Magnetoencephalographic Brain Research Articles

Magnetoencephalographic brain activity evoked by the optic-flow task is correlated with β-amyloid burden and parahippocampal atrophy

Visuospatial perception is often impaired in people with Alzheimer’s disease (AD). Because visuospatial information is thought to be processed in the visual dorsal stream, it is believed that brain activities in the dorsal stream will be altered in AD patients. In this study, we investigated whether regional brain activity related to visuospatial perception were associated with AD progression markers. An optic-flow task, which activates the dorsal stream associated with visuospatial perception, was performed, and the brain activities evoked by the task were evaluated using magnetoencephalography (MEG). First, we evaluated the responses to optic-flow stimuli in 21 cognitively unimpaired participants and determined the regions of interest (ROIs) where optic-flow activities were activated. Task-related activations were observed in 14 cortical regions including the dorsal stream: the right and left medial ventral occipital cortex (MVOcC), lateral occipital cortex (LOcC), precuneus (Pcun), inferior parietal lobule (IPL), superior parietal lobule (SPL), posterior superior temporal sulcus (pSTS), and fusiform gyri (FuG). Next, we performed correlation analyses between task-related activity in each ROI and two AD progression markers, global amyloid burden and parahippocampal gyrus (PHG) volume, for 25 participants who underwent amyloid positron emission tomography (PET) scans. We found that the global amyloid burden was negatively correlated with task-related activity in the left MVOcC and right SPL [r = -0.488 (p = 0.013) and r = -0.421 (p = 0.038), respectively]. Furthermore, significant positive correlations were observed between PHG volume and task-related activity in both the left and right SPL [r = 0.500 (p = 0.011) and r = 0.549 (p = 0.005), respectively]. Since the SPL is known to be responsible for visuospatial perception, these results suggest that MEG neuronal activity of patients performing the optic-flow activity can detect changes in brain activity associated with visuospatial impairment related to AD.

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography.

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements. Data were collected from 10 healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances/ipa/ and /api/, produced at normal and faster rates. The results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8-12 Hz) and beta band (13-30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques. These results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.

Schizophrenia MEG Network Analysis Based on Kernel Granger Causality.

Network analysis is an important approach to explore complex brain structures under different pathological and physiological conditions. In this paper, we employ the multivariate inhomogeneous polynomial kernel Granger causality (MKGC) to construct directed weighted networks to characterize schizophrenia magnetoencephalography (MEG). We first generate data based on coupled autoregressive processes to test the effectiveness of MKGC in comparison with the bivariate linear Granger causality and bivariate inhomogeneous polynomial kernel Granger causality. The test results suggest that MKGC outperforms the other two methods. Based on these results, we apply MKGC to construct effective connectivity networks of MEG for patients with schizophrenia (SCZs). We measure three network features, i.e., strength, nonequilibrium, and complexity, to characterize schizophrenia MEG. Our results suggest that MEG of the healthy controls (HCs) has a denser effective connectivity network than that of SCZs. The most significant difference in the in-connectivity strength is observed in the right frontal network (p=0.001). The strongest out-connectivity strength for all subjects occurs in the temporal area, with the most significant between-group difference in the left occipital area (p=0.0018). The total connectivity strength of the frontal, temporal, and occipital areas of HCs exhibits higher values compared with SCZs. The nonequilibrium feature over the whole brain of SCZs is significantly higher than that of the HCs (p=0.012); however, the results of Shannon entropy suggest that healthy MEG networks have higher complexity than schizophrenia networks. Overall, MKGC provides a reliable approach to construct MEG brain networks and characterize the network characteristics.

Feasibility of Magneto-Encephalography Scan under Color-Tailored Illumination

Color plays an important part in human activities, and it also affects circadian cycle and the decision making process. Therefore, it is important to investigate human judgment under different color of illumination, especially because color perception is subjective. In this study, we developed required instrumentation to control the red (R), green (G), blue (B), and amber (A) colored light emitting diode (LED) lamp for carrying out magneto-encephalography (MEG) brain scans. We developed a software to generate all the colors in the visual spectrum, predefined white light combinations and saturation of an illuminated objects by using RGBA color pallet. The lamp is required to control from outside of the MEG electromagnetically shielded room with the LED lamp located inside the MEG room. Hence, USB is used for the communication mode. The feasibility of using LED lamp with MEG brain scanner has been validated for bio-medical and psychological MEG experiments.

