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Advancements in deep learning algorithms over the past decade have led to extensive developments in brain–computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions.

In Parkinson’s disease (PD) functional changes in the brain occur years before significant cognitive symptoms manifest yet core large-scale networks that maintain cognition and predict future cognitive decline are poorly understood. The present study investigated internetwork functional connectivity of visual (VN), anterior and posterior default mode (aDMN, pDMN), left/right frontoparietal (LFPN, RFPN), and salience (SN) networks in 63 cognitively normal PD (PDCN) and 43 healthy controls who underwent resting-state functional MRI. The functional relevance of internetwork coupling topologies was tested by their correlations with baseline cognitive performance in each group and with 2-year cognitive changes in a PDCN subsample. To disentangle heterogeneity in neurocognitive functioning, we also studied whether α-synuclein (SNCA) and microtubule-associated protein tau (MAPT) variants alter internetwork connectivity and/or accelerate cognitive decline. We found that internetwork connectivity was largely preserved in PDCN, except for reduced pDMN-RFPN/LFPN couplings, which correlated with poorer baseline global cognition. Preserved internetwork couplings also correlated with domain-specific cognition but differently for the two groups. In PDCN, stronger positive internetwork coupling topologies correlated with better cognition at baseline, suggesting a compensatory mechanism arising from less effective deployment of networks that supported cognition in healthy controls. However, stronger positive internetwork coupling topologies typically predicted greater longitudinal decline in most cognitive domains, suggesting that they were surrogate markers of neuronal vulnerability. In this regard, stronger aDMN-SN, LFPN-SN, and/or LFPN-VN connectivity predicted longitudinal decline in attention, working memory, executive functioning, and visual cognition, which is a risk factor for dementia. Coupling strengths of some internetwork topologies were altered by genetic variants. PDCN carriers of the SNCA risk allele showed amplified anticorrelations between the SN and the VN/pDMN, which supported cognition in healthy controls, but strengthened pDMN-RFPN connectivity, which maintained visual memory longitudinally. PDCN carriers of the MAPT risk allele showed greater longitudinal decline in working memory and increased VN-LFPN connectivity, which in turn predicted greater decline in visuospatial processing. Collectively, the results suggest that cognition is maintained by functional reconfiguration of large-scale internetwork communications, which are partly altered by genetic risk factors and predict future domain-specific cognitive progression.

Visuospatial working memory (WM) impairments in Parkinson's disease (PD) are more prominent and evolve earlier than verbal WM deficits, suggesting some differences in underlying pathology. WM is regulated by dopaminergic neurotransmission in the prefrontal cortex, but the effect of dopamine on specific processes supporting visuospatial WM are not well understood. Dopamine therapeutic effects on different WM processes may also differ given the heterogeneity of cognitive changes in PD. The present study examined the effect of dopamine therapy on memory load and distraction during visuospatial WM. Exploratory analyses evaluated whether individual differences in medication effects were associated with a gene, catechol-O-methyltransferase (COMT), which regulates prefrontal cortex dopamine levels. Cognitively normal PD participants (n=28) and controls (n=25) performed a visuospatial WM task, which manipulated memory load and the presence/absence of distractors. PD participants performed the task on and off medication. PD COMT groups were comprised of Met homozygote (lower COMT activity) and heterozygote and Val homozygote carriers (higher COMT activity, Het/Val). The results showed that handling higher memory loads and suppressing distraction were impaired in PD off, but not on medication. Medication improved distraction resistance in Met, but not Het/Val group. COMT did not modulate medication effects on memory load. These findings demonstrate that dopaminergic therapy restores visuospatial WM processes in patients without cognitive impairment and suggest that COMT variants may partly explain the mixed effects of medication on specific processes governed by distinct brain systems. Future investigations into gene-modulated effects of medication could lead to individualized strategies for treating cognitive decline.

Decline in semantic cognition in early stages of Parkinson’s disease (PD) is a leading risk factor for future dementia, yet the underlying neural mechanisms are not understood. The present study addressed this gap by investigating the functional connectivity of regions involved in semantic recollection. We further examined whether microtubule-associated protein tau (MAPT) risk variants, which may accelerate cognitive decline, altered the strength of regional functional connections. Cognitively normal PD and healthy elder controls underwent fMRI while performing a fame-discrimination task, which activates the semantic network. Analyses focused on disturbances in fame-modulated functional connectivity in PD for regions that govern semantic recollection and interrelated processes. Group differences were found in multiple connectivity features, which were reduced into principal components that reflected the strength of fame-modulated regional couplings with other brain areas. Despite the absence of group differences in semantic cognition, two aberrant connectivity patterns were uncovered in PD. One pattern was related to a loss in frontal, parietal, and temporal connection topologies that governed semantic recollection in older controls. Another pattern was characterized by functional reconfiguration, wherein frontal, parietal, temporal and caudate couplings were strengthened with areas that were not recruited by controls. Correlations between principal component scores and cognitive measures suggested that reconfigured frontal coupling topologies in PD supported compensatory routes for accessing semantic content, whereas reconfigured parietal, temporal, and caudate connection topologies were detrimental or unrelated to cognition. Increased tau transcription diminished recruitment of compensatory frontal topologies but amplified recruitment of parietal topologies that were unfavorable for cognition. Collectively, the findings provide a new understanding of early vulnerabilities in the functional architecture of regional connectivity during semantic recollection in cognitively normal PD. The findings also have implications for tracking cognitive progression and selecting patients who stand to benefit from therapeutic interventions.

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30–80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.

