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Human Brain Mapping Dec 2023Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typically...
Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typically subject-specific and does not generalise well over subjects, due to high amounts of between subject variability. Techniques that overcome this will not only provide richer neuroscientific insights but also make it possible for group-level models to outperform subject-specific models. Here, we propose a method that uses subject embedding, analogous to word embedding in natural language processing, to learn and exploit the structure in between-subject variability as part of a decoding model, our adaptation of the WaveNet architecture for classification. We apply this to magnetoencephalography data, where 15 subjects viewed 118 different images, with 30 examples per image; to classify images using the entire 1 s window following image presentation. We show that the combination of deep learning and subject embedding is crucial to closing the performance gap between subject- and group-level decoding models. Importantly, group models outperform subject models on low-accuracy subjects (although slightly impair high-accuracy subjects) and can be helpful for initialising subject models. While we have not generally found group-level models to perform better than subject-level models, the performance of group modelling is expected to be even higher with bigger datasets. In order to provide physiological interpretation at the group level, we make use of permutation feature importance. This provides insights into the spatiotemporal and spectral information encoded in the models. All code is available on GitHub (https://github.com/ricsinaruto/MEG-group-decode).
Topics: Humans; Deep Learning; Brain; Magnetoencephalography; Brain Mapping; Brain-Computer Interfaces
PubMed: 37753636
DOI: 10.1002/hbm.26500 -
Brain Communications 2023Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue....
Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.
PubMed: 37953844
DOI: 10.1093/braincomms/fcad292 -
Journal of the Association For Research... Dec 2023Tinnitus has been widely investigated in order to draw conclusions about the underlying causes and altered neural activity in various brain regions. Existing studies... (Review)
Review
Tinnitus has been widely investigated in order to draw conclusions about the underlying causes and altered neural activity in various brain regions. Existing studies have based their work on different tinnitus frameworks, ranging from a more local perspective on the auditory cortex to the inclusion of broader networks and various approaches towards tinnitus perception and distress. Magnetoencephalography (MEG) provides a powerful tool for efficiently investigating tinnitus and aberrant neural activity both spatially and temporally. However, results are inconclusive, and studies are rarely mapped to theoretical frameworks. The purpose of this review was to firstly introduce MEG to interested researchers and secondly provide a synopsis of the current state. We divided recent tinnitus research in MEG into study designs using resting state measurements and studies implementing tone stimulation paradigms. The studies were categorized based on their theoretical foundation, and we outlined shortcomings as well as inconsistencies within the different approaches. Finally, we provided future perspectives on how to benefit more efficiently from the enormous potential of MEG. We suggested novel approaches from a theoretical, conceptual, and methodological point of view to allow future research to obtain a more comprehensive understanding of tinnitus and its underlying processes.
Topics: Humans; Magnetoencephalography; Tinnitus; Brain; Auditory Cortex
PubMed: 38015287
DOI: 10.1007/s10162-023-00916-z -
NeuroImage Sep 2023Multivariate analysis methods are widely used in neuroscience to investigate the presence and structure of neural representations. Representational similarities across...
Multivariate analysis methods are widely used in neuroscience to investigate the presence and structure of neural representations. Representational similarities across time or contexts are often investigated using pattern generalization, e.g. by training and testing multivariate decoders in different contexts, or by comparable pattern-based encoding methods. It is however unclear what conclusions can be validly drawn on the underlying neural representations when significant pattern generalization is found in mass signals such as LFP, EEG, MEG, or fMRI. Using simulations, we show how signal mixing and dependencies between measurements can drive significant pattern generalization even though the true underlying representations are orthogonal. We suggest that, using an accurate estimate of the expected pattern generalization given identical representations, it is nonetheless possible to test meaningful hypotheses about the generalization of neural representations. We offer such an estimate of the expected magnitude of pattern generalization and demonstrate how this measure can be used to assess the similarity and differences of neural representations across time and contexts.
