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Objective. Microstimulation via electrodes that penetrate the visual cortex creates visual perceptions called phosphenes. Besides providing electrical stimulation to induce perceptions, each electrode can be used to record the brain signals from the cortex region under the electrode which contains brain state information. Since the future visual prosthesis interfaces will be implanted chronically in the visual cortex of blind people, it is important to study the long-term stability of the signals acquired from the electrodes. Here, we studied the changes over time and the repercussions of electrical stimulation on the brain signals acquired with an intracortical 96-channel microelectrode array implanted in the visual cortex of a blind volunteer for 6 months. Approach. We used variance, power spectral density, correlation, coherence, and phase coherence to study the brain signals acquired in resting condition before and after the administration of electrical stimulation during a period of 6 months. Main results. Variance and power spectral density up to 750 Hz do not show any significant trend in the 6 months, but correlation coherence and phase coherence significantly decrease over the implantation time and increase after electrical stimulation. Significance. The stability of variance and power spectral density in time is important for long-term clinical applications based on the intracortical signals collected by the electrodes. The decreasing trends of correlation, coherence, and phase coherence might be related to plasticity changes in the visual cortex due to electrical microstimulation., (Creative Commons Attribution license.)

BACKGROUNDA long-held goal of vision therapy is to transfer information directly to the visual cortex of blind individuals, thereby restoring a rudimentary form of sight. However, no clinically available cortical visual prosthesis yet exists.METHODSWe implanted an intracortical microelectrode array consisting of 96 electrodes in the visual cortex of a 57-year-old person with complete blindness for a 6-month period. We measured thresholds and the characteristics of the visual percepts elicited by intracortical microstimulation.RESULTSImplantation and subsequent explantation of intracortical microelectrodes were carried out without complications. The mean stimulation threshold for single electrodes was 66.8 ± 36.5 μA. We consistently obtained high-quality recordings from visually deprived neurons and the stimulation parameters remained stable over time. Simultaneous stimulation via multiple electrodes was associated with a significant reduction in thresholds (P < 0.001, ANOVA) and evoked discriminable phosphene percepts, allowing the blind participant to identify some letters and recognize object boundaries.CONCLUSIONSOur results demonstrate the safety and efficacy of chronic intracortical microstimulation via a large number of electrodes in human visual cortex, showing its high potential for restoring functional vision in the blind.TRIAL REGISTRATIONClinicalTrials.gov identifier NCT02983370.FUNDINGThe Spanish Ministerio de Ciencia Innovación y Universidades, the Generalitat Valenciana (Spain), the Europan Union's Horizon 2020 programme, the Bidons Egara Research Chair of the University Miguel Hernández (Spain), and the John Moran Eye Center of the University of Utah.

The development of suitable EEG-based emotion recognition systems has become a main target in the last decades for Brain Computer Interface applications (BCI). However, there are scarce algorithms and procedures for real-time classification of emotions. The present study aims to investigate the feasibility of real-time emotion recognition implementation by the selection of parameters such as the appropriate time window segmentation and target bandwidths and cortical regions. We recorded the EEG-neural activity of 24 participants while they were looking and listening to an audiovisual database composed of positive and negative emotional video clips. We tested 12 different temporal window sizes, 6 ranges of frequency bands and 60 electrodes located along the entire scalp. Our results showed a correct classification of 86.96% for positive stimuli. The correct classification for negative stimuli was a little bit less (80.88%). The best time window size, from the tested 1 s to 12 s segments, was 12 s. Although more studies are still needed, these preliminary results provide a reliable way to develop accurate EEG-based emotion classification.