Learning cortical topography from spatiotemporal stimuli

Stimulus representation is a functional interpretation of early sensory cortices. Early sensory cortices are subject to stimulus-induced modifications. Common models for stimulus-induced learning within topographic representations are based on the stimuli's spatial structure and probability distribution. Furthermore, we argue that average temporal stimulus distances reflect the stimuli's relatedness. As topographic representations reflect the stimuli's relatedness, the temporal structure of incoming stimuli is important for the learning in cortical maps. Motivated by recent neurobiological findings, we present an approach of cortical self-organization that additionally takes temporal stimulus aspects into account. The proposed model transforms average interstimulus intervals into representational distances. Thereby, neural topography is related to stimulus dynamics. This offers a new time-based interpretation of cortical maps. Our approach is based on a wave-like spread of cortical activity. Interactions between dynamics and feedforward activations lead to shifts of neural activity. The psychophysical saltation phenomenon may represent an analogue to the shifts proposed here. With regard to cortical plasticity, we offer an explanation for neurobiological findings that other models cannot explain. Moreover, we predict cortical reorganizations under new experimental, spatiotemporal conditions. With regard to psychophysics, we relate the saltation phenomenon to dynamics and interaction in early sensory cortices and predict further effects in the perception of spatiotemporal stimuli. Received: 17 March 1999 / Accepted in revised form: 10 August 1999     

High-content behavioral analysis of Caenorhabditis elegans in precise spatiotemporal chemical environments

To quantitatively understand chemosensory behaviors, it is desirable to present many animals with repeatable, well-defined chemical stimuli. To that end, we describe a microfluidic system to analyze Caenorhabditis elegans behavior in defined temporal and spatial stimulus patterns. A 2 cm × 2 cm structured arena allowed C. elegans to perform crawling locomotion in a controlled liquid environment. We characterized behavioral responses to attractive odors with three stimulus patterns: temporal pulses, spatial stripes and a linear concentration gradient, all delivered in the fluid phase to eliminate variability associated with air-fluid transitions. Different stimulus configurations preferentially revealed turning dynamics in a biased random walk, directed orientation into an odor stripe and speed regulation by odor. We identified both expected and unexpected responses in wild-type worms and sensory mutants by quantifying dozens of behavioral parameters. The devices are inexpensive, easy to fabricate, reusable and suitable for delivering any liquid-borne stimulus.     

Sensory systems

Our understanding of sensory systems has grown impressively in recent years as a result of intense efforts to characterize the mechanisms underlying perception. A large body of evidence has accrued regarding the processes through which sensory information at the biochemical, electrophysiological, and systems levels contributes to the conscious experience of a stimulus. Our efforts to understand the function of sensory systems have been aided by the development of new techniques, including powerful methods of molecular biology, refined short- and long-term approaches to recording from single and multiple neurons, and non-invasive neuroimaging techniques that allow us to study activity within the human brain while subjects perform a variety of cognitive tasks. In future research, the last approach is likely to form a bridge between the large body of electrophysiological knowledge acquired in animal experiments and that currently being obtained in human imaging research.     

Learning through maps: functional significance of topographic organization in primary sensory cortex.

The presence of "maps" in sensory cortex is a hallmark of the mammalian nervous system, but the functional significance of topographic organization has been called into question by physiological studies claiming that patterns of neural behavioral activity transcend topographic boundaries. This paper discusses recent behavioral and physiological studies suggesting that, when animals or human subjects learn perceptual tasks, the neural modifications associated with the learning are distributed according to the spatial arrangement of the primary sensory cortical map. Topographical cortical representations of sensory events, therefore, appear to constitute a true structural framework for information processing and plasticity.     

The Value of Artificial Stimuli in Behavioral Research: Making the Case for Egg Rejection Studies in Avian Brood Parasitism

Experimentation is at the heart of classical and modern behavioral ecology research. The manipulation of natural cues allows us to establish causation between aspects of the environment, both internal and external to organisms, and their effects on animals' behaviors. In recognition systems research, including the quest to understand the coevolution of sensory cues and decision rules underlying the rejection of foreign eggs by hosts of avian brood parasites, artificial stimuli have been used extensively, but not without controversy. In response to repeated criticism about the value of artificial stimuli, we describe four potential benefits of using them in egg recognition research, two each at the proximate and ultimate levels of analysis: (1) the standardization of stimuli for developmental studies and (2) the disassociation of correlated traits of egg phenotypes used for sensory discrimination, as well as (3) the estimation of the strength of selection on parasitic egg mimicry and (4) the establishment of the evolved limits of sensory and cognitive plasticity. We also highlight constraints of the artificial stimulus approach and provide a specific test of whether responses to artificial cues can accurately predict responses to natural cues. Artificial stimuli have a general value in ethological research beyond research in brood parasitism and may be especially critical in field studies involving the manipulation of a single parameter, where other, confounding variables are difficult or impossible to control experimentally or statistically.     

