scholarly journals Properties and computational consequences of fast dendritic spikes during natural behavior

2021 ◽  
Author(s):  
Alain destexhe ◽  
mayank R mehta
Keyword(s):  
Computational Models ◽  
Biophysical Models ◽  
Neuronal Dendrites ◽  
Dendritic Membrane ◽  
Voltage Dependent ◽  
Dendritic Spikes ◽  
Dendritic Spike ◽  
Experimental Findings ◽  
Dendritic Branches ◽  
First Time

Dendritic membrane potential was recently measured for the first time in drug-free, naturally behaving rats over several days. These showed that neuronal dendrites generate a lot of sodium spikes, up to ten times as many as the somatic spikes. These key experimental findings are reviewed here, along with a discussion of computational models, and computational consequences of such intense spike traffic in dendrites. We overview the experimental techniques that enabled these measurements as well as a variety of models, ranging from conceptual models to detailed biophysical models. The biophysical models suggest that the intense dendritic spiking activity can arise from the biophysical properties of the dendritic voltage-dependent and synaptic ion channels, and delineate some computational consequences of fast dendritic spike activity. One remarkable aspect is that in the model, with fast dendritic spikes, the efficacy of synaptic strength in terms of driving the somatic activity is much less dependent on the position of the synapse in dendrites. This property suggests that fast dendritic spikes is a way to confer to neurons the possibility to grow complex dendritic trees with little computational loss for the distal most synapses, and thus form very complex networks with high density of connections, such as typically in the human brain. Another important consequence is that dendritically localized spikes can allow simultaneous but different computations on different dendritic branches, thereby greatly increasing the computational capacity and complexity of neuronal networks.

scholarly journals Dendritic spikes expand the range of well-tolerated population noise structures

2018 ◽  
Author(s):  
Alon Poleg-Polsky
Keyword(s):  
Noise Mitigation ◽  
Population Activity ◽  
Neuronal Dendrites ◽  
Size Constraints ◽  
Signal Encoding ◽  
Dendritic Spikes ◽  
Random Variability ◽  
Dendritic Spike ◽  
Brain States ◽  
The Brain

AbstractThe brain operates surprisingly well despite the noisy nature of individual neurons. The central mechanism for noise mitigation in the nervous system is thought to involve averaging over multiple noise-corrupted inputs. Subsequently, there has been considerable interest recently to identify noise structures that can be integrated linearly in a way that preserves reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a complementary de-noising approach that is mediated by focal dendritic spikes. Dendritic spikes might seem to be unlikely candidates for noise reduction due to their miniscule integration compartments and poor averaging abilities. Nonetheless, the extra thresholding step introduced by dendritic spike generation increases neuronal performance for a broad category of computational tasks, including analog and binary discrimination, as well as for a range of correlated and uncorrelated noise structures, some of which cannot be adequately resolved with averaging. This property of active dendrites compensates for compartment size constraints and expands the repertoire of brain states and presynaptic population activity dynamics can be reliably de-noised by biologically-realistic neurons.Significance StatementNoise, or random variability, is a prominent feature of the neuronal code and poses a fundamental challenge for information processing. To reconcile the surprisingly accurate output of the brain with the inherent noisiness of biological systems, previous work examined signal integration in idealized neurons. The notion that emerged from this body of work is that accurate signal representation relies largely on input averaging in neuronal dendrites. In contrast to the prevailing view, I show that de-noising in simulated neurons with realistic morphology and biophysical properties follows a different strategy: dendritic spikes act as classifiers that assist in extracting information from a variety of noise structures that have been considered before to be particularly disruptive for reliable brain function.

scholarly journals Somatic Depolarization Enhances Hippocampal CA1 Dendritic Spike Propagation and Distal Input Driven Synaptic Plasticity

2021 ◽  
Author(s):  
Tobias Bock ◽  
Steven A. Siegelbaum
Keyword(s):  
Synaptic Plasticity ◽  
Hippocampal Slices ◽  
Memory Storage ◽  
Resting Potential ◽  
Neuronal Dendrites ◽  
Cable Properties ◽  
Dendritic Spikes ◽  
Dendritic Spike ◽  
Acute Hippocampal Slices ◽  
Somatic Response

AbstractSynaptic inputs that target distal regions of neuronal dendrites can often generate local dendritic spikes that can amplify synaptic depolarization, induce synaptic plasticity, and enhance neuronal output. However, distal dendritic spikes are subject to significant attenuation by dendritic cable properties, and often produce only a weak subthreshold depolarization of the soma. Nonetheless, such spikes have been implicated in memory storage, sensory perception and place field formation. How can such a weak somatic response produce such powerful behavioral effects? Here we use dual dendritic and somatic recordings in acute hippocampal slices to reveal that dendritic spike propagation, but not spike initiation, is strongly enhanced when the somatic resting potential is depolarized, likely as a result of increased inactivation of A-type K+ channels. Somatic depolarization also facilitates the induction of a form of dendritic spike driven heterosynaptic plasticity that enhances memory specificity. Thus, the effect of somatic membrane depolarization to enhance dendritic spike propagation and long-term synaptic plasticity is likely to play an important role in hippocampal-dependent spatial representations as well as learning and memory.

