Computational neuroscience

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.

computational model used in machine learning, based on connected, hierarchical functions

process by which neurons communicate with each other by changes in their membrane potentials.

theoretical class of AI able to perform any intelligence-based task humans can

confident unjustified claim by an AI

regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization

field in cognitive science

brainwaves, repetitive patterns of neural activity in the central nervous system

thumb|A 'second wave' connectionist (ANN) model with a hidden layer Connectionism is an approach to the study of human mental processes and cognition that utilizes mathematical models known as connectionist networks or artificial neural networks.

thumb|Nerve tract|White matter tracts within a human brain, as visualized by [[MRI tractography]] thumb|Rendering of a group connectome based on 20 subjects. Anatomical fibers that constitute the white matter architecture of the human brain are visualized color-coded by traversing direction (xyz-directions mapping to RGB colors respectively). Visualization of fibers was done using TrackVis software.

alignment of AI systems towards human goals, preferences and ethical principles

study of brain function in terms of the information processing properties of the structures that make up the nervous system

function that maps a k-element real-valued vector to a k-element categorical probability distribution

Swiss brain research initiative

small, membranous protrusion from a dendrite that forms a postsynaptic compartment

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: the development of computational models of the nervous system and neural processes; the development of tools for analyzing and modeling neuroscience data; and the development of tools and databases for management and sharing of neuroscience data at all levels of analysis.

mathematical model describing how action potentials in neurons are initiated and propagated

arms race for the most advanced technologies in terms of artificial intelligence

software and hardware with cognitive abilities similar to those of the animal or human brain

algorithms to detect AI-generated content

artificial intelligence that implements a limited part of mind, or, as narrow AI, is focused on one narrow task

method by which information is represented in the brain

intelligent Tutoring System

hypothesis in neuroscience proposed by Karl Friston

scientific research project

theory within consciousness research

2018 film directed by Lazar Bodroža

describes a prototype of an excitable system (e.g., a neuron)

research project

mathematical description of the properties of certain cells in the nervous system that generate sharp electrical potentials across their cell membrane, roughly one millisecond in duration

artificial neural network that mimics real neurons

NeurIPS/NIPS conference series on machine learning and related topics

process of automating the end-to-end process of machine learning

Mathematical model of a dendrite

philosophical and social movement advocating for a pro-technology stance that seeks to maximize the probability of a technocapital singularity

alternate term for or form of artificial intelligence

creation of a computer model of all or part of a brain

explaining the brain's abilities through statistical principles

simulation environment for modeling neurons

SpiNNaker (spiking neural network architecture) 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 (specifically ARM968) 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 (see Human Brain Project).

development of AI systems that are able to detect and respond to human emotions in an empathic way

tool for characterizing the response properties of a neuron

Brain-reading or thought identification uses the responses of multiple voxels in the brain evoked by stimulus then detected by fMRI in order to decode the original stimulus. Advances in research have made this possible by using human neuroimaging to decode a person's conscious experience based on non-invasive measurements of an individual's brain activity. Brain reading studies differ in the type of decoding (i.e. classification, identification and reconstruction) employed, the target (i.e. decoding visual patterns, auditory patterns, cognitive states), and the decoding algorithms (l

phenomenon in which after the action potential of a neuron creates a voltage spike down the axon

An autapse is a chemical or electrical synapse from a neuron onto itself. It can also be described as a synapse formed by the axon of a neuron on its own dendrites, in vivo or in vitro.

Computational neuroscientist

emerging field combining computer science and biology that studies biological computing using 3D brain cell cultures (organoids) and brain-machine interfaces

structure in nervous systems