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. Action Editor: Matthew Wiener     

Spider senses - technical perfection and biology

This essay deals with sensory biology in a broad sense. It takes mechanosensory systems of spiders to illustrate a few basic issues. Particular attention is given to two aspects. 1. There is a remarkable “ingenuity” in the uptake and transformation of the adequate stimuli way out in the sensory periphery, which is reflected by an intimate relationship between the physical properties of the stimuli and the characteristics of the structures receiving and transforming them. We need to understand the details of this relationship in order to understand the relationship of an organism to its environment. 2. Sensory systems represent interfaces between the environment and behavior. As highly selective filters they have not evolved to provide abstract knowledge but to guide a particular behavior. The signals sent to the central nervous system are meaningful only in regard to their behavioral significance. – Some details of stimulus transformation in biological strain gauges (slit sensilla), airflow detectors (trichobothria) and touch receptors (tactile hairs) are described. Some of the refinement in the periphery is then meshed with the behavior of the whole organism. In this way the value shall be underlined of trying to understand reductionist details as building blocks of the complexity which enables an organism to behave in its own particular way in its species specific environment.     

Optimality in mono- and multisensory map formation

In the struggle for survival in a complex and dynamic environment, nature has developed a multitude of sophisticated sensory systems. In order to exploit the information provided by these sensory systems, higher vertebrates reconstruct the spatio-temporal environment from each of the sensory systems they have at their disposal. That is, for each modality the animal computes a neuronal representation of the outside world, a monosensory neuronal map. Here we present a universal framework that allows to calculate the specific layout of the involved neuronal network by means of a general mathematical principle, viz., stochastic optimality. In order to illustrate the use of this theoretical framework, we provide a step-by-step tutorial of how to apply our model. In so doing, we present a spatial and a temporal example of optimal stimulus reconstruction which underline the advantages of our approach. That is, given a known physical signal transmission and rudimental knowledge of the detection process, our approach allows to estimate the possible performance and to predict neuronal properties of biological sensory systems. Finally, information from different sensory modalities has to be integrated so as to gain a unified perception of reality for further processing, e.g., for distinct motor commands. We briefly discuss concepts of multimodal interaction and how a multimodal space can evolve by alignment of monosensory maps.     

Using hardware models to quantify sensory data acquisition across the rat vibrissal array

Our laboratory investigates how animals acquire sensory data to understand the neural computations that permit complex sensorimotor behaviors. We use the rat whisker system as a model to study active tactile sensing; our aim is to quantitatively describe the spatiotemporal structure of incoming sensory information to place constraints on subsequent neural encoding and processing. In the first part of this paper we describe the steps in the development of a hardware model (a 'sensobot') of the rat whisker array that can perform object feature extraction. We show how this model provides insights into the neurophysiology and behavior of the real animal. In the second part of this paper, we suggest that sensory data acquisition across the whisker array can be quantified using the complete derivative. We use the example of wall-following behavior to illustrate that computing the appropriate spatial gradients across a sensor array would enable an animal or mobile robot to predict the sensory data that will be acquired at the next time step.     

Network Evolution Induced by Asynchronous Stimuli through Spike-Timing-Dependent Plasticity

In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP) is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential application for examining STDP by measuring neural population activity in a cultured neural network.     

Shaping embodied neural networks for adaptive goal-directed behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves.     

Information-processing demands in electrosensory and mechanosensory lateral line systems.

The electrosensory and mechanosensory lateral line systems of fish exhibit many common features in their structural and functional organization, both at the sensory periphery as well as in central processing pathways. These two sensory systems also appear to play similar roles in many behavioral tasks such as prey capture, orientation with respect to external environmental cues, navigation in low-light conditions, and mediation of interactions with nearby animals. In this paper, we briefly review key morphological, physiological, and behavioral aspects of these two closely related sensory systems. We present arguments that the information processing demands associated with spatial processing are likely to be quite similar, due largely to the spatial organization of both systems and the predominantly dipolar nature of many electrosensory and mechanosensory stimulus fields. Demands associated with temporal processing may be quite different, however, due primarily to differences in the physical bases of electrosensory and mechanosensory stimuli (e.g. speed of transmission). With a better sense of the information processing requirements, we turn our attention to an analysis of the functional organization of the associated first-order sensory nuclei in the hindbrain, including the medial octavolateral nucleus (MON), dorsal octavolateral nucleus (DON), and electrosensory lateral line lobe (ELL). One common feature of these systems is a set of neural mechanisms for improving signal-to-noise ratios, including mechanisms for adaptive suppression of reafferent signals. This comparative analysis provides new insights into how the nervous system extracts biologically significant information from dipolar stimulus fields in order to solve a variety of behaviorally relevant problems faced by aquatic animals.     

Prolonged stimuli alter the bacterial chemosensory clusters

The clustering of membrane‐bound receptors plays an essential role in various biological systems. A notable model system for studying this phenomenon is the bacterial chemosensory cluster that allows motile bacteria to navigate along chemical gradients in their environment. While the basic structure of these chemosensory clusters is becoming clear, their dynamic nature and operation are not yet understood. By measuring the fluorescence polarization of tagged receptor clusters in live Escherichia coli cells, we provide evidence for stimulus‐induced dynamics in these sensory clusters. We find that when a stimulus is applied, the packing of the receptors slowly decreases and that the process reverses when the stimulus is removed. Consistent with these physical changes we find that the effective cooperativity of the kinase response slowly evolves in the presence of a stimulus. Time‐lapse fluorescence imaging indicates that, despite these changes, the receptor clusters do not generally dissociate upon ligand binding. These data reveal stimulus‐dependent plasticity in chemoreceptor clusters.     