Neuromagnetic 40 Hz Auditory Steady-State Response in the left auditory cortex is related to language comprehension in children with Autism Spectrum Disorder

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD), but its neural mechanisms are still poorly understood. Some studies hypothesize that the atypical low-level sensory perception in the auditory cortex accounts for the abnormal language development in these children. One of the potential non-invasive measures of such low-level perception can be the cortical gamma-band oscillations registered with magnetoencephalography (MEG), and 40 Hz Auditory Steady-State Response (40 Hz ASSR) is a reliable paradigm for eliciting auditory gamma response. Although there is research in children with and without ASD using 40 Hz ASSR, nothing is known about the relationship between this auditory response in children with ASD and their language abilities measured directly in formal assessment.In the present study, we used MEG and individual brain models to investigate 40 Hz ASSR in primary-school-aged children with and without ASD. It was also used to assess how the strength of the auditory response is related to language abilities of children with ASD, their non-verbal IQ, and social functioning. A total of 40 children were included in the study.The results demonstrated that 40 Hz ASSR was reduced in the right auditory cortex in children with ASD when comparing them to typically developing controls. Importantly, our study provides the first evidence of the association between 40 Hz ASSR in the language-dominant left auditory cortex and language comprehension in children with ASD. This link was domain-specific because the other brain-behavior correlations were non-significant.

Temporally stable beta sensorimotor oscillations and corticomuscular coupling underlie force steadiness

As humans, we seamlessly hold objects in our hands, and may even lose consciousness of these objects. This phenomenon raises the unsettled question of the involvement of the cerebral cortex, the core area for voluntary motor control, in dynamically maintaining steady muscle force. To address this issue, we measured magnetoencephalographic brain activity from healthy adults who maintained a steady pinch grip. Using a novel analysis approach, we uncovered fine-grained temporal modulations in the beta sensorimotor brain rhythm and its coupling with muscle activity, with respect to several aspects of muscle force (rate of increase/decrease or plateauing high/low). These modulations preceded changes in force features by ∼40 ms and possessed behavioral relevance, as less salient or absent modulation predicted a more stable force output. These findings have consequences for the existing theories regarding the functional role of cortico-muscular coupling, and suggest that steady muscle contractions are characterized by a stable rather than fluttering involvement of the sensorimotor cortex.

Aberrant movement-related somatosensory cortical activity mediates the extent of the mobility impairments in persons with cerebral palsy.

There are numerous clinical reports showing that persons with cerebral palsy (CP) have proprioceptive, stereognosis, and tactile discrimination deficits. The current consensus is that these altered perceptions are attributable to aberrant somatosensory cortical activity. It has been inferred from these data that persons with CP do not adequately process ongoing sensory feedback during motor actions, which accentuates the extent of their mobility impairments. However, this hypothesis has yet to be directly tested. We used magnetoencephalographic brain imaging to address this knowledge gap by quantifying the somatosensory dynamics evoked by applying electrical stimulation to the tibial nerve in 22 persons with CP and 25 neurotypical controls at rest and during an ankle plantarflexion isometric force motor task. We also quantified the spatiotemporal gait biomechanics of participants outside the scanner. Consistent with the literature, our results confirmed that the strength of somatosensory cortical activity was weaker in the persons with CP compared to the neurotypical controls. Our results also showed that the strength of the somatosensory cortical responses were significantly weaker during the isometric ankle force task than at rest. Most importantly, our results showed that the strength of somatosensory cortical activity during the ankle plantarflexion force production task mediated the relationship between somatosensory cortical activity at rest and both walking velocity and step length. These results suggest that youth with CP have aberrant somatosensory cortical activity during isometric force generation, which ultimately contributes to the extent of mobility impairments seen in this patient population. KEY POINTS: Persons with cerebral palsy have reduced somatosensory cortical responses at rest and during movement. The somatosensory cortical responses during movement mediate the relationship between the somatosensory cortical responses at rest and mobility. Persons with cerebral palsy may have altered sensorimotor feedback that ultimately contributes to impaired mobility.

Altered spontaneous cortical activity predicts pain perception in individuals with cerebral palsy.

