Spike frequency adaptation mediates looming stimulus selectivity in a collision-detecting neuron

Contrast coding in the electrosensory system: parallels with visual computation

To identify and interact with moving objects, including other members of the same species, an animal's nervous system must correctly interpret patterns of contrast in the physical signals (such as light or sound) that it receives from the environment. In weakly electric fish, the motion of objects in the environment and social interactions with other fish create complex patterns of contrast in the electric fields that they produce and detect. These contrast patterns can extend widely over space and time and represent a multitude of relevant features, as is also true for other sensory systems. Mounting evidence suggests that the computational principles underlying contrast coding in electrosensory neural networks are conserved elements of spatiotemporal processing that show strong parallels with the vertebrate visual system.

Direction-Specific Adaptation in Neuronal and Behavioral Responses of an Insect Mechanosensory System

Stimulus-specific adaptation (SSA) is considered to be the neural underpinning of habituation to frequent stimuli and novelty detection. However, neither the cellular mechanism underlying SSA nor the link between SSA-like neuronal plasticity and behavioral modulation is well understood. The wind-detection system in crickets is one of the best models for investigating the neural basis of SSA. We found that crickets exhibit stimulus-direction-specific adaptation in wind-elicited avoidance behavior. Repetitive air currents inducing this behavioral adaptation reduced firings to the stimulus and the amplitude of excitatory synaptic potentials in wind-sensitive giant interneurons (GIs) related to the avoidance behavior. Injection of a Ca(2+) chelator into GIs diminished both the attenuation of firings and the synaptic depression induced by the repetitive stimulation, suggesting that adaptation of GIs induced by this stimulation results in Ca(2+)-mediated modulation of postsynaptic responses, including postsynaptic short-term depression. Some types of GIs showed specific adaptation to the direction of repetitive stimuli, resulting in an alteration of their directional tuning curves. The types of GIs for which directional tuning was altered displayed heterogeneous direction selectivity in their Ca(2+) dynamics that was restricted to a specific area of dendrites. In contrast, other types of GIs with constant directionality exhibited direction-independent global Ca(2+) elevation throughout the dendritic arbor. These results suggest that depression induced by local Ca(2+) accumulation at repetitively activated synapses of key neurons underlies direction-specific behavioral adaptation. This input-selective depression mediated by heterogeneous Ca(2+) dynamics could confer the ability to detect novelty at the earliest stages of sensory processing in crickets.

SIGNIFICANCE STATEMENT

Stimulus-specific adaptation (SSA) is considered to be the neural underpinning of habituation and novelty detection. We found that crickets exhibit stimulus-direction-specific adaptation in wind-elicited avoidance behavior. Repetitive air currents inducing this behavioral adaptation altered the directional selectivity of wind-sensitive giant interneurons (GIs) via direction-specific adaptation mediated by dendritic Ca(2+) elevation. The GIs for which directional tuning was altered displayed heterogeneous direction selectivity in their Ca(2+) dynamics and the transient increase in Ca(2+) evoked by the repeated puffs was restricted to a specific area of dendrites. These results suggest that depression induced by local Ca(2+) accumulation at repetitively activated synapses of key neurons underlies direction-specific behavioral adaptation. Our findings elucidate the subcellular mechanism underlying SSA-like neuronal plasticity related to behavioral adaptation.

A switch in the mode of the sodium/calcium exchanger underlies an age-related increase in the slow afterhyperpolarization

During aging, the Ca(2+)-sensitive slow afterhyperpolarization (sAHP) of hippocampal neurons is known to increase in duration. This change has also been observed in the serotonergic cerebral giant cells (CGCs) of the pond snail Lymnaea stagnalis, but has yet to be characterized. In this article, we confirm that there is a reduction in firing rate, an increase in the duration of the sAHP, and an alteration in the strength and speed of spike frequency adaptation in the CGCs during aging, a finding that is compatible with an increase in the sAHP current. We go on to show that age-related changes in the kinetics of spike frequency adaptation are consistent with a reduction in Ca(2+) clearance from the cell, which we confirm with Ca(2+) imaging and pharmacological manipulation of the sodium calcium exchanger. These experiments suggest that the sodium calcium exchanger may be switching to a reverse-mode configuration in the CGCs during aging.

Spike-frequency adaptation of a two-compartment neuron modulated by extracellular electric fields

Spike-frequency adaptation has been shown to play an important role in neural coding. Based on a reduced two-compartment model, here we investigate how two common adaptation currents, i.e., voltage-sensitive potassium current (I(M)) and calcium-sensitive potassium current (I(AHP)), modulate neuronal responses to extracellular electric fields. It is shown that two adaptation mechanisms lead to distinct effects on the dynamical behavior of the neuron to electric fields. These effects depend on a neuronal morphological parameter that characterizes the ratio of soma area to total membrane area and internal coupling conductance. In the case of I(AHP) current, changing the morphological parameter switches spike initiation dynamics between saddle-node on invariant cycle bifurcation and supercritical Hopf bifurcation, whereas it only switches between subcritical and supercritical Hopf bifurcations for I(M) current. Unlike the morphological parameter, internal coupling conductance is unable to alter the bifurcation scenario for both adaptation currents. We also find that the electric field threshold for triggering neuronal steady-state firing is determined by two parameters, especially by the morphological parameter. Furthermore, the neuron with I(AHP) current generates mixed-mode oscillations through the canard phenomenon for some small values of the morphological parameter. All these results suggest that morphological properties play a critical role in field-induced effects on neuronal dynamics, which could qualitatively alter the outcome of adaptation by modulating internal current between soma and dendrite. The findings are readily testable in experiments, which could help to reveal the mechanisms underlying how the neuron responds to electric field stimulus.

Fast-onset long-term open-state block of sodium channels by A-type FHFs mediates classical spike accommodation in hippocampal pyramidal neurons

Classical accommodation is a form of spike frequency adaptation in neurons whereby excitatory drive results in action potential output of gradually decreasing frequency. Here we describe an essential molecular component underlying classical accommodation in juvenile mouse hippocampal CA1 pyramidal neurons. A-type isoforms of fibroblast growth factor homologous factors (FHFs) bound to axosomatic voltage-gated sodium channels bear an N-terminal blocking particle that drives some associated channels into a fast-onset, long-term inactivated state. Use-dependent accumulating channel blockade progressively elevates spike voltage threshold and lengthens interspike intervals. The FHF particle only blocks sodium channels from the open state, and mutagenesis studies demonstrate that this particle uses multiple aliphatic and cationic residues to both induce and maintain the long-term inactivated state. The broad expression of A-type FHFs in neurons throughout the vertebrate CNS suggests a widespread role of these sodium channel modulators in the control of neural firing.

