Biology subjects

Grewe, J.

Publications and source records attributed to Grewe, J..

9 recordsLinked to original sources

bioRxiv2026

Modelling individual ampullary afferents in two species of gymnotiform fish using simulation-based inference

Ampullary electroreceptors are widespread across aquatic vertebrates. The purpose of sensing exogeneous electric fields is conserved across species but the implementations differ and the encoding mechanisms remain incompletely understood. We compared baseline and stimulus-driven response properties of ampullary electroreceptor afferents in the weakly electric fish Apteronotus leptorhynchus and Eigenmannia virescens. We find that their activity is very well captured by an extended leaky integrate-and-fire model that generalizes across both species. The model shares similarities to a previous model of the tuberous electroreceptor afferents but further incorporates a low-pass pre-filtering and additional noise sources to reproduce the observed spectral response characteristics. The low-pass is essential to shape stimulus encoding in the high-frequency range. Accurate prediction of low-frequency stimulus encoding further requires two distinct noise sources: stimulus-independent white current noise and activity-dependent noise in the adaptation current, which is shaped by the adaptation time constant to yield pink noise dynamics. Using simulation-based inference, we trained a neural network to map model parameters to neuronal response features. This approach enables the generation of heterogeneous, biologically plausible model populations that may serve as a realistic input layer for studying neuronal processing on the next level. With this, we provide a unified and mechanistic model of ampullary electroreceptor encoding in these species and possibly beyond. The proposed model is another step towards a full model of the electrosensory periphery in these animals. Author summaryThe ability to sense exogenous electric fields, i.e. passive electroreception, is widespread among aquatic animals. It plays a central role in prey detection and, in some species, also contributes to communication. To understand higher-order brain function, we also need to grasp the sensory periphery and ideally have models that provide naturalistic peripheral responses. Using simulation-based inference (SBI), we here develop a mechanistic model of passive electroreception that is valid for at least two species of electric fish. Through detailed analyses, we identify model components, such as a source of pink noise, that are essential for matching the models spectral response properties to those of the recorded cells. The main results of this work are the model itself and the trained inference network (here called the SBI network), which can now be used to create artificial but biologically plausible populations of sensory neurons that may serve as a realistic input layer for studying higher-order neuronal processing. Our work complements the existing models of the active electric sense and is a big step towards a full model of the electrosensory periphery in these animals.

neuroscience↗

bioRxiv2024

Weakly nonlinear responses at low intrinsic noise levels in two types of electrosensory primary afferents

Spiking thresholds in neurons or rectification at synapses are essential for neuronal computations rendering neuronal processing inherently nonlinear. Nevertheless, linear response theory has been instrumental for understanding, for example, the impact of noise or neuronal synchrony on signal transmission, or the emergence of oscillatory activity, but is valid only at low stimulus amplitudes or large levels of intrinsic noise. At higher signal-to-noise ratios, however, nonlinear response components become relevant. Theoretical results for leaky integrate-and-fire neurons in the weakly nonlinear regime suggest strong responses at the sum of two input frequencies if one of these frequencies or their sum match the neurons baseline firing rate. We here analyze nonlinear responses in two types of primary electroreceptor afferents, the P-units of the active and the ampullary cells of the passive electrosensory system of the wave-type electric fish Apteronotus leptorhynchus of either sex. In our combined experimental and modeling approach we identify these predicted nonlinear responses in those 31 out of 172 P-units that are characterized by low intrinsic noise. In contrast, the majority (22 out of 30) ampullary cells show nonlinear responses. Our results provide experimental evidence for nonlinear responses of spike generators in the weakly nonlinear regime. We conclude that such nonlinear responses occur in any sensory neuron that operates in similar regimes particularly at near-threshold stimulus conditions. Significance statementThe generation of action potentials involves a strong threshold nonlinearity. Nevertheless, the encoding of stimuli with small amplitudes by neurons with sufficient intrinsic noise can be well described as a linear system. As the stimulus amplitude is increased, new spectral components start to appear in the so called weakly nonlinear regime. Theory predicts nonlinear interactions whenever one or the sum of two stimulus frequencies matches the neurons baseline firing rate. Indeed, we find these interactions in a large set of electrophysiological recordings from primary electroreceptive afferents of a weakly electric fish. The non-linear response components could boost sensory responses to weak signals emitted, for example, by distant conspecifics.