Cerebral palsy is the most common paediatric neurological disorder and results in extensive impairment to the sensorimotor system. However, these individuals also experience increased pain perception, resulting in decreased quality of life. In the present study, we utilized magnetoencephalographic brain imaging to examine whether alterations in spontaneous neural activity predict the level of pain experienced in a cohort of 38 individuals with spastic diplegic cerebral palsy and 67 neurotypical controls. Participants completed 5 min of an eyes closed resting-state paradigm while undergoing a magnetoencephalography recording. The magnetoencephalographic data were then source imaged, and the power within the delta (2–4 Hz), theta (5–7 Hz), alpha (8–12 Hz), beta (15–29 Hz), low gamma (30–59 Hz) and high gamma (60–90 Hz) frequency bands were computed. The resulting power spectral density maps were analysed vertex-wise to identify differences in spontaneous activity between groups. Our findings indicated that spontaneous cortical activity was altered in the participants with cerebral palsy in the delta, alpha, beta, low gamma and high gamma bands across the occipital, frontal and secondary somatosensory cortical areas (all pFWE < 0.05). Furthermore, we also found that the altered beta band spontaneous activity in the secondary somatosensory cortices predicted heightened pain perception in the individuals with cerebral palsy (P = 0.039). Overall, these results demonstrate that spontaneous cortical activity within individuals with cerebral palsy is altered in comparison to their neurotypical peers and may predict increased pain perception in this patient population. Potentially, changes in spontaneous resting-state activity may be utilized to measure the effectiveness of current treatment approaches that are directed at reducing the pain experienced by individuals with cerebral palsy.

Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations

Individual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have demonstrated unique characterization and accurate identification of individuals as an accomplished task. However, FC fingerprinting in magnetoencephalography (MEG) data is still widely unexplored. Here, we study resting-state MEG data from the Human Connectome Project to assess the MEG FC fingerprinting and its relationship with several factors including amplitude- and phase-coupling functional connectivity measures, spatial leakage correction, frequency bands, and behavioral significance. To this end, we first employ two identification scoring methods, differential identifiability and success rate, to provide quantitative fingerprint scores for each FC measurement. Secondly, we explore the edgewise and nodal MEG fingerprinting patterns across the different frequency bands (delta, theta, alpha, beta, and gamma). Finally, we investigate the cross-modality fingerprinting patterns obtained from MEG and fMRI recordings from the same subjects. We assess the behavioral significance of FC across connectivity measures and imaging modalities using partial least square correlation analyses. Our results suggest that fingerprinting performance is heavily dependent on the functional connectivity measure, frequency band, identification scoring method, and spatial leakage correction. We report higher MEG fingerprinting performances in phase-coupling methods, central frequency bands (alpha and beta), and in the visual, frontoparietal, dorsal-attention, and default-mode networks. Furthermore, cross-modality comparisons reveal a certain degree of spatial concordance in fingerprinting patterns between the MEG and fMRI data, especially in the visual system. Finally, the multivariate correlation analyses show that MEG connectomes have strong behavioral significance, which however depends on the considered connectivity measure and temporal scale. This comprehensive, albeit preliminary investigation of MEG connectome test-retest identifiability offers a first characterization of MEG fingerprinting in relation to different methodological and electrophysiological factors and contributes to the understanding of fingerprinting cross-modal relationships. We hope that this first investigation will contribute to setting the grounds for MEG connectome identification.

Magnetoencephalography reveals increased slow-to-fast alpha power ratios in patients with chronic pain.

Objective disease markers are a key for diagnosis and personalized interventions. In chronic pain, such markers are still not available, and therapy relies on individual patients' reports. However, several pain studies have reported group-based differences in functional magnetic resonance imaging, electroencephalography, and magnetoencephalography (MEG). We aimed to explore spectral differences in resting-state MEG brain signals between patients with chronic pain and pain-free controls and to characterize the cortical and subcortical regions involved. We estimated power spectral density over 5 minutes of resting-state MEG recordings in patients with chronic pain and controls and derived 7 spectral features at the sensor and source levels: alpha peak frequency, alpha power ratio (power 7-9 Hz divided by power 9-11 Hz), and average power in theta, alpha, beta, low-gamma, and high-gamma bands. We performed nonparametric permutation t tests (false discovery rate corrected) to assess between-group differences in these 7 spectral features. Twenty-one patients with chronic pain and 25 controls were included. No significant group differences were found in alpha peak frequency or average power in any frequency band. The alpha power ratio was significantly higher (P < 0.05) in patients with chronic pain at both the sensor and brain source levels. The brain regions showing significantly higher ratios included the occipital, parietal, temporal and frontal lobe areas, insular and cingulate cortex, and right thalamus. The alpha power ratio is a simple, promising signal marker of chronic pain, affecting an expansive range of cortical and subcortical regions, including known pain-processing areas.