Effects of spike-triggered negative feedback on receptive-field properties

Sensory neurons are often described in terms of a receptive field, that is, a linear kernel through which stimuli are filtered before they are further processed. If information transmission is assumed to proceed in a feedforward cascade, the receptive field may be interpreted as the external stimulus' profile maximizing neuronal output. The nervous system, however, contains many feedback loops, and sensory neurons filter more currents than the ones representing the transduced external stimulus. Some of the additional currents are generated by the output activity of the neuron itself, and therefore constitute feedback signals. By means of a time-frequency analysis of the input/output transformation, here we show how feedback modifies the receptive field. The model is applicable to various types of feedback processes, from spike-triggered intrinsic conductances to inhibitory synaptic inputs from nearby neurons. We distinguish between the intrinsic receptive field (filtering all input currents) and the effective receptive field (filtering only external stimuli). Whereas the intrinsic receptive field summarizes the biophysical properties of the neuron associated to subthreshold integration and spike generation, only the effective receptive field can be interpreted as the external stimulus' profile maximizing neuronal output. We demonstrate that spike-triggered feedback shifts low-pass filtering towards band-pass processing, transforming integrator neurons into resonators. For strong feedback, a sharp resonance in the spectral neuronal selectivity may appear. Our results provide a unified framework to interpret a collection of previous experimental studies where specific feedback mechanisms were shown to modify the filtering properties of neurons.

ADAPTATION-DEPENDENT SYNCHRONIZATION TRANSITIONS AND BURST GENERATIONS IN ELECTRICALLY COUPLED NEURAL NETWORKS

A typical feature of neurons is their ability to encode neural information dynamically through spike frequency adaptation (SFA). Previous studies of SFA on neuronal synchronization were mainly concentrated on the correlated firing between neuron pairs, while the synchronization of neuron populations in the presence of SFA is still unclear. In this study, the influence of SFA on the population synchronization of neurons was numerically explored in electrically coupled networks, with regular, small-world, and random connectivity, respectively. The simulation results indicate that cross-correlation indices decrease significantly when the neurons have adaptation compared with those of nonadapting neurons, similar to previous experimental observations. However, the synchronous activity of population neurons exhibits a rather complex adaptation-dependent manner. Specifically, synchronization strength of neuron populations changes nonmonotonically, depending on the degree of adaptation. In addition, single neurons in the networks can switch from regular spiking to bursting with the increase of adaptation degree. Furthermore, the connection probability among neurons exhibits significant influence on the population synchronous activity, but has little effect on the burst generation of single neurons. Accordingly, the results may suggest that synchronous activity and burst firing of population neurons are both adaptation-dependent.

Excitation and inhibition in recurrent networks mediate collision avoidance in Xenopus tadpoles

Information processing in the vertebrate brain is thought to be mediated through distributed neural networks, but it is still unclear how sensory stimuli are encoded and detected by these networks, and what role synaptic inhibition plays in this process. Here we used a collision avoidance behavior in Xenopus tadpoles as a model for stimulus discrimination and recognition. We showed that the visual system of the tadpole is selective for behaviorally relevant looming stimuli, and that the detection of these stimuli first occurs in the optic tectum. By comparing visually guided behavior, optic nerve recordings, excitatory and inhibitory synaptic currents, and the spike output of tectal neurons, we showed that collision detection in the tadpole relies on the emergent properties of distributed recurrent networks within the tectum. We found that synaptic inhibition was temporally correlated with excitation, and did not actively sculpt stimulus selectivity, but rather it regulated the amount of integration between direct inputs from the retina and recurrent inputs from the tectum. Both pharmacological suppression and enhancement of synaptic inhibition disrupted emergent selectivity for looming stimuli. Taken together these findings suggested that, by regulating the amount of network activity, inhibition plays a critical role in maintaining selective sensitivity to behaviorally-relevant visual stimuli.

A neural code for looming and receding motion is distributed over a population of electrosensory ON and OFF contrast cells

Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. As such, contrast-detecting neurons (ON/OFF cells) are found in many sensory systems, responding respectively to increased or decreased intensity within their receptive field centers. This differential sensitivity suggests that ON and OFF cells initiate segregated streams of information for positive and negative sensory contrast. However, while recording in vivo from the ON and OFF cells of Apteronotus leptorhynchus, we report that the reversal of stimulus motion triggers paradoxical responses to electrosensory contrast. By considering the instantaneous firing rates of both ON and OFF cell populations, a bidirectionally symmetric representation of motion is achieved for both positive and negative contrast stimuli. Whereas the firing rates of the individual contrast detecting neurons convey scalar information, such as object distance, it is their sequential activation over longer timescales that track changes in the direction of movement.

Computation of object approach by a system of visual motion-sensitive neurons in the crab Neohelice

Similar to most visual animals, crabs perform proper avoidance responses to objects directly approaching them. The monostratified lobula giant neurons of type 1 (MLG1) of crabs constitute an ensemble of 14-16 bilateral pairs of motion-detecting neurons projecting from the lobula (third optic neuropile) to the midbrain, with receptive fields that are distributed over the extensive visual field of the animal's eye. Considering the crab Neohelice (previously Chasmagnathus) granulata, here we describe the response of these neurons to looming stimuli that simulate objects approaching the animal on a collision course. We found that the peak firing time of MLG1 acts as an angular threshold detector signaling, with a delay of δ = 35 ms, the time at which an object reaches a fixed angular threshold of 49°. Using in vivo intracellular recordings, we detected the existence of excitatory and inhibitory synaptic currents that shape the neural response. Other functional features identified in the MLG1 neurons were phasic responses at the beginning of the approach, a relation between the stimulus angular velocity and the excitation delay, and a mapping between membrane potential and firing frequency. Using this information, we propose a biophysical model of the mechanisms that regulate the encoding of looming stimuli. Furthermore, we found that the parameter encoded by the MLG1 firing frequency during the approach is the stimulus angular velocity. The proposed model fits the experimental results and predicts the neural response to a qualitatively different stimulus. Based on these and previous results, we propose that the MLG1 neuron system acts as a directional coding system for collision avoidance.

