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Biochimica Et Biophysica Acta Jan 2013Cells precisely regulate mitochondrial movement in order to balance energy needs and avoid cell death. Neurons are particularly susceptible to disturbance of... (Review)
Review
Cells precisely regulate mitochondrial movement in order to balance energy needs and avoid cell death. Neurons are particularly susceptible to disturbance of mitochondrial motility and distribution due to their highly extended structures and specialized function. Regulation of mitochondrial motility plays a vital role in neuronal health and death. Here we review the current understanding of regulatory mechanisms that govern neuronal mitochondrial transport and probe their implication in health and disease. This article is part of a Special Issue entitled: Mitochondrial dynamics and physiology.
Topics: Animals; Biological Transport; Disease; Humans; Mitochondria; Mitochondrial Dynamics; Models, Biological; Movement; Neurons
PubMed: 22548961
DOI: 10.1016/j.bbamcr.2012.04.007 -
EMBO Reports Sep 2006For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials... (Review)
Review
For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials only in response to suprathreshold stimuli. Although modelling studies predicted that single neurons constitute a much more powerful computational entity, able to perform an array of nonlinear calculations, this possibility was not explored experimentally until the discovery of active mechanisms in the dendrites of most neuron types. Here, we review several modelling studies that have addressed information processing in single neurons, starting with those characterizing the arithmetic of different dendritic components, to those tackling neuronal integration at the cell body and, finally, those analysing the computational abilities of the axon. We present modelling predictions along with supporting experimental data in an effort to highlight the significant contribution of modelling work to enhancing our understanding of single-neuron arithmetic.
Topics: Animals; Axons; Computer Simulation; Dendrites; Drosophila; Forecasting; Mice; Models, Neurological; Neurons; Nonlinear Dynamics; Regeneration; Synapses
PubMed: 16953202
DOI: 10.1038/sj.embor.7400789 -
Brain Research Sep 2016Healthy neurons have an optimal operating range, coded globally by the frequency of action potentials or locally by calcium. The maintenance of this range is governed by... (Review)
Review
Healthy neurons have an optimal operating range, coded globally by the frequency of action potentials or locally by calcium. The maintenance of this range is governed by homeostatic plasticity. Here, we discuss how new approaches to treat depression alter synaptic activity. These approaches induce the neuron to recruit homeostatic mechanisms to relieve depression. Homeostasis generally implies that the direction of activity necessary to restore the neuron's critical operating range is opposite in direction to its current activity pattern. Unconventional antidepressant therapies-deep brain stimulation and NMDAR antagonists-alter the neuron's "depressed" state by pushing the neuron's current activity in the same direction but to the extreme edge. These therapies rally the intrinsic drive of neurons in the opposite direction, thereby allowing the cell to return to baseline activity, form new synapses, and restore proper communication. In this review, we discuss seminal studies on protein synthesis dependent homeostatic plasticity and their contribution to our understanding of molecular mechanisms underlying the effectiveness of NMDAR antagonists as rapid antidepressants. Rapid antidepressant efficacy is likely to require a cascade of mRNA translational regulation. Emerging evidence suggests that changes in synaptic strength or intrinsic excitability converge on the same protein synthesis pathways, relieving depressive symptoms. Thus, we address the question: Are there multiple homeostatic mechanisms that induce the neuron and neuronal circuits to self-correct to regulate mood in vivo? Targeting alternative ways to induce homeostatic protein synthesis may provide, faster, safer, and longer lasting antidepressants. This article is part of a Special Issue entitled SI:RNA Metabolism in Disease.
Topics: Animals; Antidepressive Agents; Autophagy; Brain; Depressive Disorder; Homeostasis; Humans; Neuronal Plasticity; Neurons; Protein Biosynthesis; Receptors, GABA-B; Receptors, N-Methyl-D-Aspartate; TOR Serine-Threonine Kinases
PubMed: 27125595
DOI: 10.1016/j.brainres.2016.04.020 -
Hippocampus Sep 2018Hippocampal neurons become tuned to stimuli that predict behaviorally salient outcomes. This plasticity suggests that memory formation depends upon shifts in how... (Review)
Review
Hippocampal neurons become tuned to stimuli that predict behaviorally salient outcomes. This plasticity suggests that memory formation depends upon shifts in how different anatomical inputs can drive hippocampal activity. Here, I present evidence that inhibitory neurons can provide such a mechanism for learning-related changes in the tuning of pyramidal cells. Inhibitory currents arriving on the dendrites of pyramidal cells determine whether an excitatory input can drive action potential output. Specificity and plasticity of this dendritic modulation allows for precise, modifiable changes in how afferent inputs are integrated, a process that defines a neuron's receptive field. In addition, feedback inhibition plays a fundamental role in biasing which excitatory neurons may be co-active. By defining the rules of synchrony and the rules of input integration, interneurons likely play an important role in the organization of memory representation within the hippocampus.
