Sniffing is a rhythmic motor process essential for the acquisition of olfactory information. Recent behavioral experiments show that using a single sniff rats can accurately discriminate between very similar odors and...
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Sniffing is a rhythmic motor process essential for the acquisition of olfactory information. Recent behavioral experiments show that using a single sniff rats can accurately discriminate between very similar odors and fail to improve their accuracy by taking multiple sniffs. This implies that each sniff has the potential to provide a complete snapshot of the local olfactory environment. The discrete and intermittent nature of sniffing has implications beyond the physical process of odor capture as it strongly shapes the flow of information into the olfactory system. We review electrophysiological studies-primarily from anesthetized rodents-demonstrating that olfactory neural responses are coupled to respiration. Hence, the "sniff cycle" might play a role in odor coding, by allowing the timing of spikes with respect to the phase of the respiration cycle to encode information about odor identity or concentration. We also discuss behavioral and physiological results indicating that sniffing can be dynamically coordinated with other rhythmic behaviors, such as whisking, as well as with rhythmic neural activity, such as hippocampal theta oscillations. Thus, the sniff cycle might also facilitate the coordination of the olfactory system with other brain areas. These converging lines of empirical data support the notion that each sniff is a unit of olfactory processing relevant for both neural coding and inter-areal coordination. Further electrophysiological recordings in behaving animals will be necessary to assess these proposals.
The EMBO workshop on the The Assembly and Function of Neuronal Circuits was held at the Centro Stefano Franscini in Monte Verit, Ascona, Switzerland, from 25 to 30 Sep 2005. The meeting was the first in a new series t...
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The EMBO workshop on the The Assembly and Function of Neuronal Circuits was held at the Centro Stefano Franscini in Monte Verit, Ascona, Switzerland, from 25 to 30 Sep 2005. The meeting was the first in a new series that intends to bring together both developmental and systems neuroscientists. The talks covered a wide range of areas in neurobiology in many model organisms from worms to primates.
Understanding how neurons represent, process, and manipulate information is one of the main goals of neuroscience. These issues are fundamentally abstract, and information theory plays a key role in formalizing and ad...
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The peripheral nervous system consists of a large number of axons which transmit information from peripheral receptors to the central nervous system or from central nervous system to the muscles and glands in the peri...
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ISBN:
(纸本)9781424402526
The peripheral nervous system consists of a large number of axons which transmit information from peripheral receptors to the central nervous system or from central nervous system to the muscles and glands in the periphery. The theoretical maximum information transmission rate in those axons has been proposed to be much, even hundreds of bits per second in one axon. But, what are the information rates in practice, when the noise and other distorting factors are present in transmission, is not accurately known. To evaluate the practical information transmission rate in the peripheral nerves an in vitro information transmission study was done by using a frog sciatic nerve as a channel in artificial information transmission from one computer to another in laboratory environment. The highest achieved non-erroneous information transmission rate was 164 bit/s and the highest rate, including some errors, was 228 bit/s.
Information theoretic techniques are often used to investigate neural coding. Results - in terms of bits per second or bits per spike - have been used as evidence to support temporal or rate coding, spike timing preci...
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ISBN:
(纸本)0780378989
Information theoretic techniques are often used to investigate neural coding. Results - in terms of bits per second or bits per spike - have been used as evidence to support temporal or rate coding, spike timing precision, etc. Despite its use this way, information theory does not tell one what the neural code (or any code) is. In artificial systems, codes are often purposefully made sub-optimal from a pure information density point of view. This work tests the feasibility of a neural code containing error correction characteristics which uses greater spike timing precision than might be necessary to simply transmit a given amount of information. A model of the recognized prototype of an inhibitory synapse shows that, even compared to small input imprecision and in the: presence of robust dynamical behaviors, high timing precision can enable error correction.
We report on an experiment in which a population of rat cortical neurons, cultured on a micro-electrode array, was connected bi-directionally to a mobile robot. Bi-directional communication between a neural population...
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We report on an experiment in which a population of rat cortical neurons, cultured on a micro-electrode array, was connected bi-directionally to a mobile robot. Bi-directional communication between a neural population and an external device requires to translate time-varying signals into spatio-temporal patterns of neural activity, and back. Here, we describe the experimental setup and the computational modules of the neural interface, and work on characterization of the 'transfer function' of the neural preparation, as it emerges from closed-loop experiments, and selection of stimulation and recording sites which are best compatible with a desired behavior. (c) 2004 Elsevier B.V. All rights reserved.
When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discu...
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When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.
neural responses in the cerebral cortex exhibit tremendous variability. Understanding the origin and the functional meaning of this variability is of critical importance for our understanding of neural coding. The pre...
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neural responses in the cerebral cortex exhibit tremendous variability. Understanding the origin and the functional meaning of this variability is of critical importance for our understanding of neural coding. The present study investigates the neural response variability from the view of statistical inference. We will show that high variability can also arise due to the inferential sensitivity in neural coding. This view is supported by the simulation on the representation of nature images. (c) 2004 Elsevier B.V. All rights reserved.
Mutual information enjoys wide use in the computational neuroscience community for analyzing spiking neural systems. Its direct calculation is difficult because estimating the joint stimulus-response distribution requ...
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Mutual information enjoys wide use in the computational neuroscience community for analyzing spiking neural systems. Its direct calculation is difficult because estimating the joint stimulus-response distribution requires a prohibitive amount of data. Consequently, several techniques have appeared for bounding mutual information that rely on less data. We examine two upper bound techniques and find that they are unreliable and can introduce strong assumptions about the neural code. We also examine two lower bounds, showing that they can be very loose and possibly bear little relation to the mutual information's actual value. (c) 2004 Elsevier B.V. All rights reserved.
We have examined the information contained in the coordination of groups of cells in the primary visual cortex of the cat recorded with a 5 x 5 microelectrode array. When testing small differences ( 10 degrees) are di...
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We have examined the information contained in the coordination of groups of cells in the primary visual cortex of the cat recorded with a 5 x 5 microelectrode array. When testing small differences (< 10 degrees) in stimulus orientation with an information-theoretic distance, response discrimination depended on the temporal resolution of response sampling and improved when including response history. Joint activity also enhanced response discrimination and the enhancement was proportionally larger when more cells were sampled. Spike timing and intervals provided information about fine orientation differences. Even a small rotation of the visual stimulus produced clear time shifts in the response structure with little or no change in the spike count. Larger orientation differences (> 10 degrees) are discriminated easily on the basis of the independent spike Counts. We conclude that synchrony provides a reliable mechanism to transmit fine structure of visual information and offers an efficient cooperative neural code that we have only begun to explore. (c) 2005 Elsevier B.V. All rights reserved.
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