The Experts below are selected from a list of 141 Experts worldwide ranked by ideXlab platform
Eric S. Fortune - One of the best experts on this subject based on the ideXlab platform.
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Physiology of Tuberous Electrosensory Systems
Reference Module in Life Sciences, 2017Co-Authors: Michael G. Metzen, Eric S. Fortune, Maurice J. ChacronAbstract:Tuberous Electrosensory Systems are found in two orders of weakly electrogenic fishes, the Gymnotiformes of South America and the Mormyriformes of Africa. Tuberous Electrosensory Systems in both of these clades encode perturbations of the autogenous electric field produced by each fish. Here we review some of the organizational features and mechanisms used in tuberous Electrosensory Systems to represent information and extract salient features from these perturbations. At the periphery, Electrosensory neurons use combinations of rate and/or timing codes to broadly encode information. This information is subjected to complex filtering at the first stage of processing in the central nervous system, a hindbrain structure known as the Electrosensory lateral line lobe (ELL). Neurons in the ELL also receive massive descending feedback that dramatically alters their encoding properties. Neurons in the ELL in turn transmit Electrosensory information to the midbrain where complex features, such as moving objects and certain social signals, are extracted.
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DETECTION AND GENERATION OF ELECTRIC SIGNALS | Physiology of Tuberous Electrosensory Systems
Encyclopedia of Fish Physiology, 2011Co-Authors: Eric S. Fortune, Maurice J. ChacronAbstract:Tuberous Electrosensory Systems are found in two orders of weakly electrogenic fishes, the Gymnotiformes of South America and the Mormyriformes of Africa. In both of these clades encode perturbations of the autogenous electric field produced by each fish. Here, we review some of the organizational features and mechanisms used in tuberous Electrosensory Systems to represent information and extract salient features from these perturbations. At the periphery, Electrosensory neurons use combinations of rate and/or timing codes to broadly encode information. This information is subjected to complex filtering at the next stage of processing, a hindbrain structure known as the Electrosensory lateral line lobe (ELL). Neurons in the ELL receive massive descending feedback that can dramatically alters their encoding properties. Neurons in the ELL, in turn, transmit Electrosensory information to the midbrain where complex features, such as moving objects and certain social signals, are extracted.
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detection and generation of electric signals physiology of tuberous Electrosensory Systems
Encyclopedia of Fish Physiology#R##N#From Genome to Environment, 2011Co-Authors: Eric S. Fortune, Maurice J. ChacronAbstract:Tuberous Electrosensory Systems are found in two orders of weakly electrogenic fishes, the Gymnotiformes of South America and the Mormyriformes of Africa. In both of these clades encode perturbations of the autogenous electric field produced by each fish. Here, we review some of the organizational features and mechanisms used in tuberous Electrosensory Systems to represent information and extract salient features from these perturbations. At the periphery, Electrosensory neurons use combinations of rate and/or timing codes to broadly encode information. This information is subjected to complex filtering at the next stage of processing, a hindbrain structure known as the Electrosensory lateral line lobe (ELL). Neurons in the ELL receive massive descending feedback that can dramatically alters their encoding properties. Neurons in the ELL, in turn, transmit Electrosensory information to the midbrain where complex features, such as moving objects and certain social signals, are extracted.
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The decoding of Electrosensory Systems
Current opinion in neurobiology, 2006Co-Authors: Eric S. FortuneAbstract:Progress in the study of Electrosensory Systems has been facilitated by the systematic use of behavior as a tool to probe the nervous system. Indeed, a specific behavior that is found in a subset of weakly electric fishes, the jamming avoidance response, was used to identify and characterize an entire suite of brain circuits, from sensory receptors to motor units, that are involved in control of this behavior. Recent progress has focused on a re-analysis of this circuit in relation to newly described Electrosensory behaviors, including prey capture, social signaling and the tracking of Electrosensory objects. This re-analysis has led to a re-evaluation of the broader functional relevance of specific neural solutions to computational problems that are related to the control of the jamming avoidance response. Some of the recent insights that have emerged from this work include descriptions of mechanisms underlying dynamic receptive field properties, descriptions of the neural activity related to simultaneously occurring sensory stimuli, and a greater understanding of the role of short-term synaptic plasticity in temporal processing.