Topics: Animals; Feedback, Physiological; Hippocampus; Membrane Potentials; Memory; Neural Inhibition; Neuronal Plasticity; Neurons
PubMed: 28921762
DOI: 10.1002/hipo.22803 -
Neuron May 2022Functional ultrasound imaging (fUSI) is an appealing method for measuring blood flow and thus infer brain activity, but it relies on the physiology of neurovascular...
Functional ultrasound imaging (fUSI) is an appealing method for measuring blood flow and thus infer brain activity, but it relies on the physiology of neurovascular coupling and requires extensive signal processing. To establish to what degree fUSI trial-by-trial signals reflect neural activity, we performed simultaneous fUSI and neural recordings with Neuropixels probes in awake mice. fUSI signals strongly correlated with the slow (<0.3 Hz) fluctuations in the local firing rate and were closely predicted by the smoothed firing rate of local neurons, particularly putative inhibitory neurons. The optimal smoothing filter had a width of ∼3 s, matched the hemodynamic response function of awake mice, was invariant across mice and stimulus conditions, and was similar in the cortex and hippocampus. fUSI signals also matched neural firing spatially: firing rates were as highly correlated across hemispheres as fUSI signals. Thus, blood flow measured by ultrasound bears a simple and accurate relationship to neuronal firing.
Topics: Animals; Cerebral Cortex; Hemodynamics; Mice; Neurons; Neurovascular Coupling; Ultrasonography
PubMed: 35278361
DOI: 10.1016/j.neuron.2022.02.012 -
Current Opinion in Cell Biology Aug 2012In a biological sense, polarity refers to the extremity of the main axis of an organelle, cell, or organism. In neurons, morphological polarity begins with the... (Review)
Review
In a biological sense, polarity refers to the extremity of the main axis of an organelle, cell, or organism. In neurons, morphological polarity begins with the appearance of the first neurite from the cell body. In multipolar neurons, a second phase of polarization occurs when a single neurite initiates a phase of rapid growth to become the neuron's axon, while the others later differentiate as dendrites. Finally, during a third phase, axons and dendrites develop an elaborate architecture, acquiring special morphological and molecular features that commit them to their final identities. Mechanistically, each phase must be preceded by spatial restriction of growth activity. We will review recent work on the mechanisms underlying the polarized growth of neurons.
Topics: Cell Polarity; Neurites; Neurons; Organelles
PubMed: 22726583
DOI: 10.1016/j.ceb.2012.05.011 -
Current Opinion in Neurobiology Aug 2017For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses,... (Review)
Review
For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses, and fine-tuning these synapses in response to neural activity. Synaptic specificity is common at both a neuron's input and output synapses, whereby unique synapses are built depending on the partnering neuron. Neuroscientists have long appreciated the remarkable specificity of neural circuits but identifying molecular mechanisms mediating synaptic specificity has only recently accelerated. Here, we focus on recent progress in understanding input and output synaptic specificity in the mammalian brain. We review newly identified circuit examples for both and the latest research identifying molecular mediators including Kirrel3, FGFs, and DGLα. Lastly, we expect the pace of research on input and output specificity to continue to accelerate with the advent of new technologies in genomics, microscopy, and proteomics.
Topics: Animals; Humans; Neurons; Signal Transduction; Synapses
PubMed: 28388510
DOI: 10.1016/j.conb.2017.03.006 -
Journal of Neurophysiology Nov 2020Both experimenter-controlled stimuli and stimulus-independent variables impact cortical neural activity. A major hurdle to understanding neural representation is...