Comparing the strength of behavioural plasticity and consistency across situations: animal personalities in the hermit crab Pagurus bernhardus

Many phenotypic traits show plasticity but behaviour is often considered the 'most plastic' aspect of phenotype as it is likely to show the quickest response to temporal changes in conditions or 'situation'. However, it has also been noted that constraints on sensory acuity, cognitive structure and physiological capacities place limits on behavioural plasticity. Such limits to plasticity may generate consistent differences in behaviour between individuals from the same population. It has recently been suggested that these consistent differences in individual behaviour may be adaptive and the term 'animal personalities' has been used to describe them. In many cases, however, a degree of both behavioural plasticity and relative consistency is probable. To understand the possible functions of animal personalities, it is necessary to determine the relative strength of each tendency and this may be achieved by comparison of statistical effect sizes for tests of difference and concordance. Here, we describe a new statistical framework for making such comparisons and investigate cross-situational plasticity and consistency in the duration of startle responses in the European hermit crab Pagurus bernhardus, in the field and the laboratory. The effect sizes of tests for behavioural consistency were greater than for tests of behavioural plasticity, indicating for the first time the presence of animal personalities in a crustacean model.     

Evolving experience-dependent robust behaviour in embodied agents

In this work, based on behavioural and dynamical evidence, a study of simulated agents with the capacity to change feedback from their bodies to accomplish a one-legged walking task is proposed to understand the emergence of coupled dynamics for robust behaviour. Agents evolve with evolutionary-defined biases that modify incoming body signals (sensory offsets). Analyses on whether these agents show further dependence to their environmental coupled dynamics than others with no feedback control is described in this article. The ability to sustain behaviours is tested during lifetime experiments with mutational and sensory perturbations after evolution. Using dynamical systems analysis, this work identifies conditions for the emergence of dynamical mechanisms that remain functional despite sensory perturbations. Results indicate that evolved agents with evolvable sensory offset depends not only on where in neural space the state of the neural system operates, but also on the transients to which the inner-system was being driven by sensory signals from its interactions with the environment, controller, and agent body. Experimental evidence here leads discussions on a dynamical systems perspective on behavioural robustness that goes beyond attractors of controller phase space.     

Increasing sensor flexibility through neuromodulation

Both biological and man-made motor control networks require input from sensors to allow for modification of the motor program. Real sensory neurons are more flexible than typical robotic sensors because they are dynamic rather than static. The membrane properties of neurons and hence their excitability can be modified by the presence of neuromodulatory substances. In the case of a sensory neuron, this can change, in a functionally significant way, the code used to describe a stimulus. For instance, extension of the neuron's dynamic range or modification of its filtering characteristics can result. This flexibility has an apparent cost. The code used may be situation-dependent and hence difficult to interpret. To address this issue and to understand how neuromodulation is used effectively in a motor control network, I am studying the GPR2 stretch receptor in the crustacean stomatogastric nervous system. Several different neuromodulatory substances can modify its encoding properties. Comparisons of physiological and anatomical evidence suggest that neuromodulation can be effected both by GPR2 itself and by other neurons in the network. These results suggest that the analog of neuromodulation might be useful for improving sensor performance in an artificial motor control system.     

Nature as a model for technical sensors

Nature has developed a stunning diversity of sensory systems. Humans and many animals mainly rely on visual information. In addition, they may use acoustic, olfactory, and tactile cues for object detection and spatial orientation. Beyond these sensory systems a large variety of highly specialized sensors have evolved. For instance, some buprestid beetles use infrared organs for the detection of forest fires. The infrared sensors of boid and crotalid snakes are used for prey detection at night. For object detection and spatial orientation many species of nocturnal fish employ active electrolocation. This review describes certain aspects of the detection and processing of infrared and electrosensory information. We show that the study of natural exotic sensory systems can lead to discoveries that are useful for the construction of technical sensors and artificial control systems. Comparative studies of animal sensory systems have the power to uncover at least a small fraction of the gigantic untapped reservoir of natural solutions for perceptive problems.     

In silico reconstitution of DNA replication. Lessons from single-molecule imaging and cryo-tomography applied to single-particle cryo-EM

DNA replication has been reconstituted in vitro with yeast proteins, and the minimal system requires the coordinated assembly of 16 distinct replication factors, consisting of 42 polypeptides. To understand the molecular interplay between these factors at the single residue level, new structural biology tools are being developed. Inspired by advances in single-molecule fluorescence imaging and cryo-tomography, novel single-particle cryo-EM experiments have been used to characterise the structural mechanism for the loading of the replicative helicase. Here, we discuss how in silico reconstitution of single-particle cryo-EM data can help describe dynamic systems that are difficult to approach with conventional three-dimensional classification tools.