Combat‐related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active‐duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep‐learning neural network method, 3D‐MEGNET, and applied it to resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat‐deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All‐frequency model, which combined delta‐theta (1–7 Hz), alpha (8–12 Hz), beta (15–30 Hz), and gamma (30–80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D‐MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver‐operator‐characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta‐theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta‐theta and gamma‐band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta‐band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all‐frequency model offered more discriminative power than each frequency‐band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders., This study developed a novel resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging method, 3D‐MEGNET, using deep learning. The optimized 3D‐MEGNET method combining rs‐MEG data from all frequency bands distinguished individuals with combat‐related mild traumatic brain injury (cmTBI) from combat‐deployed healthy controls with high sensitivity, specificity, and diagnostic accuracy. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI.

Visuospatial working memory impairments are common in Parkinson's disease (PD), yet the underlying neural mechanisms are poorly understood. The present study investigated abnormalities in context-dependent functional connectivity of working memory hubs in PD. Cognitively normal PD and control participants underwent fMRI while performing a visuospatial working memory task. To identify sources of dysfunction, distraction, and load-modulated connectivity were disentangled for encoding and retrieval phases of the task. Despite normal working memory performance in PD, two features of abnormal connectivity were observed, one due to a loss in normal context-related connectivity and another related to upregulated connectivity of hubs for which the controls did not exhibit context-dependent connectivity. During encoding, striatal-prefrontal coupling was lost in PD, both during distraction and high memory loads. However, long-range connectivity of prefrontal, medial temporal and occipital hubs was upregulated in a context-specific manner. Memory retrieval was characterized by different aberrant connectivity patterns, wherein precuneus connectivity was upregulated during distraction, whereas prefrontal couplings were lost as memory load approached capacity limits. Features of abnormal functional connectivity in PD had pathological and compensatory influences as they correlated with poorer working memory or better visuospatial skills. The results offer new insights into working memory-related signatures of aberrant cortico-cortical and corticostriatal functional connections, which may portend future declines in different facets of working memory.

Objectives Diffusivity in white-matter tracts is abnormal throughout the brain in cross-sectional studies of prodromal Huntington's disease. To date, longitudinal changes have not been observed. The present study investigated cross-sectional and longitudinal changes in white-matter diffusivity in relationship to the phase of prodromal Huntington's progression, and compared them with changes in brain volumes and clinical variables that track disease progression. Methods Diffusion MRI profiles were studied for 2 years in 37 gene-negative controls and 64 prodromal Huntington's disease participants in varied phases of disease progression. To estimate the relative importance of diffusivity metrics in the prodromal phase, group effects were rank ordered relative to those obtained from analyses of brain volumes, motor, cognitive, and sensory variables. Results First, at baseline diffusivity was abnormal throughout all tracts, especially as individuals approached a manifest Huntington's disease diagnosis. Baseline diffusivity metrics in 6 tracts and basal ganglia volumes best distinguished among the groups. Second, group differences in longitudinal change in diffusivity were localized to the superior fronto-occipital fasciculus, most prominently in individuals closer to a diagnosis. Group differences were also observed in longitudinal changes of most brain volumes, but not clinical variables. Last, increases in motor symptoms across time were associated with greater changes in the superior fronto-occipital fasciculus diffusivity and corpus callosum, cerebrospinal fluid, and lateral ventricle volumes. Conclusions These novel findings provide new insights into changes within 2 years in different facets of brain structure and their clinical relevance to changes in symptomatology that is decisive for a manifest Huntington's diagnosis. © 2016 International Parkinson and Movement Disorder Society.

Huntington disease (HD) is a neurodegenerative condition with prominent motor (including oculomotor), cognitive, and psychiatric effects. While neuropsychological deficits are present in HD, motor impairments may impact performance on neuropsychological measures, especially those requiring a speeded response, as has been demonstrated in multiple sclerosis and schizophrenia. The current study is the first to explore associations between oculomotor functions and neuropsychological performance in HD. Participants with impaired oculomotor functioning performed worse than those with normal oculomotor functioning on cognitive tasks requiring oculomotor involvement, particularly on psychomotor speed tasks, controlling for covariates. Consideration of oculomotor dysfunction on neuropsychological performance is critical, particularly for populations with motor deficits.

Deficient inhibitory control in Parkinson's disease (PD) is often observed in situations requiring inhibition of impulsive or prepotent behaviors. Although activation of the right-hemisphere frontal-basal ganglia response inhibition network is partly altered in PD, disturbances in interactions of these regions are poorly understood, especially in patients without cognitive impairment. The present study investigated context-dependent connectivity of response inhibition regions in PD patients with normal cognition and control participants who underwent fMRI while performing a stop signal task. PD participants were tested off antiparkinsonian medication. To determine if functional disturbances depended on underlying brain structure, aberrant connectivity was correlated with brain volume and white-matter tissue diffusivity. We found no group differences in response inhibition proficiency. Yet the PD group showed functional reorganization in the long-range connectivity of inhibition regions, despite preserved within network connectivity. Successful inhibition in PD differed from the controls by strengthened connectivity of cortical regions, namely the right dorsolateral prefrontal cortex, pre-supplementary motor area and right caudal inferior frontal gyrus, largely with ventral and dorsal attention regions, but also the substantia nigra and default mode network regions. Successful inhibition in controls was distinguished by strengthened connectivity of the right rostral inferior frontal gyrus and subcortical inhibition nodes (right caudate, substantia nigra, and subthalamic nucleus). In both groups, the strength of context-dependent connectivity correlated with various indices of response inhibition performance. Mechanisms that may underlie aberrantly stronger context-specific connectivity include reduced coherence within reorganized systems, compensatory mechanisms, and/or the reorganization of intrinsic networks. In PD, but not controls, abnormally strengthened connectivity was linked to individual differences in underlying brain volumes and tissue diffusivity, despite no group differences in structural variables. The pattern of structural-functional associations suggested that subtle decreases in tissue diffusivity of underlying tracts and posterior cortical volumes may undermine the enhancement of normal cortical-striatal connectivity or cause strengthening in cortical-cortical connectivity. These novel findings demonstrate that functionally reorganized interactions of inhibition regions predates the development of inhibition deficits and clinically significant cognitive impairment in PD. We speculate that altered interactions of inhibition regions with attention-related networks and the dopaminergic system may presage future decline in inhibitory control.

