm in the stop-signal task is a theory-based anxiety disorder biomarker.

Psychiatric diagnoses currently rely on a patient's presenting symptoms or signs, lacking much-needed theory-based biomarkers. Our neuropsychological theory of anxiety, recently supported by human imaging, is founded on a longstanding, reliable, rodent 'theta' brain rhythm model of human clinical anxiolytic drug action. We have now developed a human scalp EEG homolog-goal-conflict-specific rhythmicity (GCSR), i.e., EEG rhythmicity specific to a balanced conflict between goals (e.g., approach-avoidance). Critically, GCSR is consistently reduced by different classes of anxiolytic drug and correlates with clinically-relevant trait anxiety scores (STAI-T). Here we show elevated GCSR in student volunteers divided, after testing, on their STAI-T scores into low, medium, and high (typical of clinical anxiety) groups. We then tested anxiety disorder patients (meeting diagnostic criteria) and similar controls recruited separately from the community. The patient group had higher average GCSR than their controls-with a mixture of high and low GCSR that varied with, but cut across, conventional disorder diagnosis. Consequently, GCSR scores should provide the first theoretically-based biomarker that could help diagnose, and so redefine, a psychiatric disorder.

Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia.

BACKGROUND: Longitudinal neuroimaging provides spatiotemporal brain data (STBD) measurement that can be utilised to understand dynamic changes in brain structure and/or function underpinning cognitive activities. Making sense of such highly interactive information is challenging, given that the features manifest intricate temporal, causal relations between the spatially distributed neural sources in the brain. METHODS: The current paper argues for the advancement of deep learning algorithms in brain-inspired spiking neural networks (SNN), capable of modelling structural data across time (longitudinal measurement) and space (anatomical components). The paper proposes a methodology and a computational architecture based on SNN for building personalised predictive models from longitudinal brain data to accurately detect, understand, and predict the dynamics of an individual's functional brain state. The methodology includes finding clusters of similar data to each individual, data interpolation, deep learning in a 3-dimensional brain-template structured SNN model, classification and prediction of individual outcome, visualisation of structural brain changes related to the predicted outcomes, interpretation of results, and individual and group predictive marker discovery. RESULTS: To demonstrate the functionality of the proposed methodology, the paper presents experimental results on a longitudinal magnetic resonance imaging (MRI) dataset derived from 175 older adults of the internationally recognised community-based cohort Sydney Memory and Ageing Study (MAS) spanning 6 years of follow-up. SIGNIFICANCE: The models were able to accurately classify and predict 2 years ahead of cognitive decline, such as mild cognitive impairment (MCI) and dementia with 95% and 91% accuracy, respectively. The proposed methodology also offers a 3-dimensional visualisation of the MRI models reflecting the dynamic patterns of regional changes in white matter hyperintensity (WMH) and brain volume over 6 years. CONCLUSION: The method is efficient for personalised predictive modelling on a wide range of neuroimaging longitudinal data, including also demographic, genetic, and clinical data. As a case study, it resulted in finding predictive markers for MCI and dementia as dynamic brain patterns using MRI data.

The role of Hebbian learning in human perception: a methodological and theoretical review of the human Visual Long-Term Potentiation paradigm.

Long-term potentiation (LTP) is one of the most widely studied forms of neural plasticity, and is thought to be the principle mechanism underlying long-term memory and learning in the brain. Sensory paradigms utilising electroencephalography (EEG) and sensory stimulation to induce LTP have allowed translation from rodent and primate invasive research to non-invasive human investigations. This review focusses on visual sensory LTP induced using repetitive visual stimulation, resulting in changes in the visually evoked response recorded at the scalp with EEG. Across 15 years of use and replication in humans several major paradigm variants for eliciting visual LTP have emerged. The application of different paradigms, and the broad implementation of visual LTP across different populations combines to provide a rich and sensitive account of Hebbian LTP, and potentially non-Hebbian plasticity mechanisms. This review will conclude with a discussion of how these findings have advanced existing theories of perceptual learning by positioning Hebbian learning both alongside and within other major theories such as Predictive Coding and The Free Energy Principle.

Ketamine Enhances Visual Sensory Evoked Potential Long-term Potentiation in Patients With Major Depressive Disorder.

