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Alcohol Research & Health : the Journal... 2008Nerve cells (i.e., neurons) communicate via a combination of electrical and chemical signals. Within the neuron, electrical signals driven by charged particles allow... (Review)
Review
Nerve cells (i.e., neurons) communicate via a combination of electrical and chemical signals. Within the neuron, electrical signals driven by charged particles allow rapid conduction from one end of the cell to the other. Communication between neurons occurs at tiny gaps called synapses, where specialized parts of the two cells (i.e., the presynaptic and postsynaptic neurons) come within nanometers of one another to allow for chemical transmission. The presynaptic neuron releases a chemical (i.e., a neurotransmitter) that is received by the postsynaptic neuron's specialized proteins called neurotransmitter receptors. The neurotransmitter molecules bind to the receptor proteins and alter postsynaptic neuronal function. Two types of neurotransmitter receptors exist-ligand-gated ion channels, which permit rapid ion flow directly across the outer cell membrane, and G-protein-coupled receptors, which set into motion chemical signaling events within the cell. Hundreds of molecules are known to act as neurotransmitters in the brain. Neuronal development and function also are affected by peptides known as neurotrophins and by steroid hormones. This article reviews the chemical nature, neuronal actions, receptor subtypes, and therapeutic roles of several transmitters, neurotrophins, and hormones. It focuses on neurotransmitters with important roles in acute and chronic alcohol effects on the brain, such as those that contribute to intoxication, tolerance, dependence, and neurotoxicity, as well as maintained alcohol drinking and addiction.
Topics: Alcoholism; Animals; Brain; Humans; Neurons; Neurotransmitter Agents; Receptors, G-Protein-Coupled; Receptors, Neurotransmitter; Synapses
PubMed: 23584863
DOI: No ID Found -
Neuroscience and Biobehavioral Reviews Nov 2018What any sensory neuron knows about the world is one of the cardinal questions in Neuroscience. Information from the sensory periphery travels across synaptically... (Review)
Review
What any sensory neuron knows about the world is one of the cardinal questions in Neuroscience. Information from the sensory periphery travels across synaptically coupled neurons as each neuron encodes information by varying the rate and timing of its action potentials (spikes). Spatiotemporally correlated changes in this spiking regimen across neuronal populations are the neural basis of sensory representations. In the somatosensory cortex, however, spiking of individual (or pairs of) cortical neurons is only minimally informative about the world. Recent studies showed that one solution neurons implement to counteract this information loss is adapting their rate of information transfer to the ongoing synaptic activity by changing the membrane potential at which spike is generated. Here we first introduce the principles of information flow from the sensory periphery to the primary sensory cortex in a model sensory (whisker) system, and subsequently discuss how the adaptive spike threshold gates the intracellular information transfer from the somatic post-synaptic potential to action potentials, controlling the information content of communication across somatosensory cortical neurons.
Topics: Action Potentials; Animals; Cell Communication; Information Theory; Neurons; Perception; Somatosensory Cortex; Vibrissae
PubMed: 30227142
DOI: 10.1016/j.neubiorev.2018.09.007 -
Journal of Neurophysiology Dec 2016Regularly spiking neurons can be described as oscillators. In this article we review some of the insights gained from this conceptualization and their relevance for... (Review)
Review
Regularly spiking neurons can be described as oscillators. In this article we review some of the insights gained from this conceptualization and their relevance for systems neuroscience. First, we explain how a regularly spiking neuron can be viewed as an oscillator and how the phase-response curve (PRC) describes the response of the neuron's spike times to small perturbations. We then discuss the meaning of the PRC for a single neuron's spiking behavior and review the PRCs measured from a variety of neurons in a range of spiking regimes. Next, we show how the PRC can be related to a number of common measures used to quantify neuronal firing, such as the spike-triggered average and the peristimulus histogram. We further show that the response of a neuron to correlated inputs depends on the shape of the PRC. We then explain how the PRC of single neurons can be used to predict neural network behavior. Given the PRC, conduction delays, and the waveform and time course of the synaptic potentials, it is possible to predict neural population behavior such as synchronization. The PRC also allows us to quantify the robustness of the synchronization to heterogeneity and noise. We finally ask how to combine the measured PRCs and the predictions based on PRC to further the understanding of systems neuroscience. As an example, we discuss how the change of the PRC by the neuromodulator acetylcholine could lead to a destabilization of cortical network dynamics. Although all of these studies are grounded in mathematical abstractions that do not strictly hold in biology, they provide good estimates for the emergence of the brain's network activity from the properties of individual neurons. The study of neurons as oscillators can provide testable hypotheses and mechanistic explanations for systems neuroscience.
