Representation of sensory information in the cricket cercal sensory system. I. Response properties of the primary interneurons

Motor state changes escape behavior of crickets

Animals change their behavior depending on external circumstances, internal factors, and their interactions. Locomotion state is a crucial internal factor that profoundly affects sensory perception and behavior. However, studying the behavioral impacts of locomotion state in free-moving animals has been challenging due to difficulty in reproducing quantitatively identical stimuli in freely moving animals. We utilized a closed-loop controlled servosphere treadmill system, enabling unrestricted confinement and orientation of small animals, and investigated wind-induced escape behavior in freely moving crickets. When stimulated during locomotion, the crickets quickly stopped before initiating escape behavior. Moving crickets exhibited a higher probability of escape response compared to stationary crickets. The threshold for pausing response in moving crickets was also much lower than the escape response threshold. Moving crickets had delayed reaction times for escape and greater variance in movement direction compared to stationary crickets. The locomotion-related response delay may be compensated by an elevated sensitivity to airflow.

The self as part of the sensory ecology: how behavior affects sensation from the inside out

Insects exhibit remarkable sensory and motor capabilities to successfully navigate their environment. As insects move, they activate sensory afferents. Hence, insects are inextricably part of their sensory ecology. Insects must correctly attribute self- versus external sources of sensory activation to make adaptive behavioral choices. This is achieved via corollary discharge circuits (CDCs), motor-to-sensory neuronal pathways providing predictive motor signals to sensory networks to coordinate sensory processing within the context of ongoing behavior. While CDCs provide predictive motor signals, their underlying mechanisms of action and functional consequences are diverse. Here, we describe inferred CDCs and identified corollary discharge interneurons (CDIs) in insects, highlighting their anatomical commonalities and our limited understanding of their synaptic integration into the nervous system. By using connectomics information, we demonstrate that the complexity with which identified CDIs integrate into the central nervous system (CNS) can be revealed.

Disrupted visual input unveils the computational details of artificial neural networks for face perception

Background

Convolutional Neural Network (DCNN), with its great performance, has attracted attention of researchers from many disciplines. The studies of the DCNN and that of biological neural systems have inspired each other reciprocally. The brain-inspired neural networks not only achieve great performance but also serve as a computational model of biological neural systems.

Methods

Here in this study, we trained and tested several typical DCNNs (AlexNet, VGG11, VGG13, VGG16, DenseNet, MobileNet, and EfficientNet) with a face ethnicity categorization task for experiment 1, and an emotion categorization task for experiment 2. We measured the performance of DCNNs by testing them with original and lossy visual inputs (various kinds of image occlusion) and compared their performance with human participants. Moreover, the class activation map (CAM) method allowed us to visualize the foci of the "attention" of these DCNNs.

Results

The results suggested that the VGG13 performed the best: Its performance closely resembled human participants in terms of psychophysics measurements, it utilized similar areas of visual inputs as humans, and it had the most consistent performance with inputs having various kinds of impairments.

Discussion

In general, we examined the processing mechanism of DCNNs using a new paradigm and found that VGG13 might be the most human-like DCNN in this task. This study also highlighted a possible paradigm to study and develop DCNNs using human perception as a benchmark.

Roles of neural communication between the brain and thoracic ganglia in the selection and regulation of the cricket escape behavior

To survive a predator's attack, prey animals must exhibit escape responses that are appropriately regulated in terms of their moving speed, distance, and direction. Insect locomotion is considered to be controlled by an interaction between the brain, which is involved in behavioral decision-making, and the thoracic ganglia (TG), which are primary motor centers. However, it remains unknown which descending and ascending signals between these neural centers are involved in the regulation of the escape behavior. We addressed the distinct roles of the brain and TG in the wind-elicited escape behavior of crickets by assessing the effects of partial ablation of the intersegmental communications on escape responses. We unilaterally cut the ventral nerve cord (VNC) at different locations, between the brain and TG, or between the TG and terminal abdominal ganglion (TAG), a primary sensory center of the cercal system. The partial ablation of ascending signals to the brain greatly reduced the jumping response rather than running, indicating that sensory information processing in the brain is essential for the choice of escape responses. The ablation of descending signals from the brain to the TG impaired locomotor performance and directional control of the escape responses, suggesting that locomotion in the escape behavior largely depends on the descending signals from the brain. Finally, the extracellular recording from the cervical VNC indicated a difference in the descending activities preceding the escape responses between running and jumping. Our results demonstrated that the brain sends the descending signals encoding the behavioral choice and locomotor regulation to the TG, while the TG seem to have other specific roles, such as in the preparation of escape movement.

ENCODING OF SMALL-SCALE AIR MOTION DYNAMICS IN THE CRICKET ACHETA DOMESTICUS

The cercal sensory system of the cricket mediates the detection, localization and identification of air current signals generated by predators, mates and competitors. This mechanosensory system has been used extensively for experimental and theoretical studies of sensory coding at the cellular and system levels. It is currently thought that sensory interneurons in the terminal abdominal ganglion extract information about the direction, velocity, and acceleration of the air currents in the animal's immediate environment, and project a coarse-coded representation of those parameters to higher centers. All feature detection is thought to be carried out in higher ganglia by more complex, specialized circuits. We present results that force a substantial revision of current hypotheses. Using multiple extracellular recordings and a special sensory stimulation device, we demonstrate that four well-studied interneurons in this system respond with high sensitivity and selectivity to complex dynamic multi-directional features of air currents which have a spatial scale smaller than the physical dimensions of the cerci. The INs showed much greater sensitivity for these features than for unidirectional bulk-flow stimuli used in previous studies. Thus, in addition to participating in the ensemble encoding of bulk air flow stimulus characteristics, these interneurons are capable of operating as feature detectors for naturalistic stimuli. In this sense, these interneurons are encoding and transmitting information about different aspects of their stimulus environment: they are multiplexing information. Major aspects of the stimulus-response specificity of these interneurons can be understood from the dendritic anatomy and connectivity with the sensory afferent map.

