Biology subjects

Wolf, F.

Publications and source records attributed to Wolf, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Signatures of Hebbian plasticity in the nanoscale morphodynamics of cortical spines

The size, shape, and nanoscale organization of synaptic spines are predictive of physiological synaptic strength and thus key to connectome-based neural circuit models. In the intact brain, spine size and shape undergo continuous morphological remodeling. While these nanoscale morphodynamics are not well understood, it is clear that morphological changes that strongly impact synaptic strength should modify spine head and neck in a coordinated manner and that such coordinated remodeling can be triggered by spike-timing-dependent synaptic plasticity. Here we demonstrate unambiguous signatures of such coordinated spine remodeling from in vivo long-term nanoscopy of cortical spines. We infer data-driven generative models of synaptic spine morphodynamics. These models imply that although coordinated remodeling represents the smallest component of ongoing morphodynamic fluctuations, this component causes massive fluctuations in instantaneous synaptic strength. Despite these fluctuations, synaptic strengths exhibit a synapse-specific long-term persistent component that results from spine fluctuations exploring only a limited subregion of accessible spine morphospace. Our results suggest that nanoscale morphodynamic spine remodeling injects substantial fluctuations of instantaneous synaptic strength into the operation of cortical circuits. Connectome-based neural circuit models thus need to consider features of spine organization beyond spine head size and should be augmented by data-driven generative models of spine morphodynamics.

neuroscience↗

bioRxiv2026

Multi-omics profiling links epigenetic and lncRNA changes to early human endochondral ossification priming

Differentiation programs remain incompletely understood across stem cell types, including for human bone marrow mesenchymal stromal/stem (BM-MSCs) cells, a heterogenous population orchestrating bone formation and establishing a functional hematopoietic niche in the bone marrow. BM-MSCs form and repair bone through the evolutionarily conserved process of endochondral ossification (EO), initiated by deposition of a transient cartilage template subsequently remodeled into bone and bone marrow tissues. Despite their considerable potential for skeletal regeneration, the early molecular and cellular events underlying BM-MSCs commitment to EO remain elusive. To overcome donor dependent variability in chondrogenic potential that limits mechanistic studies, we here exploit OssiGel as a potent chondro-inductive extracellular matrix offering robust recapitulation of EO by BM-MSCs. Through multi-omics profiling of OssiGel-primed BM-MSCs, we identify rapid chromatin remodeling at chondrogenic loci as concomitant for lineage commitment. The emergence of a chondro-progenitor population is detected as early as 3 days in vivo and correlates with successful EO recapitulation. Mechanistically, we identify LINC02511 as novel enhancer-associated element involved in the onset of EO. We confirm presence of LINC02511 in human skeletal atlases, and its CRISPR-mediated silencing significantly impaired EO. By integrating human tissue engineering strategies with single cell multi-omics profiling, our study provides a framework for deciphering BM-MSCs fate decisions, highlighting the role of enhancer and non-coding elements as key determinants of early lineage specification. These findings advance our understanding of BM-MSCs biology and will prompt their translational exploitation in regenerative medicine.

cell biology↗

bioRxiv2026

Rewiring the Human Brain: On the Fabric of Associative Thinking

Concept cells are neurons in the medial temporal lobe that represent an abstract concept, such as a familiar person, in a context-independent way. They are activated by heterogeneous and potentially multi-modal sensory input related to the concept, such as viewing a photo of the person, reading the persons name, or hearing the persons voice. Learning the concept implies connecting the cortical cells that are triggered when such features are perceived with the cells of the concept, resulting in an associative memory engram. Traditional models explain the formation of such an engram with Hebbian learning through synaptic plasticity, the strengthening of existing synapses in response to co-stimulation. However, the low edge density of the brain suggests that direct connections in the form of preexisting synapses between these cells are relatively unlikely, rendering such constructs inefficient and volatile. Instead, it is plausible that more persistent concept engrams rely on structural plasticity, involving the creation of synapses de novo. Yet, it has still been unclear how neurons can project their axons across such a considerable distance, finding a target they do not know in advance. In this paper, we simulate the formation of such structural engrams in the connectomes of healthy subjects, offering a model hypothesis of how such engrams can be formed on a structural level. Based on our model, we further demonstrate how activating a concept can trigger related concepts through overlapping sensory associations, in a process we call a percept-concept loop.

