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Biophysical Journal Nov 2023Dendritic spines are small protrusions that mediate most of the excitatory synaptic transmission in the brain. Initially, the anatomical structure of spines has... (Review)
Review
Dendritic spines are small protrusions that mediate most of the excitatory synaptic transmission in the brain. Initially, the anatomical structure of spines has suggested that they serve as isolated biochemical and electrical compartments. Indeed, following ample experimental evidence, it is now widely accepted that a significant physiological role of spines is to provide biochemical compartmentalization in signal integration and plasticity in the nervous system. In contrast to the clear biochemical role of spines, their electrical role is uncertain and is currently being debated. This is mainly because spines are small and not accessible to conventional experimental methods of electrophysiology. Here, I focus on reviewing the literature on the electrical properties of spines, including the initial morphological and theoretical modeling studies, indirect experimental approaches based on measurements of diffusional resistance of the spine neck, indirect experimental methods using two-photon uncaging of glutamate on spine synapses, optical imaging of intracellular calcium concentration changes, and voltage imaging with organic and genetically encoded voltage-sensitive probes. The interpretation of evidence from different preparations obtained with different methods has yet to reach a consensus, with some analyses rejecting and others supporting an electrical role of spines in regulating synaptic signaling. Thus, there is a need for a critical comparison of the advantages and limitations of different methodological approaches. The only experimental study on electrical signaling monitored optically with adequate sensitivity and spatiotemporal resolution using voltage-sensitive dyes concluded that mushroom spines on basal dendrites of cortical pyramidal neurons in brain slices have no electrical role.
Topics: Dendritic Spines; Dendrites; Pyramidal Cells; Synaptic Transmission; Glutamic Acid; Synapses
PubMed: 37837192
DOI: 10.1016/j.bpj.2023.10.008 -
Frontiers in Neural Circuits 2024For neural circuit construction in the brain, coarse neuronal connections are assembled prenatally following genetic programs, being reorganized postnatally by... (Review)
Review
For neural circuit construction in the brain, coarse neuronal connections are assembled prenatally following genetic programs, being reorganized postnatally by activity-dependent mechanisms to implement area-specific computational functions. Activity-dependent dendrite patterning is a critical component of neural circuit reorganization, whereby individual neurons rearrange and optimize their presynaptic partners. In the rodent primary somatosensory cortex (barrel cortex), driven by thalamocortical inputs, layer 4 (L4) excitatory neurons extensively remodel their basal dendrites at neonatal stages to ensure specific responses of barrels to the corresponding individual whiskers. This feature of barrel cortex L4 neurons makes them an excellent model, significantly contributing to unveiling the activity-dependent nature of dendrite patterning and circuit reorganization. In this review, we summarize recent advances in our understanding of the activity-dependent mechanisms underlying dendrite patterning. Our focus lays on the mechanisms revealed by time-lapse imaging, and the role of activity-dependent Golgi apparatus polarity regulation in dendrite patterning. We also discuss the type of neuronal activity that could contribute to dendrite patterning and hence connectivity.
Topics: Animals; Dendrites; Somatosensory Cortex; Vibrissae; Animals, Newborn
PubMed: 38827189
DOI: 10.3389/fncir.2024.1409993 -
Current Osteoporosis Reports Dec 2022The purpose of this review is to discuss the molecular mechanisms involved in osteocyte dendrite formation, summarize the similarities between osteocytic and neuronal... (Review)
Review
PURPOSE OF REVIEW
The purpose of this review is to discuss the molecular mechanisms involved in osteocyte dendrite formation, summarize the similarities between osteocytic and neuronal projections, and highlight the importance of osteocyte dendrite maintenance in human skeletal disease.
RECENT FINDINGS
It is suggested that there is a causal relationship between the loss of osteocyte dendrites and the increased osteocyte apoptosis during conditions including aging, microdamage, and skeletal disease. A few mechanisms are proposed to control dendrite formation and outgrowth, such as via the regulation of actin polymerization dynamics. This review addresses the impact of osteocyte dendrites in bone health and disease. Recent advances in multi-omics, in vivo and in vitro models, and microscopy-based imaging have provided novel approaches to reveal the underlying mechanisms that regulate dendrite development. Future therapeutic approaches are needed to target the process of osteocyte dendrite formation.
Topics: Humans; Osteocytes; Bone and Bones; Aging; Dendrites
PubMed: 36087214
DOI: 10.1007/s11914-022-00753-8 -
Current Opinion in Neurobiology Oct 2021Synaptic clusters on dendrites are extraordinarily compact computational building blocks. They contribute to key local computations through biophysical and biochemical... (Review)
Review
Synaptic clusters on dendrites are extraordinarily compact computational building blocks. They contribute to key local computations through biophysical and biochemical signaling that utilizes convergence in space and time as an organizing principle. However, these computations can only arise in very special contexts. Dendritic cluster computations, their highly organized input connectivity, and the mechanisms for their formation are closely linked, yet these have not been analyzed as parts of a single process. Here, we examine these linkages. The sheer density of axonal and dendritic arborizations means that there are far more potential connections (close enough for a spine to reach an axon) than actual ones. We see how dendritic clusters draw upon electrical, chemical, and mechano-chemical signaling to implement the rules for formation of connections and subsequent computations. Crucially, the same mechanisms that underlie their functions also underlie their formation.
