In an embodiment, the invention relates to neural prosthetic devices in which control signals are based on the cognitive activity of the prosthetic user. The control signals may be used to control an array of external devices, such as prosthetics, computer systems, and speech synthesizers. Data obtained from a 4×4 mm patch of the posterial parietal cortex illustrated that a single neural recording array could decoded movements of a large extent of the body. Cognitive activity is functionally segregated between body parts.

A neural network and its information processing method, information processing system. The neural network includes N layers of neuron layers connected to each other one by one, except for a first layer of neuron layer, each of the neurons of the other neuron layers includes m dendritic units and one hippocampal unit; the dendritic unit includes a resistance value graded device, the hippocampal unit includes a resistance value mutation device, and the m dendritic units can be provided with different threshold voltage or current, respectively; and the neurons on the nth layer neuron layer are connected to the m dendritic units of the neurons on the n+1th layer neuron layer; wherein N is an integer larger than 3, m is an integer larger than 1, n is an integer larger than 1 and less than N.

Apparatus and methods for 3D-Scanless Holographic Optogenetics with Temporal focusing (3D-SHOT), which allows precise, simultaneous photo-activation of arbitrary sets of neurons anywhere within the addressable volume of the microscope. Soma-targeted (ST) optogenetic tools, ST-ChroME and IRES-ST-eGtACR 1, optimized for multiphoton activation and suppression are also provided. The methods use point-cloud holography to place multiple copies of a temporally focused disc matching the dimensions of a designated neuron's cell body. Experiments in cultured cells, brain slices, and in living mice demonstrate single-neuron spatial resolution even when optically targeting randomly distributed groups of neurons in 3D.

A neural system comprises multiple neurons interconnected via synapse devices. Each neuron integrates input signals arriving on its dendrite, generates a spike in response to the integrated input signals exceeding a threshold, and sends the spike to the interconnected neurons via its axon. The system further includes multiple noruens, each noruen is interconnected via the interconnect network with those neurons that the noruen's corresponding neuron sends its axon to. Each noruen integrates input spikes from connected spiking neurons and generates a spike in response to the integrated input spikes exceeding a threshold. There can be one noruen for every corresponding neuron. For a first neuron connected via its axon via a synapse to dendrite of a second neuron, a noruen corresponding to the second neuron is connected via its axon through the same synapse to dendrite of the noruen corresponding to the first neuron.

Disclosed herein are system, method, and computer program product embodiments for determining a score for a degree of activation of a biological network. An embodiment constructs a tree graph comprising a root node and a set of child nodes. The root node represents a biological network having a reference node and causal connections among a set of nodes that represent biological entities, biological processes, or other biological networks. Each child node represents a particular node in the biological network and is connected to the root node by a signed, directed edge pointing from the root node to that child node. Each child node also has an associated weight based on one or more paths connecting the child node to the reference node in the biological network. The embodiment further scores the tree graph based on scores assigned to the child nodes and the signs of the singed, directed edges.

A nanosheet 4T2R unit cell for neuromorphic computing is provided. In one aspect, a method of forming a 4T2R unit cell includes: forming nanosheets on a substrate having alternating sacrificial and channel nanosheets; patterning the nanosheets into FET stacks; forming lower/upper source and drains on opposite sides of lower/upper portions of the FET stacks; forming a first gate of an FET1 in the upper portion of a first FET stack, a second gate of an FET2 in the upper portion of a second FET stack, a third gate of an FET3 in the lower portion of a second FET stack, and a fourth gate of an FET4 in the lower portion of a third FET stack; and forming RRAM devices in contact vias to the source and drains of the FET1 and the FET4. A 4T2R unit cell and method for neuromorphic computing are also provided.

Techniques are disclosed for fabricating and using a neuromorphic computing device including biological neurons. For example, a method for fabricating a neuromorphic computing device includes forming a channel in a first substrate and forming at least one sensor in a second substrate. At least a portion of the channel in the first substrate is seeded with a biological neuron growth material. The second substrate is attached to the first substrate such that the at least one sensor is proximate to the biological neuron growth material and growth of the seeded biological neuron growth material is stimulated to grow a neuron in the at least a portion of the channel.

An method of operating an implantable device includes sensing a neural signal generated in a tissue of a body, recognizing input information to process a cryptocurrency-based financial transaction by analyzing the sensed neural signal, and processing the cryptocurrency-based financial transaction based on the recognized input information.

One embodiment of the invention provides a system for mapping a neural network onto a neurosynaptic substrate. The system comprises a metadata analysis unit for analyzing metadata information associated with one or more portions of an adjacency matrix representation of the neural network, and a mapping unit for mapping the one or more portions of the matrix representation onto the neurosynaptic substrate based on the metadata information.

A contactless position and/or distance sensor for determining the distance, the spatial orientation, the material properties, or the like of a target object, and a method for operating the same, uses at least two sensor elements, which form a sensor module, Signals provided by the at least two sensor elements are jointly evaluated using at least one artificial neural network.