Voltage-Dependent Properties of Dendrites That Eliminate Location-Dependent Variability of Synaptic Input

1999 ◽  
Vol 81 (2) ◽  
pp. 535-543 ◽  
Author(s):  
Erik P. Cook ◽  
Daniel Johnston
Keyword(s):  
Synaptic Input ◽  
Outward Current ◽  
Compartment Model ◽  
Inward Current ◽  
Voltage Gated ◽  
Cable Properties ◽  
Dendritic Membrane ◽  
Voltage Dependent ◽  
Dendritic Location ◽  
Voltage Gated Channels

Voltage-dependent properties of dendrites that eliminate location-dependent variability of synaptic input. We examined the hypothesis that voltage-dependent properties of dendrites allow for the accurate transfer of synaptic information to the soma independent of synapse location. This hypothesis is motivated by experimental evidence that dendrites contain a complex array of voltage-gated channels. How these channels affect synaptic integration is unknown. One hypothesized role for dendritic voltage-gated channels is to counteract passive cable properties, rendering all synapses electrotonically equidistant from the soma. With dendrites modeled as passive cables, the effect a synapse exerts at the soma depends on dendritic location (referred to as location-dependent variability of the synaptic input). In this theoretical study we used a simplified three-compartment model of a neuron to determine the dendritic voltage-dependent properties required for accurate transfer of synaptic information to the soma independent of synapse location. A dendrite that eliminates location-dependent variability requires three components: 1) a steady-state, voltage-dependent inward current that together with the passive leak current provides a net outward current and a zero slope conductance at depolarized potentials, 2) a fast, transient, inward current that compensates for dendritic membrane capacitance, and 3) both αamino-3-hydroxy-5-methyl-4-isoxazolepropionic acid– and N-methyl-d-aspartate–like synaptic conductances that together permit synapses to behave as ideal current sources. These components are consistent with the known properties of dendrites. In addition, these results indicate that a dendrite designed to eliminate location-dependent variability also actively back-propagates somatic action potentials.

scholarly journals BAX requires VDAC2 to mediate apoptosis and to limit tumor development

2018 ◽  
Author(s):  
Hui San Chin ◽  
Mark F. van Delft ◽  
Robert L. Ninnis ◽  
Mark X. Li ◽  
Iris K. L. Tan ◽  
...  
Keyword(s):  
Tumor Development ◽  
Anion Channel ◽  
Tumor Formation ◽  
Cytotoxic Action ◽  
Voltage Dependent Anion Channel ◽  
Genome Wide ◽  
Anti Cancer ◽  
Voltage Dependent ◽  
Genetic Deletion ◽  
First Time

AbstractIntrinsic apoptosis is critical for normal physiology including the prevention of tumor formation. BAX and BAK are essential for mediating this process and for the cytotoxic action of many anticancer drugs. BAX and BAK are thought to act in a functionally redundant manner and are considered to be regulated similarly. From an unbiased genome-wide CRISPR/Cas9 screen, we identified VDAC2 (voltage-dependent anion channel 2) as essential for BAX, but not BAK, to function. The genetic deletion of VDAC2 abrogated the association of BAX and BAK with mitochondrial complexes that contain VDAC1, VDAC2 and VDAC3. By disrupting its localization to mitochondria, BAX is rendered completely ineffective. Moreover, we defined an interface unique to VDAC2 that is required to drive BAX activity. Consequently, interfering with this interaction or deleting VDAC2 phenocopied the loss of BAX, including impairing the killing of tumor cells by anti-cancer agents such as the BCL-2 inhibitor venetoclax. Furthermore, the ability of BAX to prevent tumor formation was attenuated in the absence of VDAC2. Taken together, our studies show for the first time that BAX-mediated apoptosis, but not BAK-mediated apoptosis, is critically dependent on VDAC2, hence revealing the differential regulation of BAX and BAK.

scholarly journals A Combined Computational and Experimental Study of Methane Activation during Oxidative Coupling of Methane (OCM) by Surface Metal Oxide Catalysts

2021 ◽  
Author(s):  
Daniyal Kiani ◽  
Sagar Sourav ◽  
Jonas Baltrusaitis ◽  
Israel E Wachs
Keyword(s):  
Experimental Study ◽  
Metal Oxide ◽  
Oxidative Coupling ◽  
Active Sites ◽  
Computational Models ◽  
Oxidative Coupling Of Methane ◽  
Catalytic Active Sites ◽  
Surface Metal ◽  
Heterolytic Dissociation ◽  
First Time

The experimentally validated computational models developed herein, for the first time, show that Mn-promotion does not enhance the activity of the surface Na2WO4 catalytic active sites for CH4 heterolytic dissociation...