Cognitive, motor and psychiatric changes in prodromal Huntington’s disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington’s disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls ( n = 16) and prodromal Huntington’s disease individuals ( n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington’s disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington’s disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. * Abbreviations : AUC : area under the curve CAP : CAG–age product NBS : network-based statistic

The ability to complete daily tasks is diminished in Huntington disease (HD), an autosomal dominantly inherited neurodegenerative disorder resulting from an expansion in cytosine, adenine and guanine (CAG) bases in the HTT gene (Huntington's Disease Collaborative Research Group, 1993). Cognitive, behavioral, and motor changes all occur in HD, with cognitive changes identifiable prior to motor onset (Beglinger et al., 2010; Biglan et al., 2013; Duff et al., 2010), which is the period of prodromal HD. Functional impairment increases in prodromal HD as motor diagnosis approaches (Muthen & Muthen, 1998–2010; Paulsen et al., 2006, 2008, 2010; Tabrizi et al., 2009, 2011, 2012), impacting daily living skills, work functions, and interpersonal relationships (Downing et al., 2013; Downing, Williams, Leserman, & Paulsen, 2012; Paulsen, 2010; Williams, Downing, Vaccarino, Guttman, & Paulsen, 2011). Assessment of daily function changes in prodromal HD is important for clinical monitoring and management, as well as for tracking functional capacity in clinical trials (Beglinger et al., 2010; Paulsen et al., 2010). Previous work examining functional impairments in HD focused primarily on those who had already been given a motor diagnosis. Functional decline, as measured by the Total Functional Capacity (TFC) scale (Huntington Study Group, 1996), has been used widely in clinical trials as an outcome measure (Marder et al., 2000). Although motor impairments clearly lead to a variety of functional deficits (Brandt et al., 1984; Rothlind, Bylsma, Peyser, Folstein, & Brandt, 1993), many studies have shown cognitive and psychiatric impairments associated with HD significantly contribute to degree of functional impairment independent of motor impairments (Nehl, Paulsen, & Huntington Study Group, 2004). In particular, impairments in executive function have been associated with worsened activities of daily living (Hamilton et al., 2003). Additionally, greater degree of overall cognitive impairment has also been shown to predict rate of functional decline, such that those with greater cognitive impairment at study baseline show more rapid decline (Marder, et al., 2000). Such findings are consistent with the wider literature examining the important role of cognitive function in the ability to do daily tasks in normal aging as well as in Alzheimer disease (Benke et al., 2013; Martyr & Clare, 2012). Based on the finding that changes in everyday function can be observed in the prodromal stage of dementia – known as mild cognitive impairment (MCI) – it would be anticipated that functional changes likely accompany the very early cognitive changes occurring in prodromal HD. Indeed, recent research by our group demonstrates functional changes during the prodromal HD period (Downing et al., 2013; Paulsen et al., 2010). One obstacle to studying early functional changes in HD has been limitation of assessment methods. Instruments such as the TFC (Huntington Study Group, 1996) appear to be sensitive to changes following a motor diagnosis of HD (Marder et al., 2000) but may not have sufficient sensitivity to changes during prodromal HD (Downing et al., 2013; Paulsen et al., 2010). Further, given that cognitive impairments are among the very first signs of HD to emerge, there is a need for new functional assessment tools that specifically target cognitively-based functional abilities. Another issue relevant to measuring functional capacities in HD and prodromal HD is determining which method of ascertainment is most appropriate. Both companion and self-report of functional abilities have been used in HD and other populations. Due to the possibility of diminishing self-awareness as motor onset nears (Duff et al., 2010; Ho, Robbins, & Barker, 2006; Hoth et al., 2007), assessment from a companion may provide an important source of data. Discrepancies between participant and companion ratings in awareness of cognitive, behavioral and functional changes have been reported in those estimated to be closest to diagnosis (Downing et al., 2013; Duff et al., 2010). To address some of the gaps in knowledge about the nature of very early functional changes in prodromal HD, the present study examines self- and companion-rated everyday cognition in prodromal HD and compares ratings with the widely-used TFC. The four study aims were: (a) Compare the factor structure of the Everyday Cognition (ECog) scales (Farias et al., 2008) in a sample of people with prodromal HD to the factor structure of the original ECog using baseline data; (b) analyze baseline and longitudinal changes in participant and companion ratings of the ECog by disease progression groups; (c) compare participant and companion ratings over time in each disease progression group; and (d) assess the sensitivity of the ECog by comparison to the TFC for detecting change over the prodromal phase of HD. We hypothesized that the factor structure in the revised ECog would be similar to the original ECog. We anticipated that both participants and companions would report functional changes over time. However, we expected that companion ratings would diverge from participant ratings as participants become nearer to the time of diagnosis, owing to diminishing self-awareness in the participant group. Lastly, we expected that the ECog would be more sensitive than the TFC in detecting specific domains of daily cognitive function.

Summary Background Although the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntington's disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntington's disease. Methods In this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntington's disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntington's disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntington's Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis. Findings 1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0–12·0). 225 (21%) of these participants received a motor diagnosis of Huntington's disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26–4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37–4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88–2·87). Interpretation Prediction of diagnosis of Huntington's disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntington's disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials. Funding US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.

Mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members, Veterans, and civilians. However, few treatments are available for mTBI, partially because the mechanism of persistent mTBI deficits is not fully understood.We used magnetoencephalography (MEG) to investigate neuronal changes in individuals with mTBI following a passive neurofeedback-based treatment programme called IASIS. This programme involved applying low-intensity pulses using transcranial electrical stimulation (LIP-tES) with electroencephalography monitoring. Study participants included six individuals with mTBI and persistent post-concussive symptoms (PCS). MEG exams were performed at baseline and follow-up to evaluate the effect of IASIS on brain functioning.At the baseline MEG exam, all participants had abnormal slow-waves. In the follow-up MEG exam, the participants showed significantly reduced abnormal slow-waves with an average reduction of 53.6 ± 24.6% in slow-wave total score. The participants also showed significant reduction of PCS scores after IASIS treatment, with an average reduction of 52.76 ± 26.4% in PCS total score.The present study demonstrates, for the first time, the neuroimaging-based documentation of the effect of LIP-tES treatment on brain functioning in mTBI. The mechanisms of LIP-tES treatment are discussed, with an emphasis on LIP-tES's potentiation of the mTBI healing process.

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson’s disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.

Blast mild traumatic brain injury (mTBI) is a leading cause of sustained impairment in military service members and veterans. However, the mechanism of persistent disability is not fully understood. The present study investigated disturbances in brain functioning in mTBI participants using a source-imaging-based approach to analyze functional connectivity (FC) from resting-state magnetoencephalography (rs-MEG). Study participants included 26 active-duty service members or veterans who had blast mTBI with persistent post-concussive symptoms, and 22 healthy control active-duty service members or veterans. The source time courses from regions of interest (ROIs) were used to compute ROI to whole-brain (ROI-global) FC for different frequency bands using two different measures: 1) time-lagged cross-correlation and 2) phase-lock synchrony. Compared with the controls, blast mTBI participants showed increased ROI-global FC in beta, gamma, and low-frequency bands, but not in the alpha band. Sources of abnormally increased FC included the: 1) prefrontal cortex (right ventromedial prefrontal cortex [vmPFC], right rostral anterior cingulate cortex [rACC]), and left ventrolateral and dorsolateral prefrontal cortex; 2) medial temporal lobe (bilateral parahippocampus, hippocampus, and amygdala); and 3) right putamen and cerebellum. In contrast, the blast mTBI group also showed decreased FC of the right frontal pole. Group differences were highly consistent across the two different FC measures. FC of the left ventrolateral prefrontal cortex correlated with executive functioning and processing speed in mTBI participants. Altogether, our findings of increased and decreased regionalpatterns of FC suggest that disturbances in intrinsic brain connectivity may be the result of multiple mechanisms, and are associated with cognitive sequelae of the injury.

Subtle changes in motor function have been observed in individuals with prodromal Huntington disease (prHD), but the underlying neural mechanisms are not well understood nor is the cumulative effect of the disease (disease burden) on functional connectivity. The present study examined the resting-state functional magnetic resonance imaging (rs-fMRI) connectivity of the primary motor cortex (M1) in 16 gene-negative (NEG) controls and 48 gene-positive prHD participants with various levels of disease burden. The results showed that the strength of the left M1 connectivity with the ipsilateral M1 and somatosensory areas decreased as disease burden increased and correlated with motor symptoms. Weakened M1 connectivity within the motor areas was also associated with abnormalities in long-range connections that evolved with disease burden. In this study, M1 connectivity was decreased with visual centers (bilateral cuneus), but increased with a hub of the default mode network (DMN; posterior cingulate cortex). Changes in connectivity measures were associated with worse performance on measures of cognitive–motor functioning. Short- and long-range functional connectivity disturbances were also associated with volume loss in the basal ganglia, suggesting that weakened M1 connectivity is partly a manifestation of striatal atrophy. Altogether, the results indicate that the prodromal phase of HD is associated with abnormal interhemispheric interactions among motor areas and disturbances in the connectivity of M1 with visual centers and the DMN. These changes may, respectively, contribute to increased motor symptoms, visuomotor integration problems, and deficits in the executive control of movement as individuals approach a manifest diagnosis.

The ability to reach for and dynamically manipulate objects in a dexterous fashion requires scaling and coordination of arm, hand, and fingertip forces during reach and grasp components of this behavior. The neural substrates underlying dynamic object manipulation are not well understood. Insight into the role of basal ganglia-thalamocortical circuits in object manipulation can come from the study of patients with Parkinson's disease (PD). We hypothesized that scaling and coordination aspects of motor control are differentially affected by this disorder. We asked 20 PD patients and 23 age-matched control subjects to reach for, grasp, and lift virtual objects along prescribed paths. The movements were subdivided into two types, intensive (scaling) and coordinative, by detecting their underlying self-similarity. PD patients off medication were significantly impaired relative to control subjects for both aspects of movement. Intensive deficits, reduced peak speed and aperture, were seen during the reach. Coordinative deficits were observed during the reach, namely, the relative position along the trajectory at which peak speed and aperture were achieved, and during the lift, when objects tilted with respect to the gravitational axis. These results suggest that basal ganglia-thalamocortical circuits may play an important role in fine motor coordination. Dopaminergic therapy significantly improved intensive but not coordinative aspects of movements. These findings are consistent with a framework in which tonic levels of dopamine in the dorsal striatum encode the energetic cost of a movement, thereby improving intensive or scaling aspects of movement. However, repletion of brain dopamine levels does not restore finely coordinated movement.

