Beat encoding at mistuned octaves within single electrosensory neurons.

Beats are slow periodic amplitude modulations resulting from the superposition of two spectrally close periodic signals. The difference frequency between the signals sets the frequency of the beat. A field study in the electric fish Apteronotus rostratus showed the behavioral relevance of very high difference frequencies. Contrary to expectations from previous studies, our electrophysiological data show strong responses of p-type electroreceptor afferents whenever the difference frequency approaches integer multiples (mistuned octaves) of the fish's own electric field frequency (carrier). Mathematical reasoning and simulations show that common approaches to extract amplitude modulations, such as Hilbert transform or half-wave rectification, are not sufficient to explain the responses at carrier octaves. Instead, half-wave rectification needs to be smoothed out, for example by a cubic function. Because electroreceptive afferents share many properties with auditory nerve fibers, these mechanisms may underly the human perception of beats at mistuned octaves as described by Ohm and Helmholtz.

Loss or gain of function? Effects of ion channel mutations on neuronal firing depend on the neuron type.

Introduction: Clinically relevant mutations to voltage-gated ion channels, called channelopathies, alter ion channel function, properties of ionic currents, and neuronal firing. The effects of ion channel mutations are routinely assessed and characterized as loss of function (LOF) or gain of function (GOF) at the level of ionic currents. However, emerging personalized medicine approaches based on LOF/GOF characterization have limited therapeutic success. Potential reasons are among others that the translation from this binary characterization to neuronal firing is currently not well-understood-especially when considering different neuronal cell types. In this study, we investigate the impact of neuronal cell type on the firing outcome of ion channel mutations. Methods: To this end, we simulated a diverse collection of single-compartment, conductance-based neuron models that differed in their composition of ionic currents. We systematically analyzed the effects of changes in ion current properties on firing in different neuronal types. Additionally, we simulated the effects of known mutations in KCNA1 gene encoding the KV1.1 potassium channel subtype associated with episodic ataxia type 1 (EA1). Results: These simulations revealed that the outcome of a given change in ion channel properties on neuronal excitability depends on neuron type, i.e., the properties and expression levels of the unaffected ionic currents. Discussion: Consequently, neuron-type specific effects are vital to a full understanding of the effects of channelopathies on neuronal excitability and are an important step toward improving the efficacy and precision of personalized medicine approaches.

Stimulator compensation and generation of Gaussian noise stimuli with defined amplitude spectra for studying input-output relations of sensory systems.

Gaussian noise is an important stimulus for the study of biological systems, especially sensory and neural systems. Since these systems are inherently nonlinear, the properties of the noise strongly influence the outcome of the analysis. Therefore, it is crucial to use a well-defined and controlled noise stimulus. In this paper, we first use the example of an insect filiform sensillum, a simple mechanoreceptor with a single sensory cell, to show that changes in the amplitude and spectral properties of the noise stimulus indeed affect the linear transfer function of the sensillum. We then explain step-by-step how to use the inverse fast Fourier transform to generate a Gaussian noise that has an arbitrary user-defined amplitude spectrum, including a band-limited white noise with a perfectly sharp cutoff edge. Finally, we demonstrate how such a perfect band-limited Gaussian white noise stimulus can also be generated with a non-perfect stimulator using a simple procedure that compensates for the filtering properties of the stimulator. With this approach, one can generate well-defined Gaussian noise stimuli that can be adapted to any application. For example, one can generate visual, sound, or vibrational stimuli for experimental research in visual physiology, auditory physiology, and biotremology, as well as inputs for testing various models in theoretical research.

Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings.

