Atypical paroxysmal slow cortical activity in healthy adults: Relationship to age and cognitive performance

Paroxysmal patterns of slow cortical activity have been detected in EEG recordings from individuals with age-related neuropathology and have been shown to be correlated with cognitive dysfunction and blood-brain barrier disruption in these participants. The prevalence of these events in healthy participants, however, has not been studied. In this work, we inspect MEG recordings from 623 healthy participants from the Cam-CAN dataset for the presence of paroxysmal slow wave events (PSWEs). PSWEs were detected in approximately 20% of healthy participants in the dataset, and participants with PSWEs tended to be older and have lower cognitive performance than those without PSWEs. In addition, event features changed linearly with age and cognitive performance, resulting in longer and slower events in older adults, and more widespread events in those with low cognitive performance. These findings provide the first evidence of PSWEs in a subset of purportedly healthy adults. Going forward, these events may have utility as a diagnostic biomarker for atypical brain activity in older adults.

Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset

Human neuromagnetic activity is characterised by a complex combination of transient bursts with varying spatial and temporal characteristics. The characteristics of these transient bursts change during task performance and normal ageing in ways that can inform about underlying cortical sources. Many methods have been proposed to detect transient bursts, with the most successful ones being those that employ multi-channel, data-driven approaches to minimize bias in the detection procedure. There has been little research, however, into the application of these data-driven methods to large datasets for group-level analyses. In the current work, we apply a data-driven convolutional dictionary learning (CDL) approach to detect neuromagnetic transient bursts in a large group of healthy participants from the Cam-CAN dataset. CDL was used to extract repeating spatiotemporal motifs in 538 participants between the ages of 18-88 during a sensorimotor task. Motifs were then clustered across participants based on similarity, and relevant task-related clusters were analysed for age-related trends in their spatiotemporal characteristics. Seven task-related motifs resembling known transient burst types were identified through this analysis, including beta, mu, and alpha type bursts. All burst types showed positive trends in their activation levels with age that could be explained by increasing burst rate with age. This work validated the data-driven CDL approach for transient burst detection on a large dataset and identified robust information about the complex characteristics of human brain signals and how they change with age.

Age-related trends in the cortical sources of transient beta bursts during a sensorimotor task and rest

Interpreting neurophysiology recordings as a series of transient bursts with varying temporal and spectral characteristics provides meaningful insight into mechanisms underlying neural networks. Previous research has revealed age-related changes in the time-frequency dynamics of sensorimotor beta bursts, but to date, there has been little focus on the spatial localization of these beta bursts or how the localization patterns change with normal healthy ageing. The objective of the current study is to implement existing source localization algorithms for use in the detection of the cortical sources of transient beta bursts, and to uncover age-related trends in the resulting source localization patterns. Two well-established source localization algorithms (minimum-norm estimation and beamformer) were applied to localize beta bursts detected over the sensorimotor cortices in a cohort of 561 healthy participants between the ages of 18 and 88 (CamCAN open access dataset). Age-related trends were then investigated by applying regression analysis between participant age and average source power within several cortical regions of interest. This analysis revealed that beta bursts localized primarily to the sensorimotor cortex ipsilateral to the side of the sensor used for their detection. Region of interest analysis revealed that there were age-related changes in the beta burst localization pattern, with most substantial changes evidenced in frontal brain regions. In addition, regression analysis revealed a tendency of age-related trends to peak around 60 years of age suggesting that 60 is a potential critical age in this population. These results show for the first time that source localization techniques can be implemented for the identification of the sources of transient beta bursts. The exploration of these sources provides us with insight into the anatomical generators of transient beta activity and how they change across the lifespan.

Age-related trends in neuromagnetic transient beta burst characteristics during a sensorimotor task and rest in the Cam-CAN open-access dataset

Non-invasive neurophysiological recordings, such as those measured by magnetoencelography (MEG), provide insight into the behaviour of neural networks and how these networks change with factors such as task performance, disease state, and age. Recently, there has been a trend in describing neurophysiological recordings as a series of transient bursts of neural activity rather than averaged sustained oscillations as burst characteristics may be more directly correlated with the neurological generators of brain activity. In this work, we investigate how beta burst characteristics change with age in a large open access dataset. The objectives are (1) to detect and characterize transient beta bursts over the ipsilateral and contralateral primary sensorimotor cortices during a unilateral motor task performance and during wakeful resting, and (2) to identify age-related changes in beta burst characteristics, in the context of earlier reports of age-related changes in beta suppression and the post-movement beta rebound. MEG data, acquired at the Cambridge Centre for Ageing and Neuroscience, of roughly 600 participants with a nearly uniform distribution of ages between 18 and 88 years old was used for analysis. We found that burst rate is the predominant factor related to age-related changes in the amplitude of the induced beta rhythm responses associated with a button press task. Furthermore, we present a cross-validation of burst parameters detected at the sensor- (peak sensor and sensor ROI) and source-level (beamformer spatial filter). This work is as an important step in characterizing transient bursts in neuromagnetic signals in the temporal domain, towards a better understanding of the healthy aging human brain.