neuroscience↗

bioRxiv2026

Shapes of condensate droplets containing filaments

The interactions of droplets and filaments can lead to mutual deformations and complex combined behavior. Such interactions also occur within the cell, where biomolecular condensates, distinct liquid phases often composed of proteins, have been observed to structure and affect the organization of the cytoskeleton. In particular, biomolecular condensates have been shown to undergo characteristic deformations when cytoskeletal filaments are fully embedded within them. However, a full understanding of the underlying physical mechanisms is still missing. Here, we combine experiments with coarse-grained molecular dynamics simulations and analytical models to uncover the physical mechanisms that define emerging shapes of droplets containing filaments. We find that the surface tension of the liquid phase and the bending energy of the filament(s) suffice to accurately capture emerging shapes if the length of the filament is small compared to the liquid volume. As the volume fraction of filament(s) increases, wetting effects become increasingly important, setting physical constraints within which surface and bending energies compete to define the droplet shapes. We find that mutual deformations of condensate and filament extend accessible shapes beyond classical stability considerations, leading to structuring and entrapment of contained filaments. Shape deformations may further affect ripening dynamics that favor certain geometries. Our findings provide a physical framework for a better understanding of the possible roles of biomolecular condensates in cytoskeletal organization.

biophysics↗

bioRxiv2026

Multivariate Transfer Entropy Quantifies Information Transfer Between Dyadic Partners During Real-Time Perceptual Decision-Making

1Many social behaviours unfold continuously in time, yet most studies of social influence rely on discrete, trial-based paradigms. To quantify how humans actually integrate sensory and social signals during ongoing perceptual decision-making we here apply an information-theoretic analysis to data obtained with the Continuous Perceptual Report (CPR) paradigm. In the CPR task, pairs of participants tracked a dynamic random-dot motion stimulus, continuously reporting perceived direction and their confidence. Crucially, each participant had access to their partners moment-by-moment direction and confidence reports embedded within the stimulus display. We quantified information flow between the stimulus and behavioural responses using multivariate transfer entropy, allowing us to detect whether participants acquired additional information from their partner once stimulus information had been received and integrated it into their behavioural response. We show that real-time social interactions predominantly occur within matching behavioural dimensions: partners perceptual choices influence participants own choices, and partners confidence influences participants confidence. Using both, more stimulus and social information contributed to improved task performance, and participants selectively acquired more information from better-performing partners. Crucially, information integration was flexibly modulated by stimulus reliability: as sensory evidence became noisier, participants relied more on social information, but only when interacting with a highly reliable (e.g. computer-controlled) partner. Latency analyses further revealed that participants responded faster to changes in their partners perceptual choices of direction than to changes in stimulus direction. They also responded more slowly to changes in their partners confidence than to changes in their partners choice of direction. Together, these findings demonstrate that humans dynamically and adaptively integrate social information in a time-continuous manner, and they establish multivariate information-theoretic analyses as a powerful framework for studying real-time social cognition.

animal behavior and cognition↗

bioRxiv2025

Evaluation of Tissue-Engineered Blood Vessels as Three-Dimensional In Vitro Testing System in Cardiovascular Research and Device Approval