Recent technological advances greatly improved the possibility to study freely behaving animals in natural conditions. However, many systems still rely on animal-mounted devices, which can already bias behavioral observations. Alternatively, animal behaviors can be detected and tracked in recordings of stationary sensors, e.g., video cameras. While these approaches circumvent the influence of animal-mounted devices, identification of individuals is much more challenging. We take advantage of the individual-specific electric fields electric fish generate by discharging their electric organ (EOD) to record and track their movement and communication behaviors without interfering with the animals themselves. EODs of complete groups of fish can be recorded with electrode arrays submerged in the water and then be tracked for individual fish. Here, we present an improved algorithm for tracking electric signals of wave-type electric fish. Our algorithm benefits from combining and refining previous approaches of tracking individual specific EOD frequencies and spatial electric field properties. In this process, the similarity of signal pairs in extended data windows determines their tracking order, making the algorithm more robust against detection losses and intersections. We quantify the performance of the algorithm and show its application for a data set recorded with an array of 64 electrodes distributed over a 12 m2 section of a stream in the Llanos, Colombia, where we managed, for the first time, to track Apteronotus leptorhynchus over many days. These technological advances make electric fish a unique model system for a detailed analysis of social and communication behaviors, with strong implications for our research on sensory coding.

Dravet Variant SCN1A A1783V Impairs Interneuron Firing Predominantly by Altered Channel Activation.

Dravet syndrome (DS) is a developmental epileptic encephalopathy mainly caused by functional NaV1.1 haploinsufficiency in inhibitory interneurons. Recently, a new conditional mouse model expressing the recurrent human p.(Ala1783Val) missense variant has become available. In this study, we provided an electrophysiological characterization of this variant in tsA201 cells, revealing both altered voltage-dependence of activation and slow inactivation without reduced sodium peak current density. Based on these data, simulated interneuron (IN) firing properties in a conductance-based single-compartment model suggested surprisingly similar firing deficits for NaV1.1A1783V and full haploinsufficiency as caused by heterozygous truncation variants. Impaired NaV1.1A1783V channel activation was predicted to have a significantly larger impact on channel function than altered slow inactivation and is therefore proposed as the main mechanism underlying IN dysfunction. The computational model was validated in cortical organotypic slice cultures derived from conditional Scn1a A1783V mice. Pan-neuronal activation of the p.Ala1783V in vitro confirmed a predicted IN firing deficit and revealed an accompanying reduction of interneuronal input resistance while demonstrating normal excitability of pyramidal neurons. Altered input resistance was fed back into the model for further refinement. Taken together these data demonstrate that primary loss of function (LOF) gating properties accompanied by altered membrane characteristics may match effects of full haploinsufficiency on the neuronal level despite maintaining physiological peak current density, thereby causing DS.

Therapeutic Potential of Sodium Channel Blockers as a Targeted Therapy Approach in KCNA1-Associated Episodic Ataxia and a Comprehensive Review of the Literature.

Introduction: Among genetic paroxysmal movement disorders, variants in ion channel coding genes constitute a major subgroup. Loss-of-function (LOF) variants in KCNA1, the gene coding for KV1.1 channels, are associated with episodic ataxia type 1 (EA1), characterized by seconds to minutes-lasting attacks including gait incoordination, limb ataxia, truncal instability, dysarthria, nystagmus, tremor, and occasionally seizures, but also persistent neuromuscular symptoms like myokymia or neuromyotonia. Standard treatment has not yet been developed, and different treatment efforts need to be systematically evaluated. Objective and Methods: Personalized therapeutic regimens tailored to disease-causing pathophysiological mechanisms may offer the specificity required to overcome limitations in therapy. Toward this aim, we (i) reviewed all available clinical reports on treatment response and functional consequences of KCNA1 variants causing EA1, (ii) examined the potential effects on neuronal excitability of all variants using a single compartment conductance-based model and set out to assess the potential of two sodium channel blockers (SCBs: carbamazepine and riluzole) to restore the identified underlying pathophysiological effects of KV1.1 channels, and (iii) provide a comprehensive review of the literature considering all types of episodic ataxia. Results: Reviewing the treatment efforts of EA1 patients revealed moderate response to acetazolamide and exhibited the strength of SCBs, especially carbamazepine, in the treatment of EA1 patients. Biophysical dysfunction of KV1.1 channels is typically based on depolarizing shifts of steady-state activation, leading to an LOF of KCNA1 variant channels. Our model predicts a lowered rheobase and an increase of the firing rate on a neuronal level. The estimated concentration dependent effects of carbamazepine and riluzole could partially restore the altered gating properties of dysfunctional variant channels. Conclusion: These data strengthen the potential of SCBs to contribute to functional compensation of dysfunctional KV1.1 channels. We propose riluzole as a new drug repurposing candidate and highlight the role of personalized approaches to develop standard care for EA1 patients. These results could have implications for clinical practice in future and highlight the need for the development of individualized and targeted therapies for episodic ataxia and genetic paroxysmal disorders in general.

