Sensory processingSensory processing is the process that organizes and distinguishes sensation (sensory information) from one's own body and the environment, thus making it possible to use the body effectively within the environment. Specifically, it deals with how the brain processes multiple sensory modality inputs, such as proprioception, vision, auditory system, tactile, olfactory, vestibular system, interoception, and taste into usable functional outputs. It has been believed for some time that inputs from different sensory organs are processed in different areas in the brain.
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Computational neuroscienceComputational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.
Dorsal column–medial lemniscus pathwayThe dorsal column–medial lemniscus pathway (DCML) (also known as the posterior column-medial lemniscus pathway, PCML) is a sensory pathway of the central nervous system that conveys sensations of fine touch, vibration, two-point discrimination, and proprioception (body position) from the skin and joints. It transmits information from the body to the primary somatosensory cortex in the postcentral gyrus of the parietal lobe of the brain.
Hierarchical temporal memoryHierarchical temporal memory (HTM) is a biologically constrained machine intelligence technology developed by Numenta. Originally described in the 2004 book On Intelligence by Jeff Hawkins with Sandra Blakeslee, HTM is primarily used today for anomaly detection in streaming data. The technology is based on neuroscience and the physiology and interaction of pyramidal neurons in the neocortex of the mammalian (in particular, human) brain. At the core of HTM are learning algorithms that can store, learn, infer, and recall high-order sequences.
Mushroom bodiesThe mushroom bodies or corpora pedunculata are a pair of structures in the brain of arthropods, including insects and crustaceans, and some annelids (notably the ragworm Platynereis dumerilii). They are known to play a role in olfactory learning and memory. In most insects, the mushroom bodies and the lateral horn are the two higher brain regions that receive olfactory information from the antennal lobe via projection neurons. They were first identified and described by French biologist Félix Dujardin in 1850.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Models of neural computationModels of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof. This article aims to provide an overview of the most definitive models of neuro-biological computation as well as the tools commonly used to construct and analyze them.
Single-unit recordingIn neuroscience, single-unit recordings (also, single-neuron recordings) provide a method of measuring the electro-physiological responses of a single neuron using a microelectrode system. When a neuron generates an action potential, the signal propagates down the neuron as a current which flows in and out of the cell through excitable membrane regions in the soma and axon. A microelectrode is inserted into the brain, where it can record the rate of change in voltage with respect to time.
Thalamocortical radiationsIn neuroanatomy, thalamocortical radiations also known as thalamocortical fibres, are the efferent fibres that project from the thalamus to distinct areas of the cerebral cortex. They form fibre bundles that emerge from the lateral surface of the thalamus. Thalamocortical fibers (TC fibres) have been referred to as one of the two constituents of the isothalamus, the other being microneurons. Thalamocortical fibers have a bush or tree-like appearance as they extend into the internal capsule and project to the layers of the cortex.