Forward Dendritic Spikes

2011 ◽  
pp. 42-59
Author(s):  
Oscar Herreras ◽  
Julia Makarova ◽  
José Manuel Ibarz
Keyword(s):  
Action Potentials ◽  
Remarkable Property ◽  
Synaptic Inputs ◽  
Brain Circuits ◽  
Voltage Dependent ◽  
Dendritic Spikes ◽  
Underlying Mechanisms ◽  
The Brain ◽  
Made In

Neurons send trains of action potentials to communicate each other. Different messages are issued according to varying inputs, but they can also mix them up in a multiplexed language transmitted through a single cable, the axon. This remarkable property arises from the capability of dendritic domains to work semi autonomously and even decide output. We review the underlying mechanisms and theoretical implications of the role of voltage-dependent dendritic currents on the forward transmission of synaptic inputs, with special emphasis in the initiation, integration and forward conduction of dendritic spikes. When these spikes reach the axon, output decision was made in one of many parallel dendritic substations. When failed, they still serve as an internal language to transfer information between dendritic domains. This notion brakes with the classic view of neurons as the elementary units of the brain and attributes them computational/storage capabilities earlier billed to complex brain circuits.

Synaptic Interactions in a Passive Dendritic Tree

1998 ◽  
Author(s):  
Christof Koch
Keyword(s):  
Nervous System ◽  
Dendritic Tree ◽  
Extreme Case ◽  
Pyramidal Cells ◽  
Inhibitory Synapses ◽  
Dendritic Trees ◽  
Central Processing ◽  
Voltage Dependent ◽  
Dendritic Spikes ◽  
Spatial Positioning

Nerve cells are the targets of many thousands of excitatory and inhibitory synapses. An extreme case are the Purkinje cells in the primate cerebellum, which receive between one and two hundred thousand synapses onto dendritic spines from an equal number of parallel fibers (Braitenberg and Atwood, 1958; Llinas and Walton, 1998). In fact, this structure has a crystalline-like quality to it, with each parallel fiber making exactly one synapse onto a spine of a Purkinje cell. For neocortical pyramidal cells, the total number of afferent synapses is about an order of magnitude lower (Larkman, 1991). These numbers need to be compared against the connectivity in the central processing unit (CPU) of modern computers, where the gate of a typical transistor usually receives input from one, two, or three other transistors or connects to one, two, or three other transistor gates. The large number of synapses converging onto a single cell provide the nervous system with a rich substratum for implementing a very large class of linear and nonlinear neuronal operations. As we discussed in the introductory chapter, it is only these latter ones, such as multiplication or a threshold operation, which are responsible for “computing” in the nontrivial sense of information processing. It therefore becomes crucial to study the nature of the interaction among two or more synaptic inputs located in the dendritic tree. Here, we restrict ourselves to passive dendritic trees, that is, to dendrites that do not contain voltage-dependent membrane conductances. While such an assumption seemed reasonable 20 or even 10 years ago, we now know that the dendritic trees of many, if not most, cells contain significant nonlinearities, including the ability to generate fast or slow all-or-none electrical events, so-called dendritic spikes. Indeed, truly passive dendrites may be the exception rather than the rule in the nervous In Sec. 1.5, we studied this interaction for the membrane patch model. With the addition of the dendritic tree, the nervous system has many more degrees of freedom to make use of, and the strength of the interaction depends on the relative spatial positioning, as we will see now. That this can be put to good use by the nervous system is shown by the following experimental observation and simple model.

