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A new look at state-space models for neural data

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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Differential neural representation of oral ethanol by central taste-sensitive neurons in ethanol-preferring and genetically heterogeneous rats

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JOURNAL OF NEUROPHYSIOLOGY 2011年第6期106卷 3145-3156页

作者： Lemon, Christian H. Wilson, David M. Brasser, Susan M. St Louis Univ Sch Med Dept Pharmacol & Physiol Sci St Louis MO 63104 USA San Diego State Univ Dept Psychol San Diego CA 92182 USA

Lemon CH, Wilson DM, Brasser SM. Differential neural representation of oral ethanol by central taste-sensitive neurons in ethanol-preferring and genetically heterogeneous rats. J Neurophysiol 106: 3145-3156, 2011. First published September 14, 2011;doi: 10.1152/jn.00580.2011.-In randomly bred rats, orally applied ethanol stimulates neural substrates for appetitive sweet taste. To study associations between ethanol's oral sensory characteristics and genetically mediated ethanol preference, we made electrophysiological recordings of oral responses (spike density) by taste-sensitive nucleus tractus solitarii neurons in anesthetized selectively bred ethanol-preferring (P) rats and their genetically heterogeneous Wistar (W) control strain. Stimuli (25 total) included ethanol [3%, 5%, 10%, 15%, 25%, and 40% (vol/vol)], a sucrose series (0.01, 0.03, 0.1, 0.3, 0.5, and 1 M), and other sweet, salt, acidic, and bitter stimuli;50 P and 39 W neurons were sampled. k-means clustering applied to the sucrose response series identified cells showing high (S-1) or relatively low (S-0) sensitivity to sucrose. A three-way factorial analysis revealed that activity to ethanol was influenced by a neuron's sensitivity to sucrose, ethanol concentration, and rat line (P = 0.01). Ethanol produced concentration-dependent responses in S-1 neurons that were larger than those in S-0 cells. Although responses to ethanol by S-1 cells did not differ between lines, neuronal firing rates to ethanol in S-0 cells increased across concentration only in P rats. Correlation and multivariate analyses revealed that ethanol evoked responses in W neurons that were strongly and selectively associated with activity to sweet stimuli, whereas responses to ethanol by P neurons were not easily associated with activity to representative sweet, sodium salt, acidic, or bitter stimuli. These findings show differential central neural representation of oral ethanol between genetically heterogeneous rats and P rats genetic

关键词： genetics neural coding solitary tract taste alcohol

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A Method for Generating Natural and User-Defined Sniffing Patterns in Anesthetized or Reduced Preparations

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CHEMICAL SENSES 2009年第1期34卷 63-76页

作者： Cheung, Man Ching Carey, Ryan M. Wachowiak, Matt Boston Univ Dept Biol Boston MA 02215 USA Boston Univ Dept Biomed Engn Boston MA 02215 USA

Sniffing has long been thought to play a critical role in shaping neural responses to odorants at multiple levels of the nervous system. However, it has been difficult to systematically examine how particular parameters of sniffing behavior shape odorant-evoked activity, in large part because of the complexity of sniffing behavior and the difficulty in reproducing this behavior in an anesthetized or reduced preparation. Here we present a method for generating naturalistic sniffing patterns in such preparations. The method involves a nasal ventilator whose movement is controlled by an analog command voltage. The command signal may consist of intranasal pressure transients recorded from awake rats and mice or user-defined waveforms. This "sniff playback" device generates intranasal pressure and airflow transients in anesthetized animals that approximate those recorded from the awake animal and are reproducible across trials and across preparations. The device accurately reproduces command waveforms over an amplitude range of approximately 1 log unit and up to frequencies of approximately 12 Hz. Further, odorant-evoked neural activity imaged during sniff playback appears similar to that seen in awake animals. This method should prove useful in investigating how the parameters of odorant sampling shape neural responses in a variety of experimental settings.

关键词： active sensing artificial sniffing behavior imaging neural coding respiration

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Phase-locking of bursting neuronal firing to dominant LFP frequency components

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BIOSYSTEMS 2015年 136卷 73-79页

作者： Constantinou, Maria Elijah, Daniel H. Squirrel, Daniel Gigg, John Montemurro, Marcelo A. Univ Manchester Fac Life Sci Manchester M13 9PT Lancs England

Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code. (C) 2015 The Authors. Published by Elsevier Ireland Ltd.