Coding space-time stimulus dynamics in auditory brain maps

Sensory maps are often distorted representations of the environment, where ethologically-important ranges are magnified. The implication of a biased representation extends beyond increased acuity for having more neurons dedicated to a certain range. Because neurons are functionally interconnected, non-uniform representations influence the processing of high-order features that rely on comparison across areas of the map. Among these features are time-dependent changes of the auditory scene generated by moving objects. How sensory representation affects high order processing can be approached in the map of auditory space of the owl's midbrain, where locations in the front are over-represented. In this map, neurons are selective not only to location but also to location over time. The tuning to space over time leads to direction selectivity, which is also topographically organized. Across the population, neurons tuned to peripheral space are more selective to sounds moving into the front. The distribution of direction selectivity can be explained by spatial and temporal integration on the non-uniform map of space. Thus, the representation of space can induce biased computation of a second-order stimulus feature. This phenomenon is likely observed in other sensory maps and may be relevant for behavior.

Spatiotemporal stimulus properties modulate responses to trajectory changes in a locust looming-sensitive pathway

The lobula giant movement detector (LGMD) and descending contralateral movement detector (DCMD) constitute one motion-sensitive pathway in the locust visual system that is implicated in collision-avoidance behaviors. While this pathway is thought to respond preferentially to objects approaching on a direct collision course, emerging studies suggest the firing rate is able to monitor more complicated movements that would occur under natural conditions. While previous studies have compared the response of the DCMD to objects on collision courses that travel at different speeds, velocity has not been manipulated for other simple or compound trajectories. Here we test the possibility that the LGMD/DCMD pathway is capable of responding uniquely to complex aspects of object motion, including translation and trajectory changes at different velocities. We found that the response of the DCMD to translational motion initiated in the caudal visual field was a low-amplitude peak in firing rate that occurred before the object crossed 90° azimuth that was invariant to different object velocities. Direct looms at different velocities resulted in peak firing rates that occurred later in time and with greater amplitude for higher velocities. In response to transitions from translational motion to a collision course, the firing rate change depended on both the location within the visual field and the velocity. These results suggest that this pathway is capable of conveying information about multiple properties of a moving object's trajectory.

Muscle group dependent responses to stimuli in a grasshopper model for tonic immobility

Tonic Immobility (TI) is a prolonged immobile condition exhibited by a variety of animals when exposed to certain stimuli, and is thought to be associated with a specific state of arousal. In our study, we characterize this state by using the reliably inducible TI state of the grasshopper (Hieroglyphus banian) and by monitoring abdominal pulsations and body movements in response to visual and auditory stimuli. These pulsations are present during the TI and ‘awake’, standing states, but not in the CO₂ anesthetized state. In response to the stimuli, animals exhibited a suppression in pulsation and a startle response. The suppression of pulsation lasted longer than the duration of stimulus application. During TI, the suppression of pulsation does not habituate over time, whereas the startle response does. In response to the translating visual stimulus, the pulsations are suppressed at a certain phase independent of the time of stimulus application. Thus, we describe TI in Hieroglyphus banian as a state more similar to an ‘awake’ state than to an anesthetized state. During TI, the circuitry to the muscle outputs controlling the abdomen pulsation and the startle response are, at least in some part, different. The central pattern generators that maintain the abdomen pulsation receive inputs from visual and auditory pathways.

Speed-invariant encoding of looming object distance requires power law spike rate adaptation

Neural representations of a moving object's distance and approach speed are essential for determining appropriate orienting responses, such as those observed in the localization behaviors of the weakly electric fish, Apteronotus leptorhynchus. We demonstrate that a power law form of spike rate adaptation transforms an electroreceptor afferent's response to "looming" object motion, effectively parsing information about distance and approach speed into distinct measures of the firing rate. Neurons with dynamics characterized by fixed time scales are shown to confound estimates of object distance and speed. Conversely, power law adaptation modifies an electroreceptor afferent's response according to the time scales present in the stimulus, generating a rate code for looming object distance that is invariant to speed and acceleration. Consequently, estimates of both object distance and approach speed can be uniquely determined from an electroreceptor afferent's firing rate, a multiplexed neural code operating over the extended time scales associated with behaviorally relevant stimuli.

Multiphasic on/off pheromone signalling in moths as neural correlates of a search strategy

Insects and robots searching for odour sources in turbulent plumes face the same problem: the random nature of mixing causes fluctuations and intermittency in perception. Pheromone-tracking male moths appear to deal with discontinuous flows of information by surging upwind, upon sensing a pheromone patch, and casting crosswind, upon losing the plume. Using a combination of neurophysiological recordings, computational modelling and experiments with a cyborg, we propose a neuronal mechanism that promotes a behavioural switch between surge and casting. We show how multiphasic On/Off pheromone-sensitive neurons may guide action selection based on signalling presence or loss of the pheromone. A Hodgkin-Huxley-type neuron model with a small-conductance calcium-activated potassium (SK) channel reproduces physiological On/Off responses. Using this model as a command neuron and the antennae of tethered moths as pheromone sensors, we demonstrate the efficiency of multiphasic patterning in driving a robotic searcher toward the source. Taken together, our results suggest that multiphasic On/Off responses may mediate olfactory navigation and that SK channels may account for these responses.

Looming detection by identified visual interneurons during larval development of the locust Locusta migratoria

Insect larvae clearly react to visual stimuli, but the ability of any visual neuron in a newly hatched insect to respond selectively to particular stimuli has not been directly tested. We characterised a pair of neurons in locust larvae that have been extensively studied in adults, where they are known to respond selectively to objects approaching on a collision course: the lobula giant motion detector (LGMD) and its postsynaptic partner, the descending contralateral motion detector (DCMD). Our physiological recordings of DCMD axon spikes reveal that at the time of hatching, the neurons already respond selectively to objects approaching the locust and they discriminate between stimulus approach speeds with differences in spike frequency. For a particular approaching stimulus, both the number and peak frequency of spikes increase with instar. In contrast, the number of spikes in responses to receding stimuli decreases with instar, so performance in discriminating approaching from receding stimuli improves as the locust goes through successive moults. In all instars, visual movement over one part of the visual field suppresses a response to movement over another part. Electron microscopy demonstrates that the anatomical substrate for the selective response to approaching stimuli is present in all larval instars: small neuronal processes carrying information from the eye make synapses both onto LGMD dendrites and with each other, providing pathways for lateral inhibition that shape selectivity for approaching objects.