Variability and bias between magnetoencephalography systems in localization of the primary visual cortex

OBJECTIVES

When using MEG for pre-surgical mapping it is critically important that reliable estimates of functional locations, such as the primary visual cortex (V1) can be provided. Several different models of MEG systems exist, each with varying software and hardware configurations, and it is not currently known how the system type contributes to variability in V1 localization.

PATIENTS AND METHODS

In this study, participants underwent MEG sessions using two different systems (Vector View and CTF) during which they were presented with a repeating grating stimulus to the lower-left visual quadrant to generate a visual evoked field (VEF). The location, amplitude and latency of the VEF source was compared between systems for each participant.

RESULTS

No significant differences were found in latency and amplitude between systems, however, a significant bias in the latero-medial position of the localization was present. The median inter-system Euclidian distance between V1 localization across participants was 10.5 mm.

CONCLUSIONS

Overall, our results indicate that mapping of V1 can be reliably reproduced within approximately one centimetre by different MEG systems.

SIGNIFICANCE

This result provides knowledge of the useful limits on the reliability of localization which can be taken into consideration in clinical practice.

Probing the temporal dynamics of movement inhibition in motor imagery

Beyond the lack of overt movement in motor imagery (MI), MI is thought to be functionally equivalent to motor execution (ME). Two theories appear viable to explain the neural mechanism underlying the inhibition of movement in MI, with one suggesting the inhibition of movement in MI occurs early in the planning process, and the other suggesting it occurs after the planning for movement is compete. Here we sought to generate evidence related to the timing of movement inhibition in MI. Participants performed a motor task via MI and ME that had distinct preparation and performance phases, with brain activity obtained throughout. Analysis of sensor-level data was performed to isolate event related desynchrony (ERD) in the mu and beta frequency bands in both a sensorimotor and left parietal region of interest (ROI). The magnitude of ERD in the sensorimotor ROI was significantly greater in ME than MI during both the preparatory and performance phases. The reduced ERD in the mu and beta frequency bands in the sensorimotor ROI during the preparatory phase for MI, compared to ME, suggests that movement planning is inhibited (or at least reduced) in MI, contributing to the lack of movement. While past work has shown that the networks of functional brain activity underlying MI and ME are heavily overlapping, differences in the temporal dynamics of this activity suggest that MI and ME are not equivalent processes.

Evidence for age-related changes in sensorimotor neuromagnetic responses during cued button pressing in a large open-access dataset

Mu, beta, and gamma rhythms increase and decrease in amplitude during movement. This event-related synchronization (ERS) and desynchronization (ERD) can be readily recorded non-invasively using magneto- and electro-encephalography (M/EEG). In addition, event-related potentials and fields (i.e., evoked responses) can be elucidated during movement. There is some evidence that the frequency, amplitude and latency of the movement-related ERS/ERD changes with ageing, however the evidence surrounding this topic comes mainly from studies in sample sizes on the order of tens of participants. The objective of this study was to examine a large open-access MEG dataset for age-related changes in movement-related ERS/ERD and evoked responses. MEG data acquired at the Cambridge Centre for Ageing and Neuroscience during cued button pressing was used from 567 participants between the ages of 18 and 88 years. The characteristics movement-related ERD/ERS and evoked responses were calculated for each individual participant. Based on linear regression analysis, significant relationships were found between participant age and some response characteristics, although the predictive value of these relationships was low. Specifically, we conclude that peak beta rebound frequency and amplitude decreased with age, peak beta suppression amplitude increased with age, movement-related gamma burst amplitude decreased with age, and peak motor-evoked response amplitude increased with age. Given our current understanding of the underlying mechanisms of these responses, our findings suggest the existence of age-related changes in the neurophysiology of thalamocortical loops and local circuitry in the primary somatosensory and motor cortices.