This study investigated the ability of individuals with Parkinson’s disease (PD) to synthesize temporal information across the senses, namely audition and vision. Auditory signals (A) are perceived as lasting longer than visual signals (V) when they are compared together, since attention is captured and sustained more easily than for visual information. We used the audiovisual illusion to probe for disturbances in brain networks that govern the resolution of time in two intersensory conditions that putatively differ in their attention demands. PD patients and controls judged the relative duration of successively presented pairs of unimodal (AA, VV) and crossmodal (VA, AV) signals whilst undergoing fMRI. There were four main findings. First, underestimation of time was exaggerated in PD when timing depended on controlled attention (AV), whereas subtle deficits were found when audition dominated and attention was more easily sustained (VA). Second, group differences in regional activation were observed only for the AV-unimodal comparison, where the PD group failed to modulate basal ganglia, anterior insula, and inferior cerebellum activity in accord with the timing condition. Third, the intersensory timing conditions were dissociated by patterns of abnormal functional connectivity. When intersensory timing emphasized controlled attention, patients showed weakened connectivity of the cortico-thalamus-basal ganglia (CTBG) circuit and the anterior insula with widespread cortical regions, yet enhanced cerebellar connectivity. When audition dominated intersensory timing, patients showed enhanced connectivity of CTBG elements, the anterior insula, and the cerebellum with the caudate tail and frontal cortex. Fourth, abnormal connectivity measures showed excellent sensitivity and specificity in accurately classifying subjects. The results demonstrate that intersensory timing deficits in PD were well characterized by context-dependent patterns of functional connectivity within a presumed core timing system (CTBG) and a ventral attention hub (anterior insula), and enhanced cerebellar connectivity irrespective of the hypothesized attention demands of timing.

Introduction The brain mechanisms of cognitive impairment in prodromal Huntington disease (prHD) are not well understood. Although striatal atrophy correlates with some cognitive abilities, few studies of prHD have investigated whether cortical gray matter morphometry correlates in a regionally specific manner with functioning in different cognitive domains. This knowledge would inform the selection of cognitive measures for clinical trials that would be most sensitive to the target of a treatment intervention. Method In this study, random forest analysis was used to identify neuroanatomical correlates of functioning in five cognitive domains including attention and information processing speed, working memory, verbal learning and memory, negative emotion recognition, and temporal processing. Participants included 325 prHD individuals with varying levels of disease progression and 119 gene-negative controls with a family history of HD. In intermediate analyses, we identified brain regions that showed significant differences between the prHD and the control groups in cortical thickness and striatal volume. Brain morphometry in these regions was then correlated with cognitive functioning in each of the domains in the prHD group using random forest methods. We hypothesized that different regional patterns of brain morphometry would be associated with performances in distinct cognitive domains. Results The results showed that performances in different cognitive domains that are vulnerable to decline in prHD were correlated with regionally specific patterns of cortical and striatal morphometry. Putamen and/or caudate volumes were top-ranked correlates of performance across all cognitive domains, as was cortical thickness in regions related to the processing demands of each domain. Conclusions The results underscore the importance of identifying structural magnetic resonance imaging (sMRI) markers of functioning in different cognitive domains, as their relative sensitivity depends on the extent to which processing is called upon by different brain networks. The findings have implications for identifying neuroimaging and cognitive outcome measures for use in clinical trials.

A challenge in Parkinson's disease (PD) is to identify biomarkers of early cognitive change because functioning in some domains may be more prognostic of dementia. Few studies have investigated whether structural magnetic resonance imaging (MRI) correlates in a regionally specific manner with functioning in different cognitive domains. The aim of this study was to identify neuroanatomical correlates of executive functioning, memory, and visual cognition in PD without dementia. 3T MRI was conducted in 51 PD patients and 39 control participants. Brain volumes were measured in structures comprising the frontostriatal cognitive-control system, the medial temporal memory system, the ventral object-based system, and the dorsal spatial-based system. Measures of executive functioning (Stroop Test; Letter Fluency), memory (California Verbal Learning Test), visuospatial cognition (Judgment of Line Orientation), and visuoconstruction (Pentagon Copy) were correlated with volumes comprising each system. Poorer executive functioning largely correlated with decreased frontostriatal volumes. Poorer memory correlated with decreased volumes in all medial temporal regions, but also with frontostriatal volumes. Poorer visuospatial cognition correlated with decreased volumes in the object-based system, whereas poorer visuoconstruction correlated with decreased frontal and object-based system volumes. These relationships were nonsignificant in the control group. This is the first study to demonstrate that subtle changes in multiple cognitive domains in PD without dementia correlate with regional volumes in specific systems implicated in the development of cognitive impairment. The findings suggest that structural MRI holds promise as a marker of early changes in different brain systems, some of which may predict future cognitive deterioration.

Our research group recently demonstrated that a person with tetraplegia could use a brain-computer interface (BCI) to control a sophisticated anthropomorphic robotic arm with skill and speed approaching that of an able-bodied person. This multiyear study exemplifies important principles in translating research from foundational theory and animal experiments into a clinical study. We present a roadmap that may serve as an example for other areas of clinical device research as well as an update on study results. Prior to conducting a multiyear clinical trial, years of animal research preceded BCI testing in an epilepsy monitoring unit, and then in a short-term (28 days) clinical investigation. Scientists and engineers developed the necessary robotic and surgical hardware, software environment, data analysis techniques, and training paradigms. Coordination among researchers, funding institutes, and regulatory bodies ensured that the study would provide valuable scientific information in a safe environment for the study participant. Finally, clinicians from neurosurgery, anesthesiology, physiatry, psychology, and occupational therapy all worked in a multidisciplinary team along with the other researchers to conduct a multiyear BCI clinical study. This teamwork and coordination can be used as a model for others attempting to translate basic science into real-world clinical situations.

The medial cortico-striatal-thalamo-cortical (CSTC) motor circuit is a core system that exerts control over interval timing and action. A common network generates these behaviors possibly owing to cellular coding of temporal and non-temporal information, which in turn promotes reconfiguration of functional connectivity in accord with behavioral goals. At the neuroanatomical level, support for flexible CSTC reconfiguration comes from studies of temporal illusions demonstrating that this system calibrates the experience of time through functional interactions with various context-sensitive brain regions. Revelations that CSTC effective connectivity is pivotal for context-dependent facets of voluntary actions, namely action planning, complement its role in predictive processes such as timing. These observations suggest that the CSTC is positioned to represent high-level information about ‘what to do’ and ‘when to do it’ by dynamically reconfiguring effective connectivity as circumstances arise.