BACKGROUND: The rapid-acting clinical effects of ketamine as a novel treatment for depression along with its complex pharmacology have made it a growing research area. One of the key mechanistic hypotheses for how ketamine works to alleviate depression is by enhancing long-term potentiation (LTP)-mediated neural plasticity. METHODS: The objective of this study was to investigate the plasticity hypothesis in 30 patients with depression noninvasively using visual LTP as an index of neural plasticity. In a double-blind, active placebo-controlled crossover trial, electroencephalography-based LTP was recorded approximately 3 to 4 hours following a single 0.44-mg/kg intravenous dose of ketamine or active placebo (1.7 ng/mL remifentanil) in 30 patients. Montgomery-Åsberg Depression Rating Scale scores were used to measure clinical symptoms. Visual LTP was measured as a change in the visually evoked potential following high-frequency visual stimulation. Dynamic causal modeling investigated the underlying neural architecture of visual LTP and the contribution of ketamine. RESULTS: Montgomery-Åsberg Depression Rating Scale scores revealed that 70% of participants experienced 50% or greater reduction in their depression symptoms within 1 day of receiving ketamine. LTP was demonstrated in the N1 (p = .00002) and P2 (p = 2.31 × 10-11) visually evoked components. Ketamine specifically enhanced P2 potentiation compared with placebo (p = .017). Dynamic causal modeling replicated the recruitment of forward and intrinsic connections for visual LTP and showed complementary effects of ketamine indicative of downstream and proplasticity modulation. CONCLUSIONS: This study provides evidence that LTP-based neural plasticity increases within the time frame of the antidepressant effects of ketamine in humans and supports the hypothesis that changes to neural plasticity may be key to the antidepressant properties of ketamine.

Methamphetamine induces neuronal death: Evidence from rodent studies.

Animal studies have consistently observed neuronal death following methamphetamine (MA) administration, however, these have not been systematically reviewed. This systematic review aims to present the evidence for MA-induced neuronal death in animals (rodents) and identify the regions affected. Locating the brain regions in which neuronal death occurs in animal studies will provide valuable insight into the linkage between MA consumption and the structural alterations observed in the human brain. The data were collected from three databases: Scopus, Ovid, and the Web of Science. Thirty-seven studies met the inclusion criteria and were divided into two sub-groups, i.e. acute and repeated administration. Twenty-six (of 27) acute and ten (of 11) repeated administration studies observed neuronal death. A meta-analysis was not possible due to different variables between studies, i.e. species, treatment regimens, withdrawal periods, methods of quantification, and regions studied. Acute MA treatment induced neuronal death in the frontal cortex, striatum, and substantia nigra, but not in the hippocampus, whereas repeated MA administration led to neuronal loss in the hippocampus, frontal cortex, and striatum. In addition, when animals self-administered the drug, neuronal death was observed at much lower doses than the doses administered by experimenters. There is some overlap in the regions where neuronal death occurred in animals and the identified regions from human studies. For instance, gray matter deficits have been observed in the prefrontal cortex and hippocampus of MA users. The findings presented in this review implicate that not only does MA induce neuronal death in animals, but it also damages the same regions affected in human users. Despite the inter-species differences, animal studies have contributed significantly to addiction research, and are still of great assistance for future research with a more relevant model of compulsive drug use in humans.

The brain-derived neurotrophic factor Val66Met genotype does not influence the grey or white matter structures underlying recognition memory.

A single nucleotide polymorphism (SNP) in the gene coding for brain-derived neurotrophic factor (BDNF) has previously been associated with a reduction in recognition memory performance. While previous findings have highlighted that this SNP contributes to recognition memory, little is known about its influence on subprocesses of recognition, familiarity and recollection. Previous research has reported reduced hippocampal volume and decreased fractional anisotropy in carriers of the Met allele across a range of white matter tracts, including those networks that may support recognition memory. Here, in a sample of 61 healthy young adults, we used a source memory task to measure accuracy on each recognition subprocess, in order to determine whether the Val66Met SNP (rs6265) influences these equally. Additionally, we compared grey matter volume between these groups for structures that underpin familiarity and recollection separately. Finally, we used probabilistic tractography to reconstruct tracts that subserve each of these two recognition systems. Behaviourally, we found group differences on the familiarity measure, but not on recollection. However, we did not find any group difference on grey- or white-matter structures. Together, these results suggest a functional influence of the Val66Met SNP that is independent of coarse structural changes, and nuance previous research highlighting the relationship between BDNF, brain structure, and behaviour.

