Properties and computational consequences of fast dendritic spikes during natural behavior

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.

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

Synaptic 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.

Altered A-type potassium channel function impairs dendritic spike initiation and temporammonic long-term potentiation in Fragile X syndrome

Fragile X syndrome (FXS) is the leading monogenetic cause of cognitive impairment and autism spectrum disorder. Area CA1 of the hippocampus receives current information about the external world from the entorhinal cortex via the temporoammonic (TA) pathway. Given its role in learning and memory, it is surprising that little is known about TA long-term potentiation (TA-LTP) in FXS. We found that TA-LTP was impaired in fmr1 KO mice. Furthermore, dendritic Ca2+ influx was smaller and dendritic spike threshold was depolarized in fmr1 KO mice. Dendritic spike threshold and TA-LTP were restored by block of A-type K+ channels. The impairment of TA-LTP coupled with enhanced Schaffer collateral LTP may contribute to spatial memory alterations in FXS. Furthermore, as both of these LTP phenotypes are attributed to changes in A-type K+ channels in FXS, our findings provide a potential therapeutic target to treat cognitive impairments in FXS.

Analyzing Branch‐specific Dendritic Spikes Using an Ultrafast Laser Scalpel

Dendritic spikes facilitate neuronal computation and they have been reported to occur in various regions of the dendritic tree of cortical neurons. Spikes that occur only on a select few branches are particularly difficult to analyze especially in complex and intertwined dendritic arborizations where highly localized application of pharmacological blocking agents is not feasible. Here, we present a technique based on highly targeted dendrotomy to tease out and study dendritic spikes that occur in oblique branches of cortical layer five pyramidal neurons. We first analyze the effect of cutting dendrites in silico and then confirmed in vitro using an ultrafast laser scalpel. A dendritic spike evoked in an oblique branch manifests at the soma as an increase in the afterdepolarization (ADP). The spikes are branch-specific since not all but only a few oblique dendrites are observed to evoke spikes. Both our model and experiments show that cutting certain oblique branches, where dendritic spikes are evoked, curtailed the increase in the ADP. On the other hand, cutting neighboring oblique branches that do not evoke spikes maintained the ADP. Our results show that highly targeted dendrotomy can facilitate causal analysis of how branch-specific dendritic spikes influence neuronal output.

Robust emergence of sharply tuned place cell responses in hippocampal neurons with structural and biophysical heterogeneities

ABSTRACTHippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somato-dendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models, we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a nonspecific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of virtual knockout models, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological micro-structure, in achieving sharp feature encoding and excitability homeostasis.

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

The 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.