Topics: Action Potentials; Animals; Biological Clocks; Humans; Models, Neurological; Neurons
PubMed: 27683887
DOI: 10.1152/jn.00525.2015 -
Advances in Experimental Medicine and... 2019As the nervous system evolved from the diffused to centralised form, the neurones were joined by the appearance of the supportive cells, the neuroglia. Arguably, these... (Review)
Review
As the nervous system evolved from the diffused to centralised form, the neurones were joined by the appearance of the supportive cells, the neuroglia. Arguably, these non-neuronal cells evolve into a more diversified cell family than the neurones are. The first ancestral neuroglia appeared in flatworms being mesenchymal in origin. In the nematode C. elegans proto-astrocytes/supportive glia of ectodermal origin emerged, albeit the ensheathment of axons by glial cells occurred later in prawns. The multilayered myelin occurred by convergent evolution of oligodendrocytes and Schwann cells in vertebrates above the jawless fishes. Nutritive partitioning of the brain from the rest of the body appeared in insects when the hemolymph-brain barrier, a predecessor of the blood-brain barrier was formed. The defensive cellular mechanism required specialisation of bona fide immune cells, microglia, a process that occurred in the nervous system of leeches, bivalves, snails, insects and above. In ascending phylogeny, new type of glial cells, such as scaffolding radial glia, appeared and as the bran sizes enlarged, the glia to neurone ratio increased. Humans possess some unique glial cells not seen in other animals.
Topics: Animals; Biological Evolution; Caenorhabditis elegans; Humans; Myelin Sheath; Neuroglia; Neurons; Oligodendroglia
PubMed: 31583583
DOI: 10.1007/978-981-13-9913-8_2 -
Developmental Biology Sep 2022Neurons are highly polarized cells with extensive axonal and dendritic projections that send and receive signals over long distances. Neuronal polarity requires sorting... (Review)
Review
Neurons are highly polarized cells with extensive axonal and dendritic projections that send and receive signals over long distances. Neuronal polarity requires sorting and maintaining a unique set of proteins to the neuron's distinct axonal and somatodendritic domains. The axon initial segment (AIS) is a specialized subcellular region located between these two domains and is critical for neuronal polarity. The AIS has a complex and elaborately organized molecular structure that enables its functions in neuronal polarity. Disruption of the AIS is associated with neurodevelopmental and neuropsychiatric disease pathologies, thus highlighting the importance of the AIS in neuronal physiology. This review discusses recent progress toward understanding the molecular architecture of the AIS and its importance in neuronal polarity through regulating protein diffusion and vesicular trafficking.
Topics: Axon Initial Segment; Axons; Cell Polarity; Neurons; Protein Transport
PubMed: 35640681
DOI: 10.1016/j.ydbio.2022.05.016 -
Journal of Neurophysiology Oct 2018The activity of a neural network is a result of synaptic signals that convey the communication between neurons and neuron-based intrinsic currents that determine the... (Review)
Review
The activity of a neural network is a result of synaptic signals that convey the communication between neurons and neuron-based intrinsic currents that determine the neuron's input-output transfer function. Ample studies have demonstrated that cell-based excitability, and in particular intrinsic excitability, is modulated by learning and that these modifications play a key role in learning-related behavioral changes. The field of cell-based plasticity is largely growing, and it entails numerous experimental findings that demonstrate a large diversity of currents that are affected by learning. The diverse effect of learning on the neuron's excitability emphasizes the need for a framework under which cell-based plasticity can be categorized to enable the assessment of the computational roles of the intrinsic modifications. We divide the domain of cell-based plasticity into three main categories, where the first category entails the currents that mediate the passive properties and single-spike generation, the second category entails the currents that mediate spike frequency adaptation, and the third category entails a novel learning-induced mechanism where all excitatory and inhibitory synapses double their strength. Curiously, this elementary division enables a natural categorization of the computational roles of these learning-induced plasticities. The computational roles are diverse and include modification of the neuronal mode of action, such as bursting, prolonged, and fast responsive; attention-like effect where the signal detection is improved; transfer of the network into an active state; biasing the competition for memory allocation; and transforming an environmental cue into a dominant cue and enabling a quicker formation of new memories.
Topics: Adaptation, Physiological; Animals; Humans; Learning; Neuronal Plasticity; Neurons; Synaptic Potentials
PubMed: 29947597
DOI: 10.1152/jn.00102.2018 -
Neuron Apr 2015Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal... (Review)
Review
Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics.