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Encoding and processing biologically relevant temporal information in Electrosensory Systems
Journal of comparative physiology. A Neuroethology sensory neural and behavioral physiology, 2006Co-Authors: Eric S. Fortune, Gary J. Rose, Masashi KawasakiAbstract:Wave-type weakly electric fish are specialists in time-domain processing: behaviors in these animals are often tightly correlated with the temporal structure of Electrosensory signals. Behavioral responses in these fish can be dependent on differences in the temporal structure of Electrosensory signals alone. This feature has facilitated the study of temporal codes and processing in central nervous system circuits of these animals. The temporal encoding and mechanisms used to transform temporal codes in the brain have been identified and characterized in several species, including South American gymnotid species and in the African mormyrid genus Gymnarchus. These distantly related groups use similar strategies for neural computations of information on the order of microseconds, milliseconds, and seconds. Here, we describe a suite of mechanisms for behaviorally relevant computations of temporal information that have been elucidated in these Systems. These results show the critical role that behavioral experiments continue to have in the study of the neural control of behavior and its evolution.
Nathaniel B. Sawtell - One of the best experts on this subject based on the ideXlab platform.
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influences of motor Systems on Electrosensory processing
2019Co-Authors: Krista Perks, Nathaniel B. SawtellAbstract:The first central stage of Electrosensory processing in fish has proven to be a particularly useful model system for examining the general issue of how motor Systems and behavior influence sensory processing. This chapter reviews this literature, focusing on a substantial body of work elucidating the synaptic, cellular, and circuit mechanisms for predicting and canceling self-generated sensory inputs. Some additional functions of motor corollary discharge signals in weakly electric mormyrid fish are also discussed along with the implications of studies on Electrosensory Systems for other sensory modalities and brain structures, including the auditory system and the cerebellum.
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Neural Mechanisms for Predicting the Sensory Consequences of Behavior: Insights from Electrosensory Systems.
Annual review of physiology, 2016Co-Authors: Nathaniel B. SawtellAbstract:Perception of the environment requires differentiating between external sensory inputs and those that are self-generated. Some of the clearest insights into the neural mechanisms underlying this process have come from studies of the Electrosensory Systems of fish. Neurons at the first stage of Electrosensory processing generate negative images of the Electrosensory consequences of the animal's own behavior. By canceling out the effects of predictable, self-generated inputs, negative images allow for the selective encoding of unpredictable, externally generated stimuli. Combined experimental and theoretical studies of Electrosensory Systems have led to detailed accounts of how negative images are formed at the level of synaptic plasticity rules, cells, and circuits. Here, I review these accounts and discuss their implications for understanding how predictions of the sensory consequences of behavior may be generated in other sensory structures and the cerebellum.
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A comparative approach to cerebellar function: insights from Electrosensory Systems
Current Opinion in Neurobiology, 2016Co-Authors: Richard Warren, Nathaniel B. SawtellAbstract:Despite its simple and highly-ordered circuitry the function of the cerebellum remains a topic of vigorous debate. This review explores connections between the cerebellum and sensory processing structures that closely resemble the cerebellum in terms of their evolution, development, patterns of gene expression, and circuitry. Recent studies of cerebellum-like structures involved in Electrosensory processing in fish have provided insights into the functions of granule cells and unipolar brush cells — cell types shared with the cerebellum. We also discuss the possibility, supported by recent studies, that generating and subtracting predictions of the sensory consequences of motor commands may be core functions shared by both cerebellum-like structures and the cerebellum.
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Adaptive processing in Electrosensory Systems: links to cerebellar plasticity and learning.
Journal of Physiology-paris, 2008Co-Authors: Nathaniel B. Sawtell, Curtis C. BellAbstract:The first central stage of Electrosensory processing in fish takes place in structures with local circuitry that resembles the cerebellum. Cerebellum-like structures and the cerebellum itself share common patterns of gene expression and may also share developmental and evolutionary origins. Given these similarities it is natural to ask whether insights gleaned from the study of cerebellum-like structures might be useful for understanding aspects of cerebellar function and vice versa. Work from Electrosensory Systems has shown that cerebellum-like circuitry acts to generate learned predictions about the sensory consequences of the animals' own behavior through a process of associative plasticity at parallel fiber synapses. Subtraction of these predictions from the actual sensory input serves to highlight unexpected and hence behaviorally relevant features. Learning and prediction are also central to many current ideas regarding the function of the cerebellum itself. The present review draws comparisons between cerebellum-like structures and the cerebellum focusing on the properties and sites of synaptic plasticity in these structures and on connections between plasticity and learning. Examples are drawn mainly from the Electrosensory lobe (ELL) of mormyrid fish and from extensive work characterizing the role of the cerebellum in Pavlovian eyelid conditioning and vestibulo-ocular reflex (VOR) modification. Parallels with other cerebellum-like structures, including the gymnotid ELL, the elasmobranch dorsal octavolateral nucleus (DON), and the mammalian dorsal cochlear nucleus (DCN) are also discussed.
