Corollary discharge inhibition and audition in the stridulating cricket

The romantic notion of crickets singing on a warm summer’s evening is quickly dispelled when one comes ear to ear with a stridulating male. Remarkably, stridulating male crickets are able to hear sounds from the environment despite generating a 100 db song (Heiligenberg 1969; Jones and Dambach 1973). This review summarises recent work examining how they achieve this feat of sensory processing. While the responsiveness of the crickets’ peripheral auditory system (tympanic membrane, tympanic nerve, state of the acoustic spiracle) is maintained during sound production, central auditory neurons are inhibited by a feedforward corollary discharge signal precisely timed to coincide with the auditory neurons’ maximum response to self-generated sound. In this way, the corollary discharge inhibition prevents desensitisation of the crickets’ auditory pathway during sound production.     

Peripheral electrosensory imaging by weakly electric fish

Different species have developed different solutions to the problem of constructing a representation of the environment from sensory images projected onto sensory surfaces. Comprehension of how these images are formed is an essential first step in understanding the representation of external reality by a given sensory system. Modeling of the electrical sensory images of objects began with the discovery of electroreception and continues to provide general insights into the mechanisms of imaging. Progress in electric image research has made it possible to establish the physical basis of electric imaging, as well as methods to accurately predict the electric images of objects alone and as a part of a natural electric scene. In this review, we show the following. (1) The internal low resistance of the fish’s body shapes the image in two different ways: by funneling the current generated by the electric organ to the sensory surface, it increases the fields rostrally, thus enhancing the perturbation produced by nearby objects; and by increasing the projected image. (2) The electric fish’s self-generated currents are modified by capacitive objects in a distinctive manner. These modulations can be detected by different receptor types, yielding the possibility of “electric color.” (3) The effects of different objects in a scene interact with each other, generating an image that is different from the simple addition of the images of individual objects, thus causing strong contextual effects.     

Mapping information flow in sensorimotor networks

Biological organisms continuously select and sample information used by their neural structures for perception and action, and for creating coherent cognitive states guiding their autonomous behavior. Information processing, however, is not solely an internal function of the nervous system. Here we show, instead, how sensorimotor interaction and body morphology can induce statistical regularities and information structure in sensory inputs and within the neural control architecture, and how the flow of information between sensors, neural units, and effectors is actively shaped by the interaction with the environment. We analyze sensory and motor data collected from real and simulated robots and reveal the presence of information structure and directed information flow induced by dynamically coupled sensorimotor activity, including effects of motor outputs on sensory inputs. We find that information structure and information flow in sensorimotor networks (a) is spatially and temporally specific; (b) can be affected by learning, and (c) can be affected by changes in body morphology. Our results suggest a fundamental link between physical embeddedness and information, highlighting the effects of embodied interactions on internal (neural) information processing, and illuminating the role of various system components on the generation of behavior.     

Encoding of Time-varying Stimuli in Populations of Cultured Neurons

We wondered whether random populations of dissociated cultured cortical neurons, despite of their lack of structure and/or regional specialization, are capable of modulating their neural activity as the effect of a time-varying stimulation – a simulated ‘sensory’ afference. More specifically, we used localized low-frequency, non-periodic trains of stimuli to simulate sensory afferences, and asked how much information about the original trains of stimuli could be extracted from the neural activity recorded at the different sites. Furthermore, motivated by the results of studies performed both in vivo and in vitro on different preparations, which suggested that isolated spikes and bursts may play different roles in coding time-varying signals, we explored the amount of such ‘sensory’ information that could be associated to these different firing modes. Finally, we asked whether and how such ‘sensory’ information is transferred from the sites of stimulation (i.e., the ‘sensory’ areas), to the other regions of the neural populations. To do this we applied stimulus reconstruction techniques and information theoretic concepts that are typically used to investigate neural coding in sensory systems. Our main results are that (1) slow variations of the rate of stimulation are coded into isolated spikes and in the time of occurrence of bursts (but not in the bursts’ temporal structure); (2) increasing the rate of stimulation has the effect of increasing the proportion of isolated spikes in the average evoked response and their importance in coding for the stimuli; and, (3) the ability to recover the time course of the pattern of stimulation is strongly related to the degree of functional connectivity between stimulation and recording sites. These observations parallel similar findings in intact nervous systems regarding the complementary roles of bursts and tonic spikes in encoding sensory information. Our results also have interesting implications in the field of neuro-robotic interfaces. In fact, the ability of populations of neurons to code information is a prerequisite for obtaining hybrid systems, in which neuronal populations are used to control external devices.     

