Multichannel recording of median nerve somatosensory evoked potentials

Mapping of the central sulcus using non-invasive ultra-high-density brain recordings

Brain mapping is vital in understanding the brain's functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable more detailed and nuanced mapping procedures. Here, we show that the central sulcus can be clearly delineated using a novel ultra-high-density EEG system (uHD EEG) and somatosensory evoked potentials (SSEPs). This uHD EEG records from 256 channels with an inter-electrode distance of 8.6 mm and an electrode diameter of 5.9 mm. Reconstructed head models were generated from T1-weighted MRI scans, and electrode positions were co-registered to these models to create topographical plots of brain activity. EEG data were first analyzed with peak detection methods and then classified using unsupervised spectral clustering. Our topography plots of the spatial distribution from the SSEPs clearly delineate a division between channels above the somatosensory and motor cortex, thereby localizing the central sulcus. Individual EEG channels could be correctly classified as anterior or posterior to the central sulcus with 95.2% accuracy, which is comparable to accuracies from invasive intracranial recordings. Our findings demonstrate that uHD EEG can resolve the electrophysiological signatures of functional representation in the brain at a level previously only seen from surgically implanted electrodes. This novel approach could benefit numerous applications, including research, neurosurgical mapping, clinical monitoring, detection of conscious function, brain-computer interfacing (BCI), rehabilitation, and mental health.

Somatosensory omissions reveal action-related predictive processing

The intricate relation between action and somatosensory perception has been studied extensively in the past decades. Generally, a forward model is thought to predict the somatosensory consequences of an action. These models propose that when an action is reliably coupled to a tactile stimulus, unexpected absence of the stimulus should elicit prediction error. Although such omission responses have been demonstrated in the auditory modality, it remains unknown whether this mechanism generalizes across modalities. This study therefore aimed to record action-induced somatosensory omission responses using EEG in humans. Self-paced button presses were coupled to somatosensory stimuli in 88% of trials, allowing a prediction, or in 50% of trials, not allowing a prediction. In the 88% condition, stimulus omission resulted in a neural response consisting of multiple components, as revealed by temporal principal component analysis. The oN1 response suggests similar sensory sources as stimulus-evoked activity, but an origin outside primary cortex. Subsequent oN2 and oP3 responses, as previously observed in the auditory domain, likely reflect modality-unspecific higher order processes. Together, findings straightforwardly demonstrate somatosensory predictions during action and provide evidence for a partially amodal mechanism of prediction error generation.

Passive localization of the central sulcus during sleep based on intracranial EEG

We test the performance of a novel operator-independent EEG-based method for passive identification of the central sulcus (CS) and sensorimotor (SM) cortex. We studied seven patients with intractable epilepsy undergoing intracranial EEG (icEEG) monitoring, in whom CS localization was accomplished by standard methods. Our innovative approach takes advantage of intrinsic properties of the primary motor cortex (MC), which exhibits enhanced icEEG band-power and coherence across the CS. For each contact, we computed a composite power, coherence, and entropy values for activity in the high gamma band (80-115) Hz of 6-10 min of NREM sleep. Statistically transformed EEG data values that did not reach a threshold (th) were set to 0. We computed a metric M based on the transformed values and the mean Euclidian distance of each contact from contacts with Z-scores higher than 0. The last step was implemented to accentuate local network activity. The SM cortex exhibited higher EEG-band-power than non-SM cortex (P < 0.0002). There was no significant difference between the motor/premotor and sensory cortices (P < 0.47). CS was localized in all patients with 0.4 < th < 0.6. The primary hand and leg motor areas showed the highest metric values followed by the tongue motor area. Higher threshold values were specific (94%) for the anterior bank of the CS but not sensitive (42%). Intermediate threshold values achieved an acceptable trade-off (0.4: 89% specific and 70% sensitive).

