Synaptic noise

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Synaptic noise refers to the constant bombardment of synaptic activity in neurons. This occurs in the background of a cell when potentials are produced without the nerve stimulation of an action potential, and are due to the inherently random nature of synapses. These random potentials have similar time courses as excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs), yet they lead to variable neuronal responses. The variability is due to differences in the discharge times of action potentials. [1]

Contents

Causes

Many types of noise exist in cells. First, there is intrinsic noise and extrinsic, or synaptic, noise. Within each category there are two further divisions of noise – voltage noise or temporal noise. Intrinsic voltage noise is due to random changes in the membrane potential of a cell, and intrinsic temporal noise is caused by variations in spike generation timing. The following sections give explanations about the causes of synaptic noise.

Quantal release

Both synaptic voltage and temporal noise are due to the probability associated with transmitter release. [2] In an action potential, calcium channels are opened by depolarization and release Ca2+ ions into the presynaptic cell. This causes neurotransmitters, which are kept in vesicles, to be released into the synapse. Vesicles are released in quanta – packets that contain roughly 7,000 molecules of transmitters. The likelihood of quanta being released is assigned a probability that increases when the action potential arrives at synaptic terminals, and progressively decreases to a lower, resting value. Therefore, the uncertainty involved in the exact timing of neurotransmitter release is a cause for synaptic temporal noise. Furthermore, the strength of the postsynaptic response varies based on the number of quanta released. Quantal release results in the inconsistent strength and timing of a response, and this is cause for synaptic voltage noise.

Background activity

Another cause of noise is due to the exocytosis of neurotransmitters from the synaptic terminals that provide input to a given neuron. [2] This occurrence happens in the background while a cell is at resting membrane potential. Since it is happening in the background, the release is not due to a signal, but is random. This unpredictability adds to the synaptic noise level.

Synaptic noise shows up as miniature postsynaptic current, which is observed without any presynaptic input. These spontaneous currents are due to randomly released neurotransmitter vesicles. This is caused by the stochastic "opening of intracellular Ca2+ stores, synaptic Ca2+-channel noise, spontaneous triggering of the vesicle-release pathway, or spontaneous fusion of a vesicle with the membrane." [3]

Chemical sensing

Chemical sensing, such as that of taste and smell which rely on an external chemical stimulus, is affected by thermodynamics. Chemical molecules arrive at the appropriate receptor at random times based on the rate of diffusion of these particles. Also, receptors can't perfectly count the number of signaling molecules that pass through. These two factors are additional causes of synaptic noise. [3]

How the CNS manages noise

The central nervous system (CNS) deals with noise in two ways – averaging and prior knowledge.

Averaging

Averaging occurs whenever redundant information is given to a sensory input or generated by the CNS itself. When several units of cellular processing carry the same signal but are affected by different sources of noise, averaging can counter the noise. This occurrence can be seen when sensory inputs couple to work together or overlap, so that they can take an average of incoming signals and random stimuli. [3]

Averaging is also seen at divergent synapses, where one signal provides input to many neurons. It can be advantageous to send a signal multiple times over many axons and combine the information at the end, rather than to send the signal once over a single, long, noisy neuron. [3] This means that in order for the fidelity of the signal to be preserved, the initial signal must be reliable. At the final destination, signals are averaged and noise can be offset.

Prior knowledge

Prior knowledge is also used when facing noise. [3] In sensory neurons that receive redundant and structured signals, sensory processing can differentiate the signal from noise. This occurrence is known as the matched filter principle, whereby a neuron can use past experience about an expected input to distinguish noise from the actual signal and consequently reduce the impact of noise.

In the hippocampus

The significance of synaptic noise has become clear through ongoing research of the brain, specifically the hippocampus. The hippocampus is a region of the forebrain in the medial temporal lobe closely associated with memory formation and recollection. Gamma and theta oscillations, released during exploratory activities, create modulated rhythms that transform into prolonged excitation, and furthermore into memories or improper potentiation. [4] These oscillations can be partially composed of synaptic currents or synaptic noise. There is recent evidence that supports the role of synaptic noise in the signal functions within the hippocampus, and therefore in memories, whether solidifying or interfering. [4]

This focus is greatly reliant on stochastic resonance. From notable research by Stacey and Durand, synaptic noise has been credited for enhanced detection of weak or distal synaptic inputs within the hippocampus. Using a computer model, subthreshold currents were simulated in the CA3 region that directly correlated with increased CA1 action potential activity when small currents were introduced. [5] This is an example of a commonly ostracized natural occurrence that dampens important signals can now be studied and utilized for therapeutic reasons to aid neural plasticity.

