Biology subjects

De Schutter, E.

Publications and source records attributed to De Schutter, E..

18 recordsLinked to original sources

bioRxiv2026

Competing calcium sensors orchestrate various patterns of synaptic transmission

Neurotransmission critically depends on both timing and efficacy, enabling neurons to encode information with highly accuracy in millisecond timescales. While synapses often express multiple calcium sensors, such as synaptotagmin-1 (syt1) and synaptotagmin-7 (syt7), the quantitative mechanisms by which these sensors regulate synchronous release (SR) and asynchronous release (AR) remain unresolved. We develop a biophysically detailed stochastic model of a presynaptic bouton that incorporates the distinct calcium-binding kinetics of syt1 and syt7 to dissect their roles in shaping synaptic release. We demonstrate how a rich repertoire of SR and AR patterns is influenced by calcium channel distribution, sensor quantity, the external calcium concentration and buffer properties. Importantly, the interplay between syt1 and syt7-- through their distinct calcium affinities and exocytotic kinetics -- constitutes a core mechanism for neural transmission. These findings establish calcium partitioning as a core mechanism driving the diverse release patterns of syt1 and syt7, accommodating even more complex multi-sensor environments.

neuroscience↗

bioRxiv2026

Global Nernstian astrocytic depolarization breaks down during local synaptic input

Substantial progress in glial electrophysiology has revealed that astrocytes, which account for half of the cells in the human brain, exhibit membrane potentials that often reflect changes in the extracellular environment. Such responses are mediated by a variety of biochemicals, including potassium and neurotransmitters. Recent advances in voltage imaging have provided new insights into voltage activity in astrocyte peripheries, revealing highly localized depolarization that depends on local presynaptic activity. However, the electrophysiological properties of these isolated peripherals have not been explored due to limitations of spatial and temporal resolution. In this study, we aimed to explore differences in the electrophysiological response between whole-cell stimulation and isolated stimuli at different locations in the cell. Therefore, we constructed an empirical conductance-based NEURON model using a realistic morphology to simultaneously capture both astrocyte processes and soma electrophysiological dynamics. Our results predict a breakdown of the Nernstian behavior of astrocytes when potassium stimuli are localized. Instead, local responses are governed by their conductance ratios. Furthermore, we observe strong capabilities for isolating neurotransmitter responses to specific synaptic inputs, with minimal effect on the astrocyte soma. Our study highlights asymmetrical responses of astrocytic electrophysiology that depend on the spatial scale of stimulation.

neuroscience↗

bioRxiv2025

Evolution towards higher unitary conductance in mammals makes BK channels more efficient and precise

The large conductance calcium-activated potassium channel, known as the BK channel, play an essential role in neuronal firing and is characterized by a very large [~]250pS unitary conductance in mammals. However, this high unitary conductance is not consistent across all species with invertebrates demonstrating a much lower unitary conductance. We explored the calcium activation properties of BK channels of different unitary conductance in computational models and found that mammalian channels are more efficiently activated by calcium and produce a stronger potassium current compared to the channels of lower unitary conductance found in invertebrates. The lower unitary conductance channels display fierce competition for the available calcium, which results in low activation and weaker current. Due to these properties, mammalian BK channels are more suitable to repolarize sodium action potentials, which enables more precise spike timing, and may explain why evolution appears to have favored a trend towards very high unitary conductance in mammalian BK channels. This may be an essential component of the more advanced brain functions achieved by these species compared to invertebrates.

neuroscience↗

bioRxiv2025

Purkinje cell branch morphology determines effect of inhibition and SK2 modulation on somatic pauses

