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Information about Biological Neural Networks

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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.
In neuroscience, a neural network describes a population of physically interconnected neurons or a group of disparate neurons whose inputs or signalling targets define a recognizable circuit. Communication between neurons often involves an electrochemical process. The interface through which they interact with surrounding neurons usually consists of several dendrites (input connections), which are connected via synapses to other neurons, and one axon (output connection). If the sum of the input signals surpasses a certain threshold, the neuron sends an action potential (AP) at the axon hillock and transmits this electrical signal along the axon.

In contrast, a neuronal circuit is a functional entity of interconnected neurons that influence each other (similar to a control loop in cybernetics).

Early study

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Early treatments of neural networks can be found in Herbert Spencer's Principles of Psychology, 3rd edition (1872), Theodore Meynert's Psychiatry (1884), William James' Principles of Psychology (1890), and Sigmund Freud's Project for a Scientific Psychology (composed 1895). The first rule of neuronal learning was described by Hebb in 1949, Hebbian learning. Thus, Hebbian pairing of pre- and postsynaptic activity can substantially alter the dynamic characteristics of the synaptic connection and therefore facilitate or inhibit signal transmission. The neuroscientists Warren Sturgis McCulloch and Walter Pitts published the first works on the processing of neural networks called "What the frog's eye tells to the frog's brain." They showed theoretically that networks of artificial neurons could implement logical, arithmetic, and symbolic functions. Simplified models of biological neurons were set up, now usually called perceptrons or artificial neurons. These simple models accounted for neural summation, i.e. potentials at the post synaptic membrane will summate in the cell body. Later models also provided for excitatory and inhibitory synaptic transmission.

Connections between neurons

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The connections between neurons are much more complex than those implemented in neural computing architectures. The basic kinds of connections between neurons are chemical synapses and electrical gap junctions. One principle by which neurons work is neural summation, i.e. potentials at the post synaptic membrane will sum up in the cell body. If the depolarization of the neuron at the axon goes above threshold an action potential will occur that travels down the axon to the terminal endings to transmit a signal to other neurons. Excitatory and inhibitory synaptic transmission is realized mostly by inhibitory postsynaptic potentials and excitatory postsynaptic potentials.

On the electrophysiological level, there are various phenomena which alter the response characteristics of individual synapses (called synaptic plasticity) and individual neurons (intrinsic plasticity). These are often divided into shortterm plasticity and longterm plasticity. Longterm synaptic plasticity is often contended to be the most likely memory substrate. Usually the term "plasticity" refers to changes in the brain that are caused by activity or experience.

Connections display temporal and spatial characteristics. Temporal characteristics refer to the continuously modified activity-dependent efficacy of synaptic transmission, called spike dependent synaptic plasticity. It has been observed in several studies that the synaptic efficacy of this transmission can undergo shortterm 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 EPSP generated by the pre-synaptic AP, and the post-synaptic action potential. LTP is induced by a series of action potentials which cause a variety of biochemical responses. Eventually the reactions cause the insertion of new receptors into the cellular membrane of the dendrites, or serve to increase the efficacy of the receptors through phosphorylation.

Backpropagating APs are impossible because after an action potential travels down a given segment of the axon, the voltage gated sodium channels' (Na+ channels) m gate becomes closed, thus blocking any transient opening of the h gate from causing a change in the intracellular [Na+], and hence preventing the generation of an action potential back towards the cell body.

A neuron in the brain requires a single impulse to a neuromuscular junction to fire for the contraction of the postsynaptic muscle cell. In the spinal cord, however at least 75 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.

Representations in neural networks

A receptive field is a small region within the entire visual field. Any given neuron only responds to a subset of stimuli within its receptive field. This property is called tuning. As for vision, in the earlier visual areas, neurons have simpler tuning. For example, a neuron in V1 may fire to any vertical stimulus in its receptive field. In the higher visual areas, neurons have complex tuning. For example, in the fusiform gyrus, a neuron may only fire when a certain face appears in its receptive field. It is also known that many parts of the brain generate patterns of electrical activity that correspond closely to the layout of the retinal image (this is known as retinotopy). It seems further that imagery that originates from the senses and internally generated imagery may have a shared ontology at higher levels of cortical processing (see e.g. Language of thought). About many parts of the brain some characterization has been made as to what tasks are correlated with its activity.