Action selection based on multiple-stimulus aspects in wind-elicited escape behavior of crickets

Escape behavior is essential for animals to avoid attacks by predators. In some species, multiple escape responses could be employed. However, it remains unknown what aspects of threat stimuli affect the choice of an escape response. We focused on two distinct escape responses (running and jumping) to short airflow in crickets and examined the effects of multiple stimulus aspects including the angle, velocity, and duration on the choice between these responses. The faster and longer the airflow, the more frequently the crickets jumped. This meant that the choice of an escape response depends on both the velocity and duration of the stimulus and suggests that the neural basis for choosing an escape response includes the integration process of multiple stimulus parameters. In addition, the moving speed and distance changed depending on the stimulus velocity and duration for running but not for jumping. Running away would be more adaptive escape behavior.

Bio-Inspired Architectures Substantially Reduce the Memory Requirements of Neural Network Models

We propose a neural network model for the jumping escape response behavior observed in the cricket cercal sensory system. This sensory system processes low-intensity air currents in the animal's immediate environment generated by predators, competitors, and mates. Our model is inspired by decades of physiological and anatomical studies. We compare the performance of our model with a model derived through a universal approximation, or a generic deep learning, approach, and demonstrate that, to achieve the same performance, these models required between one and two orders of magnitude more parameters. Furthermore, since the architecture of the bio-inspired model is defined by a set of logical relations between neurons, we find that the model is open to interpretation and can be understood. This work demonstrates the potential of incorporating bio-inspired architectural motifs, which have evolved in animal nervous systems, into memory efficient neural network models.

Toward a Unified Framework for Cognitive Maps

In this study, we integrated neural encoding and decoding into a unified framework for spatial information processing in the brain. Specifically, the neural representations of self-location in the hippocampus (HPC) and entorhinal cortex (EC) play crucial roles in spatial navigation. Intriguingly, these neural representations in these neighboring brain areas show stark differences. Whereas the place cells in the HPC fire as a unimodal function of spatial location, the grid cells in the EC show periodic tuning curves with different periods for different subpopulations (called modules). By combining an encoding model for this modular neural representation and a realistic decoding model based on belief propagation, we investigated the manner in which self-location is encoded by neurons in the EC and then decoded by downstream neurons in the HPC. Through the results of numerical simulations, we first show the positive synergy effects of the modular structure in the EC. The modular structure introduces more coupling between heterogeneous modules with different periodicities, which provides increased error-correcting capabilities. This is also demonstrated through a comparison of the beliefs produced for decoding two- and four-module codes. Whereas the former resulted in a complete decoding failure, the latter correctly recovered the self-location even from the same inputs. Further analysis of belief propagation during decoding revealed complex dynamics in information updates due to interactions among multiple modules having diverse scales. Therefore, the proposed unified framework allows one to investigate the overall flow of spatial information, closing the loop of encoding and decoding self-location in the brain.

Trade-off between motor performance and behavioural flexibility in the action selection of cricket escape behaviour

To survive a predator’s attack successfully, animals choose appropriate actions from multiple escape responses. The motor performance of escape response governs successful survival, which implies that the action selection in escape behaviour is based on the trade-off between competing behavioural benefits. Thus, quantitative assessment of motor performance will shed light on the biological basis of decision-making. To explore the trade-off underlying the action selection, we focused on two distinct wind-elicited escape responses of crickets, running and jumping. We first hypothesized a trade-off between speed and directional accuracy. This hypothesis was rejected because crickets could control the escape direction in jumping as precisely as in running; further, jumping had advantages with regard to escape speed. Next, we assumed behavioural flexibility, including responsiveness to additional predator’s attacks, as a benefit of running. The double stimulus experiment revealed that crickets running in the first response could respond more frequently to a second stimulus and control the movement direction more precisely compared to when they chose jumping for the first response. These data suggest that not only the motor performance but also the future adaptability of subsequent behaviours are considered as behavioural benefits, which may be used for choosing appropriate escape reactions.

Nonlinearization: naturalistic stimulation and nonlinear dynamic behavior in a spider mechanoreceptor

In a previous study, we used linear frequency response analysis to show that naturalistic stimulation of spider primary mechanosensory neurons produced different response dynamics than the commonly used Gaussian random noise. We isolated this difference to the production of action potentials from receptor potential and suggested that the different distribution of frequency components in the naturalistic signal increased the nonlinearity of action potential encoding. Here, we tested the relative contributions of first- and second-order processes to the action potential signal by measuring linear and quadratic coherence functions. Naturalistic stimulation shifted the linear coherence toward lower frequencies, while quadratic coherence was always higher than linear coherence and increased with naturalistic stimulation. In an initial attempt to separate the order of time-dependent and nonlinear processes, we fitted quadratic frequency response functions by two block-structured models consisting of a power-law filter and a static second-order nonlinearity in alternate cascade orders. The same cascade models were then fitted to the original time domain data by conventional numerical analysis algorithms, using a polynomial function as the static nonlinearity. Quadratic models with a linear filter followed by a static nonlinearity were favored over the reverse order, but with weak significance. Polynomial nonlinear functions indicated that rectification is a major nonlinearity. A complete quantitative description of sensory encoding in these primary mechanoreceptors remains elusive but clearly requires quadratic and higher nonlinear operations on the input signal to explain the sensitivity of dynamic behavior to different input signal patterns.

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.