Directional summation in non-direction selective retinal ganglion cells

Retinal ganglion cells receive inputs from multiple bipolar cells which must be integrated before a decision to fire is made. Theoretical studies have provided clues about how this integration is accomplished but have not directly determined the rules regulating summation of closely timed inputs along single or multiple dendrites. Here we have examined dendritic summation of multiple inputs along On ganglion cell dendrites in whole mount rat retina. We activated inputs at targeted locations by uncaging glutamate sequentially to generate apparent motion along On ganglion cell dendrites in whole mount retina. Summation was directional and dependent13 on input sequence. Input moving away from the soma (centrifugal) resulted in supralinear summation, while activation sequences moving toward the soma (centripetal) were linear. Enhanced summation for centrifugal activation was robust as it was also observed in cultured retinal ganglion cells. This directional summation was dependent on hyperpolarization activated cyclic nucleotide-gated (HCN) channels as blockade with ZD7288 eliminated directionality. A computational model confirms that activation of HCN channels can override a preference for centripetal summation expected from cell anatomy. This type of direction selectivity could play a role in coding movement similar to the axial selectivity seen in locust ganglion cells which detect looming stimuli. More generally, these results suggest that non-directional retinal ganglion cells can discriminate between input sequences independent of the retina network.

Visual information is coded by the output of retinal ganglion cells. Through evolution retinal ganglion cells acquired unique properties that allowed them to transmit to the brain such signals as direction of movement. The quest for the cellular mechanism of the detection of movement by retinal ganglion cells has been the holy grail of research on direction selectivity. In this study we have found a mechanism that allows individual non-direction selective On retinal ganglion cells to code sequences of excitatory inputs moving either away or toward the soma. We observed that inputs moving away from the soma resulted in enhanced, supralinear EPSP summation. Evidence from computational modeling suggests that expression of a specific set of voltage-dependent channels in dendrites introduces nonlinearities that could give a ganglion cell the ability to code looming motion. We predict that in a retinal network, such a directional tuning mechanism, together with asymmetric presynaptic inhibition, could be the building block for the development of more complex detection of visual motion.

Ca(V)1.3-driven SK channel activation regulates pacemaking and spike frequency adaptation in mouse chromaffin cells

Mouse chromaffin cells (MCCs) fire spontaneous action potentials (APs) at rest. Ca(v)1.3 L-type calcium channels sustain the pacemaker current, and their loss results in depolarized resting potentials (V(rest)), spike broadening, and remarkable switches into depolarization block after BayK 8644 application. A functional coupling between Ca(v)1.3 and BK channels has been reported but cannot fully account for the aforementioned observations. Here, using Ca(v)1.3(-/-) mice, we investigated the role of Ca(v)1.3 on SK channel activation and how this functional coupling affects the firing patterns induced by sustained current injections. MCCs express SK1-3 channels whose tonic currents are responsible for the slow irregular firing observed at rest. Percentage of frequency increase induced by apamin was found inversely correlated to basal firing frequency. Upon stimulation, MCCs build-up Ca(v)1.3-dependent SK currents during the interspike intervals that lead to a notable degree of spike frequency adaptation (SFA). The major contribution of Ca(v)1.3 to the subthreshold Ca(2+) charge during an AP-train rather than a specific molecular coupling to SK channels accounts for the reduced SFA of Ca(v)1.3(-/-) MCCs. Low adaptation ratios due to reduced SK activation associated with Ca(v)1.3 deficiency prevent the efficient recovery of Na(V) channels from inactivation. This promotes a rapid decline of AP amplitudes and facilitates early onset of depolarization block following prolonged stimulation. Thus, besides serving as pacemaker, Ca(v)1.3 slows down MCC firing by activating SK channels that maintain Na(V) channel availability high enough to preserve stable AP waveforms, even upon high-frequency stimulation of chromaffin cells during stress responses.

20Hz membrane potential oscillations are driven by synaptic inputs in collision-detecting neurons in the frog optic tectum

Although the firing patterns of collision-detecting neurons have been described in detail in several species, the mechanisms generating responses in these neurons to visual objects on a collision course remain largely unknown. This is partly due to the limited number of intracellular recordings from such neurons, particularly in vertebrate species. By employing patch recordings in a novel integrated frog eye-tectum preparation we tested the hypothesis that OFF retinal ganglion cells were driving the responses to visual objects on a collision course in the frog optic tectum neurons. We found that the majority (22/26) of neurons in layer 6 responding to visual stimuli fitted the definition of η class collision-detectors: they readily responded to a looming stimulus imitating collision but not a receding stimulus (spike count difference ∼10 times) and the spike firing rate peaked after the stimulus visual angle reached a threshold value of ∼20-45°. In the majority of these neurons (15/22) a slow frequency oscillation (f=∼20Hz) of the neuronal membrane potential could be detected in the responses to a simulated collision stimulus, as well as to turning off the lights. Since OFF retinal ganglion cells could produce such oscillations, our observations are in agreement with the hypothesis that 'collision' responses in the frog optic tectum neurons are driven by synaptic inputs from OFF retinal ganglion cells.

