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Samu Taulu

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6 papers

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YNICL Journal 2023 Journal Article

Single-trial neuromagnetic analysis reveals somatosensory dysfunction in chronic Minamata disease

Masaaki Nakamura
Samu Taulu
Hisateru Tachimori
Yui Tomo
Takahiro Kawashima
Yoko Miura
Mina Itatani
Shozo Tobimatsu

Methylmercury pollution is a global problem, and Minamata disease (MD) is a stark reminder that exposure to methylmercury can cause irreversible neurological damage. A "glove and stocking type" sensory disturbance due to injured primary sensory cortex (SI) (central somatosensory disturbance) is the most common neurologic sign in MD. As this sign is also prevalent in those with polyneuropathy, we aimed to develop an objective assessment for detecting central somatosensory disturbances in cases of chronic MD. We selected 289 healthy volunteers and 42 patients with MD. We recorded the sensory nerve action potentials (SNAPs) and somatosensory evoked magnetic fields (SEFs) to median nerve stimulation with magnetoencephalography. Single-trial epochs were classified into three categories (N20m, non-response, and P20m epochs) based on the cross-correlation between averaged sensor SEFs and individual epochs. We assessed SI responses (the appearance rate of P20m [P20m rate] and non-response epochs [non-response rate]) and early somatosensory cortical processing (N20m amplitude, reproducibility of N20m in single-trial responses [cross-correlation value], and induced gamma-band oscillations of the SI [gamma response] of single epochs excluding non-response epochs). Receiver operating characteristic curve analyses were used to examine the diagnostic accuracy of each parameter. We found that SNAPs exerted a marginal effect on the N20m. The N20m amplitude, cross-correlation value, and gamma response were significantly reduced in the MD group on either side (p 0.77 (range: 0.77-0.79) for all parameters. Their confidence intervals overlapped with each other; thus, each SEF parameter likely had an approximately equivalent discrimination ability. In conclusion, chronic MD is characterized by impaired SI responses and alterations in early somatosensory cortical processing. Thus, single-trial neuromagnetic analysis of somatosensory function may be useful for detecting central somatosensory disturbance and elucidating the relevant pathophysiological mechanisms even in the context of chronic MD.

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YNIMG Journal 2022 Journal Article

Cross-Axis projection error in optically pumped magnetometers and its implication for magnetoencephalography systems

Amir Borna
Joonas Iivanainen
Tony R. Carter
Jim McKay
Samu Taulu
Julia Stephen
Peter D.D. Schwindt

Rb, as the sensing element and one or more lasers for preparation and interrogation of the magnetically sensitive states of the alkali atoms ensemble. The sensitivity of the OPM can be greatly enhanced by operating it in the SERF regime, where the alkali atoms' spin exchange rate is much faster than the Larmor precession frequency. The SERF regime accommodates remnant static magnetic fields up to ±5 nT. However, in the presented work, through simulation and experiment, we demonstrate that multi-axis magnetic signals in the presence of small remnant static magnetic fields, not violating the SERF criteria, can introduce significant error terms in OPM's output signal. We call these deterministic errors cross-axis projection errors (CAPE), where magnetic field components of the MEG signal perpendicular to the nominal sensing axis contribute to the OPM signal giving rise to substantial amplitude and phase errors. Furthermore, through simulation, we have discovered that CAPE can degrade localization and calibration accuracy of OPM-based magnetoencephalography (OPM-MEG) systems.

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YNICL Journal 2021 Journal Article

Auditory deficits in infants at risk for dyslexia during a linguistic sensitive period predict future language

Maria Mittag
Eric Larson
Maggie Clarke
Samu Taulu
Patricia K. Kuhl

Developmental dyslexia, a specific difficulty in learning to read and spell, has a strong hereditary component, which makes it possible to examine infants for early predictors of the condition even prior to the emergence of detectable symptoms. Using magnetoencephalography (MEG), we found smaller and shorter neural responses to simple sounds in infants at risk for dyslexia at 6 as compared to 12 months of age, a pattern that was reversed in age-matched controls. The findings indicate atypical auditory processing in at-risk infants across the sensitive period for native-language phoneme learning. This pattern was robust and localized to the same cortical areas regardless of the modeling parameters/algorithms used to estimate the current distribution underlying the measured activity. Its localization to left temporal and left frontal brain regions indicates a potential impact of atypical auditory processing on early language learning and later language skills because language functions are typically lateralized to the left hemisphere. This interpretation is supported by our further finding that atypical auditory responses in at-risk infants consistently predicted syntactic processing between 18 and 30 months and word production at 18 and 21 months of age. These results suggest a possible early marker of risk for dyslexia in at-risk infants.