Characterized by a highly complex branching of their dendrites, Purkinje cells (PCs) have a unique architecture that enables them to receive impressive amounts of sensorimotor information through their parallel fiber (PF) input. They are tasked to encode this information with high accuracy. In this work, we discuss the mechanisms through which PCs encode this information, and we show how they multiplex between linear-rate and burst-pause coding. Particularly, somatic pauses are of utmost importance due to their involvement in learning. Using a novel heterogeneous model, we show that all branches can achieve a burst-pause response in response to branch-specific PF clustered input. We quantify the somatic pauses obtained and propose various mechanisms to alter the pause duration. Firstly, our results show that increasing local SK2 channel conductance density systematically increases pause duration. In four branches somatic pauses occurred only when SK2 conductance was increased. Interestingly, when adding feed-forward inhibition via stellate cells, our results show either an increase or a decrease in somatic pauses, highlighting the important role of branch morphology and branch location within the PC. Significance statementPurkinje cells are characterized by highly intricate dendritic branches, which enables them to encode sensorimotor information with great accuracy. Their somatic pauses following excitatory input have been shown to have a strong impact in learning. However, little is known about the impact of morphology and inhibitory input on somatic pauses and implicitly on the learning capacity. In this study, we propose a heterogeneous Purkinje cell model which highlights the importance of branch-specific dendritic morphology on somatic responses. We uncover two different mechanisms for modulating the length of the somatic pauses: density of SK2 channels and feed-forward inhibition via stellate cells.

neuroscience↗

bioRxiv2024

Active enhancement of synapse driven depolarization of perisynaptic astrocytic processes

Recent studies show that astrocytic depolarization can be induced at the periphery of cortical somatosensory astrocytes, proposed to be the contact sites between neurons and astrocytes. However, specific mechanisms causing astrocytic depolarization have yet to be confirmed due to limitations in experimental techniques. Here, we constructed a computational whole-cell astrocyte model to assess which channels were responsible for astrocyte depolarization. Our simulations show that, unlike depolarization by bath application of potassium, local depolarization by potassium uptake and glutamate transporters required very large spillover and high-frequency stimulation. On the contrary, the model reproduced experimentally observed depolarizations by activating N-methyl-d-aspartate receptor (NMDAR) or -aminobutyric acid A receptor (GABAAR), on the astrocyte. Our models suggest two mechanisms for astrocyte depolarization, either by neurotransmitters or by potassium and glutamate transporters, which substantially alters the spatio-temporal dynamics of the phenomenon. These insights suggest new mechanisms of how astrocytic processes can locally regulate learning and memory.

neuroscience↗

bioRxiv2024

Cerebellar tonic inhibition orchestrates the maturation of information processing and motor coordination

Tonic inhibition in cerebellar granule cells (GC) is crucial in information coding fidelity for motor coordination. It emerges in activity-dependent and-independent manners, and their interplay evolves with age. However, specific molecular and cellular mechanisms and how their change affects network-level computation and motor behavior remain unclear. Here we show that, while net tonic inhibitory current remains unchanged, the main source of tonic GABA switches from synaptic spillover (neuronal activity-dependent) to astrocytic Best1 (activity-independent) throughout adolescence (4-8 weeks) in mice. Computational modeling based on experimental data demonstrated that this switch down-regulates the internally generated network activity mediating mutual inhibition between GC clusters receiving different inputs, thereby enhancing their independence. Consistent with simulations, 3D-posture analysis revealed an age-dependent increase in independent limb movements during spontaneous motion, which was impaired in Best1 knockout mice. Our findings highlight the late-stage development of complex motor coordination driven by the emergence of astrocyte-mediated tonic inhibition. O_LI6 main figures, 58 references, 5,924 words in the manuscript (excluding the abstract, tables, figure legends and references). C_LIO_LISupplementary information: 1 text (supplementary methods), 9 figures, 4 movies, and 1 table. C_LI

neuroscience↗

bioRxiv2024

Branch-specific clustered parallel fiber input controls dendritic computation in Purkinje cells

