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Hamalainen, M.

Publications and source records attributed to Hamalainen, M..

8 recordsLinked to original sources

High-Definition MEG Source Estimation using the Reciprocal Boundary Element Fast Multipole Method

Magnetoencephalographic (MEG) source estimation relies on the computation of the gain (lead-field) matrix, which embodies the linear relationship between the amplitudes of the sources and the recorded signals. However, with a realistic forward model, the calculation of the gain matrix in a "direct" fashion is a computationally expensive task because the number of dipolar sources in standard MEG pipelines is often limited to [~]10,000. We propose a fast approach based on the reciprocal relationship between MEG and transcranial magnetic stimulation (TMS). This approach couples naturally with the charge-based boundary element fast multipole method (BEM-FMM), which allows us to efficiently generate gain matrices for high-resolution multi-layer non-nested meshes involving source spaces of up to a [~]1 million dipoles. We evaluate our approach by performing MEG source reconstruction against simulated data (at varying noise levels) obtained from the direct computation of MEG readings from 2000 different dipole positions over the cortical surface of 5 healthy subjects. Additionally, we test our methods with real MEG data from evoked somatosensory fields by right-hand median nerve stimulation in these same 5 subjects. We compare our experimental source reconstruction results against the standard MNE-Python source reconstruction pipeline.

neuroscience↗

Biplanar nulling coil system for OPM-MEG using printed circuit boards

Optically pumped magnetometers (OPMs) are a promising sensor technology for non-invasive measurement of human electrophysiological signals, in particular the magnetoencephalogram (MEG). OPMs do not need cryogenic cooling and can be placed conformal to the subjects scalp, thus greatly reducing the sensor-to-source distance and improving signal sensitivity. OPMs, however, require near-zero background magnetic field to achieve linearity and minimize signal distortion. Prior work has proposed the use of biplanar field nulling coils to remove the uniform and gradient components of the background magnetic field. Biplanar coils have been expensive to construct, involving tedious error-prone manual winding of over 1000 m of copper wire. In this work, we designed and fabricated background field nulling coils (three uniform and three gradient components) on two-layer Printed Circuit Boards (PCBs). We used an open-source software (bfieldtools) to determine the current loops needed to produce the target magnetic field in a 50-cm-diameter spherical volume. We developed a software-based approach to connect the discrete current loops into a continuous conducting path traversing the two layers of the PCB. For ease of manufacture, the designed (1.5 x 1.5 m2) coils were cut along the symmetry axis and printed as pairs of 1.5 x 0.75 m2 PCBs (2 oz Cu), soldered together and mounted on a sliding aluminum frame. The efficiency of the coils (1.3 - 7.1 nT/mA) was similar or higher than previously reported in the literature. We mapped the field inside the target region after field nulling inside our single-layer shielded room and were able to reduce the largest component of the background field from 21 to 2 nT. Using our nulling coil system, we were able to operate OPMs in a lightly shielded room (background field varying from 6.5 to 108 nT in the floor-to-ceiling direction) to record somatosensory evoked fields (SEFs) comparable to those measured using SQUID-based MEG in a 3-layer shielded room. We disseminate the software and hardware as an open-source package opmcoils. This work will facilitate access to more affordable field nulling coils for OPM-MEG and help to realize the potential of OPM-MEG as an accessible sensor technology for use in human neuroscience.

neuroscience↗

Longevity Bottlenecks

The longevity field has received an influx of capital and talent over the past 5 years, but it is unclear where directing these resources would result in the biggest positive impact. We aimed to establish a systematic, rigorous and unbiased way to identify the areas where increased investment would accelerate progress across the whole longevity field the most. To do so, we surveyed [~]400 participants across various sectors of longevity, asking them to 1) identify the major bottlenecks they are experiencing, 2) list their most needed solution, and 3) rate the potential efficacy and barriers to development of various aging intervention strategies. We built a classification system of Bottlenecks and Solutions based on grouping related answers and found the most frequently listed bottlenecks to be 1) lack of validated aging biomarkers; 2) an overall lack of funding; and 3) lack of good models for aging studies. Surprisingly, the most wanted solution was greater availability of large public datasets. Indeed, a common theme across all answers was the need for a new data-centric structure of scientific research, where large datasets are routinely gathered and made available, access walls are removed, protocols are standardized, negative and unpublished data are shared, and AI systems are released on the data for automated discovery. Finally, a lack of regulatory clarity was listed as the biggest barrier to development across all interventions, whereas cellular reprogramming, organ replacement, and genetic medicine (gene therapies and gene editing) were perceived as the intervention strategies with the highest potential for increasing healthy lifespan. We provide these data as a resource for funding agencies, philanthropists, entrepreneurs and newcomers to the field as a means to identify high impact areas to fund and work on. Key takeawaysO_LI395 Participants were surveyed for their biggest bottlenecks and most needed solutions C_LIO_LITop Bottlenecks: lack of Validated Biomarkers; Overall lack of Funding and Slow & Expensive Models. C_LIO_LITop proposed Solutions: more Public Datasets; improved Regulatory Path; and Overall More Funding. C_LIO_LIBottlenecks and Solutions vary substantially across industry areas. C_LIO_LIRapamycin and calorie restriction are perceived as the most efficacious interventions in the near term. C_LIO_LISomatic reprogramming, organ replacement, and genetic medicine are perceived as the most efficacious interventions in the long term (25 years). C_LIO_LISirtuin and NAD targeting therapies are seen as the least efficacious interventions in all time-frames. C_LIO_LIAcross all interventions, Regulatory Issues are perceived as the most severely inhibiting factor in the development of the intervention. C_LI