BackgroundDisturbed crosstalk between endothelial cells (ECs) and vascular smooth muscle cells (SMCs) has an important role in atherosclerosis and restenosis after vascular intervention, however, the exact pathomechanisms are incompletely understood. Current preclinical testing models do not adequately recapitulate the complexity of human arteries. Here, we present tissue-engineered blood vessels (TEBVs) as a novel in vitro model and validate it for intimal hyperplasia. MethodsTEBVs fabricated from SMC suspended in fibrin gel, supported by a textile mesh, were seeded with ECs at various concentrations and subjected to arterial flow conditions in a bioreactor. In addition, TEBVs underwent plain old balloon angioplasty (POBA) and implantation of bare metal stents (BMS) and drug-eluting stents (DES) at day 7 after fabrication. TEBVs were dynamically conditioned in a bioreactor for 21 days in total and monitored by optical coherence tomography. ResultsTEBVs with absent or incomplete endothelial layer exhibited thicker vessel walls, more disorganized and misaligned collagen, and increased cellular proliferation compared with completely endothelialized TEBVs. POBA and stent implantation were feasible 7 days after TEBV fabrication. At 14 days post-intervention, POBA-treated TEBVs exhibited significantly thicker vessel walls than untreated controls and stented TEBVs, whereas stented TEBVs showed greater lumen diameters than unstented TEBVs. Endothelial strut coverage was significantly higher in BMS-treated compared with DES-treated TEBVs. Over the course of the conditioning period, levels of IL-6, IL-8, and MCP-1 were highest in medium samples from BMS-treated TEBVs compared to DES-treated TEBVs and compared to untreated controls. ConclusionsTEBVs are a promising approach towards an in vitro system for the study of intimal hyperplasia. Due to their similarity in size and wall thickness to human coronary arteries, TEBVs may also serve as a platform for testing new stent designs. Graphical AbstractTissue-engineered blood vessels (TEBV) fabricated from smooth muscle cell /fibroblast mixtures suspended in fibrin gel, supported by a textile mesh, were seeded with endothelial cells and conditioned in a bioreactor system for 21 days. Different endothelialization strategies resulted in differences in wall thickness. In addition, TEBVs underwent plain old balloon angioplasty (POBA) and stent implantation. POBA-treated TEBVs exhibited thicker vessel walls compared with non-treated TEBV controls and compared with stented TEBVs. We also observed significantly higher stent strut coverage with endothelial cells after implantation of bare metal stents (BMS) compared to drug-eluting stents (DES). TEBVs are a promising approach towards an in-vitro system for the study of intimal hyperplasia. Due to their similarity in size and wall thickness to human coronary arteries, TEBVs may also serve as a platform for testing new stent designs.

bioengineering↗

bioRxiv2025

Developmental plasticity facilitates the structural maturation of cochlear inner hair cell ribbon synapses

Sound detection occurs in the cochlea, where sensory inner hair cells (IHC) accurately convert auditory stimuli into neurochemical signals. Presynaptically, IHCs harbor synaptic ribbons, specialized scaffolds that facilitate ultrafast and indefatigable exocytosis. During synapse assembly and subsequent maturation, IHC ribbons increase in volume and synaptic vesicle tethering capacity. This development is thought to result from progressive precursor aggregation. However, the underlying mechanisms of ribbon synapse formation have remained elusive thus far. In this study, we established a novel triple-color live-cell imaging approach to monitor IHC pre-synaptogenesis in situ. We found that ribbon precursors are highly dynamic and undergo bidirectional plasticity. The presynaptic active zone (AZ) forms a focal point for dramatic structural remodeling of precursors, which the AZ recruits, confines and redistributes. Furthermore, silencing spontaneous synaptic activity decreased precursor mobility and plasticity at the AZ. This suggests a fundamental role for activity-dependent Ca2+ influx in the plastic development shaping the unique properties of auditory ribbon synapses.

neuroscience↗

bioRxiv2025

Charting the nanotopography of inner hair cell synapses using MINFLUX nanoscopy

For us to hear, the cochlea encodes sounds into neural signals at synapses of inner hair cells (IHCs) and the auditory nerve with remarkable fidelity. To achieve the high rates of temporally precise synaptic transmission over long periods of time, IHCs employ sophisticated ribbon-type active zones (AZ). In order for us to understand synaptic sound encoding, we need to decipher the underpinning molecular topography of these synapse which had remained challenging due to technological limitations. Here we applied 3-dimensional minimal flux optical nanoscopy to mouse IHC synapses to chart the position of key pre- and postsynaptic proteins with single digit nanometre resolution of imaging. We demonstrate that nanoclusters of channels and interacting proteins govern the topography of AZs and postsynaptic densities (PSDs). We count synaptic proteins, their nanoclusters and determine their spatial organization feeding into computational modelling of AZ function. In conclusion, this study reveals a nanocluster-based molecular AZ and PSD topography, likely serving as functional modules in synaptic sound encoding.

neuroscience↗

bioRxiv2025

Utilizing CNNs for classification and uncertainty quantification for 15 families of European fly pollinators

Pollination is essential for maintaining biodiversity and ensuring food security, and in Europe it is primarily mediated by four insect orders (Coleoptera, Diptera, Hymenoptera, Lepidoptera). However, traditional monitoring methods are costly and time consuming. Although recent automation efforts have focused on butterflies and bees, flies, a diverse and ecologically important group of pollinators, have received comparatively little attention, likely due to the challenges posed by their subtle morphological differences. In this study, we investigate the application of Convolutional Neural Networks (CNNs) for classifying 15 European pollinating fly families and quantifying the associated classification uncertainty. Our dataset comprises a wide range of morphological and phylogenetic features, such as wing venation patterns and wing shapes. We evaluated the performance of three state-of-the-art CNN architectures, ResNet18, MobileNetV3, and EfficientNetB4, and demonstrate their effectiveness in accurately distinguishing fly families. In particular, EfficientNetB4 achieved an overall accuracy of up to 95.61%. Furthermore, cropping images to the bounding boxes of the Diptera not only improved classification accuracy but also increased prediction confidence, reducing misclassifications among families. This approach represents a significant advance in automated pollinator monitoring and has promising implications for both scientific research and practical applications.