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From sparks to spikes: information processing in the Electrosensory Systems of fish
Current Opinion in Neurobiology, 2005Co-Authors: Nathaniel B. Sawtell, Alan Williams, Curtis C. BellAbstract:Recent work on Electrosensory Systems in fish has combined traditional neuroethological approaches with quantitative methods for characterizing neural coding. These studies have shed light on general issues in sensory processing, including how peripheral sensory receptors encode external stimuli and how these representations are transformed at subsequent stages of processing.
Curtis C. Bell - One of the best experts on this subject based on the ideXlab platform.
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Adaptive processing in Electrosensory Systems: links to cerebellar plasticity and learning.
Journal of Physiology-paris, 2008Co-Authors: Nathaniel B. Sawtell, Curtis C. BellAbstract:The first central stage of Electrosensory processing in fish takes place in structures with local circuitry that resembles the cerebellum. Cerebellum-like structures and the cerebellum itself share common patterns of gene expression and may also share developmental and evolutionary origins. Given these similarities it is natural to ask whether insights gleaned from the study of cerebellum-like structures might be useful for understanding aspects of cerebellar function and vice versa. Work from Electrosensory Systems has shown that cerebellum-like circuitry acts to generate learned predictions about the sensory consequences of the animals' own behavior through a process of associative plasticity at parallel fiber synapses. Subtraction of these predictions from the actual sensory input serves to highlight unexpected and hence behaviorally relevant features. Learning and prediction are also central to many current ideas regarding the function of the cerebellum itself. The present review draws comparisons between cerebellum-like structures and the cerebellum focusing on the properties and sites of synaptic plasticity in these structures and on connections between plasticity and learning. Examples are drawn mainly from the Electrosensory lobe (ELL) of mormyrid fish and from extensive work characterizing the role of the cerebellum in Pavlovian eyelid conditioning and vestibulo-ocular reflex (VOR) modification. Parallels with other cerebellum-like structures, including the gymnotid ELL, the elasmobranch dorsal octavolateral nucleus (DON), and the mammalian dorsal cochlear nucleus (DCN) are also discussed.
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From sparks to spikes: information processing in the Electrosensory Systems of fish
Current Opinion in Neurobiology, 2005Co-Authors: Nathaniel B. Sawtell, Alan Williams, Curtis C. BellAbstract:Recent work on Electrosensory Systems in fish has combined traditional neuroethological approaches with quantitative methods for characterizing neural coding. These studies have shed light on general issues in sensory processing, including how peripheral sensory receptors encode external stimuli and how these representations are transformed at subsequent stages of processing.
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Memory-based expectations in Electrosensory Systems.
Current opinion in neurobiology, 2001Co-Authors: Curtis C. BellAbstract:Adaptive processing of Electrosensory information occurs in the cerebellum-like structures of three distinct groups of fish. Associations within each of these structures result in the generation of negative images of predictable features of the sensory inflow. Addition of these negative images to the actual inflow removes the predictable features, allowing the unpredictable, information-rich sensory signals to stand out. Evidence from all three groups of fish indicates that the negative images are mediated by plasticity at parallel fiber synapses.
Laura K. Jordan - One of the best experts on this subject based on the ideXlab platform.
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Functional consequences of structural differences in stingray sensory Systems. Part II: Electrosensory system
The Journal of experimental biology, 2009Co-Authors: Laura K. Jordan, Stephen M. Kajiura, Malcolm S. GordonAbstract:Elasmobranch fishes (sharks, skates and rays) possess highly sensitive Electrosensory Systems, which enable them to detect weak electric fields such as those produced by potential prey organisms. Different species have unique Electrosensory pore numbers, densities and distributions. Functional differences in detection capabilities resulting from these structural differences are largely unknown. Stingrays and other batoid fishes have eyes positioned on the opposite side of the body from the mouth. Furthermore, they often feed on buried prey, which can be located non-visually using the Electrosensory system. In the present study we test functional predictions based on structural differences in three stingray species (Urobatis halleri, Pteroplatytrygon violacea and Myliobatis californica) with differing Electrosensory system morphology. We compare detection capabilities based upon behavioral responses to dipole electric signals (5.3-9.6 microA). Species with greater ventral pore numbers and densities were predicted to demonstrate enhanced Electrosensory capabilities. Electric field intensities at orientation were similar among these species, although they differed in response type and orientation pathway. Minimum voltage gradients eliciting feeding responses were well below 1 nVcm(-1) for all species regardless of pore number and density.