neuroscience↗

bioRxiv2024

Bursts boost nonlinear encoding in electroreceptor afferents

Nonlinear mechanisms are at the heart of neuronal information processing, for example to fire an action potential, the membrane voltage must exceed a threshold nonlinearity. Even though, linear encoding schemes are commonly used and often successfully describe large parts of sensory encoding nonlinear mechanisms such as thresholds and saturations are well known to be crucial to encode behaviorally relevant features in the stimulus space not captured by linear methods. Here we analyze the role of bursts in p-type electroreceptor afferents (P-units) in the weakly electric fish Apteronotus leptorhynchus. It is long known that subpopulations of these cells fire bursts of action potentials while others do not. Previous research suggests, that the non-bursting cells are better at encoding the stimulus time-course while bursting neurons are better suited to encode special features in the stimulus. We here show, based on the analysis of experimental data and modeling, that bursts affect the linear as well as the nonlinear encoding. Theoretical work predicts that in simple leaky-integrate-and-fire model neurons, two periodic stimuli interact nonlinearly when the sum of the two frequencies matches the neurons baseline firing rate as quantified by the second-order susceptibility. Indeed, such nonlinear responses have been found in non-bursting P-units when stimulated by two beats simultaneously but only in those cells, that exhibit very low levels of intrinsic noise. In this study, we found that bursts strongly enhance these nonlinear responses which may play a critical role in the detection of weak intruder signals in the presence of a strong female signal, i.e. an electrosensory cocktail party.

neuroscience↗

bioRxiv2023

Receptive field sizes and neuronal encoding bandwidth are constrained by axonal conduction delays.

Studies on population coding implicitly assume that spikes from the presynaptic population arrive simultaneously at the integrating neuron. In natural neuronal populations, this is usually not the case -- neuronal signalling takes time and neuronal populations cover a certain space. The spread of spike arrival times depends on population size, cell density and axonal conduction velocity. We here analyze the consequences of population size and axonal conduction delays on the stimulus encoding performance in the electrosensory system of the electric fish Apteronotus leptorhynchus. We experimentally locate p-type electroreceptor afferents along the rostro-caudal body axis and relate locations to neurophysiological response properties. In an information-theoretical approach we analyze the coding performance in homogeneous and heterogeneous populations. As expected, the amount of information increases with population size and, on average, heterogeneous populations encode better than the average same-size homogeneous population if conduction delays are compensated for. The spread of neuronal conduction delays within a receptive field strongly degrades encoding of high-frequency stimulus components. Receptive field sizes typically found in the electrosensory lateral line lobe of A. leptorhynchus appear to be a good compromise between the spread of conduction delays and encoding performance. The limitations imposed by finite axonal conduction velocity are relevant for any converging network as is shown by model populations of LIF neurons. The bandwidth of natural stimuli and the maximum meaningful population sizes are constrained by conduction delays and may thus impact the optimal design of nervous systems. Author summaryReading out the activity of a population of neurons can yield a more complete picture of the stimulus space. Generally, increasing population sizes increases the amount of information. This applies to homogeneous populations of similarly tuned neurons as well as heterogeneous populations. So far studies on population coding assumed the information to reach the integrating neuron simultanously. But neurons are neither disembodied nor does neuronal signalling happen instantaneously; populations cover a certain space and axonal conduction takes time. The interplay of encoding bandwidth, receptive field respectively population size and axonal conduction velocity has not been addressed before. Our results from the electrosensory system and of model simulations show that stimulus dynamics, receptive field sizes, and conduction velocity have to be factored in when we want to understand the design of nervous systems.

neuroscience↗

bioRxiv2022

Beat encoding at mistuned octaves within single sensory neurons

Beats are periodic amplitude modulations resulting from the superposition of two spectrally close periodic signals, where the difference between the two signal frequencies defines the frequency of the beat. Such amplitude modulations are known to be well encoded in corresponding firing rate modulations in auditory fibers as well as in electrosensory afferents. In a field study we showed the behavioral relevance of beat-like amplitude modulations exceeding spectrally close interactions in electric fish. Thus, we here study the encoding of beat-like waveforms over a wide range of difference frequencies in the electrosensory system of Apteronotus leptorhynchus. Contrary to expectations from the previously measured beat tuning, the activity of p-type electroreceptor afferents follows a repetitive pattern with slow modulations of their firing rate reoccurring around multiples of the frequency of the carrier signal. Mathematical reasoning supported by simulations of modified integrate-and-fire models reveals that neither Hilbert transform, squaring, harmonics of the carrier, half-wave rectification, nor the threshold-non-linearity of a spike generator are sufficient to extract slow beating signal envelopes around the octave of the carrier. Rather, a threshold operation smoothed out by exponentiation with a power of three is needed prior to spike generation to explain the repetitive occurrence of slow signal envelopes and electroreceptor responses. Our insights suggest the synapses of inner hair cells as candidate mechanisms underlying the perception of beats at mistuned octaves that has been described by Georg Simon Ohm, Hermann Helmholtz, and others already in the 19th century.

