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中国神经科学学会第九届全国学术会议暨第五次会员代表大会

作者： Long-Nian LIN Key Laboratory of Brain Functional Genomics(Ministry of Education and Shanghai),Institute of Brain Functional Genomics,East China Normal University,Shanghai 200062,China

Fear and anxiety both produce similar responses to certain *** is an emotional response to an imprecise or unknown threat,and fear is an affective response to a real threat or *** amygdala has been proposed to play an essential role in the mediation of emotions such as fear and ***,the neural coding mechanisms underlying fear and anxiety in the amygdala are not *** using multi-channel recording techniques,we investigated the neuronal activity in the mouse amygdala responding to various threatening contexts. Here we report that in freely behaving mice,one group of neurons in the basolateral amygdala(BLA) could respond to diverse menaces such as heights and moving *** baseline firing rates of these neurons were remarkably low,about(0.1±0.12) Hz.A subset of these neurons can be selectively activated by fear of *** firing rates increased dramatically[(11.39±0.86) Hz]when mice stayed on an elevated platform(10 cm long,7 cm wide,and 10 cm high);their firing rates could reach 50 Hz when mice fell from a high *** subset of these neurons was sensitive to the movement regardless of other properties of *** neurons could respond to all kinds of moving objects,such as moving toys,shaking hands,and flashing characters on the computer *** firing rates increased significantly to 30-60 Hz when given strikingly different moving *** group of neurons in the BLA fires tonically under anxiety conditions in both open-field and elevated plus-maze *** firing patterns of these neurons displayed a characteristic slow onset and progressively increased firing ***,these firing patterns were correlated to a gradual development of anxiety-like behaviors in the open-field ***, these neurons could be activated by any impoverished environment similar to an open-field;and introduction of both comfortable and uncomfortable stimuli temporarily suppressed the activity of t

关键词： amygdala fear anxiety neural coding

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Enhancement of neural stochastic firing in cochlear implant stimulation by the addition of noise: A computational study of the influence of stimulation settings and spontaneous activity

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COMPUTERS IN BIOLOGY AND MEDICINE 2010年第6期40卷 597-606页

作者： Paglialonga, Alessia Fiocchi, Serena Ravazzani, Paolo Tognola, Gabriella Politecn Milan CNR Ist Ingn Biomed Dipartimento BioingnISIB I-20133 Milan Italy

It is known that, in cochlear implants (CIs), the addition of noise to CI stimuli may enhance the stochastic firing in the auditory nerve (AN). The aim of this study was to investigate, by using a model of a fiber of the AN the influence of CI stimulation settings (i.e., stimulation rate and stimulus magnitude) and fiber spontaneous activity on the enhancement of stochastic firing when CI stimuli are combined with noise. Results showed that the stimulation rate had an effect on the enhancement of stochastic firing in the AN, whereas the stimulus magnitude and the spontaneous firing rate had no influence. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Cochlear implants Electrical stimulation Auditory nerve Nerve fiber models Stochastic firing neural coding Stochastic resonance Noise

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Symmetry Breaking in Soft Clustering Decoding of neural Codes

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IEEE TRANSACTIONS ON INFORMATION THEORY 2010年第2期56卷 901-927页

作者： Parker, Albert E. Dimitrov, Alexander G. Gedeon, Tomas Montana State Univ Ctr Biofilm Engn Bozeman MT 59717 USA Univ Auckland New Zealand Inst Math Auckland 1 New Zealand Montana State Univ Ctr Computat Biol Bozeman MT 59717 USA Montana State Univ Dept Cell Biol & Neurosci Bozeman MT 59717 USA Montana State Univ Dept Math Sci Bozeman MT 59717 USA