Common injuries in the hippocampus region can result in schizophrenia, epilepsy, Parkinson's and Alzheimer's diseases. Synaptic noise may be part of the development of these illnesses, however, sufficient research has not been conducted. A possible relevance is the inability of synaptic noise to fine-tune or regulate proper summation into a message. If weak signals cannot be enhanced with existing noise, synaptic plasticity is compromised, and memory and personality will be impacted. [6] The research of Stacey and Durand helped shape this new direction in the analysis and pharmaceutical development to combat hippocampal illnesses. [7]

In sensory neurons

Signals and noise in sensory receptors, which allow organisms to encode information based on their senses, set a limit on a given sensation. Often it is necessary to amplify a weak signal in order for it to be of use. For amplification to help, the signal at the synapse must be more intensified than the noise.

For example, amplification is needed when a single photon of light hits a rod photoreceptor in the retina of an eye. The amplification allows the small stimulus to overcome the noise that is an inherent characteristic of the cell. However, increasing the stimulus also increases the noise. This phenomenon has led to the question of how sensory receptors can lower synaptic noise effectively while amplifying the signal to reach threshold. [8]

The sensitivity of a neuron increases when information from many receptors is collected and integrated - an event called pooling. While this allows a cell to focus predominantly on the actions that are directly involved with the stimulus, it also combines the noise, which increases the overall amount of noise present in the system.

A sensory neuron's efficiency can be increased further if noise is eliminated as early as possible before pooling occurs, through linear filtering. The removal of noise in the beginning is crucial because once a signal and noise with similar timings combine, it is harder to separate them. Linear filtering involves the removal of noise with time frequencies that aren't associated with a given stimulus response. This removes events that are slower than the response, or not connected to the receptor in question. [8]

Implications

As a negative factor

Noise in neurons is due to intrinsic and extrinsic sources. It can disrupt activity and interfere with how well a neuron can encode a signal. Noise is observed as changes in the membrane potential of a cell. The change in potential causes the accuracy of a neuron to be limited in its transmission. [9] This limited transmission has been coined the signal-to-noise ratio. As noise levels increase, one would assume a lowered ratio and therefore diminished signals. A diminished signal can be detrimental to a cell if neuronal maintenance is disrupted, or more importantly a necessary inhibitory response is lost. [10] Noise limits the fidelity of a neuron's response to a signal or stimulus. The accuracy of the signal will impact how well higher parts of the brain or sensory system process information from the neurons. [11]

As a positive factor

Stochastic resonance is the term given to an instance when synaptic noise aids, rather than impairs, signal detection. With stochastic resonance, synaptic noise can amplify the recognition of signals that are below threshold potential in nonlinear, threshold-detecting systems. This is important in cells that receive and integrate thousands of synaptic inputs. These cells can often require numerous synaptic events to occur at the same time in order to produce an action potential, so the potential for receiving subthreshold signals is high. [12] Signals from neurons that integrate activity of various neurons, when taken together, can form a complete image stimulus.

Noise also allows neurons to detect weak visual signals by processing the level of contrast of the image. [13]

Another positive use of synaptic noise is by involving frozen noise. Frozen noise refers to random current pulses of varying amplitudes being applied to the constant current input, and then maintaining this pattern so that it can be used to observe differences in other factors. Frozen noise allows researchers to reveal whether or not part of a neuron's response is dependent on a given stimulus because the other interfering conditions are held constant. [14]

Physiological relevance

Synaptic noise has been associated with high frequency oscillations (HFOs) within the brain. HFOs are imperative to normal brain function, and research has shown that synaptic noise may be a potential initiator of HFOs. HFOs between 60–70 Hz have been recorded as normal activity within the brain by EEG (electroencephalography) recordings, however frequencies within the ranges of 100–200 Hz, also called ripples, have been associated with epilepsy. Ripples, however, are not entirely abnormal nor regular. "Ripples have been used to describe both abnormal activity associated with epileptiform sharp waves and normal behaviors such as physiological sharp waves and memory consolidation." [15]