Inter-Subject MEG Decoding for Visual Information with Hybrid Gated Recurrent Network

As an effective brain signal recording technique for neuroscience, magnetoencephalography (MEG) is widely used in cognitive research. However, due to the low signal-to-noise ratio and the structural or functional variabilities of MEG signals between different subjects, conventional methods perform poorly in decoding human brain responds. Inspired by deep recurrent network for processing sequential data, we applied the gated recurrent units for MEG signals processing. In the paper, we proposed a hybrid gated recurrent network (HGRN) for inter-subject visual MEG decoding. Without the need of any information from test subjects, the HGRN effectively distinguished MEG signals evoked by different visual stimulations, face and scrambled face. In the leave-one-out cross-validation experiments on sixteen subjects, our method achieved better performance than many existing methods. For more in-depth analysis, HGRN can be utilized to extract spatial features and temporal features of MEG signals. These features conformed to the previous cognitive studies which demonstrated the practicality of our method for MEG signal processing. Consequently, the proposed model can be considered as a new tool for decoding and analyzing brain MEG signal, which is significant for visual cognitive research in neuroscience.

Motor beta cortical oscillations are related with the gait kinematics of youth with cerebral palsy.

ObjectiveIt is widely believed that the perinatal brain injuries seen in youth with cerebral palsy (CP) impact neuronal processing of sensory information and the production of leg motor actions during gait. However, very limited efforts have been made to evaluate the connection between neural activity within sensorimotor networks and the altered spatiotemportal gait biomechanics seen in youth with CP. The objective of this investigation was to use magnetoencephalographic (MEG) brain imaging and biomechanical analysis to probe this connection.MethodsWe examined the cortical beta oscillations serving motor control of the legs in a cohort of youth with CP (N = 20; Age = 15.5 ± 3 years; GMFCS levels I‐III) and healthy controls (N = 15; Age = 14.1 ± 3 years) using MEG brain imaging and a goal‐directed isometric knee target‐matching task. Outside the scanner, a digital mat was used to quantify the spatiotemporal gait biomechanics.ResultsOur MEG imaging results revealed that the participants with CP exhibited stronger sensorimotor beta oscillations during the motor planning and execution stages compared to the controls. Interestingly, we also found that those with the strongest sensorimotor beta oscillations during motor execution also tended to walk slower and have a reduced cadence.InterpretationThese results fuel the impression that the beta sensorimotor cortical oscillations that underlie leg musculature control may play a central role in the altered mobility seen in youth with CP.

Neurofunctional Components of Simple Calculation: A Magnetoencephalography Study.

Our ability to calculate implies more than the sole retrieval of the correct solution. Essential processes for simple calculation are related to the spreading of activation through arithmetic memory networks. There is behavioral and electrophysiological evidence for these mechanisms. Their brain location is, however, still uncertain. Here, we measured magnetoencephalographic brain activity during the verification of simple multiplication problems. Following the operands, the solutions to verify could be preactivated correct solutions, preactivated table-related incorrect solutions, or unrelated incorrect solutions. Brain source estimation, based on these event-related fields, revealed 3 main brain networks involved in simple calculation: 1) bilateral inferior frontal areas mainly activated in response to correct, matching solutions; 2) a left-lateralized frontoparietal network activated in response to incorrect table-related solutions; and (3) a strikingly similar frontoparietal network in the opposite hemisphere activated in response to unrelated solutions. Directional functional connectivity analyses revealed a bidirectional causal loop between left parietal and frontal areas for table-related solutions, with frontal areas explaining the resolution of arithmetic competition behaviorally. Hence, this study isolated at least 3 neurofunctional networks orchestrated between hemispheres during calculation.

Decreased Task-Related HRV Is Associated With Inhibitory Dysfunction Through Functional Inter-Region Connectivity of PFC in Major Depressive Disorder.