Topics: Brain; Epilepsy; Humans; Movement Disorders; Neurology; Neurons
PubMed: 25856488
DOI: 10.1016/j.neuron.2015.03.058 -
The Journal of Neuroscience : the... Nov 2022Dendrites receive the vast majority of a single neuron's inputs, and coordinate the transformation of these signals into neuronal output. and theoretical evidence has... (Review)
Review
Dendrites receive the vast majority of a single neuron's inputs, and coordinate the transformation of these signals into neuronal output. and theoretical evidence has shown that dendrites possess powerful processing capabilities, yet little is known about how these mechanisms are engaged in the intact brain or how they influence circuit dynamics. New experimental and computational technologies have led to a surge in interest to unravel and harness their computational potential. This review highlights recent and emerging work that combines established and cutting-edge technologies to identify the role of dendrites in brain function. We discuss active dendritic mediation of sensory perception and learning in neocortical and hippocampal pyramidal neurons. Complementing these physiological findings, we present theoretical work that provides new insights into the underlying computations of single neurons and networks by using biologically plausible implementations of dendritic processes. Finally, we present a novel brain-computer interface task, which assays somatodendritic coupling to study the mechanisms of biological credit assignment. Together, these findings present exciting progress in understanding how dendrites are critical for learning and behavior, and highlight how subcellular processes can contribute to our understanding of both biological and artificial neural computation.
Topics: Dendrites; Pyramidal Cells; Neurons; Hippocampus; Learning; Models, Neurological; Action Potentials
PubMed: 36351832
DOI: 10.1523/JNEUROSCI.1132-22.2022 -
Journal of Cerebral Blood Flow and... Jul 2012Since its introduction 16 years ago, the astrocyte-neuron lactate shuttle (ANLS) model has profoundly modified our understanding of neuroenergetics by bringing a... (Review)
Review
Since its introduction 16 years ago, the astrocyte-neuron lactate shuttle (ANLS) model has profoundly modified our understanding of neuroenergetics by bringing a cellular and molecular resolution. Praised or disputed, the concept has never ceased to attract attention, leading to critical advances and unexpected insights. Here, we summarize recent experimental evidence further supporting the main tenets of the model. Thus, evidence for distinct metabolic phenotypes between neurons (mainly oxidative) and astrocytes (mainly glycolytic) have been provided by genomics and classical metabolic approaches. Moreover, it has become clear that astrocytes act as a syncytium to distribute energy substrates such as lactate to active neurones. Glycogen, the main energy reserve located in astrocytes, is used as a lactate source to sustain glutamatergic neurotransmission and synaptic plasticity. Lactate is also emerging as a neuroprotective agent as well as a key signal to regulate blood flow. Characterization of monocarboxylate transporter regulation indicates a possible involvement in synaptic plasticity and memory. Finally, several modeling studies captured the implications of such findings for many brain functions. The ANLS model now represents a useful, experimentally based framework to better understand the coupling between neuronal activity and energetics as it relates to neuronal plasticity, neurodegeneration, and functional brain imaging.
Topics: Animals; Astrocytes; Brain; Energy Metabolism; Humans; Lactic Acid; Models, Neurological; Neurons
PubMed: 22027938
DOI: 10.1038/jcbfm.2011.149 -
Biological Cybernetics Apr 2019Spikes in the membrane potential of neurons comprise the currency of information processing in the brain. The ability of neurons to convert any information present... (Review)
Review
Spikes in the membrane potential of neurons comprise the currency of information processing in the brain. The ability of neurons to convert any information present across their multiple inputs into a significant modification to the pattern of their emitted spikes depends on the rate at which they emit spikes. If the mean rate is near the neuron's maximum, or if the rate is near zero, then changes in the inputs have minimal impact on the neuron's firing rate. Therefore, a neuron needs to control its mean rate. Protocols that either dramatically increase or decrease a neuron's firing rate lead to multiple compensatory changes that return the neuron's mean rate toward its prior value. In this primer, first as a summary of our previous work (Cannon and Miller in J Neurophysiol 116(5):2004-2022, 2016; Cannon and Miller in J Math Neurosci 7(1):1, 2017), we describe the advantages and disadvantages of having more than one such control mechanism responding to the neuron's firing rate. We suggest how problems of two, coexisting, potentially competing mechanisms can be overcome. Key requirements are: (1) the control be of a distribution of values, which the controlled variable achieves over a fast timescale compared to the timescale of the control system; (2) at least one of the control mechanisms be nonlinear; and (3) the two control systems are satisfied by a stable distribution or range of values that can be achieved by the variable. We show examples of functional control systems, including the previously studied integral feedback controller and new simulations of a "bang-bang" controller, that allow for compensation when inputs to the system change. Finally, we present new results describing how the underlying signal processing pathways would produce mechanisms of dual control, as opposed to a single mechanism with two outputs, and compare the responses of these systems to changes of input statistics.
Topics: Action Potentials; Animals; Computer Simulation; Feedback, Physiological; Homeostasis; Models, Neurological; Neurons; Stochastic Processes
PubMed: 29955960
DOI: 10.1007/s00422-018-0768-8