Inefficient stimulus processing at encoding affects formation of high-order general representation: A study on cross-modal word-stem completion task

Correlated P300b and phasic pupil-dilation responses to motivationally significant stimuli

Motivationally significant events like oddball stimuli elicit both a characteristic event-related potential (ERPs) known as P300 and a set of autonomic responses including a phasic pupil dilation. Although co-occurring, P300 and pupil-dilation responses to oddball events have been repeatedly found to be uncorrelated, suggesting separate origins. We re-examined their relationship in the context of a three-stimulus version of the auditory oddball task, independently manipulating the frequency (rare vs. repeated) and motivational significance (relevance for the participant's task) of the stimuli. We used independent component analysis to derive a P300b component from EEG traces and linear modeling to separate a stimulus-related pupil-dilation response from a potentially confounding action-related response. These steps revealed that, once the complexity of ERP and pupil-dilation responses to oddball targets is accounted for, the amplitude of phasic pupil dilations and P300b are tightly and positively correlated (across participants: r = .69 p = .002), supporting their coordinated generation.

Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients

Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) methods have long been used for exploring brain electrical activity and functional connectivity modifications after stroke. However, results obtained so far are not univocal. Here, we used basic and advanced EEG methods to characterize how brain activity and functional connectivity change after stroke. Thirty-three unilateral post stroke patients in the sub-acute phase and ten neurologically intact age-matched right-handed subjects were enrolled. Patients were subdivided into two groups based on lesion location: cortico-subcortical (CS, n = 18) and subcortical (S, n = 15), respectively. Stroke patients were evaluated in the period ranging from 45 days since the acute event (T0) up to 3 months after stroke (T1) with both neurophysiological (resting state EEG) and clinical assessment (Barthel Index, BI) measures, while healthy subjects were evaluated once. Brain power at T0 was similar between the two groups of patients in all frequency bands considered (δ, θ, α, and β). However, evolution of θ-band power over time was different, with a normalization only in the CS group. Instead, average connectivity and specific network measures (Integration, Segregation, and Small-worldness) in the β-band at T0 were significantly different between the two groups. The connectivity and network measures at T0 also appear to have a predictive role in functional recovery (BI T1-T0), again group-dependent. The results obtained in this study showed that connectivity measures and correlations between EEG features and recovery depend on lesion location. These data, if confirmed in further studies, on the one hand could explain the heterogeneity of results so far observed in previous studies, on the other hand they could be used by researchers as biomarkers predicting spontaneous recovery, to select homogenous groups of patients for the inclusion in clinical trials.

A visual working memory dataset collection with bootstrap Independent Component Analysis for comparison of electroencephalographic preprocessing pipelines

Here we present an electroencephalographic (EEG) collection of 71-channel datasets recorded from 14 subjects (7 males, 7 females, aged 20-40 years) while performing a visual working memory task with a T set of 150 Independent Component Analysis (ICA) decompositions by Extended Infomax using RELICA, each on a bootstrap resampling of the data. These data are linked to the paper "Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition" [1]. Independent components (ICs) are clustered within subject and thereby associated with a quality index (QIc) measure of their stability to data resampling. Sets of single ICA decompositions obtained after applying Principal Component Analysis (PCA) to the data to perform dimension reduction retaining (85%, 95%, 99%) of data variance are also included, as are the positions of the best fitting equivalent dipoles for ICs whose scalp projections are compatible with a compact brain source. These bootstrap ICs may be used as benchmarks for different data preprocessing pipelines and/or ICA algorithms, allowing investigation of the effects that noise or insufficient data have on the quality of ICA decompositions.