ecology↗

bioRxiv2025

FlickerPrint: An Analysis Package for Measuring Interfacial Tension and Bending Rigidity of Biomolecular Condensates and Vesicles at Scale

1 In BriefWilliamson, Law et. al. present FlickerPrint, a computational analysis tool which can be used for measuring the interfacial tension and bending rigidity of soft fluctuating bodies, including biomolecular condensates, droplets or vesicles, from confocal microscopy images using flicker spectroscopy. This method is highly scalable so can be used to analyse the properties of whole populations of thousands of such soft bodies. 2 MotivationBiomolecular condensates play fundamental roles in sub-cellular organisation and it is well-known that the composition of condensates can affect their function. Measuring the conden-sates mechanical properties (for example, interfacial tension and bending rigidity) can aid the understanding of their biomolecular composition and cellular functions. However, measuring the properties of individual condensates under physiological conditions is very challenging and cum-bersome to scale to the population level using traditional methods. To overcome these issues, we have developed a software package to run flicker spectroscopy analysis of condensates at scale, to determine their interfacial tension and bending rigidity. At the same time, FlickerPrint can be harnessed to analyse other soft, fluctuating bodies such as lipid vesicles. 3 SummaryAccurate measurement of the mechanical properties of biomolecular condensates is an essential step in understanding their behaviour within cells. We present FlickerPrint, an open-source Python package to determine the interfacial tension and bending rigidity of thousands of biomolecular condensates using flicker spectroscopy by analysing their shape fluctuations in confocal microscopy images. We detail the workflow used by FlickerPrint to scale up these individual measurements to the population level and the computational requirements to run Flicker-Print. We provide examples of experiments in live cells and in vitro which are suitable for analysis with FlickerPrint as well as scenarios where the package cannot be used. Using these examples, we show that the results obtained from the analysis are robust to changes in the imaging setup, including frame rate. This implementation enables a step-change in the capability to measure two key properties of biomolecular condensates, the interfacial tension and bending rigidity. Moreover, the tools in FlickerPrint are also applicable for analysing other soft, fluctuating bodies, which we demonstrate here using vesicles.

cell biology↗

bioRxiv2024

Developmental control of E-cadherin junctions by mechanical contractility in Drosophila embryos

Adherens junctions are very plastic structures that change their composition and structure depending on the state of the epithelial tissue, involving mechanical stress and tissue dynamics. In Drosophila embryos, adherens junctions mature only during gastrulation following their formation a few minutes before during cellularization. Although the developmental maturation is obvious during gastrulation, the factors and conditions controlling it have remained unclear. Here, we assay the levels, distribution pattern, and mobility of E-cadherin during Drosophila gastrulation. Indicating a maturation, we find an increase in total levels at junctions and a drop in the mobile fraction of E-cadherin molecules. Both developmental changes depend on Myo-II contractility. Consistent with stereotypic Myo-II regulation, we find that interference with Rho signaling leads to corresponding changes in E-cadherin levels and mobility, at least in part. Besides Rho signaling, Src42A contributes to junction maturation, as tested by both loss-function and gain-of-function situations. Together, we demonstrate developmental maturation of adherens junctions and identify Rho signaling and Src42A as upstream regulatory pathways.

developmental biology↗

bioRxiv2024

Slow kinesin-dependent microtubular transport facilitates ribbon synapse assembly in developing cochlear inner hair cells