Most central neurons have intricately branched dendritic trees that integrate massive numbers of synaptic inputs. Intrinsic active mechanisms in dendrites can be heterogenous and be modulated in a branch-specific way. However, it remains poorly understood how heterogenous intrinsic properties contribute to processing of synaptic input. We propose the first computational model of the cerebellar Purkinje cell with dendritic heterogeneity, in which each branch is an individual unit and is characterized by its own set of ion channel conductance densities. When simultaneously activating a cluster of parallel fiber synapses, we measure the peak amplitude of a response (PAR) and observe how changes in P-type calcium channel conductance density shift PAR from a linear one to a bimodal one including dendritic calcium spikes and vice-versa. These changes relate to the morphology of each branch. We show how dendritic calcium spikes propagate and how Kv4 channels block spreading depolarization to nearby branches.

neuroscience↗

bioRxiv2023

Dynamic Regulation of Vesicle Pools in a Detailed Spatial Model of the Complete Synaptic Vesicle Cycle

Synaptic transmission is driven by a complex cycle of synaptic vesicle docking, release, and recycling, and maintained by distinct vesicle pools with differing propensities for docking and release. However, the partitioning of vesicles into distinct pools and the conditions under which they are recruited from the reserve to the recycling pool remain poorly understood. Whilst computational modeling at the molecular level has progressed massively in recent years, modeling voluminous, dynamic, and heterogenous structures such as synaptic vesicles remains an unsolved problem. Here, we use a novel vesicle modeling technology to model the complete synaptic vesicle cycle in unprecedented molecular and spatial detail at a hippocampal en passant synapse, incorporating vesicle diffusion, the accumulation and diffusion of proteins on the vesicle surface, vesicle clustering, tethering, and docking, and regulated vesicle fusion and recycling. Our model demonstrates highly dynamic and robust recycling of synaptic vesicles able to maintain stable and consistent synaptic release over time, even during high frequency and sustained firing. We also reveal how the cytosolic proteins synapsin-1 and tomosyn-1 can cooperate to regulate the recruitment of vesicles from the reserve pool during sustained periods of synaptic activity in order to maintain transmission, as well as the potential of selective vesicle tethering close to the active zone to ensure rapid vesicle replenishment and enhance the efficiency of the vesicle cycle by minimizing the recruitment of vesicles from the reserve pool.

neuroscience↗

bioRxiv2023

Hybrid vesicle and reaction-diffusion modeling with STEPS

Vesicles carry out many essential functions within cells through the processes of endocytosis, exocytosis, and passive and active transport. This includes transporting and delivering molecules between different parts of the cell, and storing and releasing neurotransmitters in neurons. To date, computational simulation of these key biological players has been rather limited and has not advanced at the same pace as other aspects of cell modeling. As computational power advances and researchers want to add new realism to their models an important advance in the field of computational biology is to simulate vesicles in a realistic yet efficient manner. We describe a general vesicle modeling tool that has been designed for wide application to a variety of cell models, implemented within our voxel-based approach to modeling reaction-diffusion processes in realistic mesh reconstructions of cell tissue in our software STEPS. The implementation is validated in an extensive test suite, parallel performance demonstrated in a realistic synaptic bouton model, and example models are visualized in a Blender extension module.

systems biology↗

bioRxiv2022

Granule cells affect dendritic tree selection in purkinje cells during cerebellar development