Evolving robots able to integrate sensory-motor information over time

Summary We will discuss in which conditions we can expect the emergence of agents able to integrate sensory-motor information over time and later use this information to modulate their behavior accordingly. In doing so we will illustrate the problems that these agents should be able to solve and the processes that might lead to a transition from simple agents that only rely on sensory information or on their internal dynamic to agents that are also able to integrate information over time. The analysis of evolved individuals revealed that: (1) individuals able to integrate information over time rely on mixed strategy in which basic sensory-motor mechanisms are complemented and enhanced with additional internal mechanisms; (2) evolved individuals tend to rely on partial, action-oriented, and action-mediated representations of the external environment.     

Conditional transitions in gaze dynamics: role of vestibular nuclei in eye-only and eye/head gaze behaviors

 The gaze control system governs distinct gaze behaviors, including visual fixation and gaze reorientations. Transitions between these gaze behaviors are frequent and smooth in healthy individuals. This study models these gaze-behavior transitions for different numbers of gaze degrees of freedom. Eye/head gaze behaviors have twice the number of degrees of freedom as eye-only gaze behaviors. Each gaze behavior is observable in the system dynamics and is correlated with neuronal behaviors in several, coordinated neural centers, including the vestibular nuclei. The coordination among the neural centers establishes a sensorimotor state which maintains each gaze behavior. This study develops a mathematical framework for synthesizing the coordination among neural centers in gaze sensorimotor states and focuses on the role of vestibular nuclei neurons in gaze sensorimotor state transitions. Received: 17 December 1999 / Accepted in revised form: 3 May 2001     

Quantifying the Extent of Lateral Gene Transfer Required to Avert a ‘Genome of Eden’

The complex pattern of presence and absence of many genes across different species provides tantalising clues as to how genes evolved through the processes of gene genesis, gene loss, and lateral gene transfer (LGT). The extent of LGT, particularly in prokaryotes, and its implications for creating a ‘network of life’ rather than a ‘tree of life’ is controversial. In this paper, we formally model the problem of quantifying LGT, and provide exact mathematical bounds, and new computational results. In particular, we investigate the computational complexity of quantifying the extent of LGT under the simple models of gene genesis, loss, and transfer on which a recent heuristic analysis of biological data relied. Our approach takes advantage of a relationship between LGT optimization and graph-theoretical concepts such as tree width and network flow.     

Self-awareness and action

In this review we discuss how we are aware that actions are self-generated. We review behavioural data that suggest that a prediction of the sensory consequences of movement might be used to label actions and their consequences as self-generated. We also describe recent functional neuroimaging experiments and studies of neurological and psychiatric patients, which suggest that the parietal cortex plays a crucial role in the awareness of action.     

Evolution of the metathoracic tympanal ear and its mesothoracic homologue in the Macrolepidoptera (Insecta)

Two independent methods of comparison, serial homology and phylogenetic character mapping, are employed to investigate the evolutionary origin of the noctuoid moth (Noctuoidea) ear sensory organ. First, neurobiotin and Janus green B staining techniques are used to describe a novel mesothoracic chordotonal organ in the hawkmoth, Manduca sexta, which is shown to be serially homologous to the noctuoid metathoracic tympanal organ. This chordotonal organ comprises a proximal scolopidial region with three bipolar sensory cells, and a long flexible strand (composed of attachment cells) that connects peripherally to an unspecialized membrane ventral to the axillary cord of the fore-wing. Homology to the tympanal chordotonal organ in the Noctuoidea is proposed from anatomical comparisons of the meso- and metathoracic nerve branches and their corresponding peripheral attachment sites. Second, the general structure (noting sensory cell numbers, gross anatomy, and location of peripheral attachment sites) of both meso- and metathoracic organs is surveyed in 23 species representing seven superfamilies of the Lepidoptera. The structure of the wing-hinge chordotonal organ in both thoracic segments was found to be remarkably conserved in all superfamilies of the Macrolepidoptera examined except the Noctuoidea, where fewer than three cells occur in the metathoracic ear (one cell in representatives of the Notodontidae and two cells in those of other families examined), and at the mesothoracic wing-hinge (two cells) in the Notodontidae only. By mapping cell numbers onto current phylogenies of the Macrolepidoptera, we demonstrate that the three-celled wing-hinge chordotonal organ, believed to be a wing proprioceptor, represents the plesiomorphic state from which the tympanal organ in the Noctuoidea evolved. This ’trend toward simplicity’ in the noctuoid ear contrasts an apparent ’trend toward complexity’ in several other insect hearing organs where atympanate homologues have been studied. The advantages to having fewer rather than more cells in the moth ear, which functions primarily to detect the echolocation calls of bats, is discussed. Accepted: 18 June 1999     