Electrocommunication signals indicate motivation to compete during dyadic interactions of an electric fish.

Animals across species compete for limited resources. Whereas in some species competition behavior is solely based on the individual's own abilities, other species assess their opponents to facilitate these interactions. Using cues and communication signals, contestants gather information about their opponent, adjust their behavior accordingly, and can thereby avoid high costs of escalating fights. We tracked electrocommunication signals known as 'rises' and agonistic behaviors of the gymnotiform electric fish Apteronotus leptorhynchus in staged competition experiments. A larger body size relative to the opponent was the sole significant predictor for winners. Sex and the frequency of the continuously emitted electric field only mildly influenced competition outcome. In males, correlations of body size and winning were stronger than in females and, especially when losing against females, communication and agonistic interactions were enhanced, suggesting that males are more motivated to compete. Fish that lost competitions emitted the majority of rises, but their quantity depended on the competitors' relative size and sex. The emission of a rise could be costly since it provoked ritualized biting or chase behaviors by the other fish. Despite winners being accurately predictable based on the number of rises after the initial 25 min, losers continued to emit rises. The number of rises emitted by losers and the duration of chase behaviors depended in similar ways on physical attributes of contestants. Detailed evaluation of these correlations suggests that A. leptorhynchus adjusts its competition behavior according to mutual assessment, where rises could signal a loser's motivation to continue assessment through ritualized fighting.

Neural adaptation.

The term 'neural adaptation' refers to the common phenomenon of decaying neuronal activities in response to repeated or prolonged stimulation. Many different roles of adaptation in neural computations have been discussed. On a single-cell level adaptation introduces a high-pass filter operation as a basic element for predictive coding. Interactions of adaptation processes with nonlinearities are key to many more computations including generation of invariances, stimulus selectivity, denoising, and sparsening. Neural adaptation is observed all the way along neuronal pathways from the sensory periphery to the motor output and adaptation usually gets stronger at higher levels. Non-adapting neurons or neurons that increase their sensitivity are rare exceptions. What computations arise by repeated adaptation mechanisms along a processing pathway? After giving some background on neural adaptation, underlying mechanisms, dynamics, and resulting filter properties, I will discuss computational properties of four examples of serial and parallel adaptation processes, demonstrating that adaptation acts together with other mechanisms, in particular threshold nonlinearities, to eventually compute meaningful perceptions. Python code and further details of the simulations illustrating this primer are available at https://github.com/janscience/adaptationprimer.

Simultaneous spike-time locking to multiple frequencies.

Locking of neural firing is ubiquitously observed in the brain and occurs when neurons fire at a particular phase or in synchronization with an external signal. Here we study in detail the locking of single neurons to multiple distinct frequencies at the example of p-type electroreceptor afferents in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus (brown ghost knifefish). We find that electrosensory afferents and pyramidal cells in the electrosensory lateral line lobe (ELL) lock to multiple frequencies, including the electric organ discharge (EOD) frequency, beat, and stimulus itself. We identify key elements necessary for locking to multiple frequencies, study its limits, and provide concise mathematical models reproducing our main findings. Our findings provide another example of 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.NEW & NOTEWORTHY Locking of neuronal spikes to external and internal signals is a ubiquitous neurophysiological mechanism that has been extensively studied in several brain areas and species. Using experimental data from the electrosensory system and concise mathematical models, we analyze how a single neuron can simultaneously lock to multiple frequencies. Our findings demonstrate how temporal and rate codes can complement each other and lead to rich neuronal representations of sensory signals.