Both experimenter-controlled stimuli and stimulus-independent variables impact cortical neural activity. A major hurdle to understanding neural representation is distinguishing between qualitatively different causes of the fluctuating population activity. We applied an unsupervised low-rank tensor decomposition analysis to the recorded population activity in the visual cortex of awake mice in response to repeated presentations of naturalistic visual stimuli. We found that neurons covaried largely independently of individual neuron stimulus response reliability and thus encoded both stimulus-driven and stimulus-independent variables. Importantly, a neuron's response reliability and the neuronal coactivation patterns substantially reorganized for different external visual inputs. Analysis of recurrent balanced neural network models revealed that both the stimulus specificity and the mixed encoding of qualitatively different variables can arise from clustered external inputs. These results establish that coactive neurons with diverse response reliability mediate a mixed representation of stimulus-driven and stimulus-independent variables in the visual cortex. V1 neurons covary largely independently of individual neuron's response reliability. A single neuron's response reliability imposes only a weak constraint on its encoding capabilities. Visual stimulus instructs a neuron's reliability and coactivation pattern. Network models revealed using clustered external inputs.
Topics: Animals; Female; Male; Mice, Transgenic; Models, Neurological; Neural Networks, Computer; Neurons; Optical Imaging; Photic Stimulation; Visual Cortex; Visual Perception
PubMed: 32965146
DOI: 10.1152/jn.00431.2020 -
Cold Spring Harbor Perspectives in... Sep 2010The spatial pattern of branches within axonal or dendritic arbors and the relative arrangement of neighboring arbors with respect to one another impact a neuron's... (Review)
Review
The spatial pattern of branches within axonal or dendritic arbors and the relative arrangement of neighboring arbors with respect to one another impact a neuron's potential connectivity. Although arbors can adopt diverse branching patterns to suit their functions, evenly spread branches that avoid clumping or overlap are a common feature of many axonal and dendritic arbors. The degree of overlap between neighboring arbors innervating a surface is also characteristic within particular neuron types. The arbors of some populations of neurons innervate a target with a comprehensive and nonoverlapping "tiled" arrangement, whereas those of others show substantial territory overlap. This review focuses on cellular and molecular studies that have provided insight into the regulation of spatial arrangements of neurite branches within and between arbors. These studies have revealed principles that govern arbor arrangements in dendrites and axons in both vertebrates and invertebrates. Diverse molecular mechanisms controlling the spatial patterning of sister branches and neighboring arbors have begun to be elucidated.
Topics: Animals; Axons; Dendrites; Humans; Models, Neurological; Nerve Net; Neurons
PubMed: 20573716
DOI: 10.1101/cshperspect.a001750 -
The Journal of Neuroscience : the... Sep 2019Cortical responses to repeated presentations of a sensory stimulus are variable. This variability is sensitive to several stimulus dimensions, suggesting that it may...
Cortical responses to repeated presentations of a sensory stimulus are variable. This variability is sensitive to several stimulus dimensions, suggesting that it may carry useful information beyond the average firing rate. Many experimental manipulations that affect response variability are also known to engage divisive normalization, a widespread operation that describes neuronal activity as the ratio of a numerator (representing the excitatory stimulus drive) and denominator (the normalization signal). Although it has been suggested that normalization affects response variability, we lack a quantitative framework to determine the relation between the two. Here we extend the standard normalization model, by treating the numerator and the normalization signal as variable quantities. The resulting model predicts a general stabilizing effect of normalization on neuronal responses, and allows us to infer the single-trial normalization strength, a quantity that cannot be measured directly. We test the model on neuronal responses to stimuli of varying contrast, recorded in primary visual cortex of male macaques. We find that neurons that are more strongly normalized fire more reliably, and response variability and pairwise noise correlations are reduced during trials in which normalization is inferred to be strong. Our results thus suggest a novel functional role for normalization, namely, modulating response variability. Our framework could enable a direct quantification of the impact of single-trial normalization strength on the accuracy of perceptual judgments, and can be readily applied to other sensory and nonsensory factors. Divisive normalization is a widespread neural operation across sensory and nonsensory brain areas, which describes neuronal responses as the ratio between the excitatory drive to the neuron and a normalization signal. Normalization plays a key role in several important computations, including adjusting the neuron's dynamic range, reducing redundancy, and facilitating probabilistic inference. However, the relation between normalization and neuronal response variability (a fundamental aspect of neural coding) remains unclear. Here we develop a new model and test it on primary visual cortex responses. We show that normalization has a stabilizing effect on neuronal activity, beyond the known suppression of firing rate. This modulation of variability suggests a new functional role for normalization in neural coding and perception.
Topics: Action Potentials; Animals; Macaca fascicularis; Male; Models, Neurological; Neurons; Photic Stimulation; Visual Cortex
PubMed: 31387914
DOI: 10.1523/JNEUROSCI.0126-19.2019