Mark E. Nelson

Brain maps and parallel computers

It is well known that neural responses in many brain regions are organized in characteristic spatial patterns referred to as brain maps. It is likely that these patterns in some way reflect aspects of the neural computations being performed, but to date there are no general guiding principles for relating the structure of a brain map to the properties of the associated computation. In the field of parallel computing, maps similar to brain maps arise when computations are distributed across the multiple processors of a parallel computer. In this case, the relationship between maps and computations is well understood and general principles for optimally mapping computations onto parallel computers have been developed. In this paper we discuss how these principles may help illuminate the relationship between maps and computations in the nervous system.

Modeling signal and background components of electrosensory scenes

Weakly electric fish are able to detect and localize prey based on microvolt-level perturbations in the fish’s self-generated electric field. In natural environments, weak prey-related signals are embedded in much stronger electrosensory background noise. To better characterize the signal and background components associated with natural electrolocation tasks, we recorded transdermal voltage modulations in restrained Apteronotus albifrons in response to moving spheres, tail bends, and large nonconducting boundaries. Spherical objects give rise to ipsilateral images with center-surround structure and contralateral images that are weak and diffuse. Tail bends and laterally placed nonconducting boundaries induce relatively strong ipsilateral and contralateral modulations of opposite polarity. We present a computational model of electric field generation and electrosensory image formation that is able to reproduce the key features of these empirically measured signal and background components in a unified framework. The model comprises an array of point sources and sinks distributed along the midline of the fish, which can conform to arbitrary body bends. The model is computationally fast and can be used to estimate the spatiotemporal pattern of activation across the entire electroreceptor array of the fish during natural behaviors.

Architectures for a biomimetic hexapod robot

Abstract This paper describes a six-legged robot based on the features of an agile insect, the American cockroach, Periplaneta americana. The robot is designed with insect-like leg structure and placement, and actuators that mimic muscles. A test leg is also described that shows how sensory feedback can serve as the basis of the control system for the robot in order for it to achieve the degree of adaptability of locomotion over rough terrain exhibited by insects.

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

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

Omnidirectional Sensory and Motor Volumes in Electric Fish

Active sensing organisms, such as bats, dolphins, and weakly electric fish, generate a 3-D space for active sensation by emitting self-generated energy into the environment. For a weakly electric fish, we demonstrate that the electrosensory space for prey detection has an unusual, omnidirectional shape. We compare this sensory volume with the animals motor volume—the volume swept out by the body over selected time intervals and over the time it takes to come to a stop from typical hunting velocities. We find that the motor volume has a similar omnidirectional shape, which can be attributed to the fishs backward-swimming capabilities and body dynamics. We assessed the electrosensory space for prey detection by analyzing simulated changes in spiking activity of primary electrosensory afferents during empirically measured and synthetic prey capture trials. The animals motor volume was reconstructed from video recordings of body motion during prey capture behavior. Our results suggest that in weakly electric fish, there is a close connection between the shape of the sensory and motor volumes. We consider three general spatial relationships between 3-D sensory and motor volumes in active and passive-sensing animals, and we examine hypotheses about these relationships in the context of the volumes we quantify for weakly electric fish. We propose that the ratio of the sensory volume to the motor volume provides insight into behavioral control strategies across all animals.

Modeling Electrosensory and Mechanosensory Images during the Predatory Behavior of Weakly Electric Fish

Black ghost knifefish (Apteronotus albifrons) are nocturnal, weakly electric fish that feed on insect larvae and small crustaceans in the freshwater rivers of South America. In the absence of visual cues, prey detection and localization in this species is likely to rely on weak electrosensory and mechanosensory cues generated by the prey. In this paper, a modeling approach is used to estimate contributions to prey capture behavior from three octavolateralis modalities: the high- (tuberous) and low- (ampullary) frequency components of the electric sense and the high-frequency (canal neuromast) component of the lateral line mechanosensory system. For each of these modalities, the physical stimulus generated by the prey is approximated using a simple dipole model. Model parameters are constrained using previously published data as well as new empirical data on the electrical impedance characteristics of Daphnia magna. Models of electrosensory and mechanosensory stimuli are combined with actual prey strike trajectories from infrared video recordings to reconstruct spatial images of the prey along the sensory surface of the fish during the behavior. Modeling results suggest that all three modalities might contribute and that the relative contributions may change as a function of environmental conditions (e.g., water conductivity) and as a function of time over the course of the prey capture event.

MDScope — A Visual Computing Environment for Structural Biology

We describe the program MDScope, an integrated set of computational tools which function as an interactive visual computing environment for the simulation and study of biopoly-mers. This environment consists of three parts: (1) vmd, a molecular visualization program for interactive display of molecular systems; (2) namd, a molecular dynamics program designed for performance, scalability, modularity, and portability, which runs in parallel on a variety of computer platforms; (3) MDCOMM, a protocol and library which functions as the unifying communication agent between the visualization and simulation components of MDScope. Modularity in both vmd and namd is accomplished through an object-oriented design, which facilitates the addition of features and new algorithms.

Neural simulations of adaptive reafference suppression in the elasmobranch electrosensory system

The electrosensory system of elasmobranchs is extremely sensitive to weak electric fields, with behavioral thresholds having been reported at voltage gradients as low as 5 nV/cm. To achieve this amazing sensitivity, the electrosensory system must extract weak extrinsic signals from a relatively large reafferent background signal associated with the animals own movements. Ventilatory movements, in particular, strongly modulate the firing rates of primary electrosensory afferent nerve fibers, but this modulation is greatly suppressed in the medullary electrosensory processing nucleus, the dorsal octavolateral nucleus. Experimental evidence suggests that the neural basis of reafference suppression involves a common-mode rejection mechanism supplemented by an adaptive filter that fine tunes the cancellation. We present a neural model and computer simulation results that support the hypothesis that the adaptive component may involve an anti-Hebbian form of synaptic plasticity at molecular layer synapses onto ascending efferent neurons, the principal output neurons of the nucleus. Parallel fibers in the molecular layer carry a wealth of proprioceptive, efference copy, and sensory signals related to the animals own movements. The proposed adaptive mechanism acts by canceling out components of the electrosensory input signal that are consistently correlated with these internal reference signals.

A mechanism for neuronal gain control by descending pathways

Many implementations of adaptive signal processing in the nervous system are likely to require a mechanism for gain control at the single neuron level. To properly adjust the gain of an individual neuron, it may be necessary to use information carried by neurons in other parts of the system. The ability to adjust the gain of neurons in one part of the brain, using control signals arising from another, has been observed in the electrosensory system of weakly electric fish, where descending pathways to a first-order sensory nucleus have been shown to influence the gain of its output neurons. Although the neural circuitry associated with this system is well studied, the exact nature of the gain control mechanism is not fully understood. In this paper, we propose a mechanism based on the regulation of total membrane conductance via synaptic activity on descending pathways. Using a simple neural model, we show how the activity levels of paired excitatory and inhibitory control pathways can regulate the gain and baseline excitation of a target neuron.

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.