Bursting neurons and ultrasound avoidance in crickets

Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance

Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features

Neurons in various regions of the brain generate spike bursts. While the number of spikes within a burst has been shown to carry information, information coding by interspike intervals (ISIs) is less well understood. In particular, a burst with k spikes has k−1 intraburst ISIs, and these k−1 ISIs could theoretically encode k−1 independent values. In this study, we demonstrate that such combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are much faster than the light intensity modulation encoded by the number of spikes. When a burst has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are regulated by two independent mechanisms responding to orthogonal oscillatory components, one of which is common to bursts with a different number of spikes. Therefore, the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs.

Neurons in various regions of the brain generate spike bursts. Bursts are typically composed of a few spikes generated within dozens of milliseconds, and individual bursts are separated by much longer periods of silence (~hundreds of milliseconds). Recent evidence indicates that the number of spikes in a burst, the interspike intervals (ISIs), and the overall duration of a burst, as well as the timing of burst onset, encode information. However, it remains unknown whether multiple ISIs within a single burst encode multiple input features. Here we demonstrate that such combinatorial ISI coding occurs for spike bursts in the retina. We recorded ganglion cell spikes from isolated salamander retinae stimulated with computer-generated movies. Visual response analyses indicated that multiple ISIs within a single burst combinatorially encode the phase and amplitude of oscillatory light sequences, which are different from the stimulus feature encoded by the spike number. The result demonstrates that the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs. Because synaptic transmission in the visual system is highly sensitive to ISIs, the combinatorial ISI coding must have a major impact on visual information processing.

Neuroethology of acoustic communication in field crickets - from signal generation to song recognition in an insect brain

Field crickets are best known for the loud calling songs produced by males to attract conspecific females. This review aims to summarize the current knowledge of the neurobiological basis underlying the acoustic communication for mate finding in field crickets with emphasis on the recent research progress to understand the neuronal networks for motor pattern generation and auditory pattern recognition of the calling song in Gryllus bimaculatus. Strong scientific interest into the neural mechanisms underlying intraspecific communication has driven persistently advancing research efforts to study the male singing behaviour and female phonotaxis for mate finding in these insects. The growing neurobiological understanding also inspired many studies testing verifiable hypotheses in sensory ecology, bioacoustics and on the genetics and evolution of behaviour. Over last decades, acoustic communication in field crickets served as a very successful neuroethological model system. It has contributed significantly to the scientific process of establishing, reconsidering and refining fundamental concepts in behavioural neurosciences such as command neurons, central motor pattern generation, corollary discharge processing and pattern recognition by sensory feature detection, which are basic building blocks of our modern understanding on how nervous systems control and generate behaviour in all animals.

Differences in Sodium Channel Densities in the Apical Dendrites of Pyramidal Cells of the Electrosensory Lateral Line Lobe

Heterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes. This principle has been thoroughly investigated in the hindbrain of the weakly electric fish A. leptorhynchus in the primary electrosensory area, the Electrosensory Lateral Line lobe (ELL). The pyramidal cells (PCs) that receive inputs from tuberous electroreceptors are organized in three maps in distinct segments of the ELL. The properties of these cells vary greatly across maps due to differences in connectivity, receptor expression, and ion channel composition. These cells are a seminal example of bursting neurons and their bursting dynamic relies on the presence of voltage-gated Na⁺ channels in the extensive apical dendrites of the superficial PCs. Other ion channels can affect burst generation and their expression varies across ELL neurons and segments. For example, SK channels cause hyperpolarizing after-potentials decreasing the likelihood of bursting, yet bursting propensity is similar across segments. We question whether the depolarizing mechanism that generates the bursts presents quantitative differences across segments that could counterbalance other differences having the opposite effect. Although their presence and role are established, the distribution and density of the apical dendrites' Na⁺ channels have not been quantified and compared across ELL maps. Therefore, we test the hypothesis that Na⁺ channel density varies across segment by quantifying their distribution in the apical dendrites of immunolabeled ELL sections. We found the Na⁺ channels to be two-fold denser in the lateral segment (LS) than in the centro-medial segment (CMS), the centro-lateral segment (CLS) being intermediate. Our results imply that this differential expression of voltage-gated Na⁺ channels could counterbalance or interact with other aspects of neuronal physiology that vary across segments (e.g., SK channels). We argue that burst coding of sensory signals, and the way the network regulates bursting, should be influenced by these variations in Na⁺ channel density.