neuroscience↗

bioRxiv2021

Nonmuscle myosin IIA dynamically guides regulatory light chain phosphorylation and assembly of nonmuscle myosin IIB

Nonmuscle myosin II minifilaments have emerged as central elements for force generation and mechanosensing by mammalian cells. Each minifilament can have a different composition and activity due to the existence of the three nonmuscle myosin II isoforms A, B and C and their respective phosphorylation pattern. We have used CRISPR/Cas9-based knockout cells, quantitative image analysis and mathematical modelling to dissect the dynamic processes that control the formation and activity of heterotypic minifilaments and found a strong asymmetry between isoforms A and B. Loss of NM IIA completely abrogates regulatory light chain phosphorylation and reduces the level of assembled NM IIB. Activated NM IIB preferentially co-assembles into pre-formed NM IIA minifilaments and stabilizes the filament in a force-dependent mechanism. NM IIC is only weakly coupled to these processes. We conclude that NM IIA and B play clearly defined complementary roles during assembly of functional minifilaments. NM IIA is responsible for the formation of nascent pioneer minifilaments. NM IIB incorporates into these and acts as a clutch that limits the force output to prevent excessive NM IIA activity. Together these two isoforms form a balanced system for regulated force generation.

cell biology↗

bioRxiv2020

Distinct roles of nonmuscle myosin II isoforms for establishing tension and elasticity during cell morphogenesis

Nonmuscle myosin II (NM II) is an integral part of essential cellular processes, including adhesion and migration. Mammalian cells express up to three isoforms termed NM IIA, B, and C. We used U2OS cells to create CRISPR/Cas9-based knockouts of all three isoforms and analyzed the phenotypes on homogeneous substrates, in collagen gels, and on micropatterned substrates. We find that NM IIA is essential to build up cellular tension during initial stages of force generation, while NM IIB is necessary to elastically stabilize NM IIA-generated tension. A scale-bridging mathematical model explains our observations by relating actin fiber stability to the molecular rates of the myosin crossbridge cycle. A dynamic cell stretch/release experiment confirms these predictions and in addition reveals a novel role for NM IIC, namely the ability to establish tensional homeostasis.

biophysics↗

bioRxiv2017

Simultaneous spike-time locking to multiple frequencies

Phase locking of neural firing is ubiquitously observed in the brain and occurs when neurons fire at a particular phase of a periodic signal. Here we study in detail how spikes of single neurons can simultaneously lock to multiple distinct frequencies at the example of p-type electroreceptor afferents in the electrosensory system of the Gymnotiform weakly electric fish Apteronotus leptorhynchus. We identify key elements for multiple frequency locking, study its determining factors and limits, and provide concise mathematical models reproducing our main findings. Our findings provide another example how rate and temporal codes can coexist and complement each other in single neurons, and demonstrate that sensory coding in p-type electroreceptor afferents provides a much richer representation of the sensory environment than commonly assumed. Since the underlying mechanisms are not specific to the electrosensory system, our results could provide the basis for studying multiple-frequency locking in other systems.

neuroscience↗

bioRxiv2017

Court and spark in the wild: communication at the limits of sensation

Sensory systems evolve in the ecological niches each species is occupying. Accordingly, the tuning of sensory neurons is expected to be adapted to the statistics of natural stimuli. For an unbiased quantification of sensory scenes we tracked natural communication behavior of the weakly electric fish Apteronotus rostratus in their Neotropical rainforest habitat with high spatio-temporal resolution over several days. In the context of courtship and aggression we observed large quantities of electrocommunication signals. Echo responses and acknowledgment signals clearly demonstrated the behavioral relevance of these signals. The known tuning properties of peripheral electrosensory neurons suggest, however, that they are barely activated by these obviously relevant signals. Frequencies of courtship signals are clearly mismatched with the frequency tuning of neuronal population activity. Our results emphasize the importance of quantifying sensory scenes derived from freely behaving animals in their natural habitats for understanding the evolution and function of neural systems.

neuroscience↗