Wave-type Electric Fish Research Articles

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.

Tethered unitary recordings suggest a spike-timing electrosensory code in the electrosensory lobe of Gymnotus omarorum

AbstractEvaluation of neural activity during natural behaviours is essential for understanding how the brain works. Here we show that neuron-specific self-evoked firing patterns are modulated by an object’s presence, at the electrosensory lobe neurons of tethered-moving Gymnotus omarorum. This novel preparation shows that electrosensory signals in these pulse-type weakly electric fish are not only encoded in the number of spikes per electric organ discharge (EOD), as is the case in wave-type electric fish, but also in the spike timing pattern after each EOD, as found in pulse-type Mormyroidea. Present data suggest that pulsant electrogenesis and spike timing coding of electrosensory signals developed concomitantly in the same species, and evolved convergently in African and American electric fish.

Waveform sensitivity of electroreceptors in the pulse-type weakly electric fish Gymnotus omarorum.

As in most sensory systems, electrosensory images in weakly electric fish are encoded in two parallel pathways, fast and slow. From work on wave-type electric fish, these fast and slow pathways are thought to encode the time and amplitude of electrosensory signals, respectively. The present study focuses on the primary afferents giving origin to the slow path of the pulse-type weakly electric fish Gymnotus omarorum We found that burst duration coders respond with a high-frequency train of spikes to each electric organ discharge. They also show high sensitivity to phase-frequency distortions of the self-generated local electric field. We explored this sensitivity by manipulating the longitudinal impedance of a probe cylinder to modulate the stimulus waveform, while extracellularly recording isolated primary afferents. Resistive loads only affect the amplitude of the re-afferent signals without distorting the waveform. Capacitive loads cause large waveform distortions aside from amplitude changes. Stepping from a resistive to a capacitive load in such a way that the stimulus waveform was distorted, without changing its total energy, caused strong changes in latency, inter-spike interval and number of spikes of primary afferent responses. These burst parameters are well correlated suggesting that they may contribute synergistically in driving downstream neurons. This correlation also suggests that each receptor encodes a single parameter in the stimulus waveform. The finding of waveform distortion sensitivity is relevant because it may contribute to: (a) enhance electroreceptive range in the peripheral 'electrosensory field', (b) a better identification of living prey at the 'foveal electrosensory field' and (c) detect the presence and orientation of conspecifics. Our results also suggest a revision of the classical view of amplitude and time encoding by fast and slow pathways in pulse-type electric fish.

Modeling cancelation of periodic inputs with burst-STDP and feedback

Prediction and cancelation of redundant information is an important feature that many neural systems must display in order to efficiently code external signals. We develop an analytic framework for such cancelation in sensory neurons produced by a cerebellar-like structure in wave-type electric fish. Our biologically plausible mechanism is motivated by experimental evidence of cancelation of periodic input arising from the proximity of conspecifics as well as tail motion. This mechanism involves elements present in a wide range of systems: (1) stimulus-driven feedback to the neurons acting as detectors, (2) a large variety of temporal delays in the pathways transmitting such feedback, responsible for producing frequency channels, and (3) burst-induced long-term plasticity. The bursting arises from back-propagating action potentials. Bursting events drive the input frequency-dependent learning rule, which in turn affects the feedback input and thus the burst rate. We show how the mean firing rate and the rate of production of 2- and 4-spike bursts (the main learning events) can be estimated analytically for a leaky integrate-and-fire model driven by (slow) sinusoidal, back-propagating and feedback inputs as well as rectified filtered noise. The effect of bursts on the average synaptic strength is also derived. Our results shed light on why bursts rather than single spikes can drive learning in such networks “online”, i.e. in the absence of a correlative discharge. Phase locked spiking in frequency specific channels together with a frequency-dependent STDP window size regulate burst probability and duration self-consistently to implement cancelation.

Coding Conspecific Identity and Motion in the Electric Sense

Interactions among animals can result in complex sensory signals containing a variety of socially relevant information, including the number, identity, and relative motion of conspecifics. How the spatiotemporal properties of such evolving naturalistic signals are encoded is a key question in sensory neuroscience. Here, we present results from experiments and modeling that address this issue in the context of the electric sense, which combines the spatial aspects of vision and touch, with the temporal aspects of audition. Wave-type electric fish, such as the brown ghost knifefish, Apteronotus leptorhynchus, used in this study, are uniquely identified by the frequency of their electric organ discharge (EOD). Multiple beat frequencies arise from the superposition of the EODs of each fish. We record the natural electrical signals near the skin of a “receiving” fish that are produced by stationary and freely swimming conspecifics. Using spectral analysis, we find that the primary beats, and the secondary beats between them (“beats of beats”), can be greatly influenced by fish swimming; the resulting motion produces low-frequency envelopes that broaden all the beat peaks and reshape the “noise floor”. We assess the consequences of this motion on sensory coding using a model electroreceptor. We show that the primary and secondary beats are encoded in the afferent spike train, but that motion acts to degrade this encoding. We also simulate the response of a realistic population of receptors, and find that it can encode the motion envelope well, primarily due to the receptors with lower firing rates. We discuss the implications of our results for the identification of conspecifics through specific beat frequencies and its possible hindrance by active swimming.