Post-molting development of wind-elicited escape behavior in the cricket

Arthropods including insects grow through several developmental stages by molting. The abrupt changes in their body size and morphology accompanying the molting are responsible for the developmental changes in behavior. While in holometabolous insects, larval behaviors are transformed into adult-specific behaviors with drastic changes in nervous system during the pupal stage, hemimetabolous insects preserve most innate behaviors whole life long, which allow us to trace the maturation process of preserved behaviors after the changes in body. Wind-elicited escape behavior is one of these behaviors and mediated by cercal system, which is a mechanosensory organ equipped by all stages of nymph in orthopteran insects like crickets. However, the maturation process of the escape behavior after the molt is unclear. In this study, we examined time-series of changes in the wind-elicited escape behavior just after the imaginal molt in the cricket. The locomotor activities are developed over the elapsed time, and matured 24h after the molt. In contrast, a stimulus-angle dependency of moving direction was unchanged over time, meaning that the cercal sensory system detecting airflow direction was workable immediately after the molt, independent from the behavioral maturation. The post-molting development of the wind-elicited behavior was considered to result not simply from maturation of the exoskeleton or musculature because the escape response to heat-shock stimulus did not change after the molt. No effect of a temporal immobilization after the imaginal molt on the maturation of the wind-elicited behavior also implies that the maturation may be innately programmed without experience of locomotion.

Decoding sound level in the marmoset primary auditory cortex

Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons.NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts.

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs.

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.

Auditory modulation of wind-elicited walking behavior in the cricket Gryllus bimaculatus

Animals flexibly change their locomotion triggered by an identical stimulus depending on the environmental context and behavioral state. This indicates that additional sensory inputs in different modality from the stimulus triggering the escape response affect the neuronal circuit governing that behavior. However, how the spatio-temporal relationships between these two stimuli effect a behavioral change remains unknown. We studied this question, using crickets, which respond to a short air-puff by oriented walking activity mediated by the cercal sensory system. In addition, an acoustic stimulus, such as conspecific 'song' received by the tympanal organ, elicits a distinct oriented locomotion termed phonotaxis. In this study, we examined the cross-modal effects on wind-elicited walking when an acoustic stimulus was preceded by an air-puff and tested whether the auditory modulation depends on the coincidence of the direction of both stimuli. A preceding 10 kHz pure tone biased the wind-elicited walking in a backward direction and elevated a threshold of the wind-elicited response, whereas other movement parameters, including turn angle, reaction time, walking speed and distance were unaffected. The auditory modulations, however, did not depend on the coincidence of the stimulus directions. A preceding sound consistently altered the wind-elicited walking direction and response probability throughout the experimental sessions, meaning that the auditory modulation did not result from previous experience or associative learning. These results suggest that the cricket nervous system is able to integrate auditory and air-puff stimuli, and modulate the wind-elicited escape behavior depending on the acoustic context.

Visual coding with a population of direction-selective neurons

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions.

Ca2+ imaging of cricket protocerebrum responses to air current stimulation

Crickets (Gryllus bimaculatus) use the cercal sensory system at the rear of the abdomen to detect air currents and direct predator avoidance behavior. Sensory information regarding the direction and dynamic properties of air currents is processed within the terminal abdominal ganglion, and conveyed by ascending giant interneurons (GIs) to higher centers including the brain. However, the brain region responsible for decoding cercal sensory information has not yet been identified, nor the response properties within the brain characterized. In this study, we performed in vivo Ca(2+) imaging to investigate wind-evoked neural activities within the cricket protocerebrum. Ca(2+) responses to air current stimuli were observed at peripheral regions of the ventrolateral neuropile (VLNP) where projection of GIs' axon terminals has been observed in larvae. The wind-evoked Ca(2+) response had temporal dynamics and directional sensitivity that varied with different recorded regions displaying transient or sustained Ca(2+) increases. Individual cells showed Ca(2+) elevation in response to air currents from a specific angle, while stimuli from a different angle evoked decreased signals. Removing the antennae reduced the air-current-evoked responses in VLNP, suggesting contribution of sensory inputs from antennae in addition to the cercal inputs. The VLNP is presumably an integrative center for mechanosensory processing from antennae and cerci where directional information is primarily decoded by protocerebral neurons.

Negative Correlations in Visual Cortical Networks

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive. We addressed this issue by performing multiple-electrode recording in the superficial layers of the primary visual cortex (V1) of alert monkey. Despite the fact that positive noise correlations decayed exponentially with the difference in the orientation preference between cells, negative correlations were uniformly distributed across the population. Using a statistical model for Fisher Information estimation, we found that a mild increase in negative correlations causes a sharp increase in network accuracy even when mean correlations were held constant. To examine the variables controlling the strength of negative correlations, we implemented a recurrent spiking network model of V1. We found that increasing local inhibition and reducing excitation causes a decrease in the firing rates of neurons while increasing the negative noise correlations, which in turn increase the population signal-to-noise ratio and network accuracy. Altogether, these results contribute to our understanding of the neuronal mechanism involved in the generation of negative correlations and their beneficial impact on cortical circuit function.

Neural responses from the filiform receptor neuron afferents of the wind-sensitive cercal system in three cockroach species

The wind-sensitive insect cercal system is involved in many important behaviors, such as initiating terrestrial escape responses and providing sensory feedback during flight. The occurrence of these behaviors vary in cockroach species Periplaneta americana (strong terrestrial response and flight), Blaberus craniifer (weak terrestrial response and flight), and Gromphodorhina portentosa (no terrestrial response and no flight). A previous study focusing on wind-sensitive interneuron (WSI) responses demonstrated that variations in sensory processing of wind information accompany these behavioral differences. In this study, we recorded extracellularly from the cercal nerve to characterize filiform afferent population responses to different wind velocities to investigate how sensory processing differs across these species at the initial encoding of wind. We compared these results and responses from the WSI population to examine information transfer at the first synapse. Our main results were: (1) G. portentosa had the weakest responses of the three species over the stimulus duration and possessed the smallest cerci with the least filiform hair receptors of the three species; (2) B. craniifer filiform responses were similar to or greater than P. americana responses even though B. craniifer possessed smaller cerci with less filiform hair receptors than P. americana; (3) the greater filiform afferent responses in B. craniifer, including a larger amplitude second positive peak compared to the other two species, suggest more synchronous activity between filiform afferents in this species; (4) the transfer of information at the first synapse appears to be similar in both P. americana and G. portentosa, but different in B. craniifer.

