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A cortical neural prosthesis for restoring and enhancing memory

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TLDR
These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.
Abstract
A primary objective in developing a neural prosthesis is to replace neural circuitry in the brain that no longer functions appropriately. Such a goal requires artificial reconstruction of neuron-to-neuron connections in a way that can be recognized by the remaining normal circuitry, and that promotes appropriate interaction. In this study, the application of a specially designed neural prosthesis using a multi-input/multi-output (MIMO) nonlinear model is demonstrated by using trains of electrical stimulation pulses to substitute for MIMO model derived ensemble firing patterns. Ensembles of CA3 and CA1 hippocampal neurons, recorded from rats performing a delayed-nonmatch-to-sample (DNMS) memory task, exhibited successful encoding of trial-specific sample lever information in the form of different spatiotemporal firing patterns. MIMO patterns, identified online and in real-time, were employed within a closed-loop behavioral paradigm. Results showed that the model was able to predict successful performance on the same trial. Also, MIMO model-derived patterns, delivered as electrical stimulation to the same electrodes, improved performance under normal testing conditions and, more importantly, were capable of recovering performance when delivered to animals with ensemble hippocampal activity compromised by pharmacologic blockade of synaptic transmission. These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.

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An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

TL;DR: A modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model is presented, able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.
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Evolving Applications, Technological Challenges and Future Opportunities in Neuromodulation: Proceedings of the Fifth Annual Deep Brain Stimulation Think Tank

TL;DR: Technical developments in DBS, design considerations for DBS electrodes, improved sensors, neuronal signal processing, advancements in development and uses of responsive DBS (closed-loop systems), updates on National Institutes of Health and DARPA DBS programs of the BRAIN initiative, and neuroethical and policy issues arising in and from DBS research and applications in practice are focused on.
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Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

TL;DR: The sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.
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A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems.

TL;DR: A review of control strategies in existing experimental, investigational and clinical neuroprosthetic systems is presented in order to establish a baseline and promote a common understanding of different feedback modes and closed-loop controllers.
References
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TL;DR: Results indicate that the synaptic receptor in the Schaffer collateral‐commissural pathway may be of the kainate or quisqualate type and although NMA receptors do not appear to be involved in normal synaptic transmission in this pathway they may play a role in synaptic plasticity.
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Cortical control of a prosthetic arm for self-feeding

TL;DR: A system that permits embodied prosthetic control is described and monkeys (Macaca mulatta) use their motor cortical activity to control a mechanized arm replica in a self-feeding task, and this demonstration of multi-degree-of-freedom embodied prosthetics control paves the way towards the development of dexterous prosthetic devices that could ultimately achieve arm and hand function at a near-natural level.
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A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.

TL;DR: A statistical framework based on the point process likelihood function to relate a neuron's spiking probability to three typical covariates: the neuron's own spiking history, concurrent ensemble activity, and extrinsic covariates such as stimuli or behavior.
Journal ArticleDOI

Brain-computer interfaces in neurological rehabilitation.

TL;DR: Non-invasive, electroencephalogram (EEG)-based brain-computer interface technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment.
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