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. Injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1–4 Hz) that can be measured and localized by magnetoencephalography (MEG). We developed a new automated MEG low-frequency source imaging method and applied this method in 45 mild TBI (23 from combat-related blasts, and 22 from non-blast causes) and 10 moderate TBI patients (non-blast causes). Seventeen of the patients with mild TBI from blasts had tertiary injuries resulting from the blast. The results show our method detected abnormalities at the rates of 87% for the mild TBI group (blast-induced plus non-blast causes) and 100% for the moderate group. Among the mild TBI patients, the rates of abnormalities were 96% and 77% for the blast and non-blast TBI groups, respectively. The spatial characteristics of abnormal slow-wave generation measured by Z scores in the mild blast TBI group significantly correlated with those in non-blast mild TBI group. Among 96 cortical regions, the likelihood of abnormal slow-wave generation was less in the mild TBI patients with blast than in the mild non-blast TBI patients, suggesting possible protective effects due to the military helmet and armor. Finally, the number of cortical regions that generated abnormal slow-waves correlated significantly with the total post-concussive symptom scores in TBI patients. This study provides a foundation for using MEG low-frequency source imaging to support the clinical diagnosis of TBI.

Beamformer spatial filters are commonly used to explore the active neuronal sources underlying magnetoencephalography (MEG) recordings at low signal-to-noise ratio (SNR). Conventional beamformer techniques are successful in localizing uncorrelated neuronal sources under poor SNR conditions. However, the spatial and temporal features from conventional beamformer reconstructions suffer when sources are correlated, which is a common and important property of real neuronal networks. Dual-beamformer techniques, originally developed by Brookes et al. to deal with this limitation, successfully localize highly-correlated sources and determine their orientations and weightings, but their performance degrades at low correlations. They also lack the capability to produce individual time courses and therefore cannot quantify source correlation. In this paper, we present an enhanced formulation of our earlier dual-core beamformer (DCBF) approach that reconstructs individual source time courses and their correlations. Through computer simulations, we show that the enhanced DCBF (eDCBF) consistently and accurately models dual-source activity regardless of the correlation strength. Simulations also show that a multi-core extension of eDCBF effectively handles the presence of additional correlated sources. In a human auditory task, we further demonstrate that eDCBF accurately reconstructs left and right auditory temporal responses and their correlations. Spatial resolution and source localization strategies corresponding to different measures within the eDCBF framework are also discussed. In summary, eDCBF accurately reconstructs source spatio-temporal behavior, providing a means for characterizing complex neuronal networks and their communication.

We examined the Trail Making Test (TMT) in a sample of 767 participants with prodromal Huntington disease (prodromal HD) and 217 healthy comparisons to determine the contributions of motor, psychiatric, and cognitive changes to TMT scores. Eight traditional and derived TMT scores were also evaluated for their ability to differentiate prodromal participants closer to estimated age of diagnosis from those farther away and prodromal individuals from healthy comparisons. Results indicate that motor signs only mildly affected part A, and psychiatric symptoms did not affect either part. Tests of perceptual processing, visual scanning, and attention were primarily associated with part A, and executive functioning (response inhibition, set-shifting), processing speed, and working memory were associated with part B. Additionally, TMT scores differentiated between healthy comparisons and prodromal HD individuals as far as 9–15 years before estimated diagnosis. In participants manifesting prodromal motor signs and psychiatric symptoms, the TMT primarily measures cognition and is able to discriminate between groups based on health status and estimated time to diagnosis.

The orienting of attention to different locations in space is fundamental to most organisms and occurs in all sensory modalities. Orienting has been extensively studied in vision, but to date, few studies have investigated neuronal networks underlying automatic orienting of attention and inhibition of return to auditory signals. In the current experiment, functional magnetic resonance imaging and behavioral data were collected while healthy volunteers performed an auditory orienting task in which a monaurally presented tone pip (cue) correctly or incorrectly cued the location of a target tone pip. The stimulus onset asynchrony (SOA) between the cue and target was 100 or 800 msec. Behavioral results were consistent with previous studies showing that valid auditory cues produced facilitation at the short SOA and inhibition of return at the long SOA. Functional results indicated that the reorienting of attention (100 msec SOA) and inhibition of return (800 msec SOA) were mediated by both common and distinct neuronal structures. Both attention mechanisms commonly activated a network consisting of fronto-oculomotor areas, the left postcentral gyrus, right premotor area, and bilateral tonsil of the cerebellum. Several distinct areas of frontal and parietal activation were identified for the reorienting condition, whereas the right inferior parietal lobule was the only structure uniquely associated with inhibition of return.

Author(s): Pirogovsky-Turk, Eva; Filoteo, J Vincent; Litvan, Irene; Harrington, Deborah L | Abstract: BackgroundChanges in episodic memory are common early in Parkinson's disease (PD) and may be a risk factor for future cognitive decline. Although medial temporal lobe (MTL) memory and frontostriatal (FS) executive systems are thought to play different roles in distinct components of episodic memory impairment in PD, no study has investigated whether different aspects of memory functioning are differentially associated with MTL and FS volumes in nondemented patients without mild cognitive impairment (PD-woMCI).ObjectivesThe present study investigated MRI markers of different facets of memory functioning in 48 PD-woMCI patients and 42 controls.MethodsRegional volumes were measured in structures comprising the MTL and FS systems and then correlated with key indices of memory from the California Verbal Learning Test.ResultsIn PD-woMCI patients, memory was impaired only for verbal learning, which was not associated with executive, attention/working memory, or visuospatial functioning. Despite an absence of cortical atrophy, smaller right MTL volumes in patients were associated with poorer verbal learning, long delayed free recall, long delayed cued recall, and recognition memory hits and false positives. Smaller right pars triangularis (inferior frontal) volumes were also associated with poorer long delayed cued recall and recognition memory hits. These relationships were not found in controls.ConclusionsThe findings indicate that MTL volumes are sensitive to subtle changes in almost all facets of memory in PD-woMCI, whereas FS volumes are sensitive only to memory performances in cued-testing formats.