Tracking activity patterns of a multispecies community of gymnotiform weakly electric fish in their neotropical habitat without tagging.

Field studies on freely behaving animals commonly require tagging and often are focused on single species. Weakly electric fish generate a species- and individual-specific electric organ discharge (EOD) and therefore provide a unique opportunity for individual tracking without tagging. Here, we present and test tracking algorithms based on recordings with submerged electrode arrays. Harmonic structures extracted from power spectra provide fish identity. Localization of fish based on weighted averages of their EOD amplitudes is found to be more robust than fitting a dipole model. We apply these techniques to monitor a community of three species, Apteronotus rostratus, Eigenmannia humboldtii and Sternopygus dariensis, in their natural habitat in Darién, Panama. We found consistent upstream movements after sunset followed by downstream movements in the second half of the night. Extrapolations of these movements and estimates of fish density obtained from additional transect data suggest that some fish cover at least several hundreds of meters of the stream per night. Most fish, including E. humboldtii, were traversing the electrode array solitarily. From in situ measurements of the decay of the EOD amplitude with distance of individual animals, we estimated that fish can detect conspecifics at distances of up to 2 m. Our recordings also emphasize the complexity of natural electrosensory scenes resulting from the interactions of the EODs of different species. Electrode arrays thus provide an unprecedented window into the so-far hidden nocturnal activities of multispecies communities of weakly electric fish at an unmatched level of detail.

Dominance in Habitat Preference and Diurnal Explorative Behavior of the Weakly Electric Fish Apteronotus leptorhynchus.

Electrocommunication and -localization behaviors of weakly electric fish have been studied extensively in the lab, mostly by means of short-term observations on constrained fish. Far less is known about their behaviors in more natural-like settings, where fish are less constrained in space and time. We tracked individual fish in a population of fourteen brown ghost knifefish (Apteronotus leptorhynchus) housed in a large 2 m3 indoor tank based on their electric organ discharges (EOD). The tank contained four different natural-like microhabitats (gravel, plants, isolated stones, stacked stones). In particular during the day individual fish showed preferences for specific habitats which provided appropriate shelter. Male fish with higher EOD frequencies spent more time in their preferred habitat during the day, moved more often between habitats during the night, and less often during the day in comparison to low-frequency males. Our data thus revealed a link between dominance indicated by higher EOD frequency, territoriality, and a more explorative personality in male A. leptorhynchus. In females, movement activity during both day and night correlated positively with EOD frequency. In the night, fish of either sex moved to another habitat after about 6 s on average. During the day, the average transition time was also very short at about 20 s. However, these activity phases were interrupted by phases of inactivity that lasted on average about 20 min during the day, but only 3 min in the night. The individual preference for daytime retreat sites did not reflect the frequent explorative movements at night.

Neuronal mechanisms of mutations in SCN8A causing epilepsy or intellectual disability.