Neural basis of stimulus-angle-dependent motor control of wind-elicited walking behavior in the cricket Gryllus bimaculatus

Crickets exhibit oriented walking behavior in response to air-current stimuli. Because crickets move in the opposite direction from the stimulus source, this behavior is considered to represent ‘escape behavior’ from an approaching predator. However, details of the stimulus-angle-dependent control of locomotion during the immediate phase, and the neural basis underlying the directional motor control of this behavior remain unclear. In this study, we used a spherical-treadmill system to measure locomotory parameters including trajectory, turn angle and velocity during the immediate phase of responses to air-puff stimuli applied from various angles. Both walking direction and turn angle were correlated with stimulus angle, but their relationships followed different rules. A shorter stimulus also induced directionally-controlled walking, but reduced the yaw rotation in stimulus-angle-dependent turning. These results suggest that neural control of the turn angle requires different sensory information than that required for oriented walking. Hemi-severance of the ventral nerve cords containing descending axons from the cephalic to the prothoracic ganglion abolished stimulus-angle-dependent control, indicating that this control required descending signals from the brain. Furthermore, we selectively ablated identified ascending giant interneurons (GIs) in vivo to examine their functional roles in wind-elicited walking. Ablation of GI8-1 diminished control of the turn angle and decreased walking distance in the initial response. Meanwhile, GI9-1b ablation had no discernible effect on stimulus-angle-dependent control or walking distance, but delayed the reaction time. These results suggest that the ascending signals conveyed by GI8-1 are required for turn-angle control and maintenance of walking behavior, and that GI9-1b is responsible for rapid initiation of walking. It is possible that individual types of GIs separately supply the sensory signals required to control wind-elicited walking.

Responses of cricket cercal interneurons to realistic naturalistic stimuli in the field

The ability of the insect cercal system to detect approaching predators has been studied extensively in the laboratory and in the field. Some previous studies have assessed the extent to which sensory noise affects the operational characteristics of the cercal system, but these studies have only been carried out in laboratory settings using white noise stimuli of unrealistic nature. Using a piston mimicking the natural airflow of an approaching predator, we recorded the neural activity through the abdominal connectives from the terminal abdominal ganglion of freely moving wood crickets (Nemobius sylvestris) in a semi-field situation. A cluster analysis of spike amplitudes revealed six clusters, or 'units', corresponding to six different subsets of cercal interneurons. No spontaneous activity was recorded for the units of larger amplitude, reinforcing the idea they correspond to the largest giant interneurons. Many of the cercal units are already activated by background noise, sometimes only weakly, and the approach of a predator is signaled by an increase in their activity, in particular for the larger-amplitude units. A scaling law predicts that the cumulative number of spikes is a function of the velocity of the flow perceived at the rear of the cricket, including a multiplicative factor that increases linearly with piston velocity. We discuss the implications of this finding in terms of how the cricket might infer the imminence and nature of a predatory attack.

Active touch in orthopteroid insects: behaviours, multisensory substrates and evolution

Orthopteroid insects (cockroaches, crickets, locusts and related species) allow examination of active sensory processing in a comparative framework. Some orthopteroids possess long, mobile antennae endowed with many chemo- and mechanoreceptors. When the antennae are touched, an animal's response depends upon the identity of the stimulus. For example, contact with a predator may lead to escape, but contact with a conspecific may usually not. Active touch of an approaching object influences the likelihood that a discrimination of identity will be made. Using cockroaches, we have identified specific descending mechanosensory interneurons that trigger antennal-mediated escape. Crucial sensory input to these cells comes from chordotonal organs within the antennal base. However, information from other receptors on the base or the long antennal flagellum allows active touch to modulate escape probability based on stimulus identity. This is conveyed, at least to some extent, by textural information. Guidance of the antennae in active exploration depends on visual information. Some of the visual interneurons and the motor neurons necessary for visuomotor control have been identified. Comparisons across Orthoptera suggest an evolutionary model where subtle changes in the architecture of interneurons, and of sensorimotor control loops, may explain differing levels of vision-touch interaction in the active guidance of behaviour.

Functional clustering drives encoding improvement in a developing brain network during awake visual learning

Sensory experience drives dramatic structural and functional plasticity in developing neurons. However, for single-neuron plasticity to optimally improve whole-network encoding of sensory information, changes must be coordinated between neurons to ensure a full range of stimuli is efficiently represented. Using two-photon calcium imaging to monitor evoked activity in over 100 neurons simultaneously, we investigate network-level changes in the developing Xenopus laevis tectum during visual training with motion stimuli. Training causes stimulus-specific changes in neuronal responses and interactions, resulting in improved population encoding. This plasticity is spatially structured, increasing tuning curve similarity and interactions among nearby neurons, and decreasing interactions among distant neurons. Training does not improve encoding by single clusters of similarly responding neurons, but improves encoding across clusters, indicating coordinated plasticity across the network. NMDA receptor blockade prevents coordinated plasticity, reduces clustering, and abolishes whole-network encoding improvement. We conclude that NMDA receptors support experience-dependent network self-organization, allowing efficient population coding of a diverse range of stimuli.

The neurobiology of Etruscan shrew active touch

The Etruscan shrew, Suncus etruscus, is not only the smallest terrestrial mammal, but also one of the fastest and most tactile hunters described to date. The shrew's skeletal muscle consists entirely of fast-twitch types and lacks slow fibres. Etruscan shrews detect, overwhelm, and kill insect prey in large numbers in darkness. The cricket prey is exquisitely mechanosensitive and fast-moving, and is as big as the shrew itself. Experiments with prey replica show that shape cues are both necessary and sufficient for evoking attacks. Shrew attacks are whisker guided by motion- and size-invariant Gestalt-like prey representations. Shrews often attack their prey prior to any signs of evasive manoeuvres. Shrews whisk at frequencies of approximately 14 Hz and can react with latencies as short as 25-30 ms to prey movement. The speed of attacks suggests that shrews identify and classify prey with a single touch. Large parts of the shrew's brain respond to vibrissal touch, which is represented in at least four cortical areas comprising collectively about a third of the cortical volume. Etruscan shrews can enter a torpid state and reduce their body temperature; we observed that cortical response latencies become two to three times longer when body temperature drops from 36°C to 24°C, suggesting that endothermy contributes to the animal's high-speed sensorimotor performance. We argue that small size, high-speed behaviour and extreme dependence on touch are not coincidental, but reflect an evolutionary strategy, in which the metabolic costs of small body size are outweighed by the advantages of being a short-range high-speed touch and kill predator.