scientific communication and education↗

On the clinical benefit of on-scalp MEG: A modeling study of on-scalp MEG epileptic activity source estimation ability

ObjectiveWhole-head on scalp magnetoencephalography (osMEG) is a novel, cutting-edge functional neuroimaging technique that positions MEG sensors closer to the cortical sources. OsMEG allows both for free head movements and improved spatial resolution compared to conventional MEG. OsMEG thus might improve clinical epilepsy evaluations. However, it remains largely unknown how osMEG characterizes epileptic activity. Here, we aimed to compare epileptic activity source estimation accuracy of osMEG, high-density EEG (hd-EEG), conventional MEG (convMEG) and subdural EEG (sbdEEG). MethodIED and seizure onset zone source estimations of osMEG, hdEEG, convMEG and sbdEEG were evaluated using equivalent current dipoles. Cancellation index of all non-invasive modalities were calculated and compared statistically. To further investigate any similarity between osMEG and sbdEEG, representational similarity analysis was used to compare IED source estimations of these two modalities. ResultsWe found that osMEG IED source estimations were significantly (p<0.05) better than both convMEG and hdEEG. Furthermore, osMEG mesial temporal lobe SOZ source estimations were superior to those of convMEG and hdEEG. OsMEG cancellation index did not differ significantly from convMEG. Interestingly, comparing osMEG and sbdEEG IED source estimation demonstrated that osMEG might be less sensitive to source directions than convMEG. ConclusionWe demonstrated that whole-head osMEG exhibited very accurate non-invasive IED and SOZ source estimations, better than both hd-EEG and convMEG. SignificanceOsMEG has a promising potential to become a safe, highly sensitive neuroimaging modality for whole head epilepsy evaluations. HighlightsO_LIAnalysis of novel on-scalp MEG (osMEG) sensors in epilepsy evaluations C_LIO_LICompares osMEG, EEG, conventional MEG & intracranial EEG epilepsy source estimations C_LIO_LIOur study demonstrates potential great clinical value of osMEG whole-head sensors C_LI

neuroscience↗

Dynamic predictive coding across the left fronto-temporal language hierarchy: Evidence from MEG, EEG and fMRI

We used MEG and ERPs to track the time-course and localization of evoked activity produced by expected, unexpected plausible and implausible words during incremental language comprehension. We interpret the full pattern of evoked responses and functional connectivity within a hierarchical predictive coding framework in which evoked activity reflects residual information (error) that is passed up and down the cortical hierarchy. Between 300-500ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), while implausible inputs produced a selectively enhanced response within left inferior frontal cortex (event-level prediction error). Between 600-1000ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that induced top-down shifts of event-level and lexico-semantic representations), while highly implausible inputs activated posterior fusiform and medial temporal cortices, supporting orthographic reanalysis and new learning. Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.

neuroscience↗

Human Neocortical Neurosolver (HNN): A new software tool for interpreting the cellular and network origin of human MEG/EEG data

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNNs core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signals origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNNs ability to associate signals across scales makes it a unique tool for translational neuroscience research.

neuroscience↗

Maturation Trajectories of Cortical Resting-State Networks Depend on the Mediating Frequency Band

The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30Hz) and gamma (31-80Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.

neuroscience↗

MEG/EEG group study with MNE: recommendations, quality assessments and best practices

Cognitive neuroscience questions are commonly tested with experiments that involve a cohort of subjects. The cohort can consist of a handful of subjects for small studies to hundreds or thousands of subjects in open datasets.\n\nWhile there exist various online resources to get started with the analysis of magnetoencephalography (MEG) or electroencephalography (EEG) data, such educational materials are usually restricted to the analysis of a single subject. This is in part because data from larger group studies are harder to share, but also analyses of such data are often require subject-specific decisions which are hard to document.\n\nThis work presents the results obtained by the reanalysis of an open dataset from Wakeman and Henson (2015) using the MNE software package. The analysis covers preprocessing steps, quality assurance steps, sensor space analysis of evoked responses, source localization, and statistics in both sensor and source space. Results with possible alternative strategies are presented and discussed at different stages such as the use of high-pass filtering versus baseline correction, tSSS versus SSS, the use of a minimum norm inverse versus LCMV beamformer, and the use of univariate or multivariate statistics. This aims to provide a comparative study of different stages of M/EEG analysis pipeline on the same dataset, with open access to all of the scripts necessary to reproduce this analysis.

neuroscience↗