Neural circuit

Source: Wikipedia, the free encyclopedia.
For larger structures of neurons, see
biological neural network. For projections from one region of the nervous system to another, see neural pathway
.
Anatomy of a multipolar neuron

A neural circuit is a population of

large scale brain networks.[2]

Neural circuits have inspired the design of

artificial neural networks
, though there are significant differences.

Early study

From "Texture of the Nervous System of Man and the Vertebrates" by Santiago Ramón y Cajal. The figure illustrates the diversity of neuronal morphologies in the auditory cortex.

Early treatments of neural

cell body
). Later models also provided for excitatory and inhibitory synaptic transmission.

Connections between neurons

See also: Synapse
Proposed organization of motor-semantic neural circuits for action language comprehension. Gray dots represent areas of language comprehension, creating a network for comprehending all language. The semantic circuit of the motor system, particularly the motor representation of the legs (yellow dots), is incorporated when leg-related words are comprehended. Adapted from Shebani et al. (2013)

The connections between neurons in the brain are much more complex than those of the

artificial neural networks. The basic kinds of connections between neurons are synapses: both chemical and electrical synapses
.

The establishment of synapses enables the connection of neurons into millions of overlapping, and interlinking neural circuits. Presynaptic proteins called neurexins are central to this process.[5]

One principle by which neurons work is

inhibitory postsynaptic potentials
(IPSPs).

On the

intrinsic plasticity). These are often divided into short-term plasticity and long-term plasticity. Long-term synaptic plasticity is often contended to be the most likely memory substrate. Usually, the term "neuroplasticity
" refers to changes in the brain that are caused by activity or experience.

Connections display temporal and spatial characteristics. Temporal characteristics refers to the continuously modified activity-dependent efficacy of synaptic transmission, called spike-timing-dependent plasticity. It has been observed in several studies that the synaptic efficacy of this transmission can undergo short-term increase (called facilitation) or decrease (depression) according to the activity of the presynaptic neuron. The induction of long-term changes in synaptic efficacy, by long-term potentiation (LTP) or depression (LTD), depends strongly on the relative timing of the onset of the excitatory postsynaptic potential and the postsynaptic action potential. LTP is induced by a series of action potentials which cause a variety of biochemical responses. Eventually, the reactions cause the expression of new receptors on the cellular membranes of the postsynaptic neurons or increase the efficacy of the existing receptors through phosphorylation.

Backpropagating action potentials cannot occur because after an action potential travels down a given segment of the axon, the

h gate from causing a change in the intracellular sodium ion (Na+) concentration, and preventing the generation of an action potential back towards the cell body. In some cells, however, neural backpropagation does occur through the dendritic branching
and may have important effects on synaptic plasticity and computation.

A neuron in the brain requires a single signal to a

afferent neurons are required to produce firing. This picture is further complicated by variation in time constant between neurons, as some cells can experience their EPSPs
over a wider period of time than others.

While in synapses in the

developing brain
synaptic depression has been particularly widely observed it has been speculated that it changes to facilitation in adult brains.

Circuitry

Model of a neural circuit in the cerebellum

An example of a neural circuit is the trisynaptic circuit in the hippocampus. Another is the Papez circuit linking the hypothalamus to the limbic lobe. There are several neural circuits in the cortico-basal ganglia-thalamo-cortical loop. These circuits carry information between the cortex, basal ganglia, thalamus, and back to the cortex. The largest structure within the basal ganglia, the striatum, is seen as having its own internal microcircuitry.[6]

Neural circuits in the spinal cord called central pattern generators are responsible for controlling motor instructions involved in rhythmic behaviours. Rhythmic behaviours include walking, urination, and ejaculation. The central pattern generators are made up of different groups of spinal interneurons.[7]

There are four principal types of neural circuits that are responsible for a broad scope of neural functions. These circuits are a diverging circuit, a converging circuit, a reverberating circuit, and a parallel after-discharge circuit.[8]

In a diverging circuit, one neuron synapses with a number of postsynaptic cells. Each of these may synapse with many more making it possible for one neuron to stimulate up to thousands of cells. This is exemplified in the way that thousands of muscle fibers can be stimulated from the initial input from a single motor neuron.[8]

In a converging circuit, inputs from many sources are converged into one output, affecting just one neuron or a neuron pool. This type of circuit is exemplified in the respiratory center of the brainstem, which responds to a number of inputs from different sources by giving out an appropriate breathing pattern.[8]

A reverberating circuit produces a repetitive output. In a signalling procedure from one neuron to another in a linear sequence, one of the neurons may send a signal back to initiating neuron. Each time that the first neuron fires, the other neuron further down the sequence fire again sending it back to the source. This restimulates the first neuron and also allows the path of transmission to continue to its output. A resulting repetitive pattern is the outcome that only stops if one or more of the synapses fail, or if an inhibitory feed from another source causes it to stop. This type of reverberating circuit is found in the respiratory center that sends signals to the

epileptic seizures.[8]

In a parallel after-discharge circuit, a neuron inputs to several chains of neurons. Each chain is made up of a different number of neurons but their signals converge onto one output neuron. Each synapse in the circuit acts to delay the signal by about 0.5 msec, so that the more synapses there are, the longer is the delay to the output neuron. After the input has stopped, the output will go on firing for some time. This type of circuit does not have a feedback loop as does the reverberating circuit. Continued firing after the stimulus has stopped is called after-discharge. This circuit type is found in the reflex arcs of certain reflexes.[8]

Study methods

See also: Neuropsychology and Cognitive neuropsychology

Different

BOLD-contrast imaging) which is closely linked to neural activity, PET, and electroencephalography
(EEG) is used.

artificial neural networks, where parts of the nodes are deliberately destroyed to see how the network performs, can also yield important insights in the working of several cell assemblies. Similarly, simulations of dysfunctional neurotransmitters in neurological conditions (e.g., dopamine in the basal ganglia of Parkinson's
patients) can yield insights into the underlying mechanisms for patterns of cognitive deficits observed in the particular patient group. Predictions from these models can be tested in patients or via pharmacological manipulations, and these studies can in turn be used to inform the models, making the process iterative.

The modern balance between the connectionist approach and the single-cell approach in

neurobiology
has been achieved through a lengthy discussion. In 1972, Barlow announced the single neuron revolution: "our perceptions are caused by the activity of a rather small number of neurons selected from a very large population of predominantly silent cells."
artificial neural networks give mathematical background to unexpected effectiveness of small neural ensembles in high-dimensional brain.[11]

Clinical significance

Sometimes neural circuitries can become pathological and cause problems such as in

neurodegenerative disorders
including Parkinson's.

See also

References

  1. ISBN 9780878936953
    .
  2. ^ "Neural Circuits | Centre of Excellence for Integrative Brain Function". Centre of Excellence for Integrative Brain Function. 13 June 2016. Retrieved 4 June 2018.
  3. ^ Michael S. C. Thomas; James L. McClelland. "Connectionist models of cognition" (PDF). Stanford University. Archived from the original (PDF) on 2015-09-06. Retrieved 2015-08-31.
  4. ^ J. Y. Lettvin; H. R. Maturana; W. S. McCulloch; W. H. Pitts (1959), "What the frog's eye tells the frog's brain.", Proc. Inst. Radio Engr., no. 47, pp. 1940–1951
  5. PMID 29100073
    .
  6. PMID 20438237
    .
  7. PMID 23403923
    .
  8. ^
    ISBN 9780071222075
    .
  9. S2CID 17487970
    .
  10. PMID 15973409
    .
  11. PMID 30366739
    .
  12. PMID 29755338
    .

Further reading

External links

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