Danger detection and escape behaviour in wood crickets

The wind-sensitive cercal system of Orthopteroid insects that mediates the detection of the approach of a predator is a very sensitive sensory system. It has been intensively analysed from a behavioural and neurobiological point of view, and constitutes a classical model system in neuroethology. The escape behaviour is triggered in orthopteroids by the detection of air-currents produced by approaching objects, allowing these insects to keep away from potential dangers. Nevertheless, escape behaviour has not been studied in terms of success. Moreover, an attacking predator is more than "air movement", it is also a visible moving entity. The sensory basis of predator detection is thus probably more complex than the perception of air movement by the cerci. We have used a piston mimicking an attacking running predator for a quantitative evaluation of the escape behaviour of wood crickets Nemobius sylvestris. The movement of the piston not only generates air movement, but it can be seen by the insect and can touch it as a natural predator. This procedure allowed us to study the escape behaviour in terms of detection and also in terms of success. Our results showed that 5-52% of crickets that detected the piston thrust were indeed touched. Crickets escaped to stimulation from behind better than to a stimulation from the front, even though they detected the approaching object similarly in both cases. After cerci ablation, 48% crickets were still able to detect a piston approaching from behind (compared with 79% of detection in intact insects) and 24% crickets escaped successfully (compared with 62% in the case of intact insects). So, cerci play a major role in the detection of an approaching object but other mechanoreceptors or sensory modalities are implicated in this detection. It is not possible to assure that other sensory modalities participate (in the case of intact animals) in the behaviour; rather, than in the absence of cerci other sensory modalities can partially mediate the behaviour. Nevertheless, neither antennae nor eyes seem to be used for detecting approaching objects, as their inactivation did not reduce their detection and escape abilities in the presence of cerci.

Temporal encoding in a nervous system

We examined the extent to which temporal encoding may be implemented by single neurons in the cercal sensory system of the house cricket Acheta domesticus. We found that these neurons exhibit a greater-than-expected coding capacity, due in part to an increased precision in brief patterns of action potentials. We developed linear and non-linear models for decoding the activity of these neurons. We found that the stimuli associated with short-interval patterns of spikes (ISIs of 8 ms or less) could be predicted better by second-order models as compared to linear models. Finally, we characterized the difference between these linear and second-order models in a low-dimensional subspace, and showed that modification of the linear models along only a few dimensions improved their predictive power to parity with the second order models. Together these results show that single neurons are capable of using temporal patterns of spikes as fundamental symbols in their neural code, and that they communicate specific stimulus distributions to subsequent neural structures.

The information coding schemes used within nervous systems have been the focus of an entire field within neuroscience. An unresolved issue within the general coding problem is the determination of the neural “symbols” with which information is encoded in neural spike trains, analogous to the determination of the nucleotide sequences used to represent proteins in molecular biology. The goal of our study was to determine if pairs of consecutive action potentials contain more or different information about the stimuli that elicit them than would be predicted from an analysis of individual action potentials. We developed linear and non-linear coding models and used likelihood analysis to address this question for sensory interneurons in the cricket cercal sensory system. Our results show that these neurons' spike trains can be decomposed into sequences of two neural symbols: isolated single spikes and short-interval spike doublets. Given the ubiquitous nature of similar neural activity reported in other systems, we suspect that the implementation of such temporal encoding schemes may be widespread across animal phyla. Knowledge of the basic coding units used by single cells will help in building the large-scale neural network models necessary for understanding how nervous systems function.

The morphology and fine structure of the giant interneurons of the wood cricket Nemobius sylvestris

The structural and ultrastructural characteristics of giant interneurons in the terminal abdominal ganglion of the cricket Nemobius sylvestris were investigated by means of cobalt and fluorescent dye backfilling and transmission electron microscopy. The projections of the 8 eight pairs of the biggest ascending interneurons (giant interneurons) are described in detail. The somata of all interneurons analyzed are located contralateral to their axons, which project to the posterior region of the terminal ganglion and arborise in the cercal glomerulus. Neuron 7-1a is an exception, because its arborisation is restricted to the anterior region of the ganglion. The fine structure of giant interneurons shows typical features of highly active cells. We observed striking indentations in the perineural layer, enabling the somata of the giant interneurons to be very close to the haemolymph. The cercal glomerulus exhibits a high diversity of synaptic contacts (i.e. axo-dendritic, axo-axonic, dendro-axonic, and dendro-dendritic), as well as areas of tight junctions. Electrical synapses seem to be present, as well as mixed synapses. The anatomical organization of the giant interneurons is finally discussed in terms of functional implications and on a comparative basis.

Characterizing the fine structure of a neural sensory code through information distortion

We present an application of the information distortion approach to neural coding. The approach allows the discovery of neural symbols and the corresponding stimulus space of a neuron or neural ensemble simultaneously and quantitatively, making few assumptions about the nature of either code or relevant features. The neural codebook is derived by quantitizing sensory stimuli and neural responses into small reproduction sets, and optimizing the quantization to minimize the information distortion function. The application of this approach to the analysis of coding in sensory interneurons involved a further restriction of the space of allowed quantitizers to a smaller family of parametric distributions. We show that, for some cells in this system, a significant amount of information is encoded in patterns of spikes that would not be discovered through analyses based on linear stimulus-response measures.

Which coordinate system for modelling path integration?

Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors.