Sensory synapses are characterized by electron-dense presynaptic specializations, so-called synaptic ribbons. In cochlear inner hair cells (IHCs), ribbons play an essential role as core active zone (AZ) organizers, where they tether synaptic vesicles, cluster calcium channels and facilitate the temporally-precise release of primed vesicles. While a multitude of studies aimed to elucidate the molecular composition and function of IHC ribbon synapses, the developmental formation of these signalling complexes remains largely elusive to date. To address this shortcoming, we performed long-term live-cell imaging of fluorescently-labelled ribbon precursors in young postnatal IHCs to track ribbon precursor motion. We show that ribbon precursors utilize the apico-basal microtubular (MT) cytoskeleton for targeted trafficking to the presynapse, in a process reminiscent of slow axonal transport in neurons. During translocation, precursor volume regulation is achieved by highly dynamic structural plasticity - characterized by regularly-occurring fusion and fission events. Pharmacological MT destabilization negatively impacted on precursor translocation and attenuated structural plasticity, whereas genetic disruption of the anterograde molecular motor Kif1a impaired ribbon volume accumulation during developmental maturation. Combined, our data thus indicate an essential role of the MT cytoskeleton and Kif1a in adequate ribbon synapse formation and structural maintenance.

neuroscience↗

bioRxiv2024

Near-optimal information relay by the neuronal population of layer 4 barrel cortex

Sixty years after the concept of population coding in neuronal networks was introduced, we still lack a comprehensive understanding of its performance limits and the role of neuronal physiology. Here, we use dynamic gain analysis in a general model of population coding and demonstrate that disparate parameters of neurons and populations determine how accurately they can encode information. These are cell number, cell size, and the correlation time of the background noise. We experimentally test and confirm these predictions on neurons of excitatory populations in the mouse barrel cortex. Surprisingly, dendrite size and background correlations are precisely matched with the number of neurons in layer 4, such that even a single thalamocortical spike at the input is reliably reflected in the population output. However, this encoding performance can be modulated by the channels that mediate M-current, suggesting that coding in layer 4 may vary as a function of brain state.

neuroscience↗

bioRxiv2023

Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism

Memory formation is usually associated with Hebbian learning, using synaptic plasticity to change the synaptic strengths but omitting structural changes. Recent work suggests that structural plasticity can also lead to silent memory engrams, reproducing a conditioned learning paradigm with neuron ensembles. However, this work is limited by its way of synapse formation, enabling the formation of only one memory engram. Overcoming this, our model allows the formation of many engrams simultaneously while retaining high neurophysiological accuracy, e.g., as found in cortical columns. We achieve this by substituting the random synapse formation with the Model of Structural Plasticity (Butz and van Ooyen, 2013). As a homeostatic model, neurons regulate their activity by growing and pruning synaptic elements based on their current activity. Utilizing synapse formation based on the Euclidean distance between the neurons with a scalable algorithm allows us to easily simulate 4 million neurons with 343 memory engrams. These engrams do not interfere with one another by default, yet we can change the simulation parameters to form long-reaching associations. Our model paves the way for simulations addressing further inquiries, ranging from memory chains and hierarchies to complex memory systems comprising areas with different learning mechanisms.

neuroscience↗

bioRxiv2023

Polychaetoid/ZO-1 strengthens cell junctions under tension while localizing differently than core adherens junction proteins

During embryonic development dramatic cell shape changes and movements re-shape the embryonic body plan. These require robust but dynamic linkage between the cell-cell adherens junctions and the force-generating actomyosin cytoskeleton. Our view of this linkage has evolved, and we now realize linkage is mediated by a mechanosensitive multiprotein complex assembled via multivalent connections. Here we combine genetic, cell biological and modeling approaches to define the mechanism of action and functions of an important player, Drosophila Polychaetoid, homolog of mammalian ZO-1. Our data reveal that Pyd reinforces cell junctions under elevated tension, and facilitates cell rearrangements. Pyd is important to maintain junctional contractility and in its absence cell rearrangements stall. We next use structured illumination microscopy to define the molecular architecture of cell-cell junctions during these events. The cadherin-catenin complex and Cno both localize to puncta along the junctional membrane, but are differentially enriched in different puncta. Pyd, in contrast, exhibits a distinct localization to strands that extend out from the region occupied by core junction proteins. We then discuss the implications for the protein network at the junction-cytoskeletal interface, suggesting different proteins localize and function in distinct ways but combine to produce robust connections.