The regulation of the autonomic nervous system (ANS) can improve cognitive function in major depressive disorders (MDD). Heart rate variability (HRV) derives from the dynamic control of the ANS and reflects the balance between the activities of the sympathetic and parasympathetic nervous systems by measuring tiny changes in adjacent heart beats. Task-related HRV may reflect the association between the flexibility of cognition and ANS function. The study was to investigate the neural mechanism of interactions between ANS and cognitive function in MDD with Magnetoencephalography (MEG) measurements. Participants included 20 MDD patients and 18 healthy controls (HCs). All participants were measured with a go/no-go task MEG. HRV indices, the standard deviation of the average normal-to-normal (NN) interval calculated over short periods (SDANN) and the square root of the mean squared differences of successive NN intervals (RMSSD), were derived from the raw MEG data. Results showed that MDD patients showed decreased SDANN and RMSSD. In MDD patients, both resting-state and task-related RMSSD were related to inhibitory and control dysfunction. In the go/no-go task, many areas in the prefrontal cortex (PFC) are responsible for an individual’s inhibitory function. A brain MEG functional connectivity analysis revealed that there were significant differences in four brain regions within the prefrontal cortex (PFC) between MDD patients and HCs. Task-related RMSSD in HCs were related to the functional connectivity between the left middle frontal gyrus and the anterior cingulate cortex (ACC), while in MDD patients, these values were not related to the above functional connectivity but were related to the functional connectivity between the left middle frontal gyrus and insula. However, the resting-state RMSSD value was not related to these significant difference functional connectivity networks in all participants. It concludes that the decreased task-related HRV is associated with inhibitory dysfunction through functional inter-region connectivity in the PFC in MDD, and the task-related HRV can be used as an index of the association between MDD and autonomic dysregulation.

Brain mechanisms in motor control during reaching movements: Transition of functional connectivity according to movement states

Understanding how the brain controls movements is a critical issue in neuroscience. The role of brain changes rapidly according to movement states. To elucidate the motor control mechanism of brain, it is essential to investigate the changes in brain network in motor-related regions according to movement states. Therefore, the objective of this study was to investigate the brain network transitions according to movement states. We measured whole brain magnetoencephalography (MEG) signals and extracted source signals in 24 motor-related areas. Functional connectivity and centralities were calculated according to time flow. Our results showed that brain networks differed between states of motor planning and movement. Connectivities between most motor-related areas were increased in the motor-planning state. In contrast, only connectivities with cerebellum and basal ganglia were increased while those of other motor-related areas were decreased during movement. Our results indicate that most processes involved in motor control are completed before movement. Further, brain developed network related to feedback rather than motor decision during movements. Our findings also suggest that neural signals during motor planning might be more predictive than neural signals during movement. They facilitate accurate prediction of movement for brain-machine interfaces and provide insight into brain mechanisms in motor control.

Autonomic Nervous System Is Related to Inhibitory and Control Function Through Functional Inter-Region Connectivities of OFC in Major Depression.

ObjectiveTo investigate the mechanism of interactions between autonomic nervous system (ANS) and cognitive function in Major depression (MD) with Magnetoencephalography (MEG) measurements.MethodsParticipants with MD (n = 20), and Health controls (HCs, n = 18) were completed MEG measurements during the performance of a go/no-go task. Heart rate variability (HRV) indices (SDANN, and RMSSD) were derived from the raw MEG data. The correlation analysis of the HRV and functional connectivities in different brain regions was conducted by Pearson’s r in two groups.ResultsThe go/no-go task performances of HCs were better than MD patients; HRV indices were lower in the MD group. Under the no-go task, a brain MEG functional connectivity analysis based on the seed regions of the orbitofrontal cortex (OFC) displayed increased functional inter-region connectivity networks of OFC in MD group. HRV indices were correlated with different functional inter-region connectivity networks of OFC in two groups, respectively.ConclusionANS is related to inhibitory and control function through functional inter-region connectivity networks of OFC in MD. These findings have important implications for the understanding pathophysiology of MD, and MEG may provide an image-guided tool for interventions.

The Strength of the Movement-related Somatosensory Cortical Oscillations Differ between Adolescents and Adults

Adolescents demonstrate increasing mastery of motor actions with age. One prevailing hypothesis is that maturation of the somatosensory system during adolescence contributes to the improved motor control. However, limited efforts have been made to determine if somatosensory cortical processing is different in adolescents during movement. In this study, we used magnetoencephalographic brain imaging to begin addressing this knowledge gap by applying an electrical stimulation to the tibial nerve as adolescents (Age = 14.8 ± 2.5 yrs.) and adults (Age = 36.8 ± 5.0 yrs.) produced an isometric ankle plantarflexion force, or sat with no motor activity. Our results showed strong somatosensory cortical oscillations for both conditions in the alpha-beta (8–30 Hz) and gamma (38–80 Hz) ranges that occurred immediately after the stimulation (0–125 ms), and a beta (18–26 Hz) oscillatory response shortly thereafter (300–400 ms). Compared with the passive condition, all of these frequency specific cortical oscillations were attenuated while producing the ankle force. The attenuation of the alpha-beta response was greater in adolescents, while the adults had a greater attenuation of the beta response. These results imply that altered attenuation of the somatosensory cortical oscillations might be central to the under-developed somatosensory processing and motor performance characteristics in adolescents.