Information-based distortion methods have been used successfully in the analysis of neural coding problems. These approaches allow the discovery of neural symbols and the corresponding stimulus space of a neuron or neural ensemble quantitatively, while making few assumptions about the nature of either the code or of relevant stimulus features. The neural code-book is derived by quantizing sensory stimuli and neural responses into a small set of clusters, and optimizing the quantization to minimize an information distortion function. The method of annealing has been used to solve the corresponding high-dimensional nonlinear optimization problem. The annealing solutions undergo a series of bifurcations, which we study using bifurcation theory in the presence of symmetries. In this contribution we describe these symmetry breaking bifurcations in detail, and indicate some of the consequences of the form of the bifurcations. In particular, we show that the annealing solutions break symmetry at pitchfork bifurcations, and that subcritical branches can exist. Thus, at a subcritical bifurcation, there are local information distortion solutions which are not found by the method of annealing. Since the annealing procedure is guaranteed to converge to a local solution eventually, the subcritical branch must turn and become optimal at some later saddle-node bifurcation, which we have shown occur generically for this class of problems. This implies that the rate distortion curve, while convex for noninformation-based distortion measures, is not convex for information-based distortion methods.

关键词： Annealing bifurcations clustering information distortion neural coding symmetry breaking

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Ecological expected utility and the mythical neural code

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COGNITIVE NEURODYNAMICS 2010年第1期4卷 25-35页

作者： Feldman, Jerome Univ Calif Berkeley Berkeley CA 94720 USA Int Comp Sci Inst Berkeley CA 94704 USA

neural spikes are an evolutionarily ancient innovation that remains nature's unique mechanism for rapid, long distance information transfer. It is now known that neural spikes sub serve a wide variety of functions and essentially all of the basic questions about the communication role of spikes have been answered. Current efforts focus on the neural communication of probabilities and utility values involved in decision making. Significant progress is being made, but many framing issues remain. One basic problem is that the metaphor of a neural code suggests a communication network rather than a recurrent computational system like the real brain. We propose studying the various manifestations of neural spike signaling as adaptations that optimize a utility function called ecological expected utility.

关键词： neural coding Ecological utility Neuroeconomics Spikes Grandmother cell Population code Binding problem

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Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2010年第1-2期29卷 49-62页

作者： Saleem, Aman B. Chadderton, Paul Apergis-Schoute, John Harris, Kenneth D. Schultz, Simon R. Univ London Imperial Coll Sci Technol & Med Dept Bioengn London SW7 2AZ England UCL Ear Inst London WC1X 8EE England Rutgers State Univ Ctr Mol & Behav Neurosci Newark NJ 07102 USA

During anesthesia, slow-wave sleep and quiet wakefulness, neuronal membrane potentials collectively switch between de- and hyperpolarized levels, the cortical UP and DOWN states. Previous studies have shown that these cortical UP/DOWN states affect the excitability of individual neurons in response to sensory stimuli, indicating that a significant amount of the trial-to-trial variability in neuronal responses can be attributed to ongoing fluctuations in network activity However, as intracellular recordings are frequently not available, it is important to be able to estimate their occurrence purely from extracellular data. Here, we combine in vivo whole cell recordings from single neurons with multi-site extracellular microelectrode recordings, to quantify the performance of various approaches to predicting UP/DOWN states from the deep-layer local field potential (LFP). We find that UP/DOWN states in deep cortical layers of rat primary

关键词： UP and DOWN states LFP State dependent coding neural coding Spontaneous activity neural oscillations

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Developmental Experience Alters Information coding in Auditory Midbrain and Forebrain Neurons

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DEVELOPMENTAL NEUROBIOLOGY 2010年第4期70卷 235-252页

作者： Woolley, Sarah M. N. Hauber, Mark E. Theunissen, Frederic E. Columbia Univ Dept Psychol New York NY 10027 USA CUNY Hunter Coll Dept Psychol New York NY 10065 USA Univ Auckland Sch Biol Sci Auckland 1 New Zealand Univ Calif Berkeley Dept Psychol Berkeley CA 94720 USA