In the brain, memories are very likely represented by patterns of activation amongst networks of neurons. However, how these representations are formed, retrieved and reach conscious awareness is not completely understood. Cognitive processes that characterize human intelligence are mainly ascribed to the emergent properties of complex dynamic characteristics in the complex systems that constitute neural networks. Therefore, the study and modeling of these networks have attracted broad interest under different paradigms and many different theories have been formulated to explain various aspects of their behavior. One of these -- and the subject of several theories -- is considered a special property of a neural network: the ability to learn complex patterns.

Philosophical issues

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Today most researchers believe in representations of some kind (representationalism) or, more general, in particular mental states (cognitivism). Thus, perception is information processing which is used to transfer information from the world into the brain/mind where it is further processed and related to other information (cognitive processes). Few others envisage a direct path back into the external world in the form of action (radical behaviourism).

Another issue, called the binding problem, relates to the question of how the activity of more or less distinct populations of neurons dealing with different aspects of perception are combined to form a unified perceptual experience and have qualia.

Study methods

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Different neuroimaging techniques have been developed to investigate the activity of neural networks. The use of 'brain scanners' or functional neuroimaging to investigate the structure or function of the brain is common, either as simply a way of better assessing brain injury with high resolution pictures, or by examining the relative activations of different brain areas. Such technologies may include fMRI (functional Magnetic Resonance Imaging), PET (Positron Emission Tomography) and CAT (Computed axial tomography). Functional neuroimaging uses specific brain imaging technologies to take scans from the brain, usually when a person is doing a particular task, in an attempt to understand how the activation of particular brain areas is related to the task. In functional neuroimaging, especially Functional Magnetic Resonance Imaging (fMRI), which measures hemodynamic activity that is closely linked to neural activity, Positron Emission Tomography (PET), and Electroencephalography (EEG) is used.

Connectionist models serve as a test platform for different hypothesis of representation, information processing, and signal transmission. Lesioning studies in such models, e.g. 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 and/or via pharmacological manipulations, and these studies can in turn be used to inform the models, making the process recursive.

See also

External links

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Nervous system
Central nervous system (Brain, Spinal cord) • Peripheral nervous system • Somatic nervous system • Autonomic nervous system (Sympathetic, Parasympathetic) • Enteric nervous system • Sensory system
Neuroscience is a field that is devoted to the scientific study of the nervous system. Such studies may include the structure, function, evolutionary history, development, genetics, biochemistry, physiology, pharmacology, and pathology of the nervous system.
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Neurons (also known as neurones and nerve cells) are electrically excitable cells in the nervous system that process and transmit information. In vertebrate animals, neurons are the core components of the brain, spinal cord and peripheral nerves.
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Electrochemistry is a branch of chemistry that studies the reactions which take place at the interface of an electronic conductor (the electrode composed of a metal or a semiconductor, including graphite) and an ionic conductor (the electrolyte).
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For the dendritic crystal structure, see .


Dendrites (from Greek dendron, “tree”) are the branched projections of a neuron that act to conduct the electrical stimulation received from other neural cells to the cell body, or
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synapse. Synapses allow nerve cells to communicate with one another through axons and dendrites, converting electrical impulses into chemical signals.]]

Chemical synapses
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axon or nerve fiber, is a long, slender projection of a nerve cell, or neuron, that conducts electrical impulses away from the neuron's cell body or soma.