Ion channel mutations can cause distinct neuropsychiatric diseases. We first studied the biophysical and neurophysiological consequences of four mutations in the human Na+ channel gene SCN8A causing either mild (E1483K) or severe epilepsy (R1872W), or intellectual disability and autism without epilepsy (R1620L, A1622D). Only combined electrophysiological recordings of transfected wild-type or mutant channels in both neuroblastoma cells and primary cultured neurons revealed clear genotype-phenotype correlations. The E1483K mutation causing mild epilepsy showed no significant biophysical changes, whereas the R1872W mutation causing severe epilepsy induced clear gain-of-function biophysical changes in neuroblastoma cells. However, both mutations increased neuronal firing in primary neuronal cultures. In contrast, the R1620L mutation associated with intellectual disability and autism-but not epilepsy-reduced Na+ current density in neuroblastoma cells and expectedly decreased neuronal firing. Interestingly, for the fourth mutation, A1622D, causing severe intellectual disability and autism without epilepsy, we observed a dramatic slowing of fast inactivation in neuroblastoma cells, which induced a depolarization block in neurons with a reduction of neuronal firing. This latter finding was corroborated by computational modelling. In a second series of experiments, we recorded three more mutations (G1475R, M1760I, G964R, causing intermediate or severe epilepsy, or intellectual disability without epilepsy, respectively) that revealed similar results confirming clear genotype-phenotype relationships. We found intermediate or severe gain-of-function biophysical changes and increases in neuronal firing for the two epilepsy-causing mutations and decreased firing for the loss-of-function mutation causing intellectual disability. We conclude that studies in neurons are crucial to understand disease mechanisms, which here indicate that increased or decreased neuronal firing is responsible for distinct clinical phenotypes.

Statistics of Natural Communication Signals Observed in the Wild Identify Important Yet Neglected Stimulus Regimes in Weakly Electric Fish.

Sensory systems evolve in the ecological niches that each species is occupying. Accordingly, encoding of natural stimuli by sensory neurons is expected to be adapted to the statistics of these stimuli. For a direct quantification of sensory scenes, we tracked natural communication behavior of male and female weakly electric fish, Apteronotus rostratus, in their Neotropical rainforest habitat with high spatiotemporal resolution over several days. In the context of courtship, we observed large quantities of electrocommunication signals. Echo responses, acknowledgment signals, and their synchronizing role in spawning demonstrated the behavioral relevance of these signals. In both courtship and aggressive contexts, we observed robust behavioral responses in stimulus regimes that have so far been neglected in electrophysiological studies of this well characterized sensory system and that are well beyond the range of known best frequency and amplitude tuning of the electroreceptor afferents' firing rate modulation. Our results emphasize the importance of quantifying sensory scenes derived from freely behaving animals in their natural habitats for understanding the function and evolution of neural systems.SIGNIFICANCE STATEMENT The processing mechanisms of sensory systems have evolved in the context of the natural lives of organisms. To understand the functioning of sensory systems therefore requires probing them in the stimulus regimes in which they evolved. We took advantage of the continuously generated electric fields of weakly electric fish to explore electrosensory stimulus statistics in their natural Neotropical habitat. Unexpectedly, many of the electrocommunication signals recorded during courtship, spawning, and aggression had much smaller amplitudes or higher frequencies than stimuli used so far in neurophysiological characterizations of the electrosensory system. Our results demonstrate that quantifying sensory scenes derived from freely behaving animals in their natural habitats is essential to avoid biases in the choice of stimuli used to probe brain function.

Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations.

We compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) a homogeneous population whose units receive independent noise and ii) a deterministic heterogeneous population, where each unit exhibits a different baseline firing rate ('disorder'). Our criterion for making both sources of variability quantitatively comparable is that the interspike-interval distributions are identical for both systems. Numerical simulations using leaky integrate-and-fire neurons unveil that a non-zero amount of both noise or disorder maximizes the encoding efficiency of the homogeneous and heterogeneous system, respectively, as a particular case of suprathreshold stochastic resonance. Our findings thus illustrate that heterogeneity can render similarly profitable effects for neuronal populations as dynamic noise. The optimal noise/disorder depends on the system size and the properties of the stimulus such as its intensity or cutoff frequency. We find that weak stimuli are better encoded by a noiseless heterogeneous population, whereas for strong stimuli a homogeneous population outperforms an equivalent heterogeneous system up to a moderate noise level. Furthermore, we derive analytical expressions of the coherence function for the cases of very strong noise and of vanishing intrinsic noise or heterogeneity, which predict the existence of an optimal noise intensity. Our results show that, depending on the type of signal, noise as well as heterogeneity can enhance the encoding performance of neuronal populations.