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Comparative morphology of stingray lateral line canal and Electrosensory Systems.
Journal of morphology, 2008Co-Authors: Laura K. JordanAbstract:Elasmobranchs (sharks, skates, and rays) possess a variety of sensory Systems including the mechanosensory lateral line and Electrosensory Systems, which are particularly complex with high levels of interspecific variation in batoids (skates and rays). Rays have dorsoventrally compressed, laterally expanded bodies that prevent them from seeing their mouths and more often than not, their prey. This study uses quantitative image analysis techniques to identify, quantify, and compare structural differences that may have functional consequences in the detection capabilities of three Eastern Pacific stingray species. The benthic round stingray, Urobatis halleri, pelagic stingray, Pteroplatytrygon (Dasyatis) violacea, and benthopelagic bat ray, Myliobatis californica, show significant differences in sensory morphology. Ventral lateral line canals correlate with feeding ecology and differ primarily in the proportion of pored and nonpored canals and the degree of branching complexity. Urobatis halleri shows a high proportion of nonpored canals, while P. violacea has an intermediate proportion of pored and nonpored canals with almost no secondary branching of pored canals. In contrast, M. californica has extensive and highly branched pored ventral lateral line canals that extended laterally toward the wing tips on the anterior edge of the pectoral fins. Electrosensory morphology correlates with feeding habitat and prey mobility; benthic feeders U. halleri and M. californica, have greater Electrosensory pore numbers and densities than P. violacea. The percentage of the wing surface covered by these sensory Systems appears to be inversely related to swimming style. These methods can be applied to a broader range of species to enable further discussion of the relationship of phylogeny, ecology, and morphology, while the results provide testable predictions of detection capabilities. J. Morphol., 2008. © 2008 Wiley-Liss, Inc.
David Bodznick - One of the best experts on this subject based on the ideXlab platform.
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Signals and noise in the elasmobranch Electrosensory system
The Journal of Experimental Biology, 1999Co-Authors: John C. Montgomery, David BodznickAbstract:Analyzing signal and noise for any sensory system requires an appreciation of the biological and physical milieu of the animal. Behavioral studies show that elasmobranchs use their Electrosensory Systems extensively for prey detection, but also for mate recognition and possibly for navigation. These biologically important signals are detected against a background of self-generated bioelectric fields. Noise-suppression mechanisms can be recognized at a number of different levels: behavior, receptor anatomy and physiology, and at the early stages of sensory processing. The peripheral filters and receptor characteristics provide a detector with permissive temporal properties but restrictive spatial characteristics. Biologically important signals probably cover the range from direct current to 10 Hz, whereas the bandwidth of the receptors is more like 0.1-10 Hz. This degree of alternating current coupling overcomes significant noise problems while still allowing the animal to detect external direct current signals by its own movement. Self-generated bioelectric fields modulated by breathing movement have similar temporal characteristics to important external signals and produce very strong modulation of Electrosensory afferents. This sensory reafference is essentially similar, or common-mode, across all afferent fibers. The principal Electrosensory neurons (ascending efferent neurons; AENs) of the dorsal octavolateralis nucleus show a greatly reduced response to common-mode signals. This suppression is mediated by the balanced excitatory and inhibitory components of their spatial receptive fields. The receptive field characteristics of AENs determine the information extracted from external stimuli for further central processing.
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An adaptive filter that cancels self-induced noise in the Electrosensory and lateral line mechanosensory Systems of fish ☆
Neuroscience letters, 1994Co-Authors: John C. Montgomery, David BodznickAbstract:In lateral line and Electrosensory Systems of fish, the animal's own movements create unwanted stimulation that could interfere with the detection of biologically important signals. Here we report that an adaptive filter in the medullary nuclei of both senses suppresses self-stimulation. Second-order Electrosensory neurons in an elasmobranch fish and mechanosensory neurons in a teleost fish learn to cancel the effects of stimuli that are presented coupled to the fish's movements. A model is proposed for how the adaptive filter is realized by the cerebellar-like circuits of the hindbrain nuclei in these senses.