Hand Motor Actions of Children With Cerebral Palsy Are Associated With Abnormal Sensorimotor Cortical Oscillations

Background. The neuroimaging literature on cerebral palsy (CP) has predominantly focused on identifying the structural aberrations (eg, fiber track integrity), with very few studies examining neural activity within the key networks that serve the production of hand movements. Objective. We aimed to start to fill this knowledge gap by using magnetoencephalographic brain imaging to quantify the temporal dynamics of the sensorimotor oscillations during a hand motor action. Methods: Children with CP (n = 12; MACS [Manual Abilities Classification System] levels I-III) and typically developing (TD) children (n = 26) performed an arrow-based version of the Eriksen flanker task where a button press was performed with either the second or third digit of the right hand depending on the arrow’s direction. Results: Overall, the children with CP were less accurate and had slower reaction times compared with the TD children. These behavioral differences were closely linked with aberrant sensorimotor cortical oscillations seen in the children with CP. Compared with the TD children, the children with CP had a weaker gamma (68-82 Hz) response during motor execution and a weaker post-movement beta rebound (PMBR; 14-26 Hz) response on movement termination. Moreover, we observed a significant correlation between the amplitude of the gamma and PMBR with reaction time, with weaker gamma and PMBR responses being linked with slower reaction times. Conclusions: Overall, these results suggest that aberrations in motor-related gamma and beta cortical oscillations are associated with the impaired hand motor actions seen in children with CP.

Dynamic cognitive remediation for a Traumatic Brain Injury (TBI) significantly improves attention, working memory, processing speed, and reading fluency.

Background:In the U.S. 3.8 million people have a Traumatic Brain Injury (TBI) each year. Rapid brain training exercises to improve cognitive function after a mild TBI are needed.Objective:This study determines whether cognitive remediation by discriminating the direction a test pattern moves relative to a stationary background (movement figure-ground discrimination) improves the vision and cognitive deficits that result from a TBI, providing a paradigm shift in treatment methods.Methods:Movement-discrimination neurotraining was used to remediate low-level visual timing deficits in the dorsal stream to determine whether it improved high-level cognitive functions, such as processing speed, reading fluency, and the executive control functions of attention and working memory in four men with a TBI between the ages of 15–68. Standardized tests, as well as Magnetoencephalography (MEG) brain imaging, were administered at the beginning and end of 8–16 weeks of intervention training to evaluate improvements in cognitive skills.Results:Movement-discrimination cognitive neurotraining remediated both low-level visual timing deficits and high-level cognitive functioning, including selective and sustained attention, reading fluency, processing speed, and working memory for all TBI patients we studied. MEG brain imaging, using the Fast-VESTAL procedure, showed that this movement-discrimination training improved time-locked activity in the dorsal stream, attention, and executive control networks.Conclusions:Remediating visual timing deficits in the dorsal stream revealed the causal role of visual movement discrimination training in improving high-level cognitive functions such as focusing and switching attention, working memory, processing speed, and reading. This study found that movement-discrimination training was very rapid and effective in remediating cognitive deficits, providing a new approach that is very beneficial for treating a mild TBI.

Magnetoencephalography applied to the study of Alzheimer's disease.

Magnetoencephalography (MEG) is a relatively modern neuroimaging technique able to study normal and pathological brain functioning with temporal resolution in the order of milliseconds and adequate spatial resolution. Although its clinical applications are still relatively limited, great advances have been made in recent years in the field of dementia and Alzheimer's disease (AD) in particular. In this chapter, we briefly describe the physiological phenomena underlying MEG brain signals and the different metrics that can be computed from these data in order to study the alterations disrupting brain activity not only in demented patients, but also in the preclinical and prodromal stages of the disease. Changes in non-linear brain dynamics, power spectral properties, functional connectivity and network topological changes observed in AD are narratively summarized in the context of the pathophysiology of the disease. Furthermore, the potential of MEG as a potential biomarker to identify AD pathology before dementia onset is discussed in the light of current knowledge and the relationship between potential MEG biomarkers and current established hallmarks of the disease is also reviewed. To this aim, findings from different approaches such as resting state or during the performance of different cognitive paradigms are discussed.Lastly, there is an increasing interest in current scientific literature in promoting interventions aimed at modifying certain lifestyles, such as nutrition or physical activity among others, thought to reduce or delay AD risk. We discuss the utility of MEG as a potential marker of the success of such interventions from the available literature.