A looming-sensitive pathway responds to changes in the trajectory of object motion

Two identified locust neurons, the lobula giant movement detector (LGMD) and its postsynaptic partner, the descending contralateral movement detector (DCMD), constitute one motion-sensitive pathway in the visual system that responds preferentially to objects that approach on a direct collision course and are implicated in collision-avoidance behavior. Previously described responses to the approach of paired objects and approaches at different time intervals (Guest BB, Gray JR. J Neurophysiol 95: 1428–1441, 2006) suggest that this pathway may also be affected by more complicated movements in the locust's visual environment. To test this possibility we presented stationary locusts with disks traveling along combinations of colliding (looming), noncolliding (translatory), and near-miss trajectories. Distinctly different responses to different trajectories and trajectory changes demonstrate that DCMD responds to complex aspects of local visual motion. DCMD peak firing rates associated with the time of collision remained relatively invariant after a trajectory change from translation to looming. Translatory motion initiated in the frontal visual field generated a larger peak firing rate relative to object motion initiated in the posterior visual field, and the peak varied with simulated distance from the eye. Transition from translation to looming produced a transient decrease in the firing rate, whereas transition away from looming produced a transient increase. The change in firing rate at the time of transition was strongly correlated with unique expansion parameters described by the instantaneous angular acceleration of the leading edge and subtense angle of the disk. However, response time remained invariant. While these results may reflect low spatial resolution of the compound eye, they also suggest that this motion-sensitive pathway may be capable of monitoring dynamic expansion properties of objects that change the trajectory of motion.

Sub- and suprathreshold adaptation currents have opposite effects on frequency tuning

Natural stimuli are often characterized by statistics that can vary over orders of magnitude. Experiments have shown that sensory neurons continuously adapt their responses to changes in these statistics, thereby optimizing information transmission. However, such adaptation can also alter the neuronal transfer function by attenuating if not eliminating responses to the low frequency components of time varying stimuli,which can create ambiguity in the neural code. We recorded from electrosensory pyramidal neurons before and after pharmacological inactivation of either calcium-activated (I(AHP)) or KCNQ voltage-gated potassium currents (I(M)). We found that blocking each current decreased adaptation in a similar fashion but led to opposite changes in the neuronal transfer function. Indeed, blocking I(AHP) increased while blocking I(M) instead decreased the response to low temporal frequencies. To understand this surprising result, we built a mathematical model incorporating each channel type. This model predicted that these differential effects could be accounted for by differential activation properties. Our results show that the mechanisms that mediate adaptation can either increase or decrease the response to low frequency stimuli. As such, they suggest that the nervous system resolves ambiguity resulting from adaptation through independent control of adaptation and the neuronal transfer function.

Impact of neural noise on a sensory-motor pathway signaling impending collision

Noise is a major concern in circuits processing electrical signals, including neural circuits. There are many factors that influence how noise propagates through neural circuits, and there are few systems in which noise levels have been studied throughout a processing pathway. We recorded intracellularly from multiple stages of a sensory-motor pathway in the locust that detects approaching objects. We found that responses are more variable and that signal-to-noise ratios (SNRs) are lower further from the sensory periphery. SNRs remain low even with the use of stimuli for which the pathway is most selective and for which the neuron representing its final sensory level must integrate many synaptic inputs. Modeling of this neuron shows that variability in the strength of individual synaptic inputs within a large population has little effect on the variability of the spiking output. In contrast, jitter in the timing of individual inputs and spontaneous variability is important for shaping the responses to preferred stimuli. These results suggest that neural noise is inherent to the processing of visual stimuli signaling impending collision and contributes to shaping neural responses along this sensory-motor pathway.

Interaction of cellular and network mechanisms for efficient pheromone coding in moths

Sensory systems, both in the living and in machines, have to be optimized with respect to their environmental conditions. The pheromone subsystem of the olfactory system of moths is a particularly well-defined example in which rapid variations of odor content in turbulent plumes require fast, concentration-invariant neural representations. It is not clear how cellular and network mechanisms in the moth antennal lobe contribute to coding efficiency. Using computational modeling, we show that intrinsic potassium currents (I(A) and I(SK)) in projection neurons may combine with extrinsic inhibition from local interneurons to implement a dual latency code for both pheromone identity and intensity. The mean latency reflects stimulus intensity, whereas latency differences carry concentration-invariant information about stimulus identity. In accordance with physiological results, the projection neurons exhibit a multiphasic response of inhibition-excitation-inhibition. Together with synaptic inhibition, intrinsic currents I(A) and I(SK) account for the first and second inhibitory phases and contribute to a rapid encoding of pheromone information. The first inhibition plays the role of a reset to limit variability in the time to first spike. The second inhibition prevents responses of excessive duration to allow tracking of intermittent stimuli.

Collision detection as a model for sensory-motor integration

Visually guided collision avoidance is critical for the survival of many animals. The execution of successful collision-avoidance behaviors requires accurate processing of approaching threats by the visual system and signaling of threat characteristics to motor circuits to execute appropriate motor programs in a timely manner. Consequently, visually guided collision avoidance offers an excellent model with which to study the neural mechanisms of sensory-motor integration in the context of a natural behavior. Neurons that selectively respond to approaching threats and brain areas processing them have been characterized across many species. In locusts in particular, the underlying sensory and motor processes have been analyzed in great detail: These animals possess an identified neuron, called the LGMD, that responds selectively to approaching threats and conveys that information through a second identified neuron, the DCMD, to motor centers, generating escape jumps. A combination of behavioral and in vivo electrophysiological experiments has unraveled many of the cellular and network mechanisms underlying this behavior.

Onset of negative interspike interval correlations in adapting neurons

Negative serial correlations in single spike trains are an effective method to reduce the variability of spike counts. One of the factors contributing to the development of negative correlations between successive interspike intervals is the presence of adaptation currents. In this work, based on a hidden Markov model and a proper statistical description of conditional responses, we obtain analytically these correlations in an adequate dynamical neuron model resembling adaptation. We derive the serial correlation coefficients for arbitrary lags, under a small adaptation scenario. In this case, the behavior of correlations is universal and depends on the first-order statistical description of an exponentially driven time-inhomogeneous stochastic process.