Coding characteristics of spiking local interneurons during imposed limb movements in the locust

The performance of adaptive behavior relies on continuous sensory feedback to produce relevant modifications to central motor patterns. The femoral chordotonal organ (FeCO) of the legs of the desert locust monitors the movements of the tibia about the femoro-tibial joint. A ventral midline population of spiking local interneurons in the metathoracic ganglia integrates inputs from the FeCO. We used a Wiener kernel cross-correlation method combined with a Gaussian white noise stimulation of the FeCO to completely characterize and model the output dynamics of the ventral midline population of interneurons. A wide range of responses were observed, and interneurons could be classified into three broad groups that received excitatory and inhibitory or principally inhibitory or excitatory synaptic inputs from the FeCO. Interneurons that received mixed inputs also had the greatest linear responses but primarily responded to extension of the tibia and were mostly sensitive to stimulus velocity. Interneurons that received principally inhibitory inputs were sensitive to extension and to joint position. A small group of interneurons received purely excitatory synaptic inputs and were also sensitive to tibial extension. In addition to capturing the linear and nonlinear dynamics of this population of interneurons, first- and second-order Wiener kernels revealed that the dynamics of the interneurons in the population were graded and formed a spectrum of responses whereby the activity of many cells appeared to be required to adequately describe a particular stimulus characteristic, typical of population coding.

Transcriptional control of behavior: engrailed knock-out changes cockroach escape trajectories

The cerci of the cockroach are covered with identified sensory hairs that detect air movements. The sensory neurons that innervate these hairs synapse with giant interneurons in the terminal ganglion that in turn synapse with interneurons and leg motor neurons in thoracic ganglia. This neural circuit mediates the animal's escape behavior. The transcription factor Engrailed (En) is expressed only in the medially born sensory neurons, which suggested that it could work as a positional determinant of sensory neuron identity. Previously, we used double-stranded RNA interference to abolish En expression and found that the axonal arborization and synaptic outputs of an identified En-positive sensory neuron changed so that it came to resemble a nearby En-negative cell, which was itself unaffected. We thus demonstrated directly that En controls synaptic choice, as well as axon projections. Is escape behavior affected as a result of this miswiring? We showed recently that adult cockroaches keep each escape unpredictable by running along one of a set of preferred escape trajectories (ETs) at fixed angles from the direction of the threatening stimulus. The probability of selecting a particular ET is influenced by wind direction. In this present study, we show that early instar juvenile cockroaches also use those same ETs. En knock-out significantly perturbs the animals' perception of posterior wind, altering the choice of ETs to one more appropriate for anterior wind. This is the first time that it has been shown that knock-out of a transcription factor controlling synaptic connectivity can alter the perception of a directional stimulus.

A 4-dimensional representation of antennal lobe output based on an ensemble of characterized projection neurons

A central problem facing studies of neural encoding in sensory systems is how to accurately quantify the extent of spatial and temporal responses. In this study, we take advantage of the relatively simple and stereotypic neural architecture found in invertebrates. We combine standard electrophysiological techniques, recently developed population analysis techniques, and novel anatomical methods to form an innovative 4-dimensional view of odor output representations in the antennal lobe of the moth Manduca sexta. This novel approach allows quantification of olfactory responses of characterized neurons with spike time resolution. Additionally, arbitrary integration windows can be used for comparisons with other methods such as imaging. By assigning statistical significance to changes in neuronal firing, this method can visualize activity across the entire antennal lobe. The resulting 4-dimensional representation of antennal lobe output complements imaging and multi-unit experiments yet provides a more comprehensive and accurate view of glomerular activation patterns in spike time resolution.

The terminal abdominal ganglion of the wood cricket Nemobius sylvestris

The abdominal cerci of the wood cricket, Nemobius sylvestris, are covered by a variety of hair-like sensilla that differ in length, thickness, and articulation. Fillings from the cercal nerves with cobalt chloride and fluorescent dyes revealed the projection of sensory axons into the terminal abdominal ganglion of the ventral nerve chain. Two projection areas on each side of the terminal abdominal ganglion midline could be identified: a posterior cercal glomerulus and an anterior bristle neuropil. Axons from some cercal sensilla ascend through the connectives to reach the metathoracic ganglionic mass. As their axons pass through each segmental abdominal ganglion, they project medial arborization. Cross-sections of the terminal abdominal ganglion and retrograde fills with cobalt chloride and fluorescent dyes from connectives revealed several small cells and seven pairs of giant ascending interneurons organized symmetrically. Giant somata are located contralateral to their axons (diameters between 20 and 45 mum). The cercal projections overlap extensively with the dendritic fields of the giant interneurons. In the terminal abdominal ganglion, we identified nine longitudinal tracts, two major tracts, and seven smaller ones. The functional implications of the neuranatomical organization of the system are discussed on a comparative basis.

Efficient coding in heterogeneous neuronal populations

A ubiquitous feature of neuronal responses within a cortical area is their high degree of inhomogeneity. Even cells within the same functional column are known to have highly heterogeneous response properties when the same stimulus is presented. Whether the wide diversity of neuronal responses is an epiphenomenon or plays a role for cortical function is unknown. Here, we examined the relationship between the heterogeneity of neuronal responses and population coding. Contrary to our expectation, we found that the high variability of intrinsic response properties of individual cells changes the structure of neuronal correlations to improve the information encoded in the population activity. Thus, the heterogeneity of neuronal responses is in fact beneficial for sensory coding when stimuli are decoded from the population response.