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals.

Weakly electric fish learn both visual and electrosensory cues in a multisensory object discrimination task.

Weakly electric fish use electrosensory, visual, olfactory and lateral line information to guide foraging and navigation behaviors. In many cases they preferentially rely on electrosensory cues. Do fish also memorize non-electrosensory cues? Here, we trained individuals of gymnotiform weakly electric fish Apteronotus albifrons in an object discrimination task. Objects were combinations of differently conductive materials covered with differently colored cotton hoods. By setting visual and electrosensory cues in conflict we analyzed the sensory hierarchy among the electrosensory and the visual sense in object discrimination. Our experiments show that: (i) black ghost knifefish can be trained to solve discrimination tasks similarly to the mormyrid fish; (ii) fish preferentially rely on electrosensory cues for object discrimination; (iii) despite the dominance of the electrosense they still learn the visual cue and use it when electrosensory information is not available; (iv) fish prefer the trained combination of rewarded cues over combinations that match only in a single feature and also memorize the non-rewarded combination.

A single mechanism driving both inactivation and adaptation in rapidly adapting currents of DRG neurons?

Rapidly adapting (RA) currents expressed in dorsal root ganglia somatosensory neurons reduce their amplitude in response to prolonged and/or repeated mechanical stimulation. Both inactivation of mechanotransducer channels and adaptation of the force acting on the channels have been suggested to independently decrease RA currents. However, these two mechanisms have similar kinetics and dependence on calcium and voltage. These experimental findings suggest that a single mechanism might underlie both. We constructed a simple Hodgkin-Huxley-type model with a single gating variable driving both inactivation and adaptation to test this hypothesis. Predictions of the model successfully describe key features of mechanical activation as well as inactivation, adaptation, and recovery. The model thus supports the possibility of a single mechanism driving inactivation and adaptation in RA currents. On its own, the model can be integrated into higher-order models of touch receptors because of its accurate simulation of RA currents.

A neural mechanism for time-window separation resolves ambiguity of adaptive coding.

The senses of animals are confronted with changing environments and different contexts. Neural adaptation is one important tool to adjust sensitivity to varying intensity ranges. For instance, in a quiet night outdoors, our hearing is more sensitive than when we are confronted with the plurality of sounds in a large city during the day. However, adaptation also removes available information on absolute sound levels and may thus cause ambiguity. Experimental data on the trade-off between benefits and loss through adaptation is scarce and very few mechanisms have been proposed to resolve it. We present an example where adaptation is beneficial for one task--namely, the reliable encoding of the pattern of an acoustic signal-but detrimental for another--the localization of the same acoustic stimulus. With a combination of neurophysiological data, modeling, and behavioral tests, we show that adaptation in the periphery of the auditory pathway of grasshoppers enables intensity-invariant coding of amplitude modulations, but at the same time, degrades information available for sound localization. We demonstrate how focusing the response of localization neurons to the onset of relevant signals separates processing of localization and pattern information temporally. In this way, the ambiguity of adaptive coding can be circumvented and both absolute and relative levels can be processed using the same set of peripheral neurons.

Computational themes of peripheral processing in the auditory pathway of insects.

Hearing in insects serves to gain information in the context of mate finding, predator avoidance or host localization. For these goals, the auditory pathways of insects represent the computational substrate for object recognition and localization. Before these higher level computations can be executed in more central parts of the nervous system, the signals need to be preprocessed in the auditory periphery. Here, we review peripheral preprocessing along four computational themes rather than discussing specific physiological mechanisms: (1) control of sensitivity by adaptation, (2) recoding of amplitude modulations of an acoustic signal into a labeled-line code (3) frequency processing and (4) conditioning for binaural processing. Along these lines, we review evidence for canonical computations carried out in the peripheral auditory pathway and show that despite the vast diversity of insect hearing, signal processing is governed by common computational motifs and principles.