Samu Taulu

Signal space separation algorithm and its application on suppressing artifacts caused by vagus nerve stimulation for magnetoencephalography recordings.

Magnetoencephalography (MEG) has been successfully applied to presurgical epilepsy foci localization and brain functional mapping. Because the neuronal magnetic signals from the brain are extremely weak, MEG measurement requires both low environment noise and the subject/patient being free of artifact-generating metal objects. This strict requirement makes it hard for patients with vagus nerve stimulator, or other similar medical devices, to benefit from the presurgical MEG examinations. Therefore, an approach that can effectively reduce the environmental noise and faithfully recover the brain signals is highly desirable. We applied spatiotemporal signal space separation method, an advanced signal processing approach that can recover bio-magnetic signal from inside the MEG sensor helmet and suppress external disturbance from outside the helmet in empirical MEG measurements, on MEG recordings from normal control subjects and patients who has vagus nerve stimulator. The original MEG recordings were heavily contaminated, and the data could not be assessed. After applying temporal signal space separation, the strong external artifacts from outside the brain were successfully removed, and the neuronal signal from the human brain was faithfully recovered. Both of the goodness-of-fit and 95% confident limit volume confirmed the significant improvement after temporal signal space separation. Hence, temporal signal space separation makes presurgical MEG examinations possible for patients with implanted vagus nerve stimulator or similar medical devices.

Speech discrimination in 11-month-old bilingual and monolingual infants: a magnetoencephalography study.

Language experience shapes infants abilities to process speech sounds, with universal phonetic discrimination abilities narrowing in the second half of the first year. Brain measures reveal a corresponding change in neural discrimination as the infant brain becomes selectively sensitive to its native language(s). Whether and how bilingual experience alters the transition to native language specific phonetic discrimination is important both theoretically and from a practical standpoint. Using whole head magnetoencephalography (MEG), we examined brain responses to Spanish and English syllables in Spanish-English bilingual and English monolingual 11-month-old infants. Monolingual infants showed sensitivity to English, while bilingual infants were sensitive to both languages. Neural responses indicate that the dual sensitivity of the bilingual brain is achieved by a slower transition from acoustic to phonetic sound analysis, an adaptive and advantageous response to increased variability in language input. Bilingual neural responses extend into the prefrontal and orbitofrontal cortex, which may be related to their previously described bilingual advantage in executive function skills. A video abstract of this article can be viewed at: https://youtu.be/TAYhj-gekqw.

Functional Connectivity of the Pedunculopontine Nucleus and Surrounding Region in Parkinson's Disease

Abstract Deep brain stimulation of the pedunculopontine nucleus and surrounding region (PPNR) is a novel treatment strategy for gait freezing in Parkinsons disease (PD). However, clinical results have been variable, in part because of the paucity of functional information that might help guide selection of the optimal surgical target. In this study, we use simultaneous magnetoencephalography and local field recordings from the PPNR in seven PD patients, to characterize functional connectivity with distant brain areas at rest. The PPNR was preferentially coupled to brainstem and cingulate regions in the alpha frequency (8‐12 Hz) band and to the medial motor strip and neighboring areas in the beta (18‐33 Hz) band. The distribution of coupling also depended on the vertical distance of the electrode from the pontomesencephalic line: most effects being greatest in the middle PPNR, which may correspond to the caudal pars dissipata of the pedunculopontine nucleus. These observations confirm the crucial position of the PPNR as a functional node between cortical areas such as the cingulate/ medial motor strip and other brainstem nuclei, particularly in the dorsal pons. In particular they suggest a special role for the middle PPNR as this has the greatest functional connectivity with other brain regions.

Infant brain responses to felt and observed touch of hands and feet: an MEG study

There is growing interest concerning the ways in which the human body, both ones own and that of others, is represented in the developing human brain. In two experiments with 7-month-old infants, we employed advances in infant magnetoencephalography (MEG) brain imaging to address novel questions concerning body representations in early development. Experiment 1 evaluated the spatiotemporal organization of infants brain responses to being touched. A punctate touch to infants hands and feet produced significant activation in the hand and foot areas of contralateral primary somatosensory cortex as well as in other parietal and frontal areas. Experiment 2 explored infant brain responses to visually perceiving another persons hand or foot being touched. Results showed significant activation in early visual regions and also in regions thought to be involved in multisensory body and self-other processing. Furthermore, observed touch of the hand and foot activated the infants own primary somatosensory cortex, although less consistently than felt touch. These findings shed light on aspects of early social cognition, including action imitation, which may build, at least in part, on infant neural representations that map equivalences between the bodies of self and other.

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. While 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. This 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.

Magnetoencephalographic Infraslow Activity: A Feasibility Study.

Purpose: To explore if background infraslow activity (ISA) can be retrieved from archived magnetoencephalographic (MEG) recordings and its potential clinical relevance. Methods: Archived recordings of 15 patients with epilepsy and 10 normal subjects were evaluated for MEG/EEG delta (0.5–3 Hz) and ISA (0.01–0.1 Hz). The data were obtained on a Neuromag/Elekta system with 204 planar gradiometers and 102 magnetometer sensors and also 60 EEG channels. To remove artifacts, all MEG files were temporal signal space separation filtered. The data were then analyzed with the BESA Research software. Results: Infraslow activity was present in all files for MEG and EEG. Good concordance between EEG and MEG ISA was seen with delta for laterality and with clinical features. Delta frequencies were always less than 2 Hz. During sleep, an inverse relationship between delta and ISA occurred. With increasing depth of sleep, delta activity increased while ISA decreased and vice versa. Intermittent higher amplitude transients, arising from background, were also seen but their nature is at present unknown. Clinically relevant ictal onset baseline shifts were likewise observed. Conclusion: Infraslow activity is a normal segment of the cerebral electromagnetic frequency spectrum. It follows physiologic rules and can be related to areas of pathology. This is in accord with previously published EEG observations and further studies of this segment of the electromagnetic frequency spectrum for its origin and changes in health and disease are indicated.

Left-Lateralized Contributions of Saccades to Cortical Activity During a One-Back Word Recognition Task

Saccadic eye movements are an inherent component of natural reading, yet their contribution to information processing at subsequent fixation remains elusive. Here we use anatomically-constrained magnetoencephalography (MEG) to examine cortical activity following saccades as healthy human subjects engaged in a one-back word recognition task. This activity was compared with activity following external visual stimulation that mimicked saccades. A combination of procedures was employed to eliminate saccadic ocular artifacts from the MEG signal. Both saccades and saccade-like external visual stimulation produced early-latency responses beginning ~70 ms after onset in occipital cortex and spreading through the ventral and dorsal visual streams to temporal, parietal and frontal cortices. Robust differential activity following the onset of saccades vs. similar external visual stimulation emerged during 150–350 ms in a left-lateralized cortical network. This network included: (i) left lateral occipitotemporal (LOT) and nearby inferotemporal (IT) cortex; (ii) left posterior Sylvian fissure (PSF) and nearby multimodal cortex; and (iii) medial parietooccipital (PO), posterior cingulate and retrosplenial cortices. Moreover, this left-lateralized network colocalized with word repetition priming effects. Together, results suggest that central saccadic mechanisms influence a left-lateralized language network in occipitotemporal and temporal cortex above and beyond saccadic influences at preceding stages of information processing during visual word recognition.

Automatic detection and visualisation of MEG ripple oscillations in epilepsy

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.