Nitric oxide-cyclic guanosine monophosphate signaling in the local circuit of the cricket abdominal nervous system

The distribution of potential nitric oxide (NO) donor neurons and NO-responsive target neurons was revealed in the terminal abdominal ganglion (TAG) of the cricket. The expression of nitric oxide synthase (NOS) in the nervous system was examined by Western blotting using universal nitric oxide synthase (uNOS) antibody that gave about a 130 kDa protein band. Immunohistochemistry using the uNOS antibody detected neurons whose cell bodies are located at the lateral region of the TAG. These neurons expanded their neuronal branches into the dorsal-median region or the dorsal-lateral region of the TAG. NADPH-diaphorase histochemistry was performed to confirm the distribution of NOS-containing neurons. The distributions of cell bodies and stained neuronal branches were similar to those revealed by uNOS immunohistochemistry. NO-induced cGMP immunohistochemistry was performed to reveal NO-responsive target neurons. Most of the cell bodies stained by immunohistochemistry appeared at the dorsal side of the TAG. At the dorsal-median region, some unpaired neuronal cell bodies were strongly stained. Some efferent neurons whose axon innervate into each nerve root were strongly stained. The generation of NO in the TAG was detected by NO electrode. We found that NO is generally produced to maintain a basal concentration of 70 nM. Hemoglobin scavenged released NO from the ganglion. The concentration of NO was partly recovered when hemoglobin was replaced by normal saline. Application of 10 microM L-arginine that is a substrate of NOS increased NO release by approximately 10 nM. Furthermore, an excitatory neurotransmitter acetylcholine (ACh) also increased NO generation by approximately 40-50 nM in concentration in addition to the basal level of 70 nM. Optical imaging with fluorescent NO-indicator demonstrated that ACh-induced enhancement of NO release was transiently observed in the outer-edge region of TAG, where cell bodies of NOS-immunoreactive neurons were located. These results suggest that ACh accelerates NO production via neuronal events activated by ACh in the TAG.

Dendritic design implements algorithm for synaptic extraction of sensory information

While sensory information is encoded by firing patterns of individual sensory neurons, it is also represented by spatiotemporal patterns of activity in populations of the neurons. Postsynaptic interneurons decode the population response and extract specific sensory information. This extraction of information represented by presynaptic activities is a process critical to defining the input-output function of postsynaptic neuron. To understand the "algorithm" for the extraction, we examined directional sensitivities of presynaptic and postsynaptic Ca(2+) responses in dendrites of two types of wind-sensitive interneurons (INs) with different dendritic geometries in the cricket cercal sensory system. In IN 10-3, whose dendrites arborize with various electrotonic distances to the spike-initiating zone (SIZ), the directional sensitivity of dendritic Ca(2+) responses corresponded to those indicated by Ca(2+) signals in presynaptic afferents arborizing on that dendrite. The directional tuning properties of individual dendrites varied from each other, and the directional sensitivity of the nearest dendrite to the SIZ dominates the tuning properties of the spiking response. In IN 10-2 with dendrites isometric to the SIZ, directional tuning properties of different dendrites were similar to each other, and each response property could be explained by the directional profile of the spatial overlap between that dendrite and Ca(2+)-elevated presynaptic terminals. For IN 10-2, the directional sensitivities extracted by the different dendritic-branches would contribute equally to the overall tuning. It is possible that the differences in the distribution of synaptic weights because of the dendritic geometry are related to the algorithm for extraction of sensory information in the postsynaptic interneurons.

How behavioral constraints may determine optimal sensory representations

The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the neuron's average response as a function of a parameter that characterizes a physical stimulus. What determines the shapes of tuning curves in a neuronal population? Previous theoretical studies and related experiments suggest that many response characteristics of sensory neurons are optimal for encoding stimulus-related information. This notion, however, does not explain the two general types of tuning profiles that are commonly observed: unimodal and monotonic. Here I quantify the efficacy of a set of tuning curves according to the possible downstream motor responses that can be constructed from them. Curves that are optimal in this sense may have monotonic or nonmonotonic profiles, where the proportion of monotonic curves and the optimal tuning-curve width depend on the general properties of the target downstream functions. This dependence explains intriguing features of visual cells that are sensitive to binocular disparity and of neurons tuned to echo delay in bats. The numerical results suggest that optimal sensory tuning curves are shaped not only by stimulus statistics and signal-to-noise properties but also according to their impact on downstream neural circuits and, ultimately, on behavior.

A quantitative theoretical approach demonstrates how optimal sensory tuning curves are shaped not only by stimulus statistics and signal-to-noise properties, but also according to their impact on downstream neural circuits and behavior.

Interaction between arthropod filiform hairs in a fluid environment

Many arthropods use filiform hairs as mechanoreceptors to detect air motion. In common house crickets (Acheta domestica) the hairs cover two antenna-like appendages called cerci at the rear of the abdomen. The biomechanical stimulus-response properties of individual filiform hairs have been investigated and modeled extensively in several earlier studies. However, only a few previous studies have considered viscosity-mediated coupling between pairs of hairs, and only in particular configurations. Here, we present a model capable of calculating hair-to-hair coupling in arbitrary configurations. We simulate the coupled motion of a small group of mechanosensory hairs on a cylindrical section of cercus. We have found that the coupling effects are non-negligible, and likely constrain the operational characteristics of the cercal sensory array.

Robust integration of motion information in the fly visual system revealed by single cell photoablation

In the brain, sensory information needs often to be read out from the ensemble activity of presynaptic neurons. In the most basic case, this may be accomplished by an individual postsynaptic neuron. In the visual system of the blowfly, an identified motion-sensitive spiking neuron is known to be postsynaptic to an ensemble of graded-potential presynaptic input elements. Both the presynaptic and postsynaptic neurons were shown previously to be capable of representing the velocity of preferred-direction motion reliably and linearly over a large frequency range of velocity fluctuations. Accordingly, the synaptic transfer properties of the connecting excitatory synapses between individual input elements and the postsynaptic neuron were shown to be linear over a similar range of presynaptic membrane potential fluctuations. It was not known, however, how the postsynaptic neuron integrates and reads out the presynaptic ensemble activity. We were able to compare the response properties of the integrating cell before and after eliminating individual presynaptic elements by a laser ablation technique. For most of the input elements, we found that their elimination strongly affected the activity of the postsynaptic neuron but did not degrade its performance to encode motion with constant and time-varying velocity. Our results suggest that the integration of individual synaptic inputs within the neural circuit operates with some redundancy. This feature might help the postsynaptic neuron to encode in a highly robust way the direction and the velocity of self-motion of the animal.