Human Sensory LTP Predicts Memory Performance and Is Modulated by the BDNF Val66Met Polymorphism.

Background: Long-term potentiation (LTP) is recognised as a core neuronal process underlying long-term memory. However, a direct relationship between LTP and human memory performance is yet to be demonstrated. The first aim of the current study was thus to assess the relationship between LTP and human long-term memory performance. With this also comes an opportunity to explore factors thought to mediate the relationship between LTP and long-term memory. The second aim of the current study was to explore the relationship between LTP and memory in groups differing with respect to brain-derived neurotrophic factor (BDNF) Val66Met; a single-nucleotide polymorphism (SNP) implicated in memory function. Methods: Participants were split into three genotype groups (Val/Val, Val/Met, Met/Met) and were presented with both an EEG paradigm for inducing LTP-like enhancements of the visually-evoked response, and a test of visual memory. Results: The magnitude of LTP 40 min after induction was predictive of long-term memory performance. Additionally, the BDNF Met allele was associated with both reduced LTP and reduced memory performance. Conclusions: The current study not only presents the first evidence for a relationship between sensory LTP and human memory performance, but also demonstrates how targeting this relationship can provide insight into factors implicated in variation in human memory performance. It is anticipated that this will be of utility to future clinical studies of disrupted memory function.

Mental Simulation of Facial Expressions: Mu Suppression to the Viewing of Dynamic Neutral Face Videos.

The mirror neuron network (MNN) has been proposed as a neural substrate of action understanding. Electroencephalography (EEG) mu suppression has commonly been studied as an index of MNN activity during execution and observation of hand and finger movements. However, in order to establish its role in higher order processes, such as recognizing and sharing emotions, more research using social emotional stimuli is needed. The current study aims to contribute to our understanding of the sensitivity of mu suppression to facial expressions. Modulation of the mu and occipital alpha (8-13 Hz) rhythms was calculated in 22 participants while they observed dynamic video stimuli, including emotional (happy and sad) and neutral (mouth opening) facial expressions, and non-biological stimulus (kaleidoscope pattern). Across the four types of stimuli, only the neutral face was associated with a significantly stronger mu suppression than the non-biological stimulus. Occipital alpha suppression was significantly greater in the non-biological stimulus than all the face conditions. Source estimation standardized low resolution electromagnetic tomography (sLORETA) analysis comparing the neural sources of mu/alpha modulation between neutral face and non-biological stimulus showed more suppression in the central regions, including the supplementary motor and somatosensory areas, than the more posterior regions. EEG and source estimation results may indicate that reduced availability of emotional information in the neutral face condition requires more sensorimotor engagement in deciphering emotion-related information than the full-blown happy or sad expressions that are more readily recognized.

Hex Maze: A new virtual maze able to track acquisition and usage of three navigation strategies.

Spatial navigation is a complex and multi-faceted skill that, in humans, is understood to encompass two distinct navigational strategies, namely allocentric and egocentric navigation. These differ in the frame of reference used and the brain networks activated. However, egocentric navigation can be further divided into two, equally distinct strategies depending on whether the navigator is using subject-to-object relations (egocentric-cue) or direction of body turns (egocentric-response) to navigate. To date, there are no experimental paradigms able to distinguish between participants' employment of allocentric, egocentric-cue and egocentric-response strategies, and to track their usage over time. The current study presents the Hex Maze: a novel virtual environment that can not only distinguish between the three navigational strategies, but can also be used to index aspects of strategy use such as preference, acquisition, stability and competence. To illustrate this, 32 male and 32 female participants were presented with the Hex Maze and sex differences in strategy usage were explored. While the results offer some support for previously identified sex differences in strategy preference, there were no significant sex differences in the novel measures of strategy acquisition, stability, or multi-strategy competence. Additionally, our results suggest that strategy preference does not preclude learning to competently navigate using other strategies. Importantly, the current study offers validation for the Hex Maze as an unbiased method of exploring spatial navigation, and it is anticipated that this easy-to-use tool will be valuable across research and clinical settings.

Musical training increases functional connectivity, but does not enhance mu suppression.