Variability and bias between magnetoencephalography systems in non-invasive localization of the primary somatosensory cortex

OBJECTIVES

Magnetoencephalography (MEG) provides functional neuroimaging data for pre-surgical planning in patients with epilepsy or brain tumour. For mapping the primary somatosensory cortex (S1), MEG data are acquired while a patient undergoes median nerve stimulation (MNS) to localize components of the somatosensory evoked field (SEF). In clinical settings, only one MEG imaging session is usually possible due to limited resources. As such, it is important to have an a priori estimate of the expected variability in localization. Variability in S1 localization between mapping sessions using the same MEG system has been previously measured as 8 mm. There are different types of MEG systems available with varied hardware and software, and it is not known how using a different MEG system will impact on S1 localization.

PATIENTS AND METHODS

In our study, healthy participants underwent the MNS procedure with two different MEG systems (Vector View and CTF). We compared the location, amplitude and latency of SEF components between data from each system to quantify variability and bias between MEG systems.

RESULTS

We found 8-11 mm variability in S1 localization between the two MEG systems, and no evidence for a systematic bias in location, amplitude or latency between the two systems.

CONCLUSION

These findings suggest that S1 localization is not biased by the type of MEG system used, and that differences between the two systems are not a major contributor to variability in localization.

The impact of goal-oriented task design on neurofeedback learning for brain-computer interface control

Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain-computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented task design. Participants were shown either a visual display or a robot, where each was manipulated using motor imagery (MI)-related electroencephalography signals. Those with the robot were instructed to quickly navigate grid spaces, as the potential for goal-oriented design to strengthen learning was central to our investigation. Both groups were hypothesized to show increased magnitude of these signals across 10 sessions, with the greatest gains being seen in those navigating the robot due to increased engagement. Participants demonstrated the predicted increase in magnitude, with no differentiation between hemispheres. Participants navigating the robot showed stronger left-hand MI increases than those with the computer display. This is likely due to success being reliant on maintaining strong MI-related signals. While older participants showed stronger signals in early sessions, this trend later reversed, suggesting greater natural proficiency but reduced flexibility. These results demonstrate capacity for modulating neurofeedback using MI over a series of training sessions, using tasks of varied design. Importantly, the more goal-oriented robot control task resulted in greater improvements.

Combined Action Observation and Motor Imagery Neurofeedback for Modulation of Brain Activity

Motor imagery (MI) and action observation have proven to be efficacious adjuncts to traditional physiotherapy for enhancing motor recovery following stroke. Recently, researchers have used a combined approach called imagined imitation (II), where an individual watches a motor task being performed, while simultaneously imagining they are performing the movement. While neurofeedback (NFB) has been used extensively with MI to improve patients' ability to modulate sensorimotor activity and enhance motor recovery, the effectiveness of using NFB with II to modulate brain activity is unknown. This project tested the ability of participants to modulate sensorimotor activity during electroencephalography-based II-NFB of a complex, multi-part unilateral handshake, and whether this ability transferred to a subsequent bout of MI. Moreover, given the goal of translating findings from NFB research into practical applications, such as rehabilitation, the II-NFB system was designed with several user interface and user experience features, in an attempt to both drive user engagement and match the level of challenge to the abilities of the subjects. In particular, at easy difficulty levels the II-NFB system incentivized contralateral sensorimotor up-regulation (via event related desynchronization of the mu rhythm), while at higher difficulty levels the II-NFB system incentivized sensorimotor lateralization (i.e., both contralateral up-regulation and ipsilateral down-regulation). Thirty-two subjects, receiving real or sham NFB attended four sessions where they engaged in II-NFB training and subsequent MI. Results showed the NFB group demonstrated more bilateral sensorimotor activity during sessions 2–4 during II-NFB and subsequent MI, indicating mixed success for the implementation of this particular II-NFB system. Here we discuss our findings in the context of the design features included in the II-NFB system, highlighting limitations that should be considered in future designs.

Head movement compensation in real-time magnetoencephalographic recordings

Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimation This work explains the technical details and validates each of these steps.

Faster and improved 3-D head digitization in MEG using Kinect

Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant's structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices—Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows—for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (1 min compared to 3 min) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20–30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in the NextEngine laser scan (~1 min). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.