Testing resonating vector strength: Auditory system, electric fish, and noise

Quite often a response to some input with a specific frequency ν(○) can be described through a sequence of discrete events. Here, we study the synchrony vector, whose length stands for the vector strength, and in doing so focus on neuronal response in terms of spike times. The latter are supposed to be given by experiment. Instead of singling out the stimulus frequency ν(○) we study the synchrony vector as a function of the real frequency variable ν. Its length turns out to be a resonating vector strength in that it shows clear maxima in the neighborhood of ν(○) and multiples thereof, hence, allowing an easy way of determining response frequencies. We study this "resonating" vector strength for two concrete but rather different cases, viz., a specific midbrain neuron in the auditory system of cat and a primary detector neuron belonging to the electric sense of the wave-type electric fish Apteronotus leptorhynchus. We show that the resonating vector strength always performs a clear resonance correlated with the phase locking that it quantifies. We analyze the influence of noise and demonstrate how well the resonance associated with maximal vector strength indicates the dominant stimulus frequency. Furthermore, we exhibit how one can obtain a specific phase associated with, for instance, a delay in auditory analysis.

Communication signals in a wave-type electric fish are encoded by synchronization and desynchronization depending on the social context

Communication signals in a wave-type electric fish are encoded by synchronization and desynchronization depending on the social context

Electric organ discharge frequency jamming during social interactions in brown ghost knifefish, Apteronotus leptorhynchus

In most communication systems, animals avoid jamming when similar signals from two individuals might overlap and cause interference. Most species of wave-type electric fish avoid jamming by shifting their electric organ discharge (EOD) frequencies away from those of conspecifics or away from mimics of sine wave EOD frequencies presented in playback experiments. Both male and female brown ghosts, however, appear to intentionally jam rivals during competitive interactions if the rival has a higher EOD frequency. We studied this behaviour in competitive interactions between two fish in a neutral arena, and in playback studies with single fish in resident–intruder and neutral arena models. During competitive interactions, females jammed the rival's EOD signal only when the rival's EOD frequency was within ∼30 Hz of their own EOD frequency, whereas males tried to jam EOD signals of rivals that were 70 Hz higher than their own EOD frequency. In the resident–intruder model experiment, fish tended to raise their EOD frequencies to within potential jamming range in response to a simulated intruder with a higher EOD frequency than their own. In a neutral arena model, fish directed the most aggressive attacks in response to simulated rivals with lower EOD frequencies, yet were less likely to attack the playback device if it played a frequency elevation that mimicked a fish with a lower EOD frequency attempting to jam them. This is the first evidence that electric fish may actively use jamming as an aggressive behaviour.

Waveform discrimination, phase sensitivity and jamming avoidance in a wave-type electric fish

The electric organ discharge (EOD) of most species of the freshwater knifefishes (Gymnotiformes) of South America is of the wave, not the pulse, type. Wave EODs are usually of constant frequency and amplitude, and show a bewildering multitude of species-characteristic waveforms. The EOD of Eigenmannia is sexually dimorphic in waveform and in the intensity of its higher harmonics. In a go/no go paradigm, trained food-rewarded fish discriminated between these waveforms, and naive (untrained) fish showed a significant preference. To determine whether spectral or waveform (time) cues are used by the fish, artificial stimuli of identical amplitude spectrum were synthesized that differed only in phase relationship between their harmonics, i.e. waveform, and the fish discriminated even among these stimulus waveforms (i.e. spectral cues are not required). Our sensory model predicts that, for successful waveform detection, a minimum frequency difference is required between the stimulus and the EOD. As expected, trained fish confused test stimuli of different waveform that were frequency-clamped and phase-locked to the EOD (frequency difference 0 Hz). Opening the electronic feedback loop immediately restored discrimination performance on an on/off basis, and a strong jamming avoidance response (JAR; a frequency shift away from the stimulus) accompanied every behavioural decision (to go for a food reward). The strong habituation of the JAR that occurs in response to stimuli of no behavioural consequence (the usual test situation) was not seen in the present experiments. The proposed sensory model (which is based on time-marking T electroreceptors) is supported by these experiments, and a biological function for the JAR - subserving EOD waveform discrimination is shown to be useful in a social context.