Concussion, or mild traumatic brain injury (mTBI), can cause persistent behavioral symptoms and cognitive impairment, but it is unclear if this condition is associated with detectable structural or functional brain changes. At two sites, chronic mTBI human subjects with persistent post-concussive symptoms (three months to five years after injury) and age- and education-matched healthy human control subjects underwent extensive neuropsychological and visual tracking eye movement tests. At one site, patients and controls also performed the visual tracking tasks while blood-oxygen-level-dependent (BOLD) signals were measured with functional magnetic resonance imaging. Although neither neuropsychological nor visual tracking measures distinguished patients from controls at the level of individual subjects, abnormal BOLD signals were reliably detected in patients. The most consistent changes were localized in white matter regions: anterior internal capsule and superior longitudinal fasciculus. In contrast, BOLD signals were normal in cortical regions, such as the frontal eye field and intraparietal sulcus, that mediate oculomotor and attention functions necessary for visual tracking. The abnormal BOLD signals accurately differentiated chronic mTBI patients from healthy controls at the single-subject level, although they did not correlate with symptoms or neuropsychological performance. We conclude that subjects with persistent post-concussive symptoms can be identified years after their TBI using fMRI and an eye movement task despite showing normal structural MRI and DTI.

Minimum L1-norm solutions have been used by many investigators to analyze MEG responses because they provide high spatial resolution images. However, conventional minimum L1-norm approaches suffer from instability in spatial construction, and poor smoothness of the reconstructed source time-courses. Activity commonly “jumps” from one grid point to (usually) the neighboring grid points. Equivalently, the time-course of one specific grid point can show substantial “spiky-looking” discontinuity. In the present study, we present a new vector-based spatial–temporal analysis using a L1-minimum-norm (VESTAL). This approach is based on a principle of MEG physics: the magnetic waveforms in sensor-space are linear functions of the source time-courses in the imaging-space. Our computer simulations showed that VESTAL provides good reconstruction of the source amplitude and orientation, with high stability and resolution in both the spatial and temporal domains. “Spiky-looking” discontinuity was not observed in the source time-courses. Importantly, the simulations also showed that VESTAL can resolve sources that are 100% correlated. We then examined the performance of VESTAL in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguishes sources very spatially close to each other, including individual primary somatosensory areas (BA 1, 2, 3b), primary motor area (BA 4), and other regions in the somatosensory system (e.g., BA 5, 7, SII, SMA, and temporal–parietal junction) with high temporal stability and resolution. VESTAL's potential for obtaining information on source extent was also examined.

Previous studies using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) of the brain have found that a distributed parietal-frontal neuronal network is activated in normals during both auditory and visual oddball tasks. The common cortical regions in this network are inferior parietal lobule (IPL)/supramarginal gyrus (SMG), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). It is not clear whether the same network is activated by oddball tasks during somatosensory stimulation. The present study addressed this question by testing healthy adults as they performed a novel median-nerve oddball paradigm while undergoing magnetoencephalography (MEG). An automated multiple dipole analysis technique, the Multi-Start Spatio-Temporal (MSST) algorithm, localized multiple neuronal generators, and identified their time-courses. IPL/SMG, ACC, and DLPFC were reliably localized in the MEG median-nerve oddball responses, with IPL/SMG activation significantly preceding ACC and DLPFC activation. Thus, the same parietal-frontal neuronal network that shows activation during auditory and visual oddball tests is activated in a median-nerve oddball paradigm. Regions uniquely related to somatosensory oddball responses (e.g., primary and secondary somatosensory, dorsal premotor, primary motor, and supplementary motor areas) were also localized. Since the parietal-frontal network supports attentional allocation during performance of the task, this study may provide a novel method, as well as normative baseline data, for examining attention-related deficits in the somatosensory system of patients with neurological or psychiatric disorders.

Motor skill learning depends upon acquiring knowledge about multiple features of sequential behaviors, including their visuomotor and spatial properties. To investigate the neural systems that distinguish these representations, we carried out functional magnetic resonance imaging (fMRI) as healthy adults learned to type sequences on a novel keyboard. On the initial training day, learning‐related changes in brain activation were found in distributed cortical regions, only a subset of which correlated with improvements in movement time (MT), suggesting their preeminence in controlling movements online. Subjects received extended training on the sequences during the ensuing week, after which they returned to the scanner for another imaging session. Relative to performance at the end of the first training day, continued plasticity was most striking in the inferior parietal cortex and new areas of plasticity were uncovered in the caudate and cerebellum. Plasticity in these regions correlated with reaction time (RT), suggesting their role in planning sequences before movement onset. Two transfer conditions probed for “what” subjects learned. The probe for visuomotor learning produced increased activation in visual analysis (left inferior visual cortex) and advance planning (left caudate) systems. The probe for spatial learning produced increased activation in visuomotor‐transformation (left dorsal visual pathway) and retrieval (left precuneus) systems. Increased activity in all of these regions correlated with increased RT, but not MT, indicating that both transfer conditions interfered with the neural representation of plans for the sequences, but not processes that controlled their implementation. These findings demonstrated that neuroanatomically dissociable systems support the acquisition of visuomotor and spatial representations of actions. Hum Brain Mapping 24:229–247, 2005. © 2004 Wiley‐Liss, Inc.