Laterality of brain activity during motor imagery is modulated by the provision of source level neurofeedback

Motor imagery (MI) may be effective as an adjunct to physical practice for motor skill acquisition. For example, MI is emerging as an effective treatment in stroke neurorehabilitation. As in physical practice, the repetitive activation of neural pathways during MI can drive short- and long-term brain changes that underlie functional recovery. However, the lack of feedback about MI performance may be a factor limiting its effectiveness. The provision of feedback about MI-related brain activity may overcome this limitation by providing the opportunity for individuals to monitor their own performance of this endogenous process. We completed a controlled study to isolate neurofeedback as the factor driving changes in MI-related brain activity across repeated sessions. Eighteen healthy participants took part in 3 sessions comprised of both actual and imagined performance of a button press task. During MI, participants in the neurofeedback group received source level feedback based on activity from the left and right sensorimotor cortex obtained using magnetoencephalography. Participants in the control group received no neurofeedback. MI-related brain activity increased in the sensorimotor cortex contralateral to the imagined movement across sessions in the neurofeedback group, but not in controls. Task performance improved across sessions but did not differ between groups. Our results indicate that the provision of neurofeedback during MI allows healthy individuals to modulate regional brain activity. This finding has the potential to improve the effectiveness of MI as a tool in neurorehabilitation.

State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network

Functional connectivity measures applied to magnetoencephalography (MEG) data have the capacity to elucidate neuronal networks. However, the task-related modulation of these measures is essential to identifying the functional relevance of the identified network. In this study, we provide evidence for the efficacy of measuring "state-related" (i.e., task vs. rest) changes in MEG functional connectivity for revealing a sensorimotor network. We investigate changes in functional connectivity, measured as cortico-cortical coherence (CCC), between rest blocks and the performance of a visually directed motor task in a healthy cohort. Task-positive changes in CCC were interpreted in the context of any concomitant modulations in spectral power. Task-related increases in whole-head CCC relative to the resting state were identified between areas established as part of the sensorimotor network as well as frontal eye fields and prefrontal cortices, predominantly in the beta and gamma frequency bands. This study provides evidence for the use of MEG to identify task-specific functionally connected sensorimotor networks in a non-invasive, patient friendly manner.

Spatial MEG laterality maps for language: clinical applications in epilepsy

Functional imaging is increasingly being used to provide a noninvasive alternative to intracarotid sodium amobarbitol testing (i.e., the Wada test). Although magnetoencephalography (MEG) has shown significant potential in this regard, the resultant output is often reduced to a simplified estimate of laterality. Such estimates belie the richness of functional imaging data and consequently limit the potential value. We present a novel approach that utilizes MEG data to compute "complex laterality vectors" and consequently "laterality maps" for a given function. Language function was examined in healthy controls and in people with epilepsy. When compared with traditional laterality index (LI) approaches, the resultant maps provided critical information about the magnitude and spatial characteristics of lateralized function. Specifically, it was possible to more clearly define low LI scores resulting from strong bilateral activation, high LI scores resulting from weak unilateral activation, and most importantly, the spatial distribution of lateralized activation. We argue that the laterality concept is better presented with the inherent spatial sensitivity of activation maps, rather than being collapsed into a one-dimensional index.

Attention modulates beta oscillations during prolonged tactile stimulation

The inter-play between changes in beta-band (14-30-Hz) cortical rhythms and attention during somatosensation informs us about where and when relevant processes occur in the brain. As such, we investigated the effects of attention on somatosensory evoked and induced responses using vibrotactile stimulation and magnetoencephalographic recording. Subjects received trains of vibration at 23 Hz to the right index finger while watching a movie and ignoring the somatosensory stimuli or paying attention to the stimuli to detect a change in the duration of the stimulus. The amplitude of the evoked 23-Hz steady-state response in the contralateral primary somatosensory cortex (SI) was enhanced by attention and the underlying dipole source was located 2 mm more medially, indicating top-down recruitment of additional neuronal populations for the functionally relevant stimulus. Attentional modulation of the somatosensory evoked response indicates facilitation of early processing of the tactile stimulus. Beta-band activity increased after vibration offset in the contralateral primary motor cortex (MI) [event-related synchronization (ERS)] and this increase was larger for attended than ignored stimuli. Beta-band activity decreased in the ipsilateral SI prior to stimulus offset [event-related desynchronization (ERD)] for attended stimuli only. Whereas attention modulation of the evoked response was confined to the contralateral SI, event-related changes of beta-band activity involved contralateral SI-MI and inter-hemispheric SI-SI connections. Modulation of neural activity in such a large sensorimotor network indicates a role for beta activity in higher-order processing.