Potencial de ação: do estímulo à adaptação neural

INTRODUÇÃO: O potencial de ação (PA) origina-se graças a uma perturbação do estado de repouso da membrana celular, com consequente fluxo de íons, por meio da membrana e alteração da concentração iônica nos meios intra e extracelular. OBJETIVOS: Sintetizar o conhecimento científico acumulado até o presente sobre o potencial de ação neural e o seu processo de adaptação sob aplicação de um estímulo constante. MATERIAIS E MÉTODOS: Busca realizada nas bases Springer, ScienceDirect, PubMed, IEEE Xplore, Google Acadêmico, Portal de Periódicos da Capes, além de livros referentes ao assunto. O idioma de preferência selecionado foi o inglês, com as keywords: action potential; adaptation; accommodation; rheobase; chronaxy; nerve impulse. Efetuou-se a procura de artigos com uma janela de tempo de 1931 a 2010 e livros de 1791 a 2007. RESULTADOS: Dos trabalhos selecionados, foram extraídas informações a respeito dos seguintes tópicos: potencial de ação e suas fases; condução nervosa; reobase; cronaxia; acomodação; e adaptação neuronal. CONCLUSÃO: Um estímulo que crie PA, se aplicado de maneira constante, pode reduzir a frequência de despolarizações em função do tempo e, consequentemente, adaptar a célula. O tempo que a célula demora, na ausência de estímulos, para recuperar sua frequência original é definido como desadaptação.

Roadside judgments in children with Developmental Co-ordination Disorder

As pedestrians, the perceptual ability to accurately judge the relative rate of approaching vehicles and select a suitable crossing gap requires sensitivity to looming. It also requires that crossing judgments are synchronized with motoric capabilities. Previous research has suggested that children with Developmental Co-ordination Disorder (DCD) may have deficits in visual processing, specifically in detecting visual motion. It is possible, therefore that this population are at greater risk at the roadside. In a series of motion prediction tasks, several component roadside skills were assessed in 15 children with DCD, or at risk of DCD, aged between 6 and 11 years along with 15 typically developing age and gender matched controls. First, threshold errors for relative approach rate judgments (looming) were measured when vehicle size (car or truck) varied. Second, thresholds for crossing gap selection were measured for vehicle approach speeds of 32, 48, 64 and 80 km/h (20-50 mph). These were related to the walking speeds of children of different ages and profiles. We found that children with DCD showed a deficit in making relative approach rate judgments, using looming, which suggests they may not discern that a vehicle is travelling faster than the urban speed limit. Children with DCD also left considerably longer temporal crossing gaps than controls perhaps reflecting a lack of confidence in their ability, these preferred gaps were over twice the average inter-car gaps that occurred on roads around their school. Our findings raise a number of issues concerning children with DCD and their competence and potential limitations as pedestrians.

Nonrenewal spike train statistics: causes and functional consequences on neural coding

Many neurons display significant patterning in their spike trains (e.g. oscillations, bursting), and there is accumulating evidence that information is contained in these patterns. In many cases, this patterning is caused by intrinsic mechanisms rather than external signals. In this review, we focus on spiking activity that displays nonrenewal statistics (i.e. memory that persists from one firing to the next). Such statistics are seen in both peripheral and central neurons and appear to be ubiquitous in the CNS. We review the principal mechanisms that can give rise to nonrenewal spike train statistics. These are separated into intrinsic mechanisms such as relative refractoriness and network mechanisms such as coupling with delayed inhibitory feedback. Next, we focus on the functional roles for nonrenewal spike train statistics. These can either increase or decrease information transmission. We also focus on how such statistics can give rise to an optimal integration timescale at which spike train variability is minimal and how this might be exploited by sensory systems to maximize the detection of weak signals. We finish by pointing out some interesting future directions for research in this area. In particular, we explore the interesting possibility that synaptic dynamics might be matched with the nonrenewal spiking statistics of presynaptic spike trains in order to further improve information transmission.

Reduced sensitivity to visual looming inflates the risk posed by speeding vehicles when children try to cross the road

Almost all locomotor animals respond to visual looming or to discrete changes in optical size. The need to detect and process looming remains critically important for humans in everyday life. Road traffic statistics confirm that children up to 15 years old are overrepresented in pedestrian casualties. We demonstrate that, for a given pedestrian crossing time, vehicles traveling faster loom less than slower vehicles, which creates a dangerous illusion in which faster vehicles may be perceived as not approaching. Our results from perceptual tests of looming thresholds show strong developmental trends in sensitivity, such that children may not be able to detect vehicles approaching at speeds in excess of 20 mph. This creates a risk of injudicious road crossing in urban settings when traffic speeds are higher than 20 mph. The risk is exacerbated because vehicles moving faster than this speed are more likely to result in pedestrian fatalities.

Linear versus nonlinear signal transmission in neuron models with adaptation currents or dynamic thresholds

Spike-frequency adaptation is a prominent aspect of neuronal dynamics that shapes a neuron's signal processing properties on timescales ranging from about 10 ms to >1 s. For integrate-and-fire model neurons spike-frequency adaptation is incorporated either as an adaptation current or as a dynamic firing threshold. Whether a physiologically observed adaptation mechanism should be modeled as an adaptation current or a dynamic threshold, however, is not known. Here we show that a dynamic threshold has a divisive effect on the onset f-I curve (the initial maximal firing rate following a step increase in an input current) measured at increasing mean threshold levels, i.e., adaptation states. In contrast, an adaptation current subtractively shifts this f-I curve to higher inputs without affecting its slope. As a consequence, an adaptation current acts essentially linearly, resulting in a high-pass filter component of the neuron's transfer function for current stimuli. With a dynamic threshold, however, the transfer function strongly depends on the input range because of the multiplicative effect on the f-I curves. Simulations of conductance-based spiking models with adaptation currents, such as afterhyperpolarization (AHP)-type, M-type, and sodium-activated potassium currents, do not show the divisive effects of a dynamic threshold, but agree with the properties of integrate-and-fire neurons with adaptation current. Notably, the effects of slow inactivation of sodium currents cannot be reproduced by either model. Our results suggest that, when lateral shifts of the onset f-I curve are seen in response to adapting inputs, adaptation should be modeled with adaptation currents and not with a dynamic threshold. In contrast, when the slope of onset f-I curves depends on the adaptation state, then adaptation should be modeled with a dynamic threshold. Further, the observation of divisively altered onset f-I curves in adapted neurons with notable variability of their spike threshold could hint to yet known biophysical mechanisms directly affecting the threshold.

Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron's sensory response to impending collision-firing rate threshold, peak firing time, and spike count-probably control three distinct motor aspects of escape behaviors.