Our perception of time depends on multiple psychological processes that allow us to anticipate events. In this study, we used event-related functional magnetic resonance imaging (fMRI) to differentiate neural systems involved in formulating representations of time from processes associated with making decisions about their duration. A time perception task consisting of two randomly presented standard intervals was used to ensure that intervals were encoded on each trial and to enhance memory requirements. During the encoding phase of a trial, activation was observed in the right caudate nucleus, right inferior parietal cortex and left cerebellum. Activation in these regions correlated with timing sensitivity (coefficient of variation). In contrast, encoding-related activity in the right parahippocampus and hippocampus correlated with the bisection point and right precuneus activation was associated with a measure of memory distortion. Decision processes were studied by examining brain activation during the decision phase of a trial that was associated with the difficulty of interval discriminations. Activation in the right parahippocampus was greater for easier than harder discriminations. In contrast, activation was greater for harder than easier discriminations in systems involved in working memory (left middle-frontal and parietal cortex) and auditory rehearsal (left inferior-frontal and superior-temporal cortex). Activity in the auditory rehearsal network correlated with memory distortion. Our results support the independence of systems that mediate interval encoding and decision processes. The results also suggest that distortions in memory for time may be due to strategic processing in cortical systems involved in either encoding or rehearsal.

The role of motor activity ipsilateral to movement remains a matter of debate, due in part to discrepancies among studies in the localization of this activity, when observed, and uncertainty about its time course. The present study used magnetoencephalography (MEG) to investigate the spatial localization and temporal dynamics of contralateral and ipsilateral motor activity during the preparation of unilateral finger movements. Eight right‐handed normal subjects carried out self‐paced finger‐lifting movements with either their dominant or nondominant hand during MEG recordings. The Multi‐Start Spatial Temporal multi‐dipole method was used to analyze MEG responses recorded during the movement preparation and early execution stage (−800 msec to +30 msec) of movement. Three sources were localized consistently, including a source in the contralateral primary motor area (M1) and in the supplementary motor area (SMA). A third source ipsilateral to movement was located significantly anterior, inferior, and lateral to M1, in the premotor area (PMA) (Brodmann area [BA] 6). Peak latency of the SMA and the ipsilateral PMA sources significantly preceded the peak latency of the contralateral M1 source by 60 msec and 52 msec, respectively. Peak dipole strengths of both the SMA and ipsilateral PMA sources were significantly weaker than was the contralateral M1 source, but did not differ from each other. Altogether, the results indicated that the ipsilateral motor activity was associated with premotor function, rather than activity in M1. The time courses of activation in SMA and ipsilateral PMA were consistent with their purported roles in planning movements. Hum. Brain Mapp. 23:26–39, 2004. © 2004 Wiley‐Liss, Inc.

A number of beamformers have been introduced to localize neuronal activity using magnetoencephalography (MEG) and electroencephalography (EEG). However, currently available information about the major aspects of existing beamformers is incomplete. In the present study, detailed analyses are performed to study the commonalities and differences among vectorized versions of existing beamformers in both theory and practice. In addition, a novel beamformer based on higher-order covariance analysis is introduced. Theoretical formulas are provided on all major aspects of each beamformer; to examine their performance, computer simulations with different levels of correlation and signal-to-noise ratio are studied. Then, an empirical data set of human MEG median-nerve responses with a large number of neuronal generators is analyzed using the different beamformers. The results show substantial differences among existing MEG/EEG beamformers in their ways of describing the spatial map of neuronal activity. Differences in performance are observed among existing beamformers in terms of their spatial resolution, false-positive background activity, and robustness to highly correlated signals. Superior performance is obtained using our novel beamformer with higher-order covariance analysis in simulated data. Excellent agreement is also found between the results of our beamformer and the known neurophysiology of the median-nerve MEG response.

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI., Highlights • A voxel-based whole-brain MEG slow-wave source imaging method for mild TBI. • The new approach showed 84.5% positive detection rate in 84 mild TBI patients. • The new approach detected loci of injury in mild TBI patients on a single-subject basis. • MEG slow-wave source imaging revealed brain areas vulnerable to mild TBI. • MEG slow-wave generations correlated with mild TBI symptoms.

The frontal and parietal cortex are intimately involved in the representation of goal-directed movements, but the crucial neuroanatomical sites are not well established in humans. In order to identify these sites more precisely, we studied stroke patients who had the classic syndrome of ideomotor limb apraxia, which disrupts goal-directed movements, such as writing or brushing teeth. Patients with and without limb apraxia were identified by assessing errors imitating gestures and specifying a cut-off for apraxia relative to a normal control group. We then used MRI or CT for lesion localization and compared areas of overlap in those patients with and without limb apraxia. Patients with ideomotor limb apraxia had damage lateralized to a left hemispheric network involving the middle frontal gyrus and intraparietal sulcus region. Thus, the results revealed that discrete areas in the left hemisphere of humans are critical for control of complex goal-directed movements.

Ideomotor limb apraxia is a classic neurological disorder manifesting as a breakdown in co-ordinated limb control with spatiotemporal deficits. We employed kinematic analyses of simple aiming movements in left hemisphere-damaged patients with and without limb apraxia and a normal control group to examine preprogramming and response implementation deficits in apraxia. Damage to the frontal and parietal lobes was more common in apraxics, but neither frontal nor parietal damage was associated with different arm movement deficits. Limb apraxia was associated with intact preprogramming but impaired response implementation. The response implementation deficits were characterized by spatial but not temporal deficits, consistent with decoupling of spatial and temporal features of movement in limb apraxia. While the apraxics' accuracy was normal when visual feedback was available, it was impaired when visual feedback of either target location or hand position was unavailable. This finding suggests that ideomotor limb apraxia is associated with disruption of the neural representations for the extrapersonal (spatial location) and intrapersonal (hand position) features of movement. The non-apraxic group's normal kinematic performance demonstrates that the deficits demonstrated in the apraxic group are not simply a reflection of left hemisphere damage per se.