Effects of stimulus transformations on estimates of sensory neuron selectivity

Stimulus selectivity of sensory systems is often characterized by analyzing response-conditioned stimulus ensembles. However, in many cases these response-triggered stimulus sets have structure that is more complex than assumed. If not taken into account, when present it will bias the estimates of many simple statistics, and distort the estimated stimulus selectivity of a neural sensory system. We present an approach that mitigates these problems by modeling some of the response-conditioned stimulus structure as being generated by a set of transformations acting on a simple stimulus distribution. This approach corrects the estimates of key statistics and counters biases introduced by the transformations. In cases involving temporal spike jitter or spatial jitter of images, the main observed effects of transformations are blurring of the conditional mean and introduction of artefacts in the spectral decomposition of the conditional covariance matrix. We illustrate this approach by analyzing and correcting a set of model stimuli perturbed by temporal and spatial jitter. We apply the approach to neurophysiological data from the cricket cercal sensory system to correct the effects of temporal jitter.

Visualization of ensemble activity patterns of mechanosensory afferents in the cricket cercal sensory system with calcium imaging

The cercal sensory system of the cricket mediates the detection and analysis of low velocity air currents in the animal's immediate environment, and is implemented around an internal representation of air current direction that demonstrates the essential features of a continuous neural map. Previous neurophysiological and anatomical studies have yielded predictions of the global spatio-temporal patterns of activity that should be evoked in the sensory afferent map by air current stimuli of different directions. We tested those predictions by direct visualization of ensemble afferent activity patterns using Ca2+ -sensitive indicators. The AM ester of the fluorescent Ca2+ indicator (Oregon Green 488 BAPTA-1 AM) was injected under the sheath of a cercal sensory nerve containing all of the mechanosensory afferent axons from one cercus. Optical signals were recorded with a digital intensified CCD camera. Control experiments using direct electrical stimulation of stained and unstained nerves demonstrated that the observed Ca2+ signals within the terminal abdominal ganglion (TAG) were due to activation of the dye-loaded sensory afferent neurons. To visualize the spatial patterns of air-current-evoked ensemble activity, unidirectional air currents were applied repeatedly from eight different directions, and the optically recorded responses from each direction were averaged. The dispersion of the optical signals by the ganglion limited the spatial resolution with which these ensemble afferent activity patterns could be observed. However, resolution was adequate to demonstrate that different directional stimuli induced different spatial patterns of Ca2+ elevation in the terminal arbors of afferents within the TAG. These coarsely- resolved, optically-recorded patterns were consistent with the anatomy-based predictions.

Tuning curves, neuronal variability, and sensory coding

Tuning curves are widely used to characterize the responses of sensory neurons to external stimuli, but there is an ongoing debate as to their role in sensory processing. Commonly, it is assumed that a neuron's role is to encode the stimulus at the tuning curve peak, because high firing rates are the neuron's most distinct responses. In contrast, many theoretical and empirical studies have noted that nearby stimuli are most easily discriminated in high-slope regions of the tuning curve. Here, we demonstrate that both intuitions are correct, but that their relative importance depends on the experimental context and the level of variability in the neuronal response. Using three different information-based measures of encoding applied to experimentally measured sensory neurons, we show how the best-encoded stimulus can transition from high-slope to high-firing-rate regions of the tuning curve with increasing noise level. We further show that our results are consistent with recent experimental findings that correlate neuronal sensitivities with perception and behavior. This study illustrates the importance of the noise level in determining the encoding properties of sensory neurons and provides a unified framework for interpreting how the tuning curve and neuronal variability relate to the overall role of the neuron in sensory encoding.

This study provides a unified framework for interpreting how a neuron's stimulus tuning curve and response variability relates to sensory encoding.

Population Coding of Self-Motion: Applying Bayesian Analysis to a Population of Visual Interneurons in the Fly

Coding of sensory information often involves the activity of neuronal populations. We demonstrate how the accuracy of a population code depends on integration time, the size of the population, and noise correlation between the participating neurons. The population we study consists of 10 identified visual interneurons in the blowfly Calliphora vicina involved in optic flow processing. These neurons are assumed to encode the animal's head or body rotations around horizontal axes by means of graded potential changes. From electrophysiological experiments we obtain parameters for modeling the neurons' responses. From applying a Bayesian analysis on the modeled population response we draw three major conclusions. First, integration of neuronal activities over a time period of only 5 ms after response onset is sufficient to decode accurately the rotation axis. Second, noise correlation between neurons has only little impact on the population's performance. And third, although a population of only two neurons would be sufficient to encode any horizontal rotation axis, the population of 10 vertical system neurons is advantageous if the available integration time is short. For the fly, short integration times to decode neuronal responses are important when controlling rapid flight maneuvers.

Learning visuomotor transformations for gaze-control and grasping

For reaching to and grasping of an object, visual information about the object must be transformed into motor or postural commands for the arm and hand. In this paper, we present a robot model for visually guided reaching and grasping. The model mimics two alternative processing pathways for grasping, which are also likely to coexist in the human brain. The first pathway directly uses the retinal activation to encode the target position. In the second pathway, a saccade controller makes the eyes (cameras) focus on the target, and the gaze direction is used instead as positional input. For both pathways, an arm controller transforms information on the target's position and orientation into an arm posture suitable for grasping. For the training of the saccade controller, we suggest a novel staged learning method which does not require a teacher that provides the necessary motor commands. The arm controller uses unsupervised learning: it is based on a density model of the sensor and the motor data. Using this density, a mapping is achieved by completing a partially given sensorimotor pattern. The controller can cope with the ambiguity in having a set of redundant arm postures for a given target. The combined model of saccade and arm controller was able to fixate and grasp an elongated object with arbitrary orientation and at arbitrary position on a table in 94% of trials.