Neural networks simulating short-term memory of two inputs with varying commonality.

The activity and connectivity of neurons in the primate brain underlying behavior cannot yet be completely specified, but neural networks provide complete models of the connectivity and activity that performs specific tasks and provide insight into the neural computations performed by the primate brain (Fetz and Shupe 2003). Studies of neurons in the monkey cortex have shown that short-term memory of sensory events may be mediated by sustained neural activity. Short-term memory tasks have been modeled with dynamic neural networks using a single continuous variable and a gate input to create a sample-and-hold (SAH) function (Zipser 1991; Maier 2003).

Flexible modeling of large-scale neural network stimulation: electrical and optical extensions to The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX).

Computational models that predict effects of neural stimulation can be used as a preliminary tool to inform research, reducing the costs, time, and ethical considerations involved. However, current models do not support the diverse neural stimulation techniques used , including the expanding selection of electrodes, stimulation modalities, and stimulation paradigms. To develop a more comprehensive software, we created several extensions to The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX), the MATLAB-based neural stimulation tool from Newcastle University.

Neurochip3: An Autonomous Multichannel Bidirectional Brain-Computer Interface for Closed-Loop Activity-Dependent Stimulation.

Toward addressing many neuroprosthetic applications, the Neurochip3 (NC3) is a multichannel bidirectional brain-computer interface that operates autonomously and can support closed-loop activity-dependent stimulation. It consists of four circuit boards populated with off-the-shelf components and is sufficiently compact to be carried on the head of a non-human primate (NHP). NC3 has six main components: (1) an analog front-end with an Intan biophysical signal amplifier (16 differential or 32 single-ended channels) and a 3-axis accelerometer, (2) a digital control system comprised of a Cyclone V FPGA and Atmel SAM4 MCU, (3) a micro SD Card for 128 GB or more storage, (4) a 6-channel differential stimulator with ±60 V compliance, (5) a rechargeable battery pack supporting autonomous operation for up to 24 h and, (6) infrared transceiver and serial ports for communication.

Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates.

Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation.

An Integrate-and-Fire Spiking Neural Network Model Simulating Artificially Induced Cortical Plasticity.

We describe an integrate-and-fire (IF) spiking neural network that incorporates spike-timing-dependent plasticity (STDP) and simulates the experimental outcomes of four different conditioning protocols that produce cortical plasticity. The original conditioning experiments were performed in freely moving non-human primates (NHPs) with an autonomous head-fixed bidirectional brain-computer interface (BCI). Three protocols involved closed-loop stimulation triggered from (1) spike activity of single cortical neurons, (2) electromyographic (EMG) activity from forearm muscles, and (3) cycles of spontaneous cortical beta activity.