Patterns of Locomotor Drive to Motoneurons and Last-Order Interneurons: Clues to the Structure of the CPG

2001 ◽  
Vol 86 (1) ◽  
pp. 447-462 ◽  
Author(s):  
R. E. Burke ◽  
A. M. Degtyarenko ◽  
E. S. Simon
Keyword(s):  
Fictive Locomotion ◽  
Cutaneous Reflex ◽  
Reflex Pathways ◽  
Locomotor Control ◽  
Low Threshold ◽  
Experimental Findings ◽  
Differential Control ◽  
Flexor Digitorum ◽  
First Time ◽  
Shed Light

We have examined the linkage between patterns of activity in several hindlimb motor pools and the modulation of oligosynaptic cutaneous reflex pathways during fictive locomotion in decerebrate unanesthetized cats to assess the notion that such linkages can shed light on the structure of the central pattern generator (CPG) for locomotion. We have concentrated attention on the cutaneous reflex pathways that project to the flexor digitorum longus (FDL) motor pool because of that muscle's unique variable behavior during normal and fictive locomotion in the cat. Differential locomotor control of last-order excitatory interneurons in pathways from low-threshold cutaneous afferents in the superficial peroneal and medial plantar afferents to FDL motoneurons is fully documented for the first time. The qualitative patterns of differential control are shown to remain the same whether the FDL muscle is active in early flexion, as usually found, or during the extension phase of fictive locomotion, which is less common during fictive stepping. The patterns of motor pool activity and of reflex pathway modulation indicate that the flexion phase of fictive locomotion has distinct early versus late components. Observations during “normal” and unusual patterns of fictive stepping suggest that some aspects of locomotor pattern formation can be separated from rhythm generation, implying that these two CPG functions may be embodied, at least in part, in distinct neural organizations. The results are discussed in relation to a provisional circuit diagram that could explain the experimental findings.

Review of Stress Effects on Dopant Solubility in Silicon and Silicon-Germanium Layers

2009 ◽  
Vol 156-158 ◽  
pp. 173-180 ◽  
Author(s):  
Nicholas S. Bennett ◽  
Chihak Ahn ◽  
Nicholas E.B. Cowern ◽  
Peter Pichler
Keyword(s):  
Silicon Germanium ◽  
Experimental Studies ◽  
Close Correlation ◽  
Theoretical Treatment ◽  
Strained Si ◽  
Early Theory ◽  
Stress Effects ◽  
Experimental Findings ◽  
First Time ◽  
Strained Sige

We present a review of both theoretical and experimental studies of stress effects on the solubility of dopants in silicon and silicon-germanium materials. Critical errors and limitations in early theory are discussed, and a recent treatment incorporating charge carrier induced lattice strain and correct statistics is presented. Considering all contributing effects, the strain compensation energy is the primary contribution to solubility enhancement in both silicon and silicon-germanium for dopants of technological interest. An exception is the case of low-solubility dopants, where a Fermi level contribution is also found. Explicit calculations for a range of dopant impurities in Si are presented that agree closely with experimental findings for As, Sb and B in strained Si. The theoretical treatment is also applied to account for stress effects in strained SiGe structures, which also show close correlation with recently derived experimental results for B-doped strained SiGe which are presented here for the first time.

scholarly journals Persistent Na+ Current Modifies Burst Discharge By Regulating Conditional Backpropagation of Dendritic Spikes

2003 ◽  
Vol 89 (1) ◽  
pp. 324-337 ◽  
Author(s):  
Brent Doiron ◽  
Liza Noonan ◽  
Neal Lemon ◽  
Ray W. Turner
Keyword(s):  
Sodium Current ◽  
Pyramidal Cells ◽  
Weakly Electric Fish ◽  
Burst Frequency ◽  
Burst Discharge ◽  
Dendritic Spikes ◽  
Dendritic Spike ◽  
Time Required ◽  
Weakly Electric ◽  
Spike Bursts

The estimation and detection of stimuli by sensory neurons is affected by factors that govern a transition from tonic to burst mode and the frequency chracteristics of burst output. Pyramidal cells in the electrosensory lobe of weakly electric fish generate spike bursts for the purpose of stimulus detection. Spike bursts are generated during repetitive discharge when a frequency-dependent broadening of dendritic spikes increases current flow from dendrite to soma to potentiate a somatic depolarizing afterpotential (DAP). The DAP eventually triggers a somatic spike doublet with an interspike interval that falls inside the dendritic refractory period, blocking spike backpropagiation and the DAP. Repetition of this process gives rise to a rhythmic dendritic spike failure, termed conditional backpropagation, that converts cell output from tonic to burst discharge. Through in vitrorecordings and compartmental modeling we show that burst frequency is regulated by the rate of DAP potentiation during a burst, which determines the time required to discharge the spike doublet that blocks backpropagation. DAP potentiation is maginfied through a postitve feedback process when an increase in dendritic spike duration activates persistent sodium current ( I NaP). I NaP further promotes a slow depolarization that induces a shift from tonic to burst discharge over time. The results are consistent with a dynamical systems analysis that shows that the threshold separating tonic and burst discharge can be represented as a saddle-node bifurcation. The interaction between dendritic K+ current and I NaP provides a physiological explanation for a variable time scale of bursting dynamics characteristic of such a bifurcation.

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