Implantable Neural Probes for Brain-Machine Interfaces - Current Developments and Future Prospects

A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings. Specifically, we focus on three key topics: (1) novel implantable neural probes that decrease the level of invasiveness without sacrificing performance, (2) multi-modal neural probes that measure both electrical and optical signals, (3) and neural probes developed using advanced materials. Because safety and precision are critical for practical applications of BMI systems, future studies should aim to enhance these properties when developing next-generation neural probes

Personalized Neuroprosthetics

Decades of technological developments have populated the field of neuroprosthetics with myriad replacement strategies, neuromodulation therapies, and rehabilitation procedures to improve the quality of life for individuals with neuromotor disorders. Despite the few but impressive clinical successes, and multiple breakthroughs in animal models, neuroprosthetic technologies remain mainly confined to sophisticated laboratory environments. We summarize the core principles and latest achievements in neuroprosthetics, but also address the challenges that lie along the path toward clinical fruition. We propose a pragmatic framework to personalise neurotechnologies and rehabilitation for patient-specific impairments to achieve the timely dissemination of neuroprosthetic medicine

The timing of exploratory decision-making revealed by single-trial topographic EEGanalyses.

Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis

Very high frequency oscillations (VHFO) as a predictor of movement

Gamma band (30-80 Hz) oscillations arising in neuronal ensembles are thought to be a crucial component of the neural code. Recent studies in animals suggest a similar functional role for very high frequency oscillations (VHFO) in the range 80-200 Hz. Since some intracerebral studies in humans link VHFO to epileptogenesis, it remains unclear if VHFO appear in the healthy human brain and if so which is their role. This study uses EEG recordings from twelve healthy volunteers, engaged in a visuo-motor reaction time task, to show that VHFO are not necessarily pathological but rather code information about upcoming movements. Oscillations within the range (30-200 Hz) occurring in the period between stimuli presentation and the fastest hand responses allow highly accurate (>96%) prediction of the laterality of the responding hand in single trials. Our results suggest that VHFO belong in functional terms to the gamma band that must be considerably enlarged to better understand the role of oscillatory activity in brain functioning. This study has therefore important implications for the recording and analysis of electrophysiological data in normal subjects and patients