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MedRxiv : the Preprint Server For... May 2024This study sought to identify magnetoencephalography (MEG) power spectra patterns associated with cerebrovascular damage (white matter hyperintensities - WMH) and their...
OBJECTIVE
This study sought to identify magnetoencephalography (MEG) power spectra patterns associated with cerebrovascular damage (white matter hyperintensities - WMH) and their relationship with cognitive performance and brain structure integrity in aging individuals without cognitive impairment.
METHODS
We hypothesized a "slowness" pattern characterized by increased power in δ and θ bands and decreased power in the β band associated with the severity of vascular damage. MEG signals were analyzed in cognitively healthy older adults to investigate these associations.
RESULTS
Contrary to expectations, we did not observe an increase in δ and θ power. However, we found a significant negative correlation between β band power and WMH volume. This β power reduction was linked to structural brain changes, such as larger lateral ventricles, reduced white matter volume, and decreased fractional anisotropy in critical white matter tracts, but not to cognitive performance. This suggests that β band power reduction may serve as an early marker of vascular damage before the onset of cognitive symptoms.
CONCLUSION
Our findings partially confirm our initial hypothesis by demonstrating a decrease in β band power with increased vascular damage but not the anticipated increase in slow band power. The lack of correlation between the βpow marker and cognitive performance suggests its potential utility in early identification of at-risk individuals for future cognitive impairment due to vascular origins. These results contribute to understanding the electrophysiological signatures of preclinical vascular damage and highlight the importance of MEG in detecting subtle brain changes associated with aging.
PubMed: 38798609
DOI: 10.1101/2024.05.15.24307438 -
NeuroImage Jul 2024Although one can recognize the environment by soundscape substituting vision to auditory signal, whether subjects could perceive the soundscape as visual or visual-like...
Although one can recognize the environment by soundscape substituting vision to auditory signal, whether subjects could perceive the soundscape as visual or visual-like sensation has been questioned. In this study, we investigated hierarchical process to elucidate the recruitment mechanism of visual areas by soundscape stimuli in blindfolded subjects. Twenty-two healthy subjects were repeatedly trained to recognize soundscape stimuli converted by visual shape information of letters. An effective connectivity method called dynamic causal modeling (DCM) was employed to reveal how the brain was hierarchically organized to recognize soundscape stimuli. The visual mental imagery model generated cortical source signals of five regions of interest better than auditory bottom-up, cross-modal perception, and mixed models. Spectral couplings between brain areas in the visual mental imagery model were analyzed. While within-frequency coupling is apparent in bottom-up processing where sensory information is transmitted, cross-frequency coupling is prominent in top-down processing, corresponding to the expectation and interpretation of information. Sensory substitution in the brain of blindfolded subjects derived visual mental imagery by combining bottom-up and top-down processing.
Topics: Humans; Male; Female; Imagination; Adult; Auditory Perception; Young Adult; Visual Perception; Acoustic Stimulation; Electroencephalography; Magnetoencephalography
PubMed: 38797383
DOI: 10.1016/j.neuroimage.2024.120621 -
Journal of Neuroscience Methods Aug 2024Accurate identification of abnormal electroencephalographic (EEG) activity is pivotal for diagnosing and treating epilepsy. Recent studies indicate that decomposing...
BACKGROUND
Accurate identification of abnormal electroencephalographic (EEG) activity is pivotal for diagnosing and treating epilepsy. Recent studies indicate that decomposing brain activity into periodic (oscillatory) and aperiodic (trend across all frequencies) components can illuminate the drivers of spectral activity changes.
NEW METHODS
We analysed intracranial EEG (iEEG) data from 234 subjects, creating a normative map. This map was compared to a cohort of 63 patients with refractory focal epilepsy under consideration for neurosurgery. The normative map was computed using three approaches: (i) relative complete band power, (ii) relative band power with the aperiodic component removed, and (iii) the aperiodic exponent. Abnormalities were calculated for each approach in the patient cohort. We evaluated the spatial profiles, assessed their ability to localize abnormalities, and replicated the findings using magnetoencephalography (MEG).
RESULTS
Normative maps of relative complete band power and relative periodic band power exhibited similar spatial profiles, while the aperiodic normative map revealed higher exponent values in the temporal lobe. Abnormalities estimated through complete band power effectively distinguished between good and bad outcome patients. Combining periodic and aperiodic abnormalities enhanced performance, like the complete band power approach.
COMPARISON WITH EXISTING METHODS AND CONCLUSIONS
Sparing cerebral tissue with abnormalities in both periodic and aperiodic activity may result in poor surgical outcomes. Both periodic and aperiodic components do not carry sufficient information in isolation. The relative complete band power solution proved to be the most reliable method for this purpose. Future studies could investigate how cerebral location or pathology influences periodic or aperiodic abnormalities.