Multisensory enhancement of burst activity in an insect auditory neuron

Detecting predators is crucial for survival. In insects, a few sensory interneurons receiving sensory input from a distinct receptive organ extract specific features informing the animal about approaching predators and mediate avoidance behaviors. Although integration of multiple sensory cues relevant to the predator enhances sensitivity and precision, it has not been established whether the sensory interneurons that act as predator detectors integrate multiple modalities of sensory inputs elicited by predators. Using intracellular recording techniques, we found that the cricket auditory neuron AN2, which is sensitive to the ultrasound-like echolocation calls of bats, responds to airflow stimuli transduced by the cercal organ, a mechanoreceptor in the abdomen. AN2 enhanced spike outputs in response to cross-modal stimuli combining sound with airflow, and the linearity of the summation of multisensory integration depended on the magnitude of the evoked response. The enhanced AN2 activity contained bursts, triggering avoidance behavior. Moreover, cross-modal stimuli elicited larger and longer lasting excitatory postsynaptic potentials (EPSP) than unimodal stimuli, which would result from a sublinear summation of EPSPs evoked respectively by sound or airflow. The persistence of EPSPs was correlated with the occurrence and structure of burst activity. Our findings indicate that AN2 integrates bimodal signals and that multisensory integration rather than unimodal stimulation alone more reliably generates bursting activity. NEW & NOTEWORTHY Crickets detect ultrasound with their tympanum and airflow with their cercal organ and process them as alert signals of predators. These sensory signals are integrated by auditory neuron AN2 in the early stages of sensory processing. Multisensory inputs from different sensory channels enhanced excitatory postsynaptic potentials to facilitate burst firing, which could trigger avoidance steering in flying crickets. Our results highlight the cellular basis of multisensory integration in AN2 and possible effects on escape behavior.

Task-specific sensory coding strategies are matched to detection and discrimination performance

The acquisition of sensory information is limited by the neural encoding method used, constraining perceptual abilities. The most relevant aspects of stimuli may change as behavioral context changes, making efficient encoding of information more challenging. Sensory systems must balance rapid detection of a stimulus with perception of fine details that enable discrimination between similar stimuli. Here, we show that in a species of weakly electric fish, Apteronotus leptorhynchus, two coding strategies are employed for these separate behavioral tasks. Using communication signals, we demonstrate a strong correlation between neural coding strategies and behavioral performance on a discrimination task. Extracellular recordings of pyramidal cells within the electrosensory lateral line lobe of alert fish show two distinct response patterns, either burst discharges with little variation between different signals of the same category, or a graded, heterogeneous response that contains sufficient information to discriminate between signals with slight variations. When faced with a discrimination-based task, the behavioral performance of the fish closely matches predictions based on coding strategy. Comparisons of these results with neural and behavioral responses observed in other model systems suggest that our study highlights a general principle in the way sensory systems utilize different neural codes.

The influence of bat echolocation call duration and timing on auditory encoding of predator distance in noctuoid moths

Animals co-occur with multiple predators, making sensory systems that can encode information about diverse predators advantageous. Moths in the families Noctuidae and Erebidae have ears with two auditory receptor cells (A1 and A2) used to detect the echolocation calls of predatory bats. Bat communities contain species that vary in echolocation call duration, and the dynamic range of A1 is limited by the duration of sound, suggesting that A1 provides less information about bats with shorter echolocation calls. To test this hypothesis, we obtained intensity-response functions for both receptor cells across many moth species for sound pulse durations representing the range of echolocation call durations produced by bat species in northeastern North America. We found that the threshold and dynamic range of both cells varied with sound pulse duration. The number of A1 action potentials per sound pulse increases linearly with increasing amplitude for long-duration pulses, saturating near the A2 threshold. For short sound pulses, however, A1 saturates with only a few action potentials per pulse at amplitudes far lower than the A2 threshold for both single sound pulses and pulse sequences typical of searching or approaching bats. Neural adaptation was only evident in response to approaching bat sequences at high amplitudes, not search-phase sequences. These results show that, for short echolocation calls, a large range of sound levels cannot be coded by moth auditory receptor activity, resulting in no information about the distance of a bat, although differences in activity between ears might provide information about direction.

Burst Firing in the Electrosensory System of Gymnotiform Weakly Electric Fish: Mechanisms and Functional Roles

Neurons across sensory systems and organisms often display complex patterns of action potentials in response to sensory input. One example of such a pattern is the tendency of neurons to fire packets of action potentials (i.e., a burst) followed by quiescence. While it is well known that multiple mechanisms can generate bursts of action potentials at both the single-neuron and the network level, the functional role of burst firing in sensory processing is not so well understood to date. Here we provide a comprehensive review of the known mechanisms and functions of burst firing in processing of electrosensory stimuli in gymnotiform weakly electric fish. We also present new evidence from existing data showing that bursts and isolated spikes provide distinct information about stimulus variance. It is likely that these functional roles will be generally applicable to other systems and species.