cell biology↗

bioRxiv2022

Boosting of neural circuit chaos at the onset of collective oscillations

Neuronal spiking activity in cortical circuits is often temporally structured by collective rhythms. Rhythmic activity has been hypothesized to regulate temporal coding and to mediate the flexible routing of information flow across the cortex. Spiking neuronal circuits, however, are non-linear systems that, through chaotic dynamics, can amplify insignificant microscopic fluctuations into network-scale response variability. In nonlinear systems in general, rhythmic oscillatory drive can induce chaotic behavior or boost the intensity of chaos. Thus, neuronal oscillations could rather disrupt than facilitate cortical coding functions by flooding the finite population bandwidth with chaotically-boosted noise. Here we tackle a fundamental mathematical challenge to characterize the dynamics on the attractor of effectively delayed network models. We find that delays introduce a transition to collective oscillations, below which ergodic theory measures have a stereotypical dependence on the delay so far only described in scalar systems and low-dimensional maps. We demonstrate that the emergence of internally generated oscillations induces a complete dynamical reconfiguration, by increasing the dimensionality of the chaotic attractor, the speed at which nearby trajectories separate from one another, and the rate at which the network produces entropy. We find that periodic input drive leads to a dramatic increase of chaotic measures at a the resonance frequency of the recurrent network. However, transient oscillatory input only has a moderate role on the collective dynamics. Our results suggest that simple temporal dynamics of the mean activity can have a profound effect on the structure of the spiking patterns and therefore on the information processing capability of neuronal networks.

neuroscience↗

bioRxiv2022

Towards 3D-bioprinting of osseous tissue of pre-defined shape using single-matrix cell-bioink constructs

Engineering living bone tissue of defined shape on-demand has remained a challenge. 3D-bioprinting (3DBP), a biofabrication process capable of yielding cell constructs of defined shape, when combined with developmental engineering can provide a possible path forward. Through the development of a bioink possessing appropriate rheological properties to carry a high cell load and concurrently yield physically stable structures, printing of stable, cell-laden, single-matrix constructs of anatomical shapes was realized without the need for fugitive or support phases. Using this bioink system, constructs of hypertrophic cartilage of predesigned geometry were engineered in vitro by printing human MSCs at a high density to drive spontaneous condensation and implanted in nude mice to evoke endochondral ossification. The implanted constructs retained their prescribed shape over a 12-week period and underwent remodeling to yield ossicles of the designed shape with neovascularization. Micro-CT, histological and immunohistochemistry assessments confirmed bone tissue characteristics and the presence of human cells. These results demonstrate the potential of 3DBP to fabricate complex bone tissue for clinical application.

bioengineering↗

bioRxiv2022

Dynamic gain decomposition reveals functional effects of dendrites, ion channels and input statistics in ultrafast population encoding

Modern, high-density neuronal recordings reveal at ever higher precision how information is represented by neural populations. Still, we lack the tools to understand these processes bottom-up, emerging from the biophysical properties of neurons, synapses, and network structure. The concept of the dynamic gain function, a spectrally resolved approximation of a populations coding capability, has the potential to link cell-level properties to network-level performance. However, the concept is not only useful but also very complex because the dynamic gains shape is co-determined by axonal and somatodendritic parameters and the populations operating regime. Previously, this complexity precluded an understanding of any individual parameters impact. Here, we decomposed the dynamic gain function into three components corresponding to separate signal transformations. This allowed attribution of network-level encoding features to specific cell-level parameters. Applying the method to data from real neurons and biophysically plausible models, we found: 1. The encoding bandwidth of real neurons, approximately 400 Hz, is constrained by the voltage dependence of axonal currents during early action potential initiation. 2. State-of-the-art models only achieve encoding bandwidths around 100 Hz and are limited mainly by subthreshold processes instead. 3. Large dendrites and low-threshold potassium currents modulate the bandwidth by shaping the subthreshold stimulus-to-voltage transformation. Our decomposition provides physiological interpretations when the dynamic gain curve changes, for instance during spectrinopathies and neurodegeneration. By pinpointing shortcomings of current models, it also guides inference of neuron models best suited for large-scale network simulations. Significant StatementThe dynamic gain function quantifies how neurons can engage in collective, network-level activity, shape brain rhythms and information encoding. Its shape results from a complex interaction between properties of different molecules (ion channels) and cell compartments (morphology, resistance), and is so far only understood for the simplest neuron models. Here we provide an interpretable analysis, decomposing the dynamic gain based on the stimulus transformation steps in individual neurons. We apply the decomposition to data from real neurons and complex models, and attribute changes of the dynamic gain to specific sub- and suprathreshold processes. Using this decomposition method, we reveal the relevance of subthreshold potassium channels for ultrafast information encoding and expose the shortcomings of even the state-of-the-art neuron models.

neuroscience↗