Parallel Projection of Amplitude and Phase Information from the Hindbrain to the Midbrain of the African Electric FishGymnarchus niloticus

Two distinct sensory cues in electrosensory signals, amplitude modulation and differential phase modulation, are essential for an African wave-type electric fish, Gymnarchus, to perform the jamming avoidance responses. Individual neurons in the first brain station for central processing, the electrosensory lateral line lobe (ELL), were investigated by the in vivo whole-cell recording and labeling technique for their physiological responses, location, morphology, and projection areas. Neurons in the dorsal zone of the ELL responded selectively to amplitude modulation. Neurons in the outer cell layer of the medial zone were categorized physiologically into two groups: amplitude-sensitive and differential phase-sensitive. All but one neuron in the inner cell layer of the medial zone responded exclusively to differential phase modulation. All neurons recorded and labeled in the ELL had pyramidal morphology with large and extensive apical dendrites and less extensive basal dendrites. They were found to project to two midbrain nuclei: the nucleus praeeminentialis and the torus semicircularis. Amplitude-sensitive neurons in the dorsal zone projected exclusively to the lateral posterior subdivision, the torus semicircularis. Neurons in the medial zone projected to the medial dorsal and lateral anterior subdivisions of the torus semicircularis. Although some neurons in the ELL responded to both amplitude and differential phase modulation, they did not differentiate between temporal patterns of the two cues that encode necessary information for the jamming avoidance response. Overlapping projection of amplitude and differential phase-sensitive neurons to the torus semicircularis suggests integration of the two sensory cues in this nucleus.

Capacitance detection in the wave-type electric fish Eigenmannia during active electrolocation

Weakly electric fish can detect nearby objects and analyse their electric properties during active electrolocation. Four individuals of the South American gymnotiform fish Eigenmannia sp., which emits a continuous wave-type electric signal, were tested for their ability to detect capacitive properties of objects and discriminate them from resistive properties. For individual fish, capacitive values of objects had to be greater than 0.22–1.7 nF (`lower threshold') and smaller than 120–680 nF (`upper threshold') in order to be detected. The capacitive values of natural objects fall well within this detection range. All fish trained could discriminate unequivocally between capacitive and resistive object properties. Thus, fish perceive capacitive properties as a separate object quality. The effects of different types of objects on the locally occurring electric signals which stimulate electroreceptors during electrolocation were examined. Purely resistive objects altered mainly local electric organ discharge (EOD) amplitude, but capacitive objects with values between about 0.5 and 600 nF changed the timing of certain EOD parameters (phase-shift) and EOD waveform. A mechanism for capacitance detection in wave-type electric fish based on time measurements is proposed and compared with the capacitance detection mechanism in mormyrid pulse-type fish, which is based on waveform measurements.

Characterization and modeling of P-type electrosensory afferent responses to amplitude modulations in a wave-type electric fish.

The first stage of information processing in the electrosensory system involves the encoding of local changes in transdermal potential into trains of action potentials in primary electrosensory afferent nerve fibers. To develop a quantitative model of this encoding process for P-type (probability-coding) afferent fibers in the weakly electric fish Apteronotus leptorhynchus, we recorded single unit activity from electrosensory afferent axons in the posterior branch of the anterior lateral line nerve and analyzed responses to electronically generated sinusoidal amplitude modulations of the local transdermal potential. Over a range of AM frequencies from 0.1 to 200 Hz, the modulation transfer function of P-type afferents is high-pass in character, with a gain that increases monotonically up to AM frequencies of 100 Hz where it begins to roll off, and a phase advance with a range of 15-60 degrees. Based on quantitative analysis of the observed gain and phase characteristics, we present a computationally efficient model of P-type afferent response dynamics which accurately characterizes changes in afferent firing rate in response to amplitude modulations of the fish's own electric organ discharge over a wide range of AM frequencies relevant to active electrolocation.

Coding of time-varying electric field amplitude modulations in a wave-type electric fish.