Complexity analysis of source activity underlying the neuromagnetic somatosensory steady-state response

Using the notion of complexity and synchrony, this study presents a data-driven pipeline of nonlinear analysis of neuromagnetic sources reconstructed from human magnetoencephalographic (MEG) data collected in reaction to vibrostimulation of the right index finger. The dynamics of MEG source activity was reconstructed with synthetic aperture magnetometry (SAM) beam-forming technique. Considering brain as a complex system, we applied complexity-based tools to identify brain areas with dynamic patterns that remain regular across repeated stimulus presentations, and to characterize their synchronized behavior. Volumetric maps of brain activation were calculated using sample entropy as a measure of signal complexity. The complexity analysis identified activity in the primary somatosensory (SI) area contralateral to stimuli and bilaterally in the posterior parietal cortex (PPC) as regions with decreased complexity, consistently expressed in a group of subjects. Seeding an activated source with low complexity in the SI area, cross-sample entropy was used to generate synchrony maps. Cross-sample entropy analysis confirmed the synchronized dynamics of neuromagnetic activity between areas SI and PPC, robustly expressed across subjects. Our results extend the understanding of synchronization between co-activated brain regions, focusing on temporal coordination between events in terms of synchronized multidimensional signal patterns.

Seeing sounds and hearing sights: the influence of prior learning on current perception

It is well known that previous perceptual experiences alter subsequent perception, but the details of the neural underpinnings of this general phenomenon are still sketchy. Here, we ask whether previous experiences with an item (such as seeing a person's face) leads to the alteration of the neural correlates related to processing of the item as such, or whether it creates additional associative connections between such substrates and those activated during prior experience. To address this question, we used magnetoencephalography (MEG) to identify neural changes accompanying subjects' viewing of unfamiliar versus famous faces and hearing the names of unfamiliar versus famous names. We were interested in the nature of the involvement of auditory brain regions in the viewing of faces, and in the involvement of visual regions in the hearing of names. Evoked responses from MEG recordings for the names and faces conditions were localized to auditory and visual cortices, respectively. Unsurprisingly, peak activation strength of evoked responses was larger for famous versus nonfamous names within the superior temporal gyrus (STG), and was similar for famous and nonfamous faces in the occipital cortex. More relevant to the issue of experience on perception, peak activation strength in the STG was larger for viewed famous versus nonfamous faces, and peak activation within the occipital cortex was larger for heard famous versus nonfamous names. Critically, these experience-related responses were present within 150-250 msec of stimulus onset. These findings support the hypothesis that prior experiences may influence processing of faces and names such that perception encompasses more than what is imparted on the senses.

Correlates of eye blinking as determined by synthetic aperture magnetometry

OBJECTIVE

To evaluate the spatiotemporal characteristics of ocular and cerebral current sources during voluntary eyeblinking.

METHODS

Whole-head magnetoencephalographic (MEG) recordings were acquired during voluntary blinking in eight healthy adults and analysed using synthetic aperture magnetometry (SAM).

RESULTS

Fronto-temporal MEG sensors showed a large slow wave lasting approximately 400 ms and a small burst of activity with frequencies above 30 Hz at the initiation of the blink. Group maps of blink-related oscillatory activity at frequencies between 1-18 Hz and 32-64 Hz showed increased activity in and around the orbits during the 400 ms following blink onset. Increased oscillatory activity occurred in occipital regions 200 ms after blink onset at frequencies between 18 and 64 Hz.

CONCLUSIONS

Blink-related MEG signals are recorded in the regions of the eyes and in the occipital cortex. The anterior activation is likely a combination of muscle contraction and eyelid currents. Occipital activation likely represents neural processes concerned with re-establishing the visual image after transient ocular occlusion.

SIGNIFICANCE

The possibility of eyeblink-related fields should be considered when interpreting frontal and occipital source activities during SAM analyses.

Small-angle X-ray scattering analysis of craze-fibril structures

Load-bearing craze fibrils are fundamental to the ability of many polymer materials to support applied tensile stress. Three models of the scattering from craze-fibril structures have been compared through a rigorous analysis procedure. The results indicate that a diffuse-boundary model provides a more accurate description of scattering from the fibril structure than the standard Porod-law technique. Previously reported methods for determining fibril diameters were found to be inappropriate for high-impact polystyrene (HIPS) materials, overestimating the fibril diameters by as much as 60%. Indirect transforms using regularization theory of the fibril scattering data provide confirmation of the fibril diameters obtained from a power-law diffuse-boundary model, which is developed specifically for the craze-fibril structure of interest.