Bilateral cortical representation of tactile roughness

Roughness is the most important feature for texture discrimination. Here we investigate how the bilateral cortical representation of touch is modulated by tactile roughness by analyzing the neural responses elicited by stimuli with various coarseness levels ranging from fine to medium. A prolonged stimulation was delivered to 10 healthy subjects by passively sliding tactile stimuli under the fingertip while recording the EEG to study the modulation of Somatosensory Evoked Potentials (SEPs) as well as activity in the theta and alpha bands. Elicited long-latency SEPs, namely bilateral P100-N140 and frontal P240 were consistent across stimuli. On the contrary, the temporal lag N140 - P240 was nonlinearly modulated both in contralateral and ipsilateral sides, in agreement with literature. Using a time-frequency analysis approach, we identified a theta band power increase in the [0 0.5]s interval and a partially overlapped power decrease in the alpha band which lasted throughout the stimulation. The estimated time these two phenomena were overlapped was comparable across stimuli, whereas a linear decrease in alpha band amplitude was reported when increasing the stimulus roughness in both contralateral and ipsilateral sides. This study showed that the selected tactile stimuli generated physiological bilateral responses that were modulated in a diversified way according to the stimulus roughness and side. Specifically, we identified sensory processing features (i.e., theta and alpha time overlap) invariant to the stimulus roughness (i.e., associated to a basic cortical mechanism of touch) and roughness-dependent cortical outputs comparable in the contralateral and ipsilateral sides that confirm a bilateral processing of tactile information.

A somatotopic bidirectional hand prosthesis with transcutaneous electrical nerve stimulation based sensory feedback

According to amputees, sensory feedback is amongst the most important features lacking from commercial prostheses. Although restoration of touch by means of implantable neural interfaces has been achieved, these approaches require surgical interventions, and their long-term usability still needs to be fully investigated. Here, we developed a non-invasive alternative which maintains some of the advantages of invasive approaches, such as a somatotopic sensory restitution scheme. We used transcutaneous electrical nerve stimulation (TENS) to induce referred sensations to the phantom hand of amputees. These sensations were characterized in four amputees over two weeks. Although the induced sensation was often paresthesia, the location corresponded to parts of the innervation regions of the median and ulnar nerves, and electroencephalographic (EEG) recordings confirmed the presence of appropriate responses in relevant cortical areas. Using these sensations as feedback during bidirectional prosthesis control, the patients were able to perform several functional tasks that would not be possible otherwise, such as applying one of three levels of force on an external sensor. Performance during these tasks was high, suggesting that this approach could be a viable alternative to the more invasive solutions, offering a trade-off between the quality of the sensation, and the invasiveness of the intervention.

Long-latency components of somatosensory evoked potentials during passive tactile perception of gratings

Perception of tactile stimuli elicits Somatosensory Evoked Potentials (SEPs) that can be recorded via non-invasive electroencephalography (EEG). However, it is not yet clear how SEPs localization, shape and latency are modulated by different stimuli during mechanical tactile stimulation of fingertips. The aim of this work is thus to characterize SEPs generated by the tactile perception of gratings during dynamic passive stimulation of the dominant fingertip by means of a mechatronic platform. Results show that a random sequence of stimuli elicited SEPs with two long-latency components: (i) a negative deflection around 140 ms located in the frontal-central-parietal side in the contralateral hemisphere; (ii) a positive deflection around 250 ms located in the frontal-central midline. Time-frequency analysis revealed significant continuous bilateral desynchronization in the alpha band throughout the passive stimulation. These results are a fundamental step towards building a model of brain responses during perception of tactile stimuli for future benchmarking studies.

Delta Power Is Higher and More Symmetrical in Ischemic Stroke Patients with Cortical Involvement