Synaptic noise is not only caused by mass signaling from surrounding neuronal impulses, but also from the direct signaling within the neuron itself. During episodes of epilepsy, the impulses fired are of greater magnitude and frequency than normal. Transient signaling, or more specifically noise, may shorten the resting potential in order to allow for quicker neural firing. [12]

There is also evidence which supports the fact that epilepsy may be one cause of synaptic noise. During an epileptic seizure, tertiary bursts of action potential occur through the neurons in the brain. Neurons fire off randomly and rapidly creating the convulsive effect which the patient exhibits during the seizure. Before these bursts, there is an increase in the extracellular potassium concentrations of the neurons. "Potassium is expected to rise during epileptic discharges, and we have preliminary evidence from ventral slices exposed to bicuculline that potassium rises to a threshold value of ~9 mM just prior to the onset of tertiary bursts." [16] The increased potassium concentrations outside the neuron can increase terminal excitability, causing possible action potential firing, which leads to synaptic noise.

Current research

It is believed that by first understanding channel noise, one might be able to more fully understand synaptic noise. [17] Channel noise is the variability in neuronal responses that is generated by the random gating of voltage-gated ion channels such as those for potassium or sodium, vital components of an action potential. This prerequisite need is proposed since both channel and synaptic noise limit the reliability of responsiveness to stimuli in neurons, as well as both being voltage dependent.

To understand the future of synaptic noise research, it would be essential to discuss the work of Alain Destexhe, a Belgian doctor who has greatly studied the importance of synaptic noise in neuronal connections. He uses the dynamic-clamp technique to understand the presence and characteristics of noise. While voltage-gated clamps record configurations, dynamic-clamp allows for the control of conductance by way of computer. A computational model of synaptic noise is created and is then implemented into the neuron, simulating synaptic noise. [18] This can be used to compare with in-vivo conditions. Destexhe states that future research can be directed towards four possible ways, in reflection of his research with dynamic-clamp. First, it could be beneficial to understand the control of synaptic noise so that the modulation of noise can be used on humans to turn unresponsive networks into a responsive state. Next, it would be necessary to understand how external noise interacts with internal neuronal properties more fully to coincide models with experimental facts. There also exists the need to further investigate experimentally the methods of dendritic integration and the role of synaptic noise when it is present. Finally, he found support that synaptic noise enhances temporal resolution in neurons, yet experimental proof has not been done to further elaborate on past modeling studies. [19] By use of dynamic-clamp, these pieces of information clarify the role of synaptic noise in the brain and how it can be harnessed for specific therapies.

More information is necessary to understand the role that noise plays in schizophrenia. However, schizophrenics and their siblings who don't have schizophrenia seem to have an increased level of noise in their prefrontal cortical information processing circuits. [10] Abnormalities in the prefrontal cortex might cause some of the symptoms associated with schizophrenia, such as auditory hallucinations, delusional states, and impacts on the working memory. Knowing how noise affects the signaling in this area of the brain, for example, not being able to distinguish noise from a signal, might provide more information on why these abnormalities occur.

Functional magnetic resonance imaging (fMRI) is affected by noise. [20] Noise that is present during scanning can impact the integrity of an image by introducing an aspect of uncertainty through noise. More research is needed to know whether this noise is specifically synaptic noise, or one of the other types. Furthermore, in order to make fMRI more useful and trustworthy, research on the noise and ways to dampen it are necessary.

Related Research Articles

<span class="mw-page-title-main">Neuron</span> Electrically excitable cell found in the nervous system of animals

Within a nervous system, a neuron, neurone, or nerve cell is an electrically excitable cell that fires electric signals called action potentials across a neural network. Neurons communicate with other cells via synapses, which are specialized connections that commonly use minute amounts of chemical neurotransmitters to pass the electric signal from the presynaptic neuron to the target cell through the synaptic gap.