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YNIMG Journal 2020 Journal Article

Neocortical activity tracks the hierarchical linguistic structures of self-produced speech during reading aloud

Mathieu Bourguignon
Nicola Molinaro
Mikel Lizarazu
Samu Taulu
Veikko Jousmäki
Marie Lallier
Manuel Carreiras
Xavier De Tiège

How the human brain uses self-generated auditory information during speech production is rather unsettled. Current theories of language production consider a feedback monitoring system that monitors the auditory consequences of speech output and an internal monitoring system, which makes predictions about the auditory consequences of speech before its production. To gain novel insights into underlying neural processes, we investigated the coupling between neuromagnetic activity and the temporal envelope of the heard speech sounds (i. e. , cortical tracking of speech) in a group of adults who 1) read a text aloud, 2) listened to a recording of their own speech (i. e. , playback), and 3) listened to another speech recording. Reading aloud was here used as a particular form of speech production that shares various processes with natural speech. During reading aloud, the reader’s brain tracked the slow temporal fluctuations of the speech output. Specifically, auditory cortices tracked phrases (<1 Hz) but to a lesser extent than during the two speech listening conditions. Also, the tracking of words (2–4 Hz) and syllables (4–8 Hz) occurred at parietal opercula during reading aloud and at auditory cortices during listening. Directionality analyses were then used to get insights into the monitoring systems involved in the processing of self-generated auditory information. Analyses revealed that the cortical tracking of speech at <1 Hz, 2–4 Hz and 4–8 Hz is dominated by speech-to-brain directional coupling during both reading aloud and listening, i. e. , the cortical tracking of speech during reading aloud mainly entails auditory feedback processing. Nevertheless, brain-to-speech directional coupling at 4–8 Hz was enhanced during reading aloud compared with listening, likely reflecting the establishment of predictions about the auditory consequences of speech before production. These data bring novel insights into how auditory verbal information is tracked by the human brain during perception and self-generation of connected speech.

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YNICL Journal 2017 Journal Article

Automatic detection and visualisation of MEG ripple oscillations in epilepsy

Nicole van Klink
Frank van Rosmalen
Jukka Nenonen
Sergey Burnos
Liisa Helle
Samu Taulu
Paul Lawrence Furlong
Maeike Zijlmans

High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

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JBHI Journal 2016 Journal Article

Virtual MEG Helmet: Computer Simulation of an Approach to Neuromagnetic Field Sampling

Mordekhay Medvedovsky
Jukka Nenonen
Alexandra Koptelova
Anna Butorina
Ritva Paetau
Jyrki P. Makela
Antti Ahonen
Juha Simola

Head movements during an MEG recording are commonly considered an obstacle. In this computer simulation study, we introduce an approach, the virtual MEG helmet (VMH), which employs the head movements for data quality improvement. With a VMH, a denser MEG helmet is constructed by adding new sensors corresponding to different head positions. Based on the Shannon's theory of communication, we calculated the total information as a figure of merit for comparing the actual 306-sensor Elekta Neuromag helmet to several types of the VMH. As source models, we used simulated randomly distributed source current (RDSC), simulated auditory and somatosensory evoked fields. Using the RDSC model with the simulation of 360 recorded events, the total information (bits/sample) was 989 for the most informative single head position and up to 1272 for the VMH (addition of 28. 6%). Using simulated AEFs, the additional contribution of a VMH was 12. 6% and using simulated SEF only 1. 1%. For the distributed and bilateral sources, a VMH can provide a more informative sampling of the neuromagnetic field during the same recording time than measuring the MEG from one head position. VMH can, in some situations, improve source localization of the neuromagnetic fields related to the normal and pathological brain activity. This should be investigated further employing real MEG recordings.

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