Burst Firing in a Motion-Sensitive Neural Pathway Correlates with Expansion Properties of Looming Objects that Evoke Avoidance Behaviors

The locust visual system contains a well-defined motion-sensitive pathway that transfers visual input to motor centers involved in predator evasion and collision avoidance. One interneuron in this pathway, the descending contralateral movement detector (DCMD), is typically described as using rate coding; edge expansion of approaching objects causes an increased rate of neuronal firing that peaks after a certain retinal threshold angle is exceeded. However, evidence of intrinsic DCMD bursting properties combined with observable oscillations in mean firing rates and tight clustering of spikes in raw traces, suggest that bursting may be important for motion detection. Sensory neuron bursting provides important timing information about dynamic stimuli in many model systems, yet no studies have rigorously investigated if bursting occurs in the locust DCMD during object approach. We presented repetitions of 30 looming stimuli known to generate behavioral responses to each of 20 locusts in order to identify and quantify putative bursting activity in the DCMD. Overall, we found a bimodal distribution of inter-spike intervals (ISI) with peaks of more frequent and shorter ISIs occurring from 1–8 ms and longer less frequent ISIs occurring from 40–50 ms. Subsequent analysis identified bursts and isolated single spikes from the responses. Bursting frequency increased in the latter phase of an approach and peaked at the time of collision, while isolated spiking was predominant during the beginning of stimulus approach. We also found that the majority of inter-burst intervals (IBIs) occurred at 40–50 ms (or 20–25 bursts/s). Bursting also occurred across varied stimulus parameters and suggests that burst timing may be a key component of looming detection. Our findings suggest that the DCMD uses two modes of coding to transmit information about looming stimuli and that these modes change dynamically with a changing stimulus at a behaviorally-relevant time.

Evolution of a Communication System by Sensory Exploitation of Startle Behavior

New communication signals can evolve by sensory exploitation if signaling taps into preexisting sensory biases in receivers [1, 2]. For mate attraction, signals are typically similar to attractive environmental cues like food [3-6], which amplifies their attractiveness to mates, as opposed to aversive stimuli like predator cues. Female field crickets approach the low-frequency calling song of males, whereas they avoid high-frequency sounds like predatory bat calls [7]. In one group of crickets (Eneopterinae: Lebinthini), however, males produce exceptionally high-frequency calling songs in the range of bat calls [8], a surprising signal in the context of mate attraction. We found that female lebinthines, instead of approaching singing males, produce vibrational responses after male calls, and males track the source of vibrations to find females. We also demonstrate that field cricket species closely related to the Lebinthini show an acoustic startle response to high-frequency sounds that generates substrate vibrations similar to those produced by female lebinthine crickets. Therefore, the startle response is the most likely evolutionary origin of the female lebinthine vibrational signal. In field crickets, the brain receives activity from two auditory interneurons; AN1 tuned to male calling song controls positive phonotaxis, and AN2 tuned to high-frequency bat calls triggers negative phonotaxis [9, 10]. In lebinthine crickets, however, we found that auditory ascending neurons are only tuned to high-frequency sounds, and their tuning matches the thresholds for female vibrational signals. Our results demonstrate how sensory exploitation of anti-predator behavior can evolve into a communication system that benefits both senders and receivers.

Thalamic neuron models encode stimulus information by burst-size modulation

Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons.

Bursting by taste-responsive cells in the rodent brain stem

Neurons that fire in bursts have been well-characterized in vision and other neural systems, but not in taste systems. We therefore examined whether brain stem gustatory neurons fire in bursts during spontaneous activity and, if so, whether such cells differ from nonbursting cells in other characteristics. We looked at neurons in the nucleus of the solitary tract (NST) of C57BL/6ByJ (B6) and 129P3/J (129) mice, and in the NST and parabrachial nucleus (PBN) of Sprague-Dawley rats. Many NST cells fired frequently with short intervals characteristic of bursting, and such neurons differed from others in their responsiveness to taste compounds. In B6 mice and rats, there was a significant positive correlation between the prevalence of short-interval firing and the net spikes evoked by application of NaCl. In contrast, in 129 mice the prevalence of short intervals was positively correlated with the size of sucrose responses. We also compared breadth-of-tuning measures based on counting either all spikes or only those following short intervals, and we found narrower tuning for the latter in the NST of B6 mice and rats. There was little evidence of spontaneous bursting in the rat PBN, and firing patterns in this nucleus were not related to the size of taste-evoked responses. We suggest that bursting may be a strategy employed by the NST to amplify the postsynaptic impact of particular taste stimuli, depending on an animal's needs. Another function may be to sharpen breadth-of-tuning and thus enhance the contrast between stimuli of different taste qualities.