Topics: Humans; Magnetoencephalography; Male; Female; Adult; Electrocorticography; Young Adult; Brain; Brain Mapping; Middle Aged; Adolescent; Signal Processing, Computer-Assisted; Drug Resistant Epilepsy; Epilepsies, Partial; Epilepsy; Cohort Studies; Electroencephalography; Brain Waves
PubMed: 38795977
DOI: 10.1016/j.jneumeth.2024.110180 -
Bioengineering (Basel, Switzerland) Apr 2024A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference...
A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy. Therefore, this study proposes a method to automatically estimate a suitable threshold. Time-frequency transformations are performed on the evoked state data to obtain the neural signal of interest and the noise signal in a specific time-frequency band, which are then used to construct the objective function describing the degree of noise suppression and signal distortion. The optimal value of the threshold in the selected range is obtained using the weighted-sum method. Our method was tested on two classical subspace projection algorithms using simulation and two sensory stimulation experiments. The thresholds estimated by the proposed method enabled the algorithms to achieve the best waveform recovery and source location error. Therefore, the threshold selected in this method enables subspace projection algorithms to achieve the best balance between noise removal and neural signal preservation in subsequent MEG analyses.
PubMed: 38790295
DOI: 10.3390/bioengineering11050428 -
Cortex; a Journal Devoted To the Study... Jul 2024Does the human brain represent perspectival shapes, i.e., viewpoint-dependent object shapes, especially in relatively higher-level visual areas such as the lateral...
Does the human brain represent perspectival shapes, i.e., viewpoint-dependent object shapes, especially in relatively higher-level visual areas such as the lateral occipital cortex? What is the temporal profile of the appearance and disappearance of neural representations of perspectival shapes? And how does attention influence these neural representations? To answer these questions, we employed functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and multivariate decoding techniques to investigate spatiotemporal neural representations of perspectival shapes. Participants viewed rotated objects along with the corresponding objective shapes and perspectival shapes (i.e., rotated round, round, and oval) while we measured their brain activities. Our results revealed that shape classifiers trained on the basic shapes (i.e., round and oval) consistently identified neural representations in the lateral occipital cortex corresponding to the perspectival shapes of the viewed objects regardless of attentional manipulations. Additionally, this classification tendency toward the perspectival shapes emerged approximately 200 ms after stimulus presentation. Moreover, attention influenced the spatial dimension as the regions showing the perspectival shape classification tendency propagated from the occipital lobe to the temporal lobe. As for the temporal dimension, attention led to a more robust and enduring classification tendency towards perspectival shapes. In summary, our study outlines a spatiotemporal neural profile for perspectival shapes that suggests a greater degree of perspectival representation than is often acknowledged.
Topics: Humans; Magnetoencephalography; Magnetic Resonance Imaging; Attention; Male; Female; Adult; Young Adult; Brain Mapping; Photic Stimulation; Occipital Lobe; Pattern Recognition, Visual; Form Perception; Brain
PubMed: 38781910
DOI: 10.1016/j.cortex.2024.04.003 -
Brain Communications 2024The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor...
The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis ( = 36) and healthy age-matched controls ( = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/ exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/ exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination () of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/ exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.
PubMed: 38779353
DOI: 10.1093/braincomms/fcae164 -
Nature Communications May 2024Our brain is constantly extracting, predicting, and recognising key spatiotemporal features of the physical world in order to survive. While neural processing of...
Our brain is constantly extracting, predicting, and recognising key spatiotemporal features of the physical world in order to survive. While neural processing of visuospatial patterns has been extensively studied, the hierarchical brain mechanisms underlying conscious recognition of auditory sequences and the associated prediction errors remain elusive. Using magnetoencephalography (MEG), we describe the brain functioning of 83 participants during recognition of previously memorised musical sequences and systematic variations. The results show feedforward connections originating from auditory cortices, and extending to the hippocampus, anterior cingulate gyrus, and medial cingulate gyrus. Simultaneously, we observe backward connections operating in the opposite direction. Throughout the sequences, the hippocampus and cingulate gyrus maintain the same hierarchical level, except for the final tone, where the cingulate gyrus assumes the top position within the hierarchy. The evoked responses of memorised sequences and variations engage the same hierarchical brain network but systematically differ in terms of temporal dynamics, strength, and polarity. Furthermore, induced-response analysis shows that alpha and beta power is stronger for the variations, while gamma power is enhanced for the memorised sequences. This study expands on the predictive coding theory by providing quantitative evidence of hierarchical brain mechanisms during conscious memory and predictive processing of auditory sequences.
Topics: Humans; Male; Magnetoencephalography; Female; Adult; Auditory Perception; Young Adult; Auditory Cortex; Brain; Acoustic Stimulation; Brain Mapping; Music; Gyrus Cinguli; Memory; Hippocampus; Recognition, Psychology
PubMed: 38773109
DOI: 10.1038/s41467-024-48302-4 -
Nature Communications May 2024When making choices, individuals differ from one another, as well as from normativity, in how they weigh different types of information. One explanation for this relates...