关键词： Bursting Local field potential Phase-locking Subiculum neural coding

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neural encoding schemes of tactile information in afferent activity of the vibrissal system

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2013年第1期34卷 89-101页

作者： Farfan, Fernando D. Albarracin, Ana L. Felice, Carmelo J. Univ Nacl Tucuman Lab Medios & Interfases LAMEIN Fac Ciencias Exactas & Tecnol FACET San Miguel De Tucuman Argentina Consejo Nacl Invest Cient & Tecn Inst Super Invest Biol INSIBIO RA-1033 Buenos Aires DF Argentina Univ Nacl Tucuman Lab Neurociencia Fac Med San Miguel De Tucuman Argentina

When rats acquire sensory information by actively moving their vibrissae, a neural code is manifested at different levels of the sensory system. Behavioral studies in tactile discrimination agree that rats can distinguish different roughness surfaces by whisking their vibrissae. The present study explores the existence of neural encoding in the afferent activity of one vibrissal nerve. Two neural encoding schemes based on "events" were proposed (cumulative event count and median inter-event time). The events were detected by using an event detection algorithm based on multiscale decomposition of the signal (Continuous Wavelet Transform). The encoding schemes were quantitatively evaluated through the maximum amount of information which was obtained by the Shannon's mutual information formula. Moreover, the effect of difference distances between rat snout and swept surfaces on the information values was also studied. We found that roughness information was encoded by events of 0.8 ms duration in the cumulative event count and event of 1.0 to 1.6 ms duration in the median inter-event count. It was also observed that an extreme decrease of the distance between rat snout and swept surfaces significantly reduces the information values and the capacity to discriminate among the sweep situations.

关键词： neural coding Vibrissae (whiskers) Roughness discrimination Maximum amount of information Information theory

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Beyond bistability: Biophysics and temporal dynamics of working memory

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NEUROSCIENCE 2006年第1期139卷 119-133页

作者： Durstewitz, D Seamans, JK Univ Plymouth Ctr Theoret & Computat Neurosci Plymouth PL4 8AA Devon England Med Univ S Carolina Dept Physiol & Neurosci Charleston SC 29425 USA

Working memory has often been modeled and conceptualized as a kind of binary (bistable) memory switch, where stimuli turn on plateau-like persistent activity in subsets of cells, in line with many in vivo electrophysiological reports. A potentially related form of bistability, termed up- and down-states, has been studied with regard to its synaptic and ionic basis in vivo and in reduced cortical preparations. Also single cell mechanisms for producing bistability have been proposed and investigated in brain slices and computationally. Recently, however, it has been emphasized that clear plateau-like bistable activity is rather rare during working memory tasks, and that neurons exhibit a multitude of different temporally unfolding activity profiles and temporal structure within their spiking dynamics. Hence, working memory seems to be a highly dynamical neural process with yet unknown mappings from dynamical to computational properties. Empirical findings on ramping activity profiles and temporal structure will be reviewed, as well as neural models that attempt to account for it and its computational significance. Furthermore, recent in vivo, neural culture, and in vitro preparations will be discussed that offer new possibilities for studying the biophysical mechanisms underlying computational processes during working memory. These preparations have revealed additional evidence for temporal structure and spatio-temporally organized attractor states in cortical networks, as well as for specific computational properties that may characterize synaptic processing during high-activity states as during working memory. Together such findings may lay the foundations for highly dynamical theories of working memory based on biophysical principles. (C) 2005 IBRO. Published by Elsevier Ltd. All rights reserved.

关键词： persistent activity up-states neural coding climbing activity timing computational model

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Partial information decomposition as a unified approach to the specification of neural goal functions

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BRAIN AND COGNITION 2017年 112卷 25-38页

作者： Wibral, Michael Priesemann, Viola Kay, Jim W. Lizier, Joseph T. Phillips, William A. Goethe Univ MEG Unit Brain Imaging Ctr Heinrich Hoffmann Str 10 D-60528 Frankfurt Germany Max Planck Inst Dynam & Self Org Dept Nonlinear Dynam Gottingen Germany Univ Glasgow Dept Stat Glasgow G12 8QQ Lanark Scotland Univ Sydney Sch Civil Engn Complex Syst Res Grp Sydney NSW 2006 Australia Univ Stirling Sch Nat Sci Stirling Scotland

In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g. sensory, cognitive, or motor tasks). This observation has spawned interest in finding a common underlying principle, a 'goal function', of information processing implemented in this structure. By definition such a goal function, if universal, cannot be cast in processing-domain specific language (e.g. 'edge filtering', 'working memory'). Thus, to formulate such a principle, we have to use a domain-independent framework. Information theory offers such a framework. However, while the classical framework of information theory focuses on the relation between one input and