Musical training provides an ideal platform for investigating action representation for sound. Learning to play an instrument requires integration of sensory and motor perception-action processes. Functional neuroimaging studies have indicated that listening to trained music can result in the activity in premotor areas, even after a short period of training. These studies suggest that action representation systems are heavily dependent on specific sensorimotor experience. However, others suggest that because humans naturally move to music, sensorimotor training is not necessary and there is a more general action representation for music. We previously demonstrated that EEG mu suppression, commonly implemented to demonstrate mirror-neuron-like action representation while observing movements, can also index action representations for sounds in pianists. The current study extends these findings to a group of non-musicians who learned to play randomised sequences on a piano, in order to acquire specific sound-action mappings for the five fingers of their right hand. We investigated training-related changes in neural dynamics as indexed by mu suppression and task-related coherence measures. To test the specificity of training effects, we included sounds similar to those encountered in the training and additionally rhythm sequences. We found no effect of training on mu suppression between pre- and post-training EEG recordings. However, task-related coherence indexing functional connectivity between electrodes over audiomotor areas increased after training. These results suggest that long-term training in musicians and short-term training in novices may be associated with different stages of audiomotor integration that can be reflected in different EEG measures. Furthermore, the changes in functional connectivity were specifically found for piano tones, and were not apparent when participants listened to rhythms, indicating some degree of specificity related to training.

High-intensity training enhances executive function in children in a randomized, placebo-controlled trial.

Background: Exercise-induced cognitive improvements have traditionally been observed following aerobic exercise interventions; that is, sustained sessions of moderate intensity. Here, we tested the effect of a 6 week high-intensity training (HIT) regimen on measures of cognitive control and working memory in a multicenter, randomized (1:1 allocation), placebo-controlled trial. Methods: 318 children aged 7-13 years were randomly assigned to a HIT or an active control group matched for enjoyment and motivation. In the primary analysis, we compared improvements on six cognitive tasks representing two cognitive constructs (N = 305). Secondary outcomes included genetic data and physiological measurements. Results: The 6-week HIT regimen resulted in improvements on measures of cognitive control [BFM = 3.38, g = 0.31 (0.09, 0.54)] and working memory [BFM = 5233.68, g = 0.54 (0.31, 0.77)], moderated by BDNF genotype, with met66 carriers showing larger gains post-exercise than val66 homozygotes. Conclusions: This study suggests a promising alternative to enhance cognition, via short and potent exercise regimens. Funding: Funded by Centre for Brain Research. Clinical trial number: NCT03255499.

Exercise has beneficial effects on the body and brain. People who perform well on tests of cardiovascular fitness also do well on tests of learning, memory and other cognitive skills. So far, studies have suggested that moderate intensity aerobic exercise that lasts for 30 to 40 minutes produces the greatest improvements in these brain abilities. Recently, short high-intensity workouts that combine cardiovascular exercise and strength training have become popular. Studies have shown that these brief bouts of strenuous exercise improve physical health, but do these benefits extend to the brain? It would also be helpful to know if the effect that exercise has on the brain depends on an individual's genetic makeup or physical health. This might help to match people to the type of exercise that will work best for them. Now, Moreau et al. show that just 10 minutes of high-intensity exercise a day over six weeks can boost the cognitive abilities of children. In the experiments, over 300 children between 7 and 13 years of age were randomly assigned to one of two groups: one that performed the high-intensity exercises, or a 'control' group that took part in less active activities ­ such as quizzes and playing computer games ­ over the same time period. The children who took part in the high-intensity training showed greater improvements in cognitive skills than the children in the control group. Specifically, the high-intensity exercise boosted working memory and left the children better able to focus on specific tasks, two skills that are important for academic success. Moreau et al. further found that the high-intensity exercises had the most benefit for the children who needed it most ­ those with poor cardiovascular health and those with gene variants that are linked to poorer cognitive skills. This suggests that genetic differences do alter the effects of exercise on the brain, but also shows that targeted exercise programs can offer everyone a chance to thrive. Moreau et al. suggest that exercise need not be time consuming to boost brain health; the key is to pack more intense exercise in shorter time periods. Further work could build on these findings to produce effective exercise routines that could ultimately form part of school curriculums, as well as proving useful to anyone who wishes to improve their cognitive skills.