This study investigates the interrelationship between primary dendrite selection of Purkinje cells and migration of their pre-synaptic partner granule cells during cerebellar development. During development of the cerebellar cortex, each Purkinje cell grows more than three dendritic trees, from which a primary tree is selected to develop further, whereas the others completely retract. Experimental studies suggest that this selection process is coordinated by physical and synaptic interactions with granule cells. However, technical limitations hinder a continuous experimental observation of multiple populations. To reveal the mechanism underlying this selection process, we constructed a computational model of dendritic developments and granule cell migrations, using a new computational framework, NeuroDevSim. Comparisons of the resulting morphologies from the model demonstrate the roles of the selection stage in regulating the growth of the selected primary trees. The study presents the first computational model that simultaneously simulates growing Purkinje cells and the dynamics of granule cell migrations, revealing the role of physical and synaptic interactions upon dendritic selection. The model provides new insights about the distinct planar morphology of Purkinje cell dendrites and about roles of the dendritic selection process during the cerebellar development. The model also supports the hypothesis that synaptic interactions by granule cells are likely to be involved in the selection procedure. Author SummaryThe mature structure of a Purkinje cell, the main neuron of the cerebellum, is composed of a large flat dendritic tree composed of a single or sometimes 2 primary dendrites. However, this neuron has multiple similar trees during development, and retracts most of them to select its primary tree. We aim to explore roles of this developmental process as either an important step to attain optimal morphology or merely a redundant step to be eliminated by evolution in the future. We especially focused on environmental interactions on Purkinje cells as criteria to select the dendritic tree, hypothesizing that developing an efficient network with other neurons is one of the main goals of neuronal morphology. We constructed and used computational models to investigate detailed physical interactions and communications between Purkinje cells and their environment. Comparisons of models suggest the role of the selection stage is to obtain favorable growth of primary trees.

neuroscience↗

bioRxiv2022

Efficient simulation of neural development using shared memory parallelization

The Neural Development Simulator, NeuroDevSim, is a Python module that simulates the most important aspects of development: growth, migration and pruning. It uses an agent-based modeling approach inherited from the NeuroMaC software. Each cycle, agents called fronts execute code. In the case of a growing dendritic or axonal front this will be a choice between extension, branching or growth termination. Somatic fronts can migrate to new positions and any front can be retracted to prune parts of neurons. NeuroDevSim is a multi-core program that uses an innovative shared memory approach to achieve parallel processing without messaging. We demonstrate close to linear strong scaling for medium size models for up to 32 cores and have run large models successfully on 128 cores. Most of the shared memory parallelism is achieved without memory locking. Instead cores have write privileges to private sections of arrays only, while being able to read the entire shared array. Memory conflicts are avoided by a coding rule that allows only active fronts to use methods that need writing access. The exception is collision detection, which is needed to avoid growth of physically overlapping structures. Here a locking mechanism was necessary to control access to grid points that register the location of nearby fronts. A custom approach using a serialized lock broker was able to manage both read and write locking. NeuroDevSim allows easy modeling of neural development for models ranging from a few complex to thousands of simple neurons or a mixture of both.

neuroscience↗

bioRxiv2022

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

AO_SCPLOWBSTRACTC_SCPLOWRecent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel implementations, inadequate. This paper introduces a new generation of the STochastic Engine for Pathway Simulation (STEPS) project, denominated STEPS 4.0, and its core components which have been designed for improved scalability, performance, and memory efficiency. STEPS 4.0 aims to enable novel scientific studies of macroscopic systems such as whole cells while capturing their nanoscale details. This class of models is out of reach for serial solvers due to the vast quantity of computation in such detailed models, and also out of reach for naive parallel solvers due to the large memory footprint. Based on a distributed mesh solution, we introduce a new parallel stochastic reaction-diffusion solver and a deterministic membrane potential solver in STEPS 4.0. The distributed mesh, together with improved data layout and algorithm designs, significantly reduces the memory footprint of parallel simulations in STEPS 4.0. This enables massively parallel simulations on modern HPC clusters and overcomes the limitations of the previous parallel STEPS implementation. Current and future improvements to the solver are not sustainable without proper software engineering practices. For this reason, we also give an overview of how the STEPS codebase and the development environment have been updated to follow modern software development practices. We benchmark performance improvement and memory footprint on three published models with different complexities, from a simple spatial stochastic reaction-diffusion model, to a more complex one that is coupled to a deterministic membrane potential solver to simulate the calcium burst activity of a Purkinje neuron. Simulation results of these models suggest that the new solution dramatically reduces the per-core memory consumption by more than a factor of 30, while maintaining similar or better performance and scalability.

neuroscience↗

bioRxiv2022

The endoplasmic reticulum in perisynaptic astrocytic processes: shape, distribution and effect on calcium activity

