The barrel cortex refers to a region of somatosensory cortex that is identifiable in some species of rodents and species of at least two other orders and contains the barrel field. The 'barrels' of the barrel field are regions within cortical layer IV that are visibly darker when stained to reveal the presence of cytochrome c oxidase, and are separated from each other by lighter areas called septa. These dark-staining regions are a major target for somatosensory inputs from the thalamus, and each barrel corresponds to a region of the body. Due to this distinctive cellular structure, organisation, and functional significance, the barrel cortex is a useful tool to understand cortical processing and has played an important role in neuroscience. The majority of what is known about corticothalamic processing comes from studying the barrel cortex and researchers have intensively studied the barrel cortex as a model of neocortical column.
A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks.
Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons. At the level of neural ensembles, synchronized activity of large numbers of neurons can give rise to macroscopic oscillations, which can be observed in an electroencephalogram. Oscillatory activity in groups of neurons generally arises from feedback connections between the neurons that result in the synchronization of their firing patterns. The interaction between neurons can give rise to oscillations at a different frequency than the firing frequency of individual neurons. A well-known example of macroscopic neural oscillations is alpha activity.
Neuronal noise or neural noise refers to the random intrinsic electrical fluctuations within neuronal networks. These fluctuations are not associated with encoding a response to internal or external stimuli and can be from one to two orders of magnitude. Most noise commonly occurs below a voltage-threshold that is needed for an action potential to occur, but sometimes it can be present in the form of an action potential; for example, stochastic oscillations in pacemaker neurons in suprachiasmatic nucleus are partially responsible for the organization of circadian rhythms.
Neural coding is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble. Based on the theory that sensory and other information is represented in the brain by networks of neurons, it is thought that neurons can encode both digital and analog information.
In neuroscience, homeostatic plasticity refers to the capacity of neurons to regulate their own excitability relative to network activity, a compensatory adjustment that occurs over the timescale of days. Synaptic scaling has been proposed as a potential mechanism of homeostatic plasticity.
Spiking neural networks (SNNs) are artificial neural network models that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs also incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not fire at each propagation cycle, but rather fire only when a membrane potential – an intrinsic quality of the neuron related to its membrane electrical charge – reaches a specific value. When a neuron fires, it generates a signal which travels to other neurons which, in turn, increase or decrease their potentials in accordance with this signal.
A cultured neuronal network is a cell culture of neurons that is used as a model to study the central nervous system, especially the brain. Often, cultured neuronal networks are connected to an input/output device such as a multi-electrode array (MEA), thus allowing two-way communication between the researcher and the network. This model has proved to be an invaluable tool to scientists studying the underlying principles behind neuronal learning, memory, plasticity, connectivity, and information processing.
Henry John Markram is an Israeli neuroscientist, professor at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and director of the Blue Brain Project and founder of the Human Brain Project.
Neural backpropagation is the phenomenon in which after the action potential of a neuron creates a voltage spike down the axon another impulse is generated from the soma and propagates toward to the apical portions of the dendritic arbor or dendrites, from which much of the original input current originated. In addition to active backpropagation of the action potential, there is also passive electrotonic spread. While there is ample evidence to prove the existence of backpropagating action potentials, the function of such action potentials and the extent to which they invade the most distal dendrites remains highly controversial.
Subthreshold membrane potential oscillations are rhythmic fluctuations of the potential difference between the interior and exterior of a neuron, in the nervous system.
Activity-dependent plasticity is a form of functional and structural neuroplasticity that arises from the use of cognitive functions and personal experience; hence, it is the biological basis for learning and the formation of new memories. Activity-dependent plasticity is a form of neuroplasticity that arises from intrinsic or endogenous activity, as opposed to forms of neuroplasticity that arise from extrinsic or exogenous factors, such as electrical brain stimulation- or drug-induced neuroplasticity. The brain's ability to remodel itself forms the basis of the brain's capacity to retain memories, improve motor function, and enhance comprehension and speech amongst other things. It is this trait to retain and form memories that is associated with neural plasticity and therefore many of the functions individuals perform on a daily basis. This plasticity occurs as a result of changes in gene expression which are triggered by signaling cascades that are activated by various signaling molecules during increased neuronal activity.
In neurophysiology, a dendritic spike refers to an action potential generated in the dendrite of a neuron. Dendrites are branched extensions of a neuron. They receive electrical signals emitted from projecting neurons and transfer these signals to the cell body, or soma. Dendritic signaling has traditionally been viewed as a passive mode of electrical signaling. Unlike its axon counterpart which can generate signals through action potentials, dendrites were believed to only have the ability to propagate electrical signals by physical means: changes in conductance, length, cross sectional area, etc. However, a large body of evidence now makes it clear that dendrites are active neuronal structures. Dendrites contain voltage-gated ion channels giving them the ability to generate action potentials. Dendritic spikes have been recorded in numerous types of neurons in the brain and are thought to have great implications in neuronal communication, memory, and learning. They are one of the major factors in long-term potentiation.
Nonsynaptic plasticity is a form of neuroplasticity that involves modification of ion channel function in the axon, dendrites, and cell body that results in specific changes in the integration of excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs). Nonsynaptic plasticity is a modification of the intrinsic excitability of the neuron. It interacts with synaptic plasticity, but it is considered a separate entity from synaptic plasticity. Intrinsic modification of the electrical properties of neurons plays a role in many aspects of plasticity from homeostatic plasticity to learning and memory itself. Nonsynaptic plasticity affects synaptic integration, subthreshold propagation, spike generation, and other fundamental mechanisms of neurons at the cellular level. These individual neuronal alterations can result in changes in higher brain function, especially learning and memory. However, as an emerging field in neuroscience, much of the knowledge about nonsynaptic plasticity is uncertain and still requires further investigation to better define its role in brain function and behavior.
Developmental plasticity is a general term referring to changes in neural connections during development as a result of environmental interactions as well as neural changes induced by learning. Much like neuroplasticity or brain plasticity, developmental plasticity is specific to the change in neurons and synaptic connections as a consequence of developmental processes. A child creates most of these connections from birth to early childhood.
Network of human nervous system comprises nodes that are connected by links. The connectivity may be viewed anatomically, functionally, or electrophysiologically. These are presented in several Wikipedia articles that include Connectionism, Biological neural network, Artificial neural network, Computational neuroscience, as well as in several books by Ascoli, G. A. (2002), Sterratt, D., Graham, B., Gillies, A., & Willshaw, D. (2011), Gerstner, W., & Kistler, W. (2002), and Rumelhart, J. L., McClelland, J. L., and PDP Research Group (1986) among others. The focus of this article is a comprehensive view of modeling a neural network. Once an approach based on the perspective and connectivity is chosen, the models are developed at microscopic, mesoscopic, or macroscopic (system) levels. Computational modeling refers to models that are developed using computing tools.
In neuroscience, synaptic scaling is a form of homeostatic plasticity, in which the brain responds to chronically elevated activity in a neural circuit with negative feedback, allowing individual neurons to reduce their overall action potential firing rate. Where Hebbian plasticity mechanisms modify neural synaptic connections selectively, synaptic scaling normalizes all neural synaptic connections by decreasing the strength of each synapse by the same factor, so that the relative synaptic weighting of each synapse is preserved.
NEST is a simulation software for spiking neural network models, including large-scale neuronal networks. NEST was initially developed by Markus Diesmann and Marc-Oliver Gewaltig and is now developed and maintained by the NEST Initiative.