Topics: Humans; Magnetic Resonance Imaging; Brain Mapping
PubMed: 37429371
DOI: 10.1016/j.neuroimage.2023.120258 -
NeuroImage Sep 2023Oscillatory power and phase synchronization map neuronal dynamics and are commonly studied to differentiate the healthy and diseased brain. Yet, little is known about... (Review)
Review
Oscillatory power and phase synchronization map neuronal dynamics and are commonly studied to differentiate the healthy and diseased brain. Yet, little is known about the course and spatial variability of these features from early adulthood into old age. Leveraging magnetoencephalography (MEG) resting-state data in a cross-sectional adult sample (n = 350), we probed lifespan differences (18-88 years) in connectivity and power and interaction effects with sex. Building upon recent attempts to link brain structure and function, we tested the spatial correspondence between age effects on cortical thickness and those on functional networks. We further probed a direct structure-function relationship at the level of the study sample. We found MEG frequency-specific patterns with age and divergence between sexes in low frequencies. Connectivity and power exhibited distinct linear trajectories or turning points at midlife that might reflect different physiological processes. In the delta and beta bands, these age effects corresponded to those on cortical thickness, pointing to co-variation between the modalities across the lifespan. Structure-function coupling was frequency-dependent and observed in unimodal or multimodal regions. Altogether, we provide a comprehensive overview of the topographic functional profile of adulthood that can form a basis for neurocognitive and clinical investigations. This study further sheds new light on how the brain's structural architecture relates to fast oscillatory activity.
Topics: Humans; Adult; Longevity; Cross-Sectional Studies; Magnetoencephalography; Brain; Brain Mapping
PubMed: 37451375
DOI: 10.1016/j.neuroimage.2023.120275 -
Alzheimer's Research & Therapy Aug 2023Studies in animal models of Alzheimer's disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction....
BACKGROUND
Studies in animal models of Alzheimer's disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction. Whether and how AD-related neurophysiological alterations translate between mice and humans remains however uncertain.
METHODS
We characterized neurophysiological alterations in mice and humans carrying AD mutations in the APP and/or PSEN1 genes, focusing on early pre-symptomatic changes. Longitudinal local field potential recordings were performed in APP/PS1 mice and cross-sectional magnetoencephalography recordings in human APP and/or PSEN1 mutation carriers. All recordings were acquired in the left frontal cortex, parietal cortex, and hippocampus. Spectral power and functional connectivity were analyzed and compared with wildtype control mice and healthy age-matched human subjects.
RESULTS
APP/PS1 mice showed increased absolute power, especially at higher frequencies (beta and gamma) and predominantly between 3 and 6 moa. Relative power showed an overall shift from lower to higher frequencies over almost the entire recording period and across all three brain regions. Human mutation carriers, on the other hand, did not show changes in power except for an increase in relative theta power in the hippocampus. Mouse parietal cortex and hippocampal power spectra showed a characteristic peak at around 8 Hz which was not significantly altered in transgenic mice. Human power spectra showed a characteristic peak at around 9 Hz, the frequency of which was significantly reduced in mutation carriers. Significant alterations in functional connectivity were detected in theta, alpha, beta, and gamma frequency bands, but the exact frequency range and direction of change differed for APP/PS1 mice and human mutation carriers.
CONCLUSIONS
Both mice and humans carrying APP and/or PSEN1 mutations show abnormal neurophysiological activity, but several measures do not translate one-to-one between species. Alterations in absolute and relative power in mice should be interpreted with care and may be due to overexpression of amyloid in combination with the absence of tau pathology and cholinergic degeneration. Future studies should explore whether changes in brain activity in other AD mouse models, for instance, those also including tau pathology, provide better translation to the human AD continuum.
Topics: Animals; Humans; Mice; Alzheimer Disease; Amyloidogenic Proteins; Mice, Transgenic; Mutation; Presenilin-1; Amyloid beta-Protein Precursor
PubMed: 37608393
DOI: 10.1186/s13195-023-01287-6 -
Communications Biology Dec 2023Our understanding of the surrounding world and communication with other people are tied to mental representations of concepts. In order for the brain to recognize an...
Our understanding of the surrounding world and communication with other people are tied to mental representations of concepts. In order for the brain to recognize an object, it must determine which concept to access based on information available from sensory inputs. In this study, we combine magnetoencephalography and machine learning to investigate how concepts are represented and accessed in the brain over time. Using brain responses from a silent picture naming task, we track the dynamics of visual and semantic information processing, and show that the brain gradually accumulates information on different levels before eventually reaching a plateau. The timing of this plateau point varies across individuals and feature models, indicating notable temporal variation in visual object recognition and semantic processing.
