Neuroscience is the scientific study of the nervous system, its functions, and its disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, psychology, physics, computer science, chemistry, medicine, statistics, and mathematical modeling to understand the fundamental and emergent properties of neurons, glia and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "epic challenge" of the biological sciences.
Computational neuroscience is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
HRL Laboratories is a research center in Malibu, California, established in 1960. Formerly the research arm of Hughes Aircraft, it is currently owned by General Motors Corporation and Boeing. It is housed in two large, white multi-story buildings overlooking the Pacific Ocean.
Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology. It relates to connectionism, social behavior, and emergence. Within computer science, bio-inspired computing relates to artificial intelligence and machine learning. Bio-inspired computing is a major subset of natural computation.
Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems. Recent advances have even discovered ways to mimic the human nervous system through liquid solutions of chemical systems.
An artificial brain is software and hardware with cognitive abilities similar to those of the animal or human brain.
Neuroinformatics is the emergent field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied:
A synapse is a neural junction used for communication between neurons
Spiking neural networks (SNNs) are artificial neural networks (ANN) that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not transmit information at each propagation cycle, but rather transmit information only when a membrane potential—an intrinsic quality of the neuron related to its membrane electrical charge—reaches a specific value, called the threshold. When the membrane potential reaches the threshold, the neuron fires, and generates a signal that travels to other neurons which, in turn, increase or decrease their potentials in response to this signal. A neuron model that fires at the moment of threshold crossing is also called a spiking neuron model.
GENESIS is a simulation environment for constructing realistic models of neurobiological systems at many levels of scale including: sub-cellular processes, individual neurons, networks of neurons, and neuronal systems. These simulations are “computer-based implementations of models whose primary objective is to capture what is known of the anatomical structure and physiological characteristics of the neural system of interest”. GENESIS is intended to quantify the physical framework of the nervous system in a way that allows for easy understanding of the physical structure of the nerves in question. “At present only GENESIS allows parallelized modeling of single neurons and networks on multiple-instruction-multiple-data parallel computers.” Development of GENESIS software spread from its home at Caltech to labs at the University of Texas at San Antonio, the University of Antwerp, the National Centre for Biological Sciences in Bangalore, the University of Colorado, the Pittsburgh Supercomputing Center, the San Diego Supercomputer Center, and Emory University.
In the field of computational neuroscience, Brain simulation is the concept of creating a functioning computer model of a brain or part of a brain. Brain simulation projects intend to contribute to a complete understanding of the brain, and eventually also assist the process of treating and diagnosing brain diseases. Simulations utilize mathematical models of biological neurons, such as the hodgkin-huxley model, to simulate the behavior of neurons, or other cells within the brain.
A physical neural network is a type of artificial neural network in which an electrically adjustable material is used to emulate the function of a neural synapse or a higher-order (dendritic) neuron model. "Physical" neural network is used to emphasize the reliance on physical hardware used to emulate neurons as opposed to software-based approaches. More generally the term is applicable to other artificial neural networks in which a memristor or other electrically adjustable resistance material is used to emulate a neural synapse.
Dharmendra S. Modha is an Indian American manager and lead researcher of the Cognitive Computing group at IBM Almaden Research Center. He is known for his pioneering works in Artificial Intelligence and Mind Simulation. In November 2009, Modha announced at a supercomputing conference that his team had written a program that simulated a cat brain. He is the recipient of multiple honors, including the Gordon Bell Prize, given each year to recognize outstanding achievement in high-performance computing applications. In November 2012, Modha announced on his blog that using 96 Blue Gene/Q racks of the Lawrence Livermore National Laboratory Sequoia supercomputer, a combined IBM and LBNL team achieved an unprecedented scale of 2.084 billion neurosynaptic cores containing 530 billion neurons and 137 trillion synapses running only 1542× slower than real time. In August 2014 a paper describing the TrueNorth Architecture, "the first-ever production-scale 'neuromorphic' computer chip designed to work more like a mammalian brain than" a processor was published in the journal Science. TrueNorth project culminated in a 64 million neuron system for running deep neural network applications.
Massimiliano Versace is the co-founder and the CEO of Neurala Inc, a Boston-based company building Artificial Intelligence emulating brain function in software and used in automating the process of visual inspection in manufacturing. He is also the founding Director of the Boston University Neuromorphics Lab. Massimiliano Versace is a Fulbright scholar and holds two PhD in Experimental Psychology from the University of Trieste, Italy and Cognitive and Neural Systems from Boston University, USA. He obtained his BSc from the University of Trieste, Italy.
Kwabena Adu Boahen is a Ghanaian-born Professor of Bioengineering and Electrical Engineering at Stanford University. He previously taught at the University of Pennsylvania.
SpiNNaker is a massively parallel, manycore supercomputer architecture designed by the Advanced Processor Technologies Research Group (APT) at the Department of Computer Science, University of Manchester. It is composed of 57,600 processing nodes, each with 18 ARM9 processors and 128 MB of mobile DDR SDRAM, totalling 1,036,800 cores and over 7 TB of RAM. The computing platform is based on spiking neural networks, useful in simulating the human brain.
A cognitive computer is a computer that hardwires artificial intelligence and machine learning algorithms into an integrated circuit that closely reproduces the behavior of the human brain. It generally adopts a neuromorphic engineering approach. Synonyms include neuromorphic chip and cognitive chip.
In computational neuroscience, SUPS or formerly CUPS is a measure of a neuronal network performance, useful in fields of neuroscience, cognitive science, artificial intelligence, and computer science.
Electrochemical Random-Access Memory (ECRAM) is a type of non-volatile memory (NVM) with multiple levels per cell (MLC) designed for deep learning analog acceleration. An ECRAM cell is a three-terminal device composed of a conductive channel, an insulating electrolyte, an ionic reservoir, and metal contacts. The resistance of the channel is modulated by ionic exchange at the interface between the channel and the electrolyte upon application of an electric field. The charge-transfer process allows both for state retention in the absence of applied power, and for programming of multiple distinct levels, both differentiating ECRAM operation from that of a field-effect transistor (FET). The write operation is deterministic and can result in symmetrical potentiation and depression, making ECRAM arrays attractive for acting as artificial synaptic weights in physical implementations of artificial neural networks (ANN). The technological challenges include open circuit potential (OCP) and semiconductor foundry compatibility associated with energy materials. Universities, government laboratories, and corporate research teams have contributed to the development of ECRAM for analog computing. Notably, Sandia National Laboratories designed a lithium-based cell inspired by solid-state battery materials, Stanford University built an organic proton-based cell, and International Business Machines (IBM) demonstrated in-memory selector-free parallel programming for a logistic regression task in an array of metal-oxide ECRAM designed for insertion in the back end of line (BEOL). In 2022, researchers at Massachusetts Institute of Technology built an inorganic, CMOS-compatible protonic technology that achieved near-ideal modulation characteristics using nanosecond fast pulses
BrainChip is an Australia-based technology company, founded in 2004 by Peter Van Der Made, that specializes in developing advanced artificial intelligence (AI) and machine learning (ML) hardware. The company's primary products are the MetaTF development environment, which allows the training and deployment of spiking neural networks (SNN), and the AKD1000 neuromorphic processor, a hardware implementation of their spiking neural network system. BrainChip's technology is based on a neuromorphic computing architecture, which attempts to mimic the way the human brain works. The company is a part of Intel Foundry Services and Arm AI partnership.