Anatomy


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Threshold may refer to:

In fiction:
  • Threshold (Doctor Who), organization of Gallifreyan/Human origin in Doctor Who comic strips
  • Threshold (fictional planet), the planet around which the ringworld Halo orbits in the video game Halo

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An action potential is a "spike" of electrical discharge that travels along the membrane of a cell. Action potentials are an essential feature of animal life, rapidly carrying information within and between tissues. They also occur in some plants.
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Axon Hillock is the anatomical part of a neuron that connects the cell body called soma (biology) to the axon. It is attributed as the place where Inhibitory Postsynaptic Potentials (IPSPs) and Excitatory Postsynaptic Potentials (EPSPs) from numerous synaptic inputs on the
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signal is any time-varying quantity. Signals are often scalar-valued functions of time (waveforms), but may be vector valued and may be functions of any other relevant independent variable.

The concept is broad, and hard to define precisely.
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In military aviation, a Control system is frequently used in place of a Ground Control Station when describing an Unmanned Aircraft System control element which may be located anywhere, not just on the ground.
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Cybernetics was defined by Norbert Wiener, in his book of that title, as the study of control and communication in the animal and the machine. Stafford Beer called it the science of effective organization and Gordon Pask extended it to include information flows "in all
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Herbert Spencer (27 April 1820 – 8 December 1903) was an English philosopher; prominent classical liberal political theorist; and sociological theorist.

Spencer developed an all-embracing conception of evolution as the progressive development of the physical world,
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Psychiatry is a branch of medicine which exists to study, prevent, and treat mental disorders in humans.[1][2][3] The art and science of the clinical application of psychiatry has been considered a bridge between the social world and those who are
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William James (January 11 1842 – August 26 1910) was a pioneering American psychologist and philosopher. He wrote influential books on the young science of psychology, educational psychology, psychology of religious experience and mysticism, and the philosophy of pragmatism.
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Psychology (from Greek: Literally "talk about the soul" (from logos)) is both an academic and applied discipline involving the scientific study of mental processes and behavior.
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Sigmund Freud

Born May 6 1856(1856--)
Freiberg, Moravia, now the Czech Republic
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Donald Olding Hebb (July 22, 1904 – August 20, 1985) was a psychologist who was influential in the area of neuropsychology, where he sought to understand how the function of neurons contributed to psychological processes such as learning.
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19th century - 20th century - 21st century
1910s  1920s  1930s  - 1940s -  1950s  1960s  1970s
1946 1947 1948 - 1949 - 1950 1951 1952

Year 1949 (MCMXLIX
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Hebbian theory describes a basic mechanism for synaptic plasticity wherein an increase in synaptic efficacy arises from the presynaptic cell's repeated and persistent stimulation of the postsynaptic cell.
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Warren Sturgis McCulloch (November 16, 1899 – September 24, 1969) was an American neurophysiologist and cybernetician.

Warren Sturgis McCulloch was born in Orange, New Jersey and studied at Yale (philosophy and psychology, A.B.
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Walter Pitts (23 April 1923 – 14 May 1969) was a logician who worked in the field of cognitive psychology. He proposed landmark theoretical formulations of neural activity and emergent processes that influenced diverse fields like cognitive sciences and psychology,
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Implementation is the realization of an application, or execution of a plan, idea, model, design, specification, standard, algorithm, or policy.

In computer science, an implementation is a realization of a technical specification or algorithm as a program, software
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Logic (from Classical Greek λόγος logos; meaning word, thought, idea, argument, account, reason, or principle) is the study of the principles and criteria of valid inference and demonstration.
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Arithmetic or arithmetics (from the Greek word αριθμός = number) is the oldest and most elementary branch of mathematics, used by almost everyone, for tasks ranging from simple day-to-day counting to advanced science and business
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Symbolism is the applied use of symbols: iconic representations that carry particular conventional meanings. Usually pictures.

The term "symbolism" is often limited to use in contrast to "representationalism"; defining the general directions of a linear spectrum - where in
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''For alternate meanings see Perceptron (disambiguation).
The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.
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An artificial neuron, also called semi-linear unit, Nv neuron, binary neuron or McCulloch-Pitts neuron, is an abstraction of biological neurons and the basic unit in an artificial neural network.
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The soma, or perikaryon, is the bulbous end of a neuron, containing the cell nucleus. It is also known as the cell body. The word soma is Greek, meaning "body"; the soma of a neuron is often called the "cell body".
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An artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach
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