1. The coding of time-varying electric fields in the weakly electric fish, Eigenmannia, was investigated in a quantitative manner. The activity of single P-type electroreceptor afferents was recorded while the amplitude of an externally applied sinusoidal electric field was stochastically modulated. The amplitude modulation waveform (i.e., the stimulus) was reconstructed from the spike trains by mean square estimation. 2. From the stimulus and the reconstructions we calculated the following: 1) the signal-to-noise ratio and thus an effective temporal bandwidth of the units; 2) the coding fraction, i.e., a measure of the fraction of the time-varying stimulus encoded in single spike trains; and 3) the mutual information provided by the reconstructions about the stimulus. 3. Signal-to-noise ratios as high as 7:1 were observed and the bandwidth ranged from 0 up to 200 Hz, consistent with the limit imposed by the sampling theorem. Reducing the cutoff frequency of the stimulus increased the signal-to-noise ratio at low frequencies, indicating a nonlinearity in the receptors' response. 4. The coding fraction and the rate of mutual information transmission increased in parallel with the standard deviation (i.e., the contrast) of the stimulus as well as the mean firing rate of the units. Significant encoding occurred 20-40 Hz above the spontaneous discharge of a unit. 5. When the temporal cutoff frequency of the stimulus was increased between 80 and 400 Hz, 1) the coding fraction decreased, 2) the rate of mutual information transmission remained constant over the same frequency range, and 3) the reconstructed filter changed. This is in agreement with predictions obtained in a simplified neuronal model. 6. Our results suggest that 1) the information transmitted by single spike trains of primary electrosensory afferents to higherorder neurons in the fish brain depends on the contrast and the cutoff frequency of the stimulus as well as on the mean firing rate of the units; and 2) under optimal conditions, more than half of the information about a Gaussian stimulus that can in principle be encoded is carried in single spike trains of P-type afferents at rates up to 200 bits per second.

Neuronal circuitry for comparison of timing in the electrosensory lateral line lobe of the African wave-type electric fish Gymnarchus niloticus

An African wave-type electric fish, Gymnarchus, compares timing on the order of microseconds of sensory feedback from from its high-frequency (approximately 400 Hz) electric organ discharges (EODs) received at different parts of its body surfaces. This capability is essential for and demonstrated by the jamming avoidance response (JAR). The organization of the timing comparison mechanisms was identified in the electrosensory lateral line lobe (ELL) in the hindbrain by field potential, extra- and intracellular recordings, and intracellular labeling with biotinylated agents. Timing of phase of the EOD feedback is carried by action potentials of S-type primary afferent fibers that project to the inner cellular layer (ICL) of the medial zone of the ELL and to the giant neurons in the ELL. The giant neurons bilaterally project to the ICL, where neurons sensitive to phase differences between different parts of the body occur. Although sensitive to dynamic phase changes of several microseconds, these differential-phase-sensitive neurons showed adaptation to steady-state changes of phase difference over a wide range (greater than +/- 100 microseconds) and continued to respond to small modulations after the mean difference was shifted. Gymnarchus and an independently evolved South American electric fish, Eigenmannia, exhibit nearly identical JARs and share a rather complex but identical set of computational algorithms for JAR. This study showed that one of the computational steps, the timing comparison between body surfaces, occurs in the hindbrain in Gymnarchus, in contrast to the midbrain in Eigenmannia. Thus, similar systems with a similar overall function may have evolved differently in different genera by assigning a subfunction to different substructures within the brain.

The African wave-type electric fish, Gymnarchus niloticus, lacks corollary discharge mechanisms for electrosensory gating

Gymnarchus niloticus, a wave-type African electric fish, performs its jamming avoidance response by relying solely upon afferent signals and does not use corollary discharges from the pacemaker nucleus in the medulla which generates the rhythmicity of electric organ discharges. This is in sharp contrast to the mode of sensory processing found in closely related African pulse-type electric fishes where afferent signals are gated by corollary discharges from the pacemaker for the distinction of exafferent and reafferent stimuli. Does Gymnarchus still possess a corollary discharge mechanism for other behavioral tasks but does not use it for the jamming avoidance response? In this study, I recorded from and labeled medullary neuronal structures that either generate or convey the pacemaker signal for electric organ discharges to examine whether this information is also sent directly to any sensory areas. The pacemaker nucleus was identified as the site of generation of the pacemaking signal. The pacemaker neurons project exclusively to the lateral relay nucleus which, in turn projects exclusively to the medial relay nucleus. Neurons in the medial relay nucleus send unbranched axons to the spinal electromotoneurons. These neurons are entirely devoted to drive the electric organ discharges, and no axon collaterals from these neurons were found to project to any sensory areas. This indicates that Gymnarchus does not possess the neuronal hardware for a corollary discharge mechanism.

TheApteronotus EOD field: Waveform and EOD field simulation

1. Electric organ discharges (EOD) were measured in a wave-type electric fish,Apteronotus, with an array of electrodes. 2. The EOD waveform observed in the transient area (area where the equipotential lines converged) was a triphasic one in comparison to a biphasic one in the rest of the area. Electronic circuit simulation suggested that the triphasic waveform resulted from incomplete electrocyte synchronization within the electric organ. 3. The EOD field was obtained by computer simulation using the finite-element-method. The simulated results were used for calculation of the transepidermal potential difference distribution. This distribution is discussed with respect to sensitivity differences of electroreceptors in various parts of the fish.

Sensory feedback from electroreceptors to electromotor pacemaker centers in gymnotids

Sensory feedback from electroreceptors to electromotor pacemaker centers in gymnotids