How noisy adaptation of neurons shapes interspike interval histograms and correlations

Channel noise is the dominant intrinsic noise source of neurons causing variability in the timing of action potentials and interspike intervals (ISI). Slow adaptation currents are observed in many cells and strongly shape response properties of neurons. These currents are mediated by finite populations of ionic channels and may thus carry a substantial noise component. Here we study the effect of such adaptation noise on the ISI statistics of an integrate-and-fire model neuron by means of analytical techniques and extensive numerical simulations. We contrast this stochastic adaptation with the commonly studied case of a fast fluctuating current noise and a deterministic adaptation current (corresponding to an infinite population of adaptation channels). We derive analytical approximations for the ISI density and ISI serial correlation coefficient for both cases. For fast fluctuations and deterministic adaptation, the ISI density is well approximated by an inverse Gaussian (IG) and the ISI correlations are negative. In marked contrast, for stochastic adaptation, the density is more peaked and has a heavier tail than an IG density and the serial correlations are positive. A numerical study of the mixed case where both fast fluctuations and adaptation channel noise are present reveals a smooth transition between the analytically tractable limiting cases. Our conclusions are furthermore supported by numerical simulations of a biophysically more realistic Hodgkin-Huxley type model. Our results could be used to infer the dominant source of noise in neurons from their ISI statistics.

Synchronized neural input shapes stimulus selectivity in a collision-detecting neuron

How higher-order sensory neurons generate complex selectivity from their simpler inputs is a fundamental question in neuroscience. The lobula giant movement detector (LGMD) is such a visual neuron in the locust Schistocerca americana that responds selectively to objects approaching on a collision course or their two-dimensional projections, looming stimuli [1-4]. To study how this selectivity arises, we designed an apparatus allowing us to stimulate, individually and independently, a sizable fraction of the ∼15,000 elementary visual inputs impinging retinotopically onto the LGMD's dendritic fan [5-7] (Figure 1Ai). We then recorded intracellularly in vivo throughout the visual pathway, assessing the LGMD's activity and that of all three successive presynaptic stages conveying local excitatory inputs. Our results suggest that as collision becomes increasingly imminent, the strength of these inputs increases, whereas their latency decreases. This latency decrease favors summation of inputs activated sequentially throughout the looming sequence, making the neuron maximally sensitive to collision-bound trajectories. Thus, the LGMD's selectivity arises partially from presynaptic mechanisms that synchronize a large population of inputs during a looming stimulus and subsequent detection by postsynaptic mechanisms within the neuron itself. Analogous mechanisms are likely to underlie the tuning properties of visual neurons in other species as well.

Collision-Sensitive Neurons in the Optic Tectum of the Bullfrog, Rana catesbeiana

In this study, we examined the neuronal correlates of frog collision avoidance behavior. Single unit recordings in the optic tectum showed that 11 neurons gave selective responses to objects approaching on a direct collision course. The collision-sensitive neurons exhibited extremely tight tuning for collision bound trajectories with mean half-width at half height values of 0.8 and 0.9° ( n = 4) for horizontal and vertical deviations, respectively. The response of frog collision-sensitive neurons can be fitted by a function that simply multiplies the size dependence of its response, e−αθ( t), by the image's instantaneous angular velocity θ′( t). Using fitting analysis, we showed that the peak firing rate always occurred after the approaching object had reached a constant visual angle of 24.2 ± 2.6° (mean ± SD; n = 8), regardless of the approaching velocity. Moreover, a linear relationship was demonstrated between parameters l/v ( l: object's half-size, v: approach velocity) and time-to-collision (time difference between peak neuronal activity and the predicted collision) in the 11 collision-sensitive neurons. In addition, linear regression analysis was used to show that peak firing rate always occurred after the object had reached a constant angular size of 21.1° on the retina. The angular thresholds revealed by both theoretical analyses were comparable and showed a good agreement with that revealed by our previous behavioral experiments. This strongly suggests that the collision-sensitive neurons of the frog comprise a threshold detector, which triggers collision avoidance behavior.

Neural processing of imminent collision in humans

Detecting a looming object and its imminent collision is imperative to survival. For most humans, it is a fundamental aspect of daily activities such as driving, road crossing and participating in sport, yet little is known about how the brain both detects and responds to such stimuli. Here we use functional magnetic resonance imaging to assess neural response to looming stimuli in comparison with receding stimuli and motion-controlled static stimuli. We demonstrate for the first time that, in the human, the superior colliculus and the pulvinar nucleus of the thalamus respond to looming in addition to cortical regions associated with motor preparation. We also implicate the anterior insula in making timing computations for collision events.

Sparse but specific temporal coding by spikes in an insect sensory-motor ocellar pathway

We investigate coding in a locust brain neuron, DNI, which transforms graded synaptic input from ocellar L-neurons into axonal spikes that travel to excite particular thoracic flight neurons. Ocellar neurons are naturally stimulated by fluctuations in light collected from a wide field of view, for example when the visual horizon moves up and down. We used two types of stimuli: fluctuating light from a light-emitting diode (LED), and a visual horizon displayed on an electrostatic monitor. In response to randomly fluctuating light stimuli delivered from the LED, individual spikes in DNI occur sparsely but are timed to sub-millisecond precision, carrying substantial information: 4.5–7 bits per spike in our experiments. In response to these light stimuli, the graded potential signal in DNI carries considerably less information than in presynaptic L-neurons. DNI is excited in phase with either sinusoidal light from an LED or a visual horizon oscillating up and down at 20 Hz, and changes in mean light level or mean horizon level alter the timing of excitation for each cycle. DNI is a multimodal interneuron, but its ability to time spikes precisely in response to ocellar stimulation is not degraded by additional excitation. We suggest that DNI is part of an optical proprioceptor system, responding to the optical signal induced in the ocelli by nodding movements of the locust head during each wing-beat.

Escapes with and without preparation: the neuroethology of visual startle in locusts

Locusts respond to the images of approaching (looming) objects with responses that include gliding while in flight and jumping while standing. For both of these responses there is good evidence that the DCMD neuron (descending contralateral movement detector), which carries spike trains from the brain to the thoracic ganglia, is involved. Sudden glides during flight, which cause a rapid loss of height, are last-chance manoeuvres without prior preparation. Jumps from standing require preparation over several tens of milliseconds because of the need to store muscle-derived energy in a catapult-like mechanism. Locusts' DCMD neurons respond selectively to looming stimuli, and make connections with some motor neurons and interneurons known to be involved in flying and jumping. For glides, a burst of high-frequency DCMD spikes is a key trigger. For jumping, a similar burst can influence timing, but neither the DCMD nor any other single interneuron has been shown to be essential for triggering any stage in preparation or take-off. Responses by the DCMD to looming stimuli can alter in different behavioural contexts: in a flying locust, arousal ensures a high level of both DCMD responsiveness and glide occurrence; and there are significant differences in DCMD activity between locusts in the gregarious and the solitarious phase.