In songbirds, species identity and developmental experience shape vocal behavior and behavioral responses to vocalizations. The interaction of species identity and developmental experience may also shape the coding, properties of sensor neurons. We tested whether responses of auditory midbrain and forebrain neurons to songs differed between species and between groups of conspecific birds with different developmental exposure to song. We also compared responses of individual neurons to conspecific and heterospecific songs. Zebra and Bengalese finches that were raised and tutored by, conspecific birds, and zebra finches that were cross-tutored by Bengalese finches were studied. Single-unit responses to zebra and Bengalese finch songs were recorded and analyzed by calculating mutual information (MI). response reliability. mean spike rate, fluctuations in time-varying spike rate. distributions of time-varying spike rates. and neural discrimination of individual Songs. MI (quantities a response's capacity to encode information about a stimulus. In midbrain and forebrain neurons, M1 was significantly higher in normal zebra finch neurons than in Bengalese finch and cross-tutored zebra finch neurons, but not between Bengalese finch and cross-tutored zebra finch neurons. Information rate differences were largely due to spike rate differences. M1 did not differ between responses to conspecific and heterospecific songs. Therefore, neurons from normal zebra finches encoded more information about songs than (fill neurons from other birds, but conspecific and heterospecific songs were encoded equally. neural discrimination of songs and M1 were highly correlated. Results demonstrate that developmental exposure to vocalizations shapes file information coding properties of songbird auditory neurons. (C) 2009 Wiley Periodicals. Inc Develop Neurobiol 70 235-252, 2010

关键词： inferior colliculus vocalization songbird neural coding song

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Encoding and decoding amplitude-modulated cochlear implant stimuli-a point process analysis

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2010年第3期28卷 405-424页

作者： Goldwyn, Joshua H. Shea-Brown, Eric Rubinstein, Jay T. Univ Washington Dept Appl Math Seattle WA 98195 USA Univ Washington Virginia Merrill Bloedel Hearing Res Ctr Dept Otolaryngol Seattle WA 98195 USA Univ Washington Dept Biomed Engn Seattle WA 98195 USA

Cochlear implant speech processors stimulate the auditory nerve by delivering amplitude-modulated electrical pulse trains to intracochlear electrodes. Studying how auditory nerve cells encode modulation information is of fundamental importance, therefore, to understanding cochlear implant function and improving speech perception in cochlear implant users. In this paper, we analyze simulated responses of the auditory nerve to amplitude-modulated cochlear implant stimuli using a point process model. First, we quantify the information encoded in the spike trains by testing an ideal observer's ability to detect amplitude modulation in a two-alternative forced-choice task. We vary the amount of information available to the observer to probe how spike timing and averaged firing rate encode modulation. Second, we construct a neural decoding method that predicts several qualitative trends observed in psychophysical tests of amplitude modulation detection in cochlear implant listeners. We find that modulation information is primarily available in the sequence of spike times. The performance of an ideal observer, however, is inconsistent with observed trends in psychophysical data. Using a neural decoding method that jitters spike times to degrade its temporal resolution and then computes a common measure of phase locking from spike trains of a heterogeneous population of model nerve cells, we predict the correct qualitative dependence of modulation detection thresholds on modulation frequency and stimulus level. The decoder does not predict the observed loss of modulation sensitivity at high carrier pulse rates, but this framework can be applied to future models that better represent auditory nerve responses to high carrier pulse rate stimuli. The supplemental material of this article contains the article's data in an active, re-usable format.

关键词： Point process model Cochlear implant Auditory nerve Amplitude modulation neural coding

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Transformation of neuronal modes associated with low-Mg²⁺/high-K⁺ conditions in an in vitro model of epilepsy

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JOURNAL OF BIOLOGICAL PHYSICS 2010年第1期36卷 95-107页

作者： Kang, Eunji E. Zalay, Osbert C. Cotic, Marija Carlen, Peter L. Bardakjian, Berj L. Univ Toronto Inst Biomat & Biomed Engn Toronto ON M5S 3G9 Canada Univ Toronto Edward S Rogers Sr Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Toronto Western Res Inst Div Fundamental Neurobiol Toronto ON M5T 2S8 Canada Univ Toronto Dept Physiol Toronto ON M5S 1A8 Canada