A brain injury resulting from unilateral stroke critically alters brain functionality and the complex balance within the cortical activity. Such modifications may critically depend on lesion location and cortical involvement. Indeed, recent findings pointed out the necessity of applying a stratification based on lesion location when investigating inter-hemispheric balance in stroke. Here, we tested whether cortical involvement could imply differences in band-specific activity and brain symmetry in post stroke patients with cortico-subcortical and subcortical strokes. We explored brain activity related to lesion location through EEG power analysis and quantitative Electroencephalography (qEEG) measures. Thirty stroke patients in the subacute phase and 10 neurologically intact age-matched right-handed subjects were enrolled. Stroke patients were equally subdivided in two groups based on lesion location: cortico-subcortical (CS, mean age ± SD: 72.21 ± 10.97 years; time since stroke ± SD: 31.14 ± 11.73 days) and subcortical (S, mean age ± SD: 68.92 ± 10.001 years; time since stroke ± SD: 26.93 ± 13.08 days) group. We assessed patients’ neurological status by means of National Institutes of Health Stroke Scale (NIHSS). High density EEG at rest was recorded and power spectral analysis in Delta (1–4 Hz) and Alpha (8–14 Hz) bands was performed. qEEG metrics as pairwise derived Brain Symmetry Index (pdBSI) and Delta/Alpha Ratio (DAR) were computed and correlated with NIHSS score. S showed a lower Delta power in the Unaffected Hemisphere (UH) compared to Affected Hemisphere (AH; z = −1.98, p < 0.05) and a higher Alpha power compared to CS (z = −2.18, p < 0.05). pdBSI was negatively correlated with NIHSS (R = −0.59, p < 0.05). CS showed a higher value and symmetrical distribution of Delta band activity (z = −2.37, p < 0.05), confirmed also by a higher DAR value compared to S (z = −2.48, p < 0.05). Patients with cortico-subcortical and subcortical lesions show different brain symmetry in the subacute phase. Interestingly, in subcortical stroke patient brain activity is related with the clinical function. qEEG measures can be explicative of brain activity related to lesion location and they could allow precise definition of diagnostic-therapeutic algorithms in stroke patients.

Spatiotemporal Dynamics of the Cortical Responses Induced by a Prolonged Tactile Stimulation of the Human Fingertips

The sense of touch is fundamental for daily behavior. The aim of this work is to understand the neural network responsible for touch processing during a prolonged tactile stimulation, delivered by means of a mechatronic platform by passively sliding a ridged surface under the subject's fingertip while recording the electroencephalogram (EEG). We then analyzed: (i) the temporal features of the Somatosensory Evoked Potentials and their topographical distribution bilaterally across the cortex; (ii) the associated temporal modulation of the EEG frequency bands. Long-latency SEP were identified with the following physiological sequence P100-N140-P240. P100 and N140 were bilateral potentials with higher amplitude in the contralateral hemisphere and with delayed latency in the ipsilateral side. Moreover, we found a late potential elicited around 200 ms after the stimulation was stopped, which likely encoded the end of tactile input. The analysis of cortical oscillations indicated an initial increase in the power of theta band (4-7 Hz) for 500 ms after the stimulus onset followed a decrease in the power of the alpha band (8-15 Hz) that lasted for the remainder of stimulation. This decrease was prominent in the somatosensory cortex and equally distributed in both contralateral and ipsilateral hemispheres. This study shows that prolonged stimulation of the human fingertip engages the cortex in widespread bilateral processing of tactile information, with different modulations of the theta and alpha bands across time.

Exploring neuro-muscular synergies of reaching movements with unified independent component analysis

The coordinated recruitment of group of muscles through muscles synergies is known to simplify the control of movements. However, how and to what extent such control scheme is encoded at a cortical level is poorly understood. So far, electroencephalography (EEG) and electromyography (EMG) have been used, separately, to investigate the cortical regions of the human brain which may be involved in activating muscle synergies. Here we aim at extending these results by looking for a hierarchical relationship between cortical and muscular sources of activity (neuro-muscular synergies) with a unified analysis of independent components (IC) simultaneously extracted from both EEG and EMG signals. We show for the first time how the direct fusion of EEG and EMG signals to extract unified ICs (unICs) can overcome the limitations of previous approaches, i.e., the difficulty in linking neural with muscular activations, and the lack of reliability of separate preprocessing techniques. Our results show that unified ICs were physiologically meaningful components in agreement with previous works. UNICA (Unified Independent Component Analysis) can also be considered as a solution for estimating overcomplete ICA on EEG and EMG data. These findings are an important step towards an understanding of the cortical control of human muscles synergies, and may have important applications for understanding movement dysfunction and to develop novel approaches for brain-computer interfaces and neuroprostheses.