Non-linear neuronal responses as an emergent property of afferent networks: a case study of the locust lobula giant movement detector

In principle it appears advantageous for single neurons to perform non-linear operations. Indeed it has been reported that some neurons show signatures of such operations in their electrophysiological response. A particular case in point is the Lobula Giant Movement Detector (LGMD) neuron of the locust, which is reported to locally perform a functional multiplication. Given the wide ramifications of this suggestion with respect to our understanding of neuronal computations, it is essential that this interpretation of the LGMD as a local multiplication unit is thoroughly tested. Here we evaluate an alternative model that tests the hypothesis that the non-linear responses of the LGMD neuron emerge from the interactions of many neurons in the opto-motor processing structure of the locust. We show, by exposing our model to standard LGMD stimulation protocols, that the properties of the LGMD that were seen as a hallmark of local non-linear operations can be explained as emerging from the dynamics of the pre-synaptic network. Moreover, we demonstrate that these properties strongly depend on the details of the synaptic projections from the medulla to the LGMD. From these observations we deduce a number of testable predictions. To assess the real-time properties of our model we applied it to a high-speed robot. These robot results show that our model of the locust opto-motor system is able to reliably stabilize the movement trajectory of the robot and can robustly support collision avoidance. In addition, these behavioural experiments suggest that the emergent non-linear responses of the LGMD neuron enhance the system's collision detection acuity. We show how all reported properties of this neuron are consistently reproduced by this alternative model, and how they emerge from the overall opto-motor processing structure of the locust. Hence, our results propose an alternative view on neuronal computation that emphasizes the network properties as opposed to the local transformations that can be performed by single neurons.

The tiny brains of insects of about 1mm³ smoothly control a flying platform while avoiding obstacles, regulating its distance to objects and search for objects of interest. This is largely achieved through a complex hierarchical processing of signals from the multitude of ommatidia in their eye to a set of highly specialized neurons that are optimized to respond to specific properties of the visual world. One of these neurons, the Lobula Giant Movement Detector (LGMD) of the locust, has been recently shown to perform a functional multiplication of its synaptic inputs. If true, that would make the LGMD neuron a unique and highly sophisticated neuron that raises questions about the non-linear operations other neurons in other neuronal systems would be able to perform. Hence it is crucial to understand its properties, its role in behaviour and to evaluate whether its responses can be explained in simpler terms. Our results emphasize the role of network architecture and distributed computation as opposed to local complex non-linear computation. We show that our model reliably reproduces the known properties of the LGMD and can be used to control a high-speed robot.

Spatiotemporal receptive field properties of a looming-sensitive neuron in solitarious and gregarious phases of the desert locust

Desert locusts (Schistocerca gregaria) can transform reversibly between the swarming gregarious phase and a solitarious phase, which avoids other locusts. This transformation entails dramatic changes in morphology, physiology, and behavior. We have used the lobula giant movement detector (LGMD) and its postsynaptic target, the descending contralateral movement detector (DCMD), which are visual interneurons that detect looming objects, to analyze how differences in the visual ecology of the two phases are served by altered neuronal function. Solitarious locusts had larger eyes and a greater degree of binocular overlap than those of gregarious locusts. The receptive field to looming stimuli had a large central region of nearly equal response spanning 120 degrees x 60 degrees in both phases. The DCMDs of gregarious locusts responded more strongly than solitarious locusts and had a small caudolateral focus of even further sensitivity. More peripherally, the response was reduced in both phases, particularly ventrally, with gregarious locusts showing greater proportional decrease. Gregarious locusts showed less habituation to repeated looming stimuli along the eye equator than did solitarious locusts. By contrast, in other parts of the receptive field the degree of habituation was similar in both phases. The receptive field organization to looming stimuli contrasts strongly with the receptive field organization of the same neurons to nonlooming local-motion stimuli, which show much more pronounced regional variation. The DCMDs of both gregarious and solitarious locusts are able to detect approaching objects from across a wide expanse of visual space, but phase-specific changes in the spatiotemporal receptive field are linked to lifestyle changes.

Precise subcellular input retinotopy and its computational consequences in an identified visual interneuron

The Lobula Giant Movement Detector (LGMD) is a higher-order visual interneuron of Orthopteran insects that responds preferentially to objects approaching on a collision course. It receives excitatory input from an entire visual hemifield that anatomical evidence suggests is retinotopic. We show that this excitatory projection activates calcium-permeable nicotinic acetylcholine receptors. In vivo calcium imaging reveals that the excitatory projection preserves retinotopy down to the level of a single ommatidium. Examining the impact of retinotopy on the LGMD's computational properties, we show that sublinear synaptic summation can explain orientation preference in this cell. Exploring retinotopy's impact on directional selectivity leads us to infer that the excitatory input to the LGMD is intrinsically directionally selective. Our results show that precise retinotopy has implications for the dendritic integration of visual information in a single neuron.

Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli

Spike-frequency adaptation is the reduction of a neuron's firing rate to a stimulus of constant intensity. In the locust, the Lobula Giant Movement Detector (LGMD) is a visual interneuron that exhibits rapid adaptation to both current injection and visual stimuli. Here, a reduced compartmental model of the LGMD is employed to explore adaptation's role in selectivity for stimuli whose intensity changes with time. We show that supralinearly increasing current injection stimuli are best at driving a high spike count in the response, while linearly increasing current injection stimuli (i.e., ramps) are best at attaining large firing rate changes in an adapting neuron. This result is extended with in vivo experiments showing that the LGMD's response to translating stimuli having a supralinear velocity profile is larger than the response to constant or linearly increasing velocity translation. Furthermore, we show that the LGMD's preference for approaching versus receding stimuli can partly be accounted for by adaptation. Finally, we show that the LGMD's adaptation mechanism appears well tuned to minimize sensitivity for the level of basal input.