Topics: Axons; Dendrites; Neuronal Plasticity; Neurons; Signal Transduction; Synapses
PubMed: 34509808
DOI: 10.1016/j.conb.2021.08.001 -
Neuroscience May 2022In this paper, we discuss the nonlinear computational power provided by dendrites in biological and artificial neurons. We start by briefly presenting biological... (Review)
Review
In this paper, we discuss the nonlinear computational power provided by dendrites in biological and artificial neurons. We start by briefly presenting biological evidence about the type of dendritic nonlinearities, respective plasticity rules and their effect on biological learning as assessed by computational models. Four major computational implications are identified as improved expressivity, more efficient use of resources, utilizing internal learning signals, and enabling continual learning. We then discuss examples of how dendritic computations have been used to solve real-world classification problems with performance reported on well known data sets used in machine learning. The works are categorized according to the three primary methods of plasticity used-structural plasticity, weight plasticity, or plasticity of synaptic delays. Finally, we show the recent trend of confluence between concepts of deep learning and dendritic computations and highlight some future research directions.
Topics: Dendrites; Machine Learning; Models, Neurological; Neuronal Plasticity; Neurons
PubMed: 34656706
DOI: 10.1016/j.neuroscience.2021.10.001 -
Nature Reviews. Neuroscience Jun 2020Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to... (Review)
Review
Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.
Topics: Animals; Dendrites; Humans; Models, Neurological; Neurosciences
PubMed: 32393820
DOI: 10.1038/s41583-020-0301-7 -
Nature Neuroscience Jun 2023The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here...
The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here we report the complete dendrite and axon morphology of nearly 2,000 neurons in mouse prefrontal cortex (PFC). We identified morphological variations of somata, dendrites and axons across laminar layers and PFC subregions and the general rules of somatodendritic scaling with cytoarchitecture. We uncovered 24 morphologically distinguishable dendrite subtypes in 1,515 pyramidal projection neurons and 405 atypical pyramidal projection neurons and spiny stellate neurons with unique axon projection patterns. Furthermore, correspondence analysis among dendrites, local axons and long-range axons revealed coherent morphological changes associated with electrophysiological phenotypes. Finally, integrative dendrite-axon analysis uncovered the organization of potential intra-column, inter-hemispheric and inter-column connectivity among projection neuron types in PFC. Together, our study provides a comprehensive structural repertoire for the reconstruction and analysis of PFC neural network.
Topics: Mice; Animals; Dendrites; Neurons; Axons; Pyramidal Cells; Prefrontal Cortex
PubMed: 37217724
DOI: 10.1038/s41593-023-01339-y -
Annual Review of Neuroscience Jul 2019The structural and functional properties of neurons have intrigued scientists since the pioneering work of Santiago Ramón y Cajal. Since then, emerging cutting-edge... (Review)
Review
The structural and functional properties of neurons have intrigued scientists since the pioneering work of Santiago Ramón y Cajal. Since then, emerging cutting-edge technologies, including light and electron microscopy, electrophysiology, biochemistry, optogenetics, and molecular biology, have dramatically increased our understanding of dendritic properties. This advancement was also facilitated by the establishment of different animal model organisms, from flies to mammals. Here we describe the emerging model system of a polymodal neuron named PVD, whose dendritic tree follows a stereotypical structure characterized by repeating candelabra-like structural units. In the past decade, progress has been made in understanding PVD's functions, morphogenesis, regeneration, and aging, yet many questions still remain.
Topics: Aging; Animals; Caenorhabditis elegans; Dendrites; Humans; Neurons; Regeneration; Sensory Receptor Cells
PubMed: 30939099
DOI: 10.1146/annurev-neuro-072116-031437 -
Advances in Experimental Medicine and... 2022The first step toward understanding the brain is to learn how individual neurons process incoming signals, the vast majority of which arrive in their dendrites.... (Review)
Review
The first step toward understanding the brain is to learn how individual neurons process incoming signals, the vast majority of which arrive in their dendrites. Dendrites were first discovered at the beginning of the twentieth century and were characterized by great anatomical variability, both within and across species. Over the past years, a rich repertoire of active and passive dendritic mechanisms has been unveiled, which greatly influences their integrative power. Yet, our understanding of how dendrites compute remains limited, mainly because technological limitations make it difficult to record from dendrites directly and manipulate them. Computational modeling, on the other hand, is perfectly suited for this task. Biophysical models that account for the morphology as well as passive and active neuronal properties can explain a wide variety of experimental findings, shedding new light on how dendrites contribute to neuronal and circuit computations. This chapter aims to help the interested reader build biophysical models incorporating dendrites by detailing how their electrophysiological properties can be described using simple mathematical frameworks. We start by discussing the passive properties of dendrites and then give an overview of how active conductances can be incorporated, leading to realistic in silico replicas of biological neurons.
Topics: Biophysics; Computer Simulation; Dendrites; Neurons; Synapses
PubMed: 35471534
DOI: 10.1007/978-3-030-89439-9_2 -
Science (New York, N.Y.) Sep 2022Information processing in neuronal networks involves the recruitment of selected neurons into coordinated spatiotemporal activity patterns. This sparse activation...
Information processing in neuronal networks involves the recruitment of selected neurons into coordinated spatiotemporal activity patterns. This sparse activation results from widespread synaptic inhibition in conjunction with neuron-specific synaptic excitation. We report the selective recruitment of hippocampal pyramidal cells into patterned network activity. During ripple oscillations in awake mice, spiking is much more likely in cells in which the axon originates from a basal dendrite rather than from the soma. High-resolution recordings in vitro and computer modeling indicate that these spikes are elicited by synaptic input to the axon-carrying dendrite and thus escape perisomatic inhibition. Pyramidal cells with somatic axon origin can be activated during ripple oscillations by blocking their somatic inhibition. The recruitment of neurons into active ensembles is thus determined by axonal morphological features.
Topics: Action Potentials; Animals; Axons; Computer Simulation; Dendrites; Inhibitory Postsynaptic Potentials; Mice; Pyramidal Cells
PubMed: 36137045
DOI: 10.1126/science.abj1861