Martin G. Bleichner

Brain–computer interfacing based on cognitive control

Brain–computer interfaces (BCIs) translate deliberate intentions and associated changes in brain activity into action, thereby offering patients with severe paralysis an alternative means of communication with and control over their environment. Such systems are not available yet, partly due to the high performance standard that is required. A major challenge in the development of implantable BCIs is to identify cortical regions and related functions that an individual can reliably and consciously manipulate. Research predominantly focuses on the sensorimotor cortex, which can be activated by imagining motor actions. However, because this region may not provide an optimal solution to all patients, other neuronal networks need to be examined. Therefore, we investigated whether the cognitive control network can be used for BCI purposes. We also determined the feasibility of using functional magnetic resonance imaging (fMRI) for noninvasive localization of the cognitive control network.

Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear

This study presents first evidence that reliable EEG data can be recorded with a new cEEGrid electrode array, which consists of ten electrodes printed on flexible sheet and arranged in a c-shape to fit around the ear. Ten participants wore two cEEGrid systems for at least seven hours. Using a smartphone for stimulus delivery and signal acquisition, resting EEG and auditory oddball data were collected in the morning and in the afternoon six to seven hours apart. Analysis of resting EEG data confirmed well-known spectral differences between eyes open and eyes closed conditions. The ERP results confirmed the predicted condition effects with significantly larger P300 amplitudes for target compared to standard tones, and a high test-retest reliability of the P300 amplitude (r > = .74). Moreover, a linear classifier trained on data from the morning session revealed similar performance in classification accuracy for the morning and the afternoon sessions (both > 70%). These findings demonstrate the feasibility of concealed and comfortable brain activity acquisition over many hours.

Fully Implanted Brain–Computer Interface in a Locked-In Patient with ALS

Options for people with severe paralysis who have lost the ability to communicate orally are limited. We describe a method for communication in a patient with late-stage amyotrophic lateral sclerosis (ALS), involving a fully implanted brain-computer interface that consists of subdural electrodes placed over the motor cortex and a transmitter placed subcutaneously in the left side of the thorax. By attempting to move the hand on the side opposite the implanted electrodes, the patient accurately and independently controlled a computer typing program 28 weeks after electrode placement, at the equivalent of two letters per minute. The brain-computer interface offered autonomous communication that supplemented and at times supplanted the patients eye-tracking device. (Funded by the Government of the Netherlands and the European Union; ClinicalTrials.gov number, NCT02224469 .).

Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery.

Motor imagery (MI) combined with real-time electroencephalogram (EEG) feedback is a popular approach for steering brain-computer interfaces (BCI). MI BCI has been considered promising as add-on therapy to support motor recovery after stroke. Yet whether EEG neurofeedback indeed targets specific sensorimotor activation patterns cannot be unambiguously inferred from EEG alone. We combined MI EEG neurofeedback with concurrent and continuous functional magnetic resonance imaging (fMRI) to characterize the relationship between MI EEG neurofeedback and activation in cortical sensorimotor areas. EEG signals were corrected online from interfering MRI gradient and ballistocardiogram artifacts, enabling the delivery of real-time EEG feedback. Significantly enhanced task-specific brain activity during feedback compared to no feedback blocks was present in EEG and fMRI. Moreover, the contralateral MI related decrease in EEG sensorimotor rhythm amplitude correlated inversely with fMRI activation in the contralateral sensorimotor areas, whereas a lateralized fMRI pattern did not necessarily go along with a lateralized EEG pattern. Together, the findings indicate a complex relationship between MI EEG signals and sensorimotor cortical activity, whereby both are similarly modulated by EEG neurofeedback. This finding supports the potential of MI EEG neurofeedback for motor rehabilitation and helps to better understand individual differences in MI BCI performance.

Frequency specific spatial interactions in human electrocorticography: V1 alpha oscillations reflect surround suppression

Electrical brain signals are often decomposed into frequency ranges that are implicated in different functions. Using subdural electrocorticography (ECoG, intracranial EEG) and functional magnetic resonance imaging (fMRI), we measured frequency spectra and BOLD responses in primary visual cortex (V1) and intraparietal sulcus (IPS). In V1 and IPS, 30-120 Hz (gamma, broadband) oscillations allowed population receptive field (pRF) reconstruction comparable to fMRI estimates. Lower frequencies, however, responded very differently in V1 and IPS. In V1, broadband activity extends down to 3 Hz. In the 4-7 Hz (theta) and 18-30 Hz (beta) ranges broadband activity increases power during stimulation within the pRF. However, V1 9-12 Hz (alpha) frequency oscillations showed a different time course. The broadband power here is exceeded by a frequency-specific power increase during stimulation of the area outside the pRF. As such, V1 alpha oscillations reflected surround suppression of the pRF, much like negative fMRI responses. They were consequently highly localized, depending on stimulus and pRF position, and independent between nearby electrodes. In IPS, all 3-25 Hz oscillations were strongest during baseline recording and correlated between nearby electrodes, consistent with large-scale disengagement. These findings demonstrate V1 alpha oscillations result from locally active functional processes and relate these alpha oscillations to negative fMRI signals. They highlight that similar oscillations in different areas reflect processes with different functional roles. However, both of these roles of alpha seem to reflect suppression of spiking activity.

Exploring miniaturized EEG electrodes for brain‐computer interfaces. An EEG you do not see?