Topics: Humans; Semantics; Visual Perception; Brain; Cognition; Magnetoencephalography
PubMed: 38066098
DOI: 10.1038/s42003-023-05611-6 -
Journal of Affective Disorders Jun 2024Electrophysiologic measures provide an opportunity to inform mechanistic models and possibly biomarker prediction of response. Serotonergic psychedelics (SPs) (i.e.,... (Review)
Review
Spectral signatures of psilocybin, lysergic acid diethylamide (LSD) and ketamine in healthy volunteers and persons with major depressive disorder and treatment-resistant depression: A systematic review.
BACKGROUND
Electrophysiologic measures provide an opportunity to inform mechanistic models and possibly biomarker prediction of response. Serotonergic psychedelics (SPs) (i.e., psilocybin, lysergic acid diethylamide (LSD)) and ketamine represent new investigational and established treatments in mood disorders respectively. There is a need to better characterize the mechanism of action of these agents.
METHODS
We conducted a systematic review investigating the spectral signatures of psilocybin, LSD, and ketamine in persons with major depressive disorder (MDD), treatment-resistant depression (TRD), and healthy controls.
RESULTS
Ketamine and SPs are associated with increased theta power in persons with depression. Ketamine and SPs are also associated with decreased spectral power in the alpha, beta and delta bands in healthy controls and persons with depression. When administered with SPs, theta power was increased in persons with MDD when administered with SPs. Ketamine is associated with increased gamma band power in both healthy controls and persons with MDD.
LIMITATIONS
The studies included in our review were heterogeneous in their patient population, exposure, dosing of treatment and devices used to evaluate EEG and MEG signatures. Our results were extracted entirely from persons who were either healthy volunteers or persons with MDD or TRD.
CONCLUSIONS
Extant literature evaluating EEG and MEG spectral signatures indicate that ketamine and SPs have reproducible effects in keeping with disease models of network connectivity. Future research vistas should evaluate whether observed spectral signatures can guide further discovery of therapeutics within the psychedelic and dissociative classes of agents, and its prediction capability in persons treated for depression.
Topics: Humans; Psilocybin; Ketamine; Lysergic Acid Diethylamide; Depressive Disorder, Major; Depression; Healthy Volunteers; Hallucinogens
PubMed: 38570038
DOI: 10.1016/j.jad.2024.03.165 -
Journal of Visualized Experiments : JoVE Oct 2023Cortical maps represent the spatial organization of location-dependent neural responses to sensorimotor stimuli in the cerebral cortex, enabling the prediction of...
Cortical maps represent the spatial organization of location-dependent neural responses to sensorimotor stimuli in the cerebral cortex, enabling the prediction of physiologically relevant behaviors. Various methods, such as penetrating electrodes, electroencephalography, positron emission tomography, magnetoencephalography, and functional magnetic resonance imaging, have been used to obtain cortical maps. However, these methods are limited by poor spatiotemporal resolution, low signal-to-noise ratio (SNR), high costs, and non-biocompatibility or cause physical damage to the brain. This study proposes a graphene array-based somatosensory mapping method as a feature of electrocorticography that offers superior biocompatibility, high spatiotemporal resolution, desirable SNR, and minimized tissue damage, overcoming the drawbacks of previous methods. This study demonstrated the feasibility of a graphene electrode array for somatosensory mapping in rats. The presented protocol can be applied not only to the somatosensory cortex but also to other cortices such as the auditory, visual, and motor cortex, providing advanced technology for clinical implementation.
Topics: Rats; Animals; Graphite; Brain Mapping; Electroencephalography; Brain; Electrodes; Magnetic Resonance Imaging; Somatosensory Cortex
PubMed: 37929971
DOI: 10.3791/64910 -
MedRxiv : the Preprint Server For... Dec 2023In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of...
In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of Parkinson's disease (PD). We obtained brain-fingerprints from PD patients and age-matched healthy controls using short, task-free magnetoencephalographic recordings. The rhythmic components of the individual brain-fingerprint distinguished between patients and healthy participants with approximately 90% accuracy. The most prominent cortical features of the Parkinson's brain-fingerprint mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also show that Parkinson's disease stages can be decoded directly from cortical neurophysiological activity. Additionally, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. We further demonstrate that the arrhythmic components of cortical activity are more variable over short periods of time in patients with Parkinson's disease than in healthy controls, making individual differentiation between patients based on these features more challenging and explaining previous negative published results. Overall, we outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and clinical staging of Parkinson's disease. For this reason, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification and to the improved identification and testing of therapeutic neurostimulation targets.
PubMed: 36798232
DOI: 10.1101/2023.02.03.23285441