The Causes and Consequences of Color Vision

The ability to see colors is not universal in the animal kingdom. Those animals that can detect differences in the wavelengths of the electromagnetic spectrum glean valuable sensory information about their environment. They use color vision to forage, avoid predators, and find high-quality mates. In the past, the colors that humans could see clouded scientists’ study of animals’ color perception. Leaving that bias behind has led to new insights about how and why the color vision of animals evolved. This paper provides a brief introduction to color vision, the genetics of color vision in humans, what colors other animals see, and how scientists study color vision. We examine the consequences of having color vision, including speciation, loss of olfactory capabilities, and sexual selection.     

Darwinian adaptation,population genetics and the streetcar theory of evolution

 This paper investigates the problem of how to conceive a robust theory of phenotypic adaptation in non-trivial models of evolutionary biology. A particular effort is made to develop a foundation of this theory in the context of n-locus population genetics. Therefore, the evolution of phenotypic traits is considered that are coded for by more than one gene. The potential for epistatic gene interactions is not a priori excluded. Furthermore, emphasis is laid on the intricacies of frequency-dependent selection. It is first discussed how strongly the scope for phenotypic adaptation is restricted by the complex nature of ‘reproduction mechanics’ in sexually reproducing diploid populations. This discussion shows that one can easily lose the traces of Darwinism in n-locus models of population genetics. In order to retrieve these traces, the outline of a new theory is given that I call ‘streetcar theory of evolution’. This theory is based on the same models that geneticists have used in order to demonstrate substantial problems with the ‘adaptationist programme’. However, these models are now analyzed differently by including thoughts about the evolutionary removal of genetic constraints. This requires consideration of a sufficiently wide range of potential mutant alleles and careful examination of what to consider as a stable state of the evolutionary process. A particular notion of stability is introduced in order to describe population states that are phenotypically stable against the effects of all mutant alleles that are to be expected in the long-run. Surprisingly, a long-term stable state can be characterized at the phenotypic level as a fitness maximum, a Nash equilibrium or an ESS. The paper presents these mathematical results and discusses – at unusual length for a mathematical journal – their fundamental role in our current understanding of evolution. Received 22 April 1994; received in revised form 10 July 1995     

Representations of uncertainty in sensorimotor control

Uncertainty is ubiquitous in our sensorimotor interactions, arising from factors such as sensory and motor noise and ambiguity about the environment. Setting it apart from previous theories, a quintessential property of the Bayesian framework for making inference about the state of world so as to select actions, is the requirement to represent the uncertainty associated with inferences in the form of probability distributions. In the context of sensorimotor control and learning, the Bayesian framework suggests that to respond optimally to environmental stimuli the central nervous system needs to construct estimates of the sensorimotor transformations, in the form of internal models, as well as represent the structure of the uncertainty in the inputs, outputs and in the transformations themselves. Here we review Bayesian inference and learning models that have been successful in demonstrating the sensitivity of the sensorimotor system to different forms of uncertainty as well as recent studies aimed at characterizing the representation of the uncertainty at different computational levels.     

Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice

Tactile information is actively acquired and processed in the brain through concerted interactions between movement and sensation. Somatosensory input is often the result of self-generated movement during the active touch of objects, and conversely, sensory information is used to refine motor control. There must therefore be important interactions between sensory and motor pathways, which we chose to investigate in the mouse whisker sensorimotor system. Voltage-sensitive dye was applied to the neocortex of mice to directly image the membrane potential dynamics of sensorimotor cortex with subcolumnar spatial resolution and millisecond temporal precision. Single brief whisker deflections evoked highly distributed depolarizing cortical sensory responses, which began in the primary somatosensory barrel cortex and subsequently excited the whisker motor cortex. The spread of sensory information to motor cortex was dynamically regulated by behavior and correlated with the generation of sensory-evoked whisker movement. Sensory processing in motor cortex may therefore contribute significantly to active tactile sensory perception.     

Pairwise competition and the replicator equation

Spite in Hamilton’s sense is defined as the willingness to harm oneself in order to harm another more. The standard replicator dynamic predicts that evolutionarily stable strategies are payoff-maximizing equilibria of the underlying game, and hence rules out the evolution of spiteful behavior. We propose a modified replicator dynamic, where selection is based on local outcomes, rather than on the population ’state’, as in standard models. We show that under this new model spite can evolve readily. The new dynamic suggests conditions under which spite in animals might be found.     