Electroencephalography (EEG) allows the study of the brain–behavior relationship in humans. Most of what we have learned with EEG was through observing the brain–behavior relationship under well‐controlled laboratory conditions. However, by reducing “normal” behavior to a minimum the ecological validity of the results can be limited. Recent developments toward mobile EEG solutions allow to study the brain–behavior relationship outside the laboratory in more natural situations. Besides mobility and robustness with respect to motion, mobile EEG systems should also interfere as little as possible with the participants behavior. For example, natural interaction with other people could be hindered when it is obvious that a participant wears an EEG cap. This study evaluates the signal quality obtained with an unobtrusive solution for EEG monitoring through the integration of miniaturized EEG ton‐electrodes into both a discreet baseball cap and an individualized ear piece. We show that such mini electrodes located at scalp and ear locations can reliably record event related potentials in a P300 brain–computer–interface application.

Functional MRI-based identification of brain areas involved in motor imagery for implantable brain–computer interfaces

For the development of minimally invasive brain-computer interfaces (BCIs), it is important to accurately localize the area of implantation. Using fMRI, we investigated which brain areas are involved in motor imagery. Twelve healthy subjects performed a motor execution and imagery task during separate fMRI and EEG measurements. fMRI results showed that during imagery, premotor and parietal areas were most robustly activated in individual subjects, but surprisingly, no activation was found in the primary motor cortex. EEG results showed that spectral power decreases in contralateral sensorimotor rhythms (8-24 Hz) during both movement and imagery. To further verify the involvement of the motor imagery areas found with fMRI, one epilepsy patient performed the same task during both fMRI and ECoG recordings. Significant ECoG low (8-24 Hz) and high (65-95 Hz) frequency power changes were observed selectively on premotor cortex and these co-localized with fMRI. During a subsequent BCI task, excellent performance (91%) was obtained based on ECoG power changes from the localized premotor area. These results indicate that other areas than the primary motor area may be more reliably activated during motor imagery. Specifically, the premotor cortex may be a better area to implant an invasive BCI.

Valence, arousal, and task effects in emotional prosody processing

Previous research suggests that emotional prosody processing is a highly rapid and complex process. In particular, it has been shown that different basic emotions can be differentiated in an early event-related brain potential (ERP) component, the P200. Often, the P200 is followed by later long lasting ERPs such as the late positive complex. The current experiment set out to explore in how far emotionality and arousal can modulate these previously reported ERP components. In addition, we also investigated the influence of task demands (implicit vs. explicit evaluation of stimuli). Participants listened to pseudo-sentences (sentences with no lexical content) spoken in six different emotions or in a neutral tone of voice while they either rated the arousal level of the speaker or their own arousal level. Results confirm that different emotional intonations can first be differentiated in the P200 component, reflecting a first emotional encoding of the stimulus possibly including a valence tagging process. A marginal significant arousal effect was also found in this time-window with high arousing stimuli eliciting a stronger P200 than low arousing stimuli. The P200 component was followed by a long lasting positive ERP between 400 and 750 ms. In this late time-window, both emotion and arousal effects were found. No effects of task were observed in either time-window. Taken together, results suggest that emotion relevant details are robustly decoded during early processing and late processing stages while arousal information is only reliably taken into consideration at a later stage of processing.

Cortical theta wanes for language.

The role of low frequency oscillations in language areas is not yet understood. Using ECoG in six human subjects, we studied whether different language regions show prominent power changes in a specific rhythm, in similar manner as the alpha rhythm shows the most prominent power changes in visual areas. Brocas area and temporal language areas were localized in individual subjects using fMRI. In these areas, the theta rhythm showed the most pronounced power changes and theta power decreased significantly during verb generation. To better understand the role of this language-related theta decrease, we then studied the interaction between low frequencies and local neuronal activity reflected in high frequencies. Amplitude-amplitude correlations showed that theta power correlated negatively with high frequency activity, specifically across verb generation trials. Phase-amplitude coupling showed that during control trials, high frequency power was coupled to theta phase, but this coupling decreased significantly during verb generation trials. These results suggest a dynamic interaction between the neuronal mechanisms underlying the theta rhythm and local neuronal activity in language areas. As visual areas show a pronounced alpha rhythm that may reflect pulsed inhibition, language regions show a pronounced theta rhythm with highly similar features.

Mismatch Between Electrocortical Stimulation and Electrocorticography Frequency Mapping of Language

BACKGROUND Electrocortical Stimulation Mapping (ESM) is the gold standard for mapping eloquent cortex in neurosurgery. This technique, however, can cause seizures and requires good patient cooperation. Electrocorticography (ECoG) could replace ESM. Several studies have directly compared ESM and ECoG frequency mapping of language cortex, with mixed results. This may be due to ECoG mapping typically being limited to one or a few language tasks, potentially leading to underestimation of language representation. OBJECTIVE To evaluate the influence of the language task on the match between ECoG and ESM, we mapped language function based on episodes of spontaneous conversation with ECoG, and compared this with ESM data in eight epilepsy patients. A verb generation and picture naming task were used as reference standard. METHODS From the continuous ECoG and video registrations, periods of conversation were identified, distinguishing three conditions: speaking, listening and rest. A power-frequency analysis was done for each condition and the two language tasks. The match between ESM and ECoG frequency mapping was evaluated on the basis of sensitivity and specificity measures. RESULTS ECoG activation during spontaneous conversation and language tasks was seen in and around classic language areas. Comparing the electrodes activated in each condition with those indicated as language positive by ESM revealed that there was high specificity but relatively low sensitivity. CONCLUSION The relatively poor match between ESM and ECoG mapping is not improved by using spontaneous language.