Toward the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes

A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion,while simultaneously receiving stimuli from the environment and controlling some part of a human brain or body.Incoming visual information can be processed by the brain in millisecond intervals.The retina computes visual scenes and sends its output to the cortex in the form of neuronal spikes for further computation.Thus,the neuronal signal of interest for a retinal neuroprosthesis is the neuronal spike.Closed-loop computation in a neuroprosthesis includes two stages:encoding a stimulus as a neuronal signal,and decoding it back into a stimulus.In this paper,we review some of the recent progress that has been achieved in visual computation models that use spikes to analyze natural scenes that include static images and dynamic videos.We hypothesize that in order to obtain a better understanding of the computational principles in the retina,a hypercircuit view of the retina is necessary,in which the different functional network motifs that have been revealed in the cortex neuronal network are taken into consideration when interacting with the retina.The different building blocks of the retina,which include a diversity of cell types and synaptic connections-both chemical synapses and electrical synapses(gap junctions)-make the retina an ideal neuronal network for adapting the computational techniques that have been developed in artificial intelligence to model the encoding and decoding of visual scenes.An overall systems approach to visual computation with neuronal spikes is necessary in order to advance the next generation of retinal neuroprosthesis as an artificial visual system.

Motor neuroprosthesis for injured spinal cord:who is an ideal candidate?

A spinal cord injury （SCI） shatters people＇s lives in a fraction of a second, leaving them paralyzed, often for the rest of their lives. The devastation caused by SCI is significant around the world. Though the exact prevalence of the injury is un- known, according to recent statistics, the number of injuries is estimated to be between 1.65 and 7.06 million worldwide （Alam and He, 2014）. A recent report from the World Health Organization （WHO） states that, every year, 250,000-500,000 new spinal cord injuries occur around the world （Bickenbach et al., 2013）. Beyond the physical sufferings of these paralyzed individuals, SCI has huge economic and social impacts. In the United States alone,

15 Years of Evolution of Non-Invasive EEG-Based Methods for Restoring Hand &Arm Function with Motor Neuroprosthetics in Individuals with High Spinal Cord Injury: A Review of Graz BCI Research

Patients who suffer from a high spinal cord injury have severe motor disabilities in the lower as well as in the upper extremities. Thus they rely on the help of other people in everyday life. Restoring the function of the upper limbs, especially the grasp function can help them to gain some independence. Using EEG-based neuroprosthetics is a way to help tetraplegic people restore different grasp types as well as moving the arm and the elbow. In this work an overview of non-invasive EEG-based methods for restoring the hand and arm function with the use of neuroprosthetics in individuals with high spinal cord injury is given. Since the Graz BCI group is leading in this area of non-invasive research mainly, the work of this group is represented.

Brain–computer interfaces for human gait restoration

In this review article, we present more than a decade of our work on the development of brain–computer interface (BCI)systems for the restoration of walking following neurological injuries such as spinal cord injury (SCI) or stroke. Most ofthis work has been in the domain of non-invasive electroencephalogram-based BCIs, including interfacing our system witha virtual reality environment and physical prostheses. Real-time online tests are presented to demonstrate the ability ofable-bodied subjects as well as those with SCI to purposefully operate our BCI system. Extensions of this work are alsopresented and include the development of a portable low-cost BCI suitable for at-home use, our ongoing eforts to develop afully implantable BCI for the restoration of walking and leg sensation after SCI, and our novel BCI-based therapy for strokerehabilitation.