Nonparametric system modeling constitutes a robust method for the analysis of physiological systems as it can be used to identify nonlinear dynamic input-output relationships and facilitate their description. First- and second-order kernels of hippocampal CA3 pyramidal neurons in an in vitro slice preparation were computed using the Volterra-Wiener approach to investigate system changes associated with epileptogenic low-magnesium/high-potassium (low-Mg2 + /high-K (+) ) conditions. The principal dynamic modes (PDMs) of neurons were calculated from the first- and second-order kernel estimates in order to characterize changes in neural coding functionality. From our analysis, an increase in nonlinear properties was observed in kernels under low-Mg2 + /high-K (+) . Furthermore, the PDMs revealed that the sampled hippocampal CA3 neurons were primarily of integrating character and that the contribution of a differentiating mode component was enhanced under low-Mg2 + /high-K (+) .

关键词： Epileptogenesis Epileptiform High potassium Low magnesium neural coding Nonlinear dynamics Volterra-Wiener Principal dynamic mode Hippocampus Epilepsy

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Retina is structured to process an excess of darkness in natural scenes

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2010年第40期107卷 17368-17373页

作者： Ratliff, Charles P. Borghuis, Bart G. Kao, Yen-Hong Sterling, Peter Balasubramanian, Vijay Univ Penn Dept Phys & Astron Philadelphia PA 19104 USA Northwestern Univ Feinberg Sch Med Dept Ophthalmol Chicago IL 60611 USA Univ Penn Dept Neurosci Philadelphia PA 19104 USA Howard Hughes Med Inst Ashburn VA 20147 USA

Retinal ganglion cells that respond selectively to a dark spot on a brighter background (OFF cells) have smaller dendritic fields than their ON counterparts and are more numerous. OFF cells also branch more densely, and thus collect more synapses per visual angle. That the retina devotes more resources to processing dark contrasts predicts that natural images contain more dark information. We confirm this across a range of spatial scales and trace the origin of this phenomenon to the statistical structure of natural scenes. We show that the optimal mosaics for encoding natural images are also asymmetric, with OFF elements smaller and more numerous, matching retinal structure. Finally, the concentration of synapses within a dendritic field matches the information content, suggesting a simple principle to connect a concrete fact of neuroanatomy with the abstract concept of information: equal synapses for equal bits.

关键词： ganglion cells neural coding vision

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A new look at state-space models for neural data

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2010年第1-2期29卷 107-126页

作者： Paninski, Liam Ahmadian, Yashar Ferreira, Daniel Gil Koyama, Shinsuke Rad, Kamiar Rahnama Vidne, Michael Vogelstein, Joshua Wu, Wei Columbia Univ Dept Stat New York NY 10027 USA Columbia Univ Ctr Theoret Neurosci New York NY USA Carnegie Mellon Univ Dept Stat Pittsburgh PA 15213 USA Johns Hopkins Univ Dept Neurosci Baltimore MD USA Florida State Univ Dept Stat Tallahassee FL 32306 USA

State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely on certain approximations which are not always accurate. Here we review direct optimization methods that avoid these approximations, but that nonetheless retain the computational efficiency of the approximate methods. We discuss a variety of examples, applying these direct optimization techniques to problems in spike train smoothing, stimulus decoding, parameter estimation. and inference of synaptic properties. Along the way, we point out connections to sonic related standard statistical methods, including spline smoothing and isotonic regression. Finally, we note that the computational methods reviewed here do not in fact depend on the state-space setting at all;instead, the key property we are exploiting involves the bandedness of certain matrices. We close by discussing some applications of this more general point of view, including Markov chain Monte Carlo methods for neural decoding and efficient estimation of spatially-varying firing rates.

关键词： neural coding State-space models Hidden Markov model Tridiagonal matrix

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