Signaling
Let us pay attention to the signaling properties of any given neuron.
As we have said there is a precise direction in the information flow within every neuronal cell. However, as the signal propagates along the cell it changes its aspect following a precise sequence of four types of signals: an input signal consisting of a synaptic potential. An integrative signal, which takes place mainly at the initial segment of the axon, the axon hillock. A conductive signal consisting of the so called action potential and an output or secretory signal located at the synaptic terminal. With the sole exception of the output signal, a given component of the signal represents a change in the electric properties of the cell membrane.
Neurons, like any other cell, maintain an electric potential difference across their external
membrane. It results from a differential distribution of electric charges across the membrane of
the cell, living the inside of the cell membrane negative in relation to the outside. The actual
value of the membrane potential in a given nerve cell is about -65 mV (It is negative because the
outside of the cell is arbitrarily defined as zero), although it may vary from -40 to -80 in different
nerve cells. Excitable cells, such as neurons and muscle cells, are different from other cells in
that they can alter their resting membrane potential and therefore can serve as a signaling
mechanism.
Input
The resting potential is an equilibrium state, and is the same throughout the cell so that there is
no current flow from one part of the cell to another in this resting state.The input signal of a
neuron, the synaptic potential, is the perturbation of its membrane potential caused by the
output of another nerve cell.
An excitatory potential represents the lowering of the membrane potential, a process also known as depolarization (it results from the sudden inrush of positively charged ions).
By contrast an inhibitory potential is the result of augmenting the membrane potential: hyperpolarization (inrush of negatively charged ions). The presinaptic cell releases a chemical transmitter that interacts with synaptic receptors at the surface of the postsynaptic input site. Alternatively the input signal can be generated by activation of a specific transducing receptor protein such as those found in sensory neurons.
In any case the activation of the
receptor molecule (either a transducing or a synaptic receptor) transforms chemical potential
energy into a membrane electrical perturbation: the synaptic potential (in the case of a sensory
neuron it is said to generate a receptor potential, since the input of this class of neurons is not a
synapse). In the case of sensory neurons the magnitude of the receptor potential is graded in
both amplitude and duration depending on the intensity or strength of the physical variable which
is being detected by that particular sensory system (i.e., heat, pressure, stretch, amount of light,
sound intensity etc.).Most receptor potentials are depolarizing or excitatory. Like the receptor
potential, synaptic potential is also graded; its amplitude and duration are functions of the amount
of neurotransmiter and the time period over which it is released. The synaptic potential can be
either depolarizing (excitatory) or hyperpolarizing (inhibitory) depending on the receptor
molecules and the type of presinaptic cell.
Integration
Once a receptor or a synaptic potential is generated it spreads passively all over the membrane
surface. At some point, normally the initial segment of the axon, the perturbation will reach a
region of high concentration of voltage sensitive sodium channels.
The action potential, the conducing component of neurons, is generated by sudden inrush of sodium ions through these voltage sensitive channels.
If the amplitude of the electric signal provided by either the synaptic or the receptor potential, is bigger than a particular threshold this region will give rise to one or more action potentials, which have the form of a spike of depolarization. At the integrative region, the activity of all receptors or synaptic potentials in the same cell is added and depending on whether the sum is higher than the threshold, the action potential may or may not be generated. Consequently this region is called the trigger zone or the integrative component.
Conduction
The aaction potential is a large depolarization signal. It can reach up to 110 mV in amplitude, it last
only 1ms and can be conducted at rates of 1 to 100 m/s. The action potential is an stereotyped
all or none signal. Its amplitude and duration does not depend on the amplitude and duration of the
input signal (the synaptic or the receptor potential).
Once the firing threshold has been reached the action potential is initiated. Unlike input potentials which spread passively and decrease in amplitude with distance, the action potential does not decay as it travels along the axon to the terminal of the neuron (this distance can be up to 1m).
Since the action potential is an all or none signal, a single action potential can not carry information about the amplitude of the input signal. So, Is the information of the input potential amplitude absolutely lost? No, The integrative component of the cell transforms the amplitude of the input signal into frequency of an action potential train. In turn, the duration of the input signal is determined by the period during which action potentials are generated.
Output
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The release of chemical neurotransmiters serves as the output signal. Once a train of action
potentials reaches the synaptic terminal, it stimulates the release of neurotransmitters. The actual
amount of transmitter released is a graded function of the number and frequency of action
potentials.The transmitter released by the presynaptic neuron diffuses across the synaptic cleft,
to the postsynaptic cell, where it causes the postsynaptic cell to generate either an excitatory or
an inhibitory synaptic potential, depending on the particular receptor protein.
Biochemical differences
The above described model of neuronal functioning is applicable to the vast majority of neurons. However, it is not accurate in detail for all neurons. Some neurons, for example, do not generate action potential. Instead, in these neurons input signals are summed and spread passively to the terminal region where they directly affect secretion. Although cells can appear similar, they can differ in important details at the molecular level. Different neurons use different combinations of ion channels in their membranes. Diversity of ion channels results in neurons having different thresholds, excitability, and firing patterns. Some neurons do not have a steady resting potential and consequently become spontaneously active.Neurons also differ in the chemical transmitters they produce, and the combination of receptors they have in their membranes.
Interconnection patterns
Now, how can these individual properties of neurons be related to the highly complex processing capabilities of the brain?. There is no simple answer to this question, which is still under current investigation. However one can start to envisage how these simple principles give rise to considerable complexity. For example, there is a type of connection pattern in which a single neuron branches many times and finally activates several hundreds of target cells.
This pattern is common specially in the input stages of the nervous system and allows for the divergence of information. On the other hand there are five to ten times more sensory neurons than motor neurons so that ultimately, many sensory signals terminate on a single motor cell. This type of connection permits convergence of information, common at the output of the of the nervous system.
The neural mediation of behavior is subdivided into discrete aspects of sensory input, intermediate processing and motor output. Each one of this aspects is mediated by a distinct group of neurons, and even a single aspect can involve several different groups of neurons. The use of several pathways to convey the same information is called parallel processing.This probably increases speed, richness and reliability in the central nervous system. Most neurons do not differ greatly in their electrical properties. However, they can carry out different functions because of the connections they make in the nervous system. These patterns of connectivity are established during development and determines the cell's role in the control of behavior. Both the synaptic efficiency and the interconnection pattern can vary during the process of learning. Thus, neurons are not rigidly committed to a particular functional configuration; they display plasticity.
The importance of connections has now been recognized by scientists attempting to construct computational models of brain function. Artificial intelligence scientists initially used serial processing models. However they soon realized that although these models solved many problems rather well, including such difficult tasks as playing chess, they performed poorly and slowly on other computations that the brain does rapidly and well, such as the immediate recognition of complex visual stimuli (like faces) and the rapid comprehension of speech. As a result these modelers have turned from serial systems to parallel distributed systems called connectionistic models. Results obtained from these models are consistent with physiological studies, and illustrate that individual elements do not transmit large amounts of information. It is the connections between many elements, not their individual contribution, which make complex information processing possible.