Termites as models of swarm cognition

Eusociality has evolved independently at least twice among the insects: among the Hymenoptera (ants and bees), and earlier among the Isoptera (termites). Studies of swarm intelligence, and by inference, swarm cognition, have focused largely on the bees and ants, while the termites have been relatively neglected. Yet, termites are among the world’s premier animal architects, and this betokens a sophisticated swarm intelligence capability. In this article, I review new findings on the workings of the mound of Macrotermes which clarify how these remarkable structures work, and how they come to be built. Swarm cognition in these termites is in the form of “extended” cognition, whereby the swarm’s cognitive abilities arise both from interaction amongst the individual agents within a swarm, and from the interaction of the swarm with the environment, mediated by the mound’s dynamic architecture. The latter provides large scale “cognitive maps” which enable termite swarms to assess the functional state of their structure and to guide repair efforts where necessary. The crucial role of the built environment in termite swarm cognition also points to certain “swarm cognitive disorders”, where swarms can be pushed into anomalous activities by manipulating crucial structural and functional attributes of the termite system of “extended cognition.”     

Using sensory weighting to model the influence of canal,otolith and visual cues on spatial orientation and eye movements

 The sensory weighting model is a general model of sensory integration that consists of three processing layers. First, each sensor provides the central nervous system (CNS) with information regarding a specific physical variable. Due to sensor dynamics, this measure is only reliable for the frequency range over which the sensor is accurate. Therefore, we hypothesize that the CNS improves on the reliability of the individual sensor outside this frequency range by using information from other sensors, a process referred to as “frequency completion.” Frequency completion uses internal models of sensory dynamics. This “improved” sensory signal is designated as the “sensory estimate” of the physical variable. Second, before being combined, information with different physical meanings is first transformed into a common representation; sensory estimates are converted to intermediate estimates. This conversion uses internal models of body dynamics and physical relationships. Third, several sensory systems may provide information about the same physical variable (e.g., semicircular canals and vision both measure self-rotation). Therefore, we hypothesize that the “central estimate” of a physical variable is computed as a weighted sum of all available intermediate estimates of this physical variable, a process referred to as “multicue weighted averaging.” The resulting central estimate is fed back to the first two layers. The sensory weighting model is applied to three-dimensional (3D) visual–vestibular interactions and their associated eye movements and perceptual responses. The model inputs are 3D angular and translational stimuli. The sensory inputs are the 3D sensory signals coming from the semicircular canals, otolith organs, and the visual system. The angular and translational components of visual movement are assumed to be available as separate stimuli measured by the visual system using retinal slip and image deformation. In addition, both tonic (“regular”) and phasic (“irregular”) otolithic afferents are implemented. Whereas neither tonic nor phasic otolithic afferents distinguish gravity from linear acceleration, the model uses tonic afferents to estimate gravity and phasic afferents to estimate linear acceleration. The model outputs are the internal estimates of physical motion variables and 3D slow-phase eye movements. The model also includes a smooth pursuit module. The model matches eye responses and perceptual effects measured during various motion paradigms in darkness (e.g., centered and eccentric yaw rotation about an earth-vertical axis, yaw rotation about an earth-horizontal axis) and with visual cues (e.g., stabilized visual stimulation or optokinetic stimulation). Received: 20 September 2000 / Accepted in revised form: 28 September 2001     

An integrative dynamic model of brain energy metabolism using <Emphasis Type="Italic">in vivo</Emphasis> neurochemical measurements

An integrative, systems approach to the modelling of brain energy metabolism is presented. Mechanisms such as glutamate cycling between neurons and astrocytes and glycogen storage in astrocytes have been implemented. A unique feature of the model is its calibration using in vivo data of brain glucose and lactate from freely moving rats under various stimuli. The model has been used to perform simulated perturbation experiments that show that glycogen breakdown in astrocytes is significantly activated during sensory (tail pinch) stimulation. This mechanism provides an additional input of energy substrate during high consumption phases. By way of validation, data from the perfusion of 50 μM propranolol in the rat brain was compared with the model outputs. Propranolol affects the glucose dynamics during stimulation, and this was accurately reproduced in the model by a reduction in the glycogen breakdown in astrocytes. The model’s predictive capacity was verified by using data from a sensory stimulation (restraint) that was not used for model calibration. Finally, a sensitivity analysis was conducted on the model parameters, this showed that the control of energy metabolism and transport processes are critical in the metabolic behaviour of cerebral tissue.