<span class="mw-page-title-main">Nervous system</span> Part of an animal that coordinates actions and senses

In biology, the nervous system is the highly complex part of an animal that coordinates its actions and sensory information by transmitting signals to and from different parts of its body. The nervous system detects environmental changes that impact the body, then works in tandem with the endocrine system to respond to such events. Nervous tissue first arose in wormlike organisms about 550 to 600 million years ago. In vertebrates it consists of two main parts, the central nervous system (CNS) and the peripheral nervous system (PNS). The CNS consists of the brain and spinal cord. The PNS consists mainly of nerves, which are enclosed bundles of the long fibers, or axons, that connect the CNS to every other part of the body. Nerves that transmit signals from the brain are called motor nerves or efferent nerves, while those nerves that transmit information from the body to the CNS are called sensory nerves or afferent. Spinal nerves are mixed nerves that serve both functions. The PNS is divided into three separate subsystems, the somatic, autonomic, and enteric nervous systems. Somatic nerves mediate voluntary movement. The autonomic nervous system is further subdivided into the sympathetic and the parasympathetic nervous systems. The sympathetic nervous system is activated in cases of emergencies to mobilize energy, while the parasympathetic nervous system is activated when organisms are in a relaxed state. The enteric nervous system functions to control the gastrointestinal system. Both autonomic and enteric nervous systems function involuntarily. Nerves that exit from the cranium are called cranial nerves while those exiting from the spinal cord are called spinal nerves.

<span class="mw-page-title-main">Chemical synapse</span> Biological junctions through which neurons signals can be sent

Chemical synapses are biological junctions through which neurons' signals can be sent to each other and to non-neuronal cells such as those in muscles or glands. Chemical synapses allow neurons to form circuits within the central nervous system. They are crucial to the biological computations that underlie perception and thought. They allow the nervous system to connect to and control other systems of the body.

An inhibitory postsynaptic potential (IPSP) is a kind of synaptic potential that makes a postsynaptic neuron less likely to generate an action potential. IPSPs were first investigated in motorneurons by David P. C. Lloyd, John Eccles and Rodolfo Llinás in the 1950s and 1960s. The opposite of an inhibitory postsynaptic potential is an excitatory postsynaptic potential (EPSP), which is a synaptic potential that makes a postsynaptic neuron more likely to generate an action potential. IPSPs can take place at all chemical synapses, which use the secretion of neurotransmitters to create cell to cell signalling. Inhibitory presynaptic neurons release neurotransmitters that then bind to the postsynaptic receptors; this induces a change in the permeability of the postsynaptic neuronal membrane to particular ions. An electric current that changes the postsynaptic membrane potential to create a more negative postsynaptic potential is generated, i.e. the postsynaptic membrane potential becomes more negative than the resting membrane potential, and this is called hyperpolarisation. To generate an action potential, the postsynaptic membrane must depolarize—the membrane potential must reach a voltage threshold more positive than the resting membrane potential. Therefore, hyperpolarisation of the postsynaptic membrane makes it less likely for depolarisation to sufficiently occur to generate an action potential in the postsynaptic neurone.

<span class="mw-page-title-main">Excitatory postsynaptic potential</span> Process causing temporary increase in postsynaptic potential

In neuroscience, an excitatory postsynaptic potential (EPSP) is a postsynaptic potential that makes the postsynaptic neuron more likely to fire an action potential. This temporary depolarization of postsynaptic membrane potential, caused by the flow of positively charged ions into the postsynaptic cell, is a result of opening ligand-gated ion channels. These are the opposite of inhibitory postsynaptic potentials (IPSPs), which usually result from the flow of negative ions into the cell or positive ions out of the cell. EPSPs can also result from a decrease in outgoing positive charges, while IPSPs are sometimes caused by an increase in positive charge outflow. The flow of ions that causes an EPSP is an excitatory postsynaptic current (EPSC).

In neurophysiology, long-term depression (LTD) is an activity-dependent reduction in the efficacy of neuronal synapses lasting hours or longer following a long patterned stimulus. LTD occurs in many areas of the CNS with varying mechanisms depending upon brain region and developmental progress.