When making choices, individuals differ from one another, as well as from normativity, in how they weigh different types of information. One explanation for this relates to idiosyncratic preferences in what information individuals represent when evaluating choice options. Here, we test this explanation with a simple risky-decision making task, combined with magnetoencephalography (MEG). We examine the relationship between individual differences in behavioral markers of information weighting and neural representation of stimuli pertinent to incorporating that information. We find that the extent to which individuals (N = 19) behaviorally weight probability versus reward information is related to how preferentially they neurally represent stimuli most informative for making probability and reward comparisons. These results are further validated in an additional behavioral experiment (N = 88) that measures stimulus representation as the latency of perceptual detection following priming. Overall, the results suggest that differences in the information individuals consider during choice relate to their risk-taking tendencies.
Topics: Humans; Risk-Taking; Male; Decision Making; Female; Magnetoencephalography; Adult; Young Adult; Heuristics; Reward; Choice Behavior; Brain; Adolescent
PubMed: 38769095
DOI: 10.1038/s41467-024-48547-z -
MedRxiv : the Preprint Server For... May 2024Psychosis spectrum disorders (PSDs) are marked by cognitive impairments, the neurobiological correlates of which remain poorly understood. Here, we investigate the...
BACKGROUND
Psychosis spectrum disorders (PSDs) are marked by cognitive impairments, the neurobiological correlates of which remain poorly understood. Here, we investigate the entropy of time-varying functional connectivity (TVFC) patterns from resting-state fMRI (rfMRI) as potential biomarker for cognitive performance in PSDs. By combining our results with multimodal reference data, we hope to generate new insights into the mechanisms underlying cognitive dysfunction in PSDs. We hypothesized that low-entropy TVFC patterns (LEN) would be more behaviorally informative than high-entropy TVFC patterns (HEN), especially for tasks that require extensive integration across diverse cognitive subdomains.
METHODS
rfMRI and behavioral data from 97 patients in the early phases of psychosis and 53 controls were analyzed. Positron-Emission Tomography (PET) and magnetoencephalography (MEG) data were taken from a public repository (Hansen et al., 2022). Multivariate analyses were conducted to examine relationships between TVFC patterns at multiple spatial scales and cognitive performance in patients.
RESULTS
Compared to HEN, LEN explained significantly more cognitive variance on average in PSD patients, driven by superior encoding of information on psychometrically more integrated tasks. HEN better captured information in specific subdomains of executive functioning. Nodal HEN-LEN transitions were spatially aligned with neurobiological gradients reflecting monoaminergic transporter densities and MEG beta power. Exploratory analyses revealed a close statistical relationship between LEN and positive PSD symptoms.
CONCLUSION
Our entropy-based analysis of TVFC patterns dissociates distinct aspects of cognition in PSDs. By linking topographies of neurotransmission and oscillatory dynamics with cognitive performance, it enhances our understanding of the mechanisms underlying cognitive deficits in PSDs.
CREDIT AUTHORSHIP CONTRIBUTION STATEMENT
Conceptualization, Methodology, Software, Formal analysis, Writing - Original Draft, Writing - Review & Editing, Visualization; Methodology, Software, Formal analysis, Writing - Review & Editing; Methodology, Software, Formal analysis, Writing - Review & Editing; Methodology, Writing - Review & Editing, Supervision, Project administration.
PubMed: 38766002
DOI: 10.1101/2024.05.07.24306932 -
Developmental Cognitive Neuroscience Jun 2024The field of developmental cognitive neuroscience is advancing rapidly, with large-scale, population-wide, longitudinal studies emerging as a key means of unraveling the... (Review)
Review
The field of developmental cognitive neuroscience is advancing rapidly, with large-scale, population-wide, longitudinal studies emerging as a key means of unraveling the complexity of the developing brain and cognitive processes in children. While numerous neuroscientific techniques like functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) have proved advantageous in such investigations, this perspective proposes a renewed focus on electroencephalography (EEG), leveraging underexplored possibilities of EEG. In addition to its temporal precision, low costs, and ease of application, EEG distinguishes itself with its ability to capture neural activity linked to social interactions in increasingly ecologically valid settings. Specifically, EEG can be measured during social interactions in the lab, hyperscanning can be used to study brain activity in two (or more) people simultaneously, and mobile EEG can be used to measure brain activity in real-life settings. This perspective paper summarizes research in these three areas, making a persuasive argument for the renewed inclusion of EEG into the toolkit of developmental cognitive and social neuroscientists.
Topics: Humans; Electroencephalography; Cognitive Neuroscience; Social Interaction; Brain
PubMed: 38759529
DOI: 10.1016/j.dcn.2024.101391