Astrocytes are now widely accepted as key regulators of brain function and behavior. Calcium (Ca2+) signals in perisynaptic astrocytic processes (PAPs) enable astrocytes to fine-tune neurotransmission at tripartite synapses. As most PAPs are below the diffraction limit, their content in Ca2+ stores and the contribution of the latter to astrocytic Ca2+ activity is unclear. Here, we reconstruct hippocampal tripartite synapses in 3D from a high resolution electron microscopy (EM) dataset and find that 75% of PAPs contain some endoplasmic reticulum (ER), a major calcium store in astrocytes. The ER in PAPs displays strikingly diverse shapes and intracellular spatial distributions. To investigate the causal relationship between each of these geometrical properties and the spatio-temporal characteristics of Ca2+ signals, we implemented an algorithm that generates 3D PAP meshes by altering the distribution of the ER independently from ER and cell shape. Reaction-diffusion simulations in these meshes reveal that astrocyte activity is governed by a complex interplay between the location of Ca2+ channels, ER surface-volume ratio and spatial distribution. In particular, our results suggest that ER-PM contact sites can act as local signal amplifiers if equipped with IP3R clusters but attenuate PAP Ca2+ activity in the absence of clustering. This study sheds new light on the ultrastructural basis of the diverse astrocytic Ca2+ microdomain signals and on the mechanisms that regulate neuron-astrocyte signal transmission at tripartite synapses. Main pointsO_LI6 nm isotropic volume EM reveals that 75% of perisynaptic astrocytic processes (PAPs) contain some ER C_LIO_LIPAPs & ER of the same cell display diverse geometric properties C_LIO_LISimulations in EM-derived meshes hint that ER geometry governs Ca2+ signals in PAPs C_LI TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/482292v4_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@e2387aorg.highwire.dtl.DTLVardef@1e9db45org.highwire.dtl.DTLVardef@3ab0d1org.highwire.dtl.DTLVardef@12e9ab2_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MF, network input) and Purkinje cells (PC, output), recorded from monkeys performing a saccade task. Unlike MFs, the properties of PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, flexible control of movement by the cerebellum crucially depends on its capacity for multi-dimensional computations.

neuroscience↗

bioRxiv2021

Astrocyte nanoscale morphology controls Ca2+ signals at tripartite synapses

Much of the Ca2+ activity in astrocytes is spatially restricted to microdomains and occurs in fine processes that form a complex anatomical meshwork, the so-called spongiform domain. A growing body of literature indicates that those astrocytic Ca2+ signals can influence the activity of neuronal synapses and thus tune the flow of information through neuronal circuits. Because of technical difficulties in accessing the small spatial scale involved, the role of astrocyte morphology on Ca2+ microdomain activity remains poorly understood. Here, we use computational tools and idealized 3D geometries of fine processes based on recent super-resolution microscopy data to investigate the mechanistic link between astrocytic nanoscale morphology and local Ca2+ activity. Simulations demonstrate that the nano-morphology of astrocytic processes powerfully shapes the spatio-temporal properties of Ca2+ signals and promotes local Ca2+ activity. The model predicts that this effect is attenuated upon astrocytic swelling, hallmark of brain diseases, which we confirm experimentally in hypo-osmotic conditions. Upon repeated neurotransmitter release events, the model predicts that swelling hinders astrocytic signal propagation. Overall, this study highlights the influence of the complex morphology of astrocytes at the nanoscale and its remodeling in pathological conditions on neuron-astrocyte communication at so-called tripartite synapses, where astrocytic processes come into close contact with pre- and postsynaptic structures. Table of ContentsO_ST_ABSMain PointsC_ST_ABSO_LIAstrocyte nano-morphology favors the compartmentalization of biochemical signals C_LIO_LIThis compartmentalization promotes local Ca2+ activity and signal propagation robustness C_LIO_LIIn contrast, its pathological remodeling upon swelling attenuates Ca2+ activity C_LI Table of Contents Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/432635v4_fig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@22b80forg.highwire.dtl.DTLVardef@1621218org.highwire.dtl.DTLVardef@191e971org.highwire.dtl.DTLVardef@751637_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Proposed mechanisms that regulate astrocytic Ca2+ activity in perisynaptic astrocytic processes. Our simulation results demonstrate that the nano-morphology of astrocytic processes, consisting in the alternation of nodes and shafts, favors the compartmentalization of biochemical signals. This compartmentalization promotes local Ca2+ activity and signal propagation robustness. Astrocyte swelling, observed in pathological conditions such as brain injury, stroke and epilepsy, results in an increased shaft width without altering node size. Our results suggest that such pathological alterations of the nanoscale morphology of astrocytes result in a decreased local Ca2+ activity, which we confirm experimentally in hypo-osmotic conditions. Upon repeated neuronal stimuli, we predict that swelling hinders astrocytic signal propagation. Overall, this study highlights the impact of astrocyte nano-morphology on astrocyte activity at tripartite synapses, in health and disease. C_FIG