<span class="mw-page-title-main">Pyramidal cell</span> Projection neurons in the cerebral cortex and hippocampus

Pyramidal cells, or pyramidal neurons, are a type of multipolar neuron found in areas of the brain including the cerebral cortex, the hippocampus, and the amygdala. Pyramidal cells are the primary excitation units of the mammalian prefrontal cortex and the corticospinal tract. Pyramidal neurons are also one of two cell types where the characteristic sign, Negri bodies, are found in post-mortem rabies infection. Pyramidal neurons were first discovered and studied by Santiago Ramón y Cajal. Since then, studies on pyramidal neurons have focused on topics ranging from neuroplasticity to cognition.

<span class="mw-page-title-main">Electrotonic potential</span>

In physiology, electrotonus refers to the passive spread of charge inside a neuron and between cardiac muscle cells or smooth muscle cells. Passive means that voltage-dependent changes in membrane conductance do not contribute. Neurons and other excitable cells produce two types of electrical potential:

<span class="mw-page-title-main">Neural circuit</span> Network or circuit of neurons

A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Multiple neural circuits interconnect with one another to form large scale brain networks.

Molecular neuroscience is a branch of neuroscience that observes concepts in molecular biology applied to the nervous systems of animals. The scope of this subject covers topics such as molecular neuroanatomy, mechanisms of molecular signaling in the nervous system, the effects of genetics and epigenetics on neuronal development, and the molecular basis for neuroplasticity and neurodegenerative diseases. As with molecular biology, molecular neuroscience is a relatively new field that is considerably dynamic.

<span class="mw-page-title-main">Neural oscillation</span> Brainwaves, repetitive patterns of neural activity in the central nervous system

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.

<span class="mw-page-title-main">Neurotransmission</span> Impulse transmission between neurons

Neurotransmission is the process by which signaling molecules called neurotransmitters are released by the axon terminal of a neuron, and bind to and react with the receptors on the dendrites of another neuron a short distance away. A similar process occurs in retrograde neurotransmission, where the dendrites of the postsynaptic neuron release retrograde neurotransmitters that signal through receptors that are located on the axon terminal of the presynaptic neuron, mainly at GABAergic and glutamatergic synapses.

<span class="mw-page-title-main">Neuronal noise</span> Random electric fluctuations in neurons

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 neuronal responses, and the relationship among the electrical activities 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 believed that neurons can encode both digital and analog information.

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 towards the apical portions of the dendritic arbor or dendrites. 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 remain highly controversial.

<span class="mw-page-title-main">Biological neuron model</span> Mathematical descriptions of the properties of certain cells in the nervous system

Biological neuron models, also known as spiking neuron models, are mathematical descriptions of neurons. In particular, these models describe how the voltage potential across the cell membrane changes over time. In an experimental setting, stimulating neurons with an electrical current generates an action potential, that propagates down the neuron's axon. This axon can branch out and connect to a large number of downstream neurons at sites called synapses. At these synapses, the spike can cause release of a biochemical substance (neurotransmitter), which in turn can change the voltage potential of downstream neurons, potentially leading to spikes in those downstream neurons, thus propagating the signal. As many as 85% of neurons in the neocortex, the outermost layer of the mammalian brain, consists of excitatory pyramidal neurons, and each pyramidal neuron receives tens of thousands of inputs from other neurons. Thus, spiking neurons are a major information processing unit of the nervous system.

Coincidence detection is a neuronal process in which a neural circuit encodes information by detecting the occurrence of temporally close but spatially distributed input signals. Coincidence detectors influence neuronal information processing by reducing temporal jitter and spontaneous activity, allowing the creation of variable associations between separate neural events in memory. The study of coincidence detectors has been crucial in neuroscience with regards to understanding the formation of computational maps in the brain.

<span class="mw-page-title-main">Subthreshold membrane potential oscillations</span>

Subthreshold membrane potential oscillations are membrane oscillations that do not directly trigger an action potential since they do not reach the necessary threshold for firing. However, they may facilitate sensory signal processing.

<span class="mw-page-title-main">Dendritic spike</span> Action potential generated in the dendrite of a neuron

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, the existence of dendritic spikes was proposed and demonstrated by W. Alden Spencer, Eric Kandel, Rodolfo Llinás and coworkers in the 1960s and 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.

<span class="mw-page-title-main">Nonsynaptic plasticity</span> Form of neuroplasticity

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 and inhibitory postsynaptic potentials. 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.

References

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