Novel Technique for Noninvasive Detection of Localized Dynamic Brain Signals by Using Transcranial Static Magnetic Fields

The techniques for noninvasive measurement of brain function such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS) have been used in diagnosing brain conditions. However, the conventional techniques have critical limitations of spatial or temporal resolution. Here, we developed a novel technique which enables the precise measurement of dynamic brain signals and localized identification of active brain regions. In this technique, termed as magnetically biased field (MBF), human brain signal is measured as the fluctuation of a transcranial static magnetic field emitted by a coil placed on the scalp. The validity of MBF was confirmed by the measurement of somatosensory evoked signals. Fast somatosensory evoked signals were successfully observed. Localized maximum positive and negative deflections appeared at the region which represents the right primary somatosensory area contralateral to the stimulated hand. The ability of MBF to detect dynamic brain activity precisely can have numerous applications such as diagnosing brain diseases and brain-machine interfaces.

Granger causal time-dependent source connectivity in the somatosensory network

Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

Whole-scalp EEG mapping of somatosensory evoked potentials in macaque monkeys

High-density scalp EEG recordings are widely used to study whole-brain neuronal networks in humans non-invasively. Here, we validate EEG mapping of somatosensory evoked potentials (SSEPs) in macaque monkeys (Macaca fascicularis) for the long-term investigation of large-scale neuronal networks and their reorganisation after lesions requiring a craniotomy. SSEPs were acquired from 33 scalp electrodes in five adult anaesthetized animals after electrical median or tibial nerve stimulation. SSEP scalp potential maps were identified by cluster analysis and identified in individual recordings. A distributed, linear inverse solution was used to estimate the intracortical sources of the scalp potentials. SSEPs were characterised by a sequence of components with unique scalp topographies. Source analysis confirmed that median nerve SSEP component maps were in accordance with the somatotopic organisation of the sensorimotor cortex. Most importantly, SSEP recordings were stable both intra- and interindividually. We aim to apply this method to the study of recovery and reorganisation of large-scale neuronal networks following a focal cortical lesion requiring a craniotomy. As a prerequisite, the present study demonstrated that a 300-mm² unilateral craniotomy over the sensorimotor cortex necessary to induce a cortical lesion, followed by bone flap repositioning, suture and gap plugging with calcium phosphate cement, did not induce major distortions of the SSEPs. In conclusion, SSEPs can be successfully and reproducibly recorded from high-density EEG caps in macaque monkeys before and after a craniotomy, opening new possibilities for the long-term follow-up of the cortical reorganisation of large-scale networks in macaque monkeys after a cortical lesion.

A time-varying source connectivity approach to reveal human somatosensory information processing

Exploration of neural sources and their effective connectivity based on transient changes in electrophysiological activities to external stimuli is important for understanding brain mechanisms of sensory information processing. However, such cortical mechanisms have not yet been well characterized in electrophysiological studies since (1) it is difficult to estimate the stimulus-activated neural sources and their activities and (2) it is difficult to identify transient effective connectivity between neural sources in the order of milliseconds. To address these issues, we developed a time-varying source connectivity approach to effectively capture fast-changing information flows between neural sources from high-density Electroencephalography (EEG) recordings. This time-varying source connectivity approach was applied to somatosensory evoked potentials (SEPs), which were elicited by electrical stimulation of right hand and recorded using 64 channels from 16 subjects, to reveal human somatosensory information processing. First, SEP sources and their activities were estimated, both at single-subject and group level, using equivalent current dipolar source modeling. Then, the functional integration among SEP sources was explored using a Kalman smoother based time-varying effective connectivity inference method. The results showed that SEPs were mainly generated from the contralateral primary somatosensory cortex (SI), bilateral secondary somatosensory cortex (SII), and cingulate cortex (CC). Importantly, we observed a serial processing of somatosensory information in human somatosensory cortices (from SI to SII) at earlier latencies (<150 ms) and a reciprocal processing between SII and CC at later latencies (>200 ms).

Neurophysiological evaluation in children with Friedreich's ataxia

INTRODUCTION

In children with Friedreich's ataxia (FRDA children), clinical ataxia outcomes are hardly substantiated by underlying neurophysiological parameters. In young FRDA children, some reports (based upon International Cooperative Ataxia Rating Scale scores (ICARS)) mention transient neurological improvement upon idebenone treatment. However, these outcomes are obtained with adult instead of pediatric reference values. It is unknown whether age-related neurophysiological parameters can really substantiate neurologic improvement.

AIM

In young FRDA children, we aimed to determine longitudinal neurophysiological parameters during idebenone treatment.

METHODS

During a two-year study period, 6 genetically proven FRDA children with cardiomyopathy (6-18years) were longitudinally assessed for neurophysiological parameters [sensory evoked potentials (SEPs), F response, peripheral nerve conduction and dynamometry] in association with age-matched ICARS-scores.

RESULTS

In all FRDA children, SEPs remained absent during the two-year study period. Peroneal nerve conduction velocity declined (from -1SD to -2SD; p<.05), whereas F responses remained essentially unaltered. Total muscle force and leg muscle force decreased (from -2 to -3SD and -2.5 to -3.5SD; both p<.05) and age-related ICARS-scores deteriorated (median increase +41%; p<.05).

CONCLUSION

In FRDA children, age-related neurophysiological and ataxia parameters deteriorate during idebenone treatment. Although we cannot exclude some (subjective) disease stabilization, age-related neurophysiological parameters do not substantiate neurologic improvement.

Quantifying interhemispheric symmetry of somatosensory evoked potentials with the intraclass correlation coefficient

Although large intersubject variability is reported for cortical somatosensory evoked potentials (SEPs), variability between hemispheres within one subject is thought to be small. Therefore, interhemispheric comparison of SEP waveforms might be clinically useful to detect unilateral abnormalities in cortical sensory processing. We developed and evaluated a new technique to quantify interhemispheric SEP symmetry that uses a time interval including multiple SEP components, measures similarity of SEP waveforms between both hemispheres and results in high symmetry values even in the presence of small interhemispheric anatomic differences. Median nerve SEPs were recorded in 50 healthy subjects (20-70 years) using 128-channel EEG. Symmetry was quantified by the intraclass correlation coefficient and correlation coefficient between global field power of left and right median nerve SEPs. In 74% of subjects left-right intraclass correlation coefficient was higher than 0.60, implying high SEP hemispheric symmetry in terms of shape and amplitude. Left-right intraclass correlation coefficients lower than 0.60 were due to differences in amplitude, unilateral absence of peaks, or shape differences. We quantified SEP waveform interhemispheric symmetry and found it to be high in most healthy subjects. This technique may therefore be useful for detection of unilateral abnormalities in cortical sensory processing.

A mouse model for studying large-scale neuronal networks using EEG mapping techniques

Human functional imaging studies are increasingly focusing on the identification of large-scale neuronal networks, their temporal properties, their development, and their plasticity and recovery after brain lesions. A method targeting large-scale networks in rodents would open the possibility to investigate their neuronal and molecular basis in detail. We here present a method to study such networks in mice with minimal invasiveness, based on the simultaneous recording of epicranial EEG from 32 electrodes regularly distributed over the head surface. Spatiotemporal analysis of the electrical potential maps similar to human EEG imaging studies allows quantifying the dynamics of the global neuronal activation with sub-millisecond resolution. We tested the feasibility, stability and reproducibility of the method by recording the electrical activity evoked by mechanical stimulation of the mystacial vibrissae. We found a series of potential maps with different spatial configurations that suggested the activation of a large-scale network with generators in several somatosensory and motor areas of both hemispheres. The spatiotemporal activation pattern was stable both across mice and in the same mouse across time. We also performed 16-channel intracortical recordings of the local field potential across cortical layers in different brain areas and found tight spatiotemporal concordance with the generators estimated from the epicranial maps. Epicranial EEG mapping thus allows assessing sensory processing by large-scale neuronal networks in living mice with minimal invasiveness, complementing existing approaches to study the neurophysiological mechanisms of interaction within the network in detail and to characterize their developmental, experience-dependent and lesion-induced plasticity in normal and transgenic animals.