neuroscience↗

bioRxiv2019

Firing rate-dependent phase responses of Purkinje cells support transient oscillations

Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. They exhibit strong firing-rate adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model we demonstrate that the rate adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na+ channels. Then we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. The changes in PRC cause oscillations and spike correlations only at high firing rates. The causal role of the PRC is confirmed using a simpler coupled oscillator network model. This mechanism enables transient oscillations between fast-spiking neurons that thereby form PC assemblies. Our work demonstrates that rate adaptation of PRCs can spatio-temporally organize the PC input to cerebellar nuclei.

neuroscience↗

bioRxiv2019

Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks

Feedforward networks (FFN) are ubiquitous structures in neural systems and have been studied to understand mechanisms of reliable signal and information transmission. In many FFNs, neurons in one layer have intrinsic properties that are distinct from those in their pre-/postsynaptic layers, but how this affects network-level information processing remains unexplored. Here we show that layer-to-layer heterogeneity arising from lamina-specific cellular properties facilitates signal and information transmission in FFNs. Specifically, we found that signal transformations, made by neighboring layers of neurons on an input-driven spike signal, are complementary to each other. This mechanism boosts information transfer carried by a propagating spike signal, and thereby supports reliable spike signal and information transmission in a deep FFN. Our study suggests that distinct cell types in neural circuits have complementary computational functions and facilitate information processing on the whole.\n\nSignificance StatementNeural systems have many cell types that differ in properties such as size, shape, cellular mechanisms, etc. Furthermore, neurons often propagate signals to other neurons that have properties very different from their own. We investigated what this phenomenon implies in neural information processing by using computational network models, inspired by a recent experimental study on the olfactory neural pathway of fruit flies. We found that different types of neurons can perform complementary functions in a network, which boosts information transfer on the whole and supports robust, stable signal propagation in a \"deep\" network with many layers. Our study demonstrates that diverse cell types with different intrinsic properties are crucial for optimal signal and information transfer in neural networks.

neuroscience↗

bioRxiv2018

Voltage- and Branch-specific Climbing Fiber Responses in Purkinje Cells

Climbing fibers (CFs) provide instructive signals driving cerebellar learning. However, conflicting experimental studies have been reported about the reliability of CF mediated Ca2+ influx in Purkinje cell (PC) distal dendrites. Mechanisms causing the wide variation in duration and spikelet numbers of complex spikes (CSs) have not been explored systematically. Using a new experimentally validated PC model, we describe the full range of modifiability of CF responses to explain the experimental data and make new predictions. We find voltage state gates the initiation and propagation of dendritic spikes. PC dendrites exhibit inhomogeneous excitability with individual branches as computational units for CF input. Somatic CSs are regulated by voltage state, CF activation phase and instantaneous CF firing rate. Concurrent synaptic inputs can affect CSs by modulating dendritic responses in a spatially precise way. These voltage- and branch-specific CF responses will increase dendritic computational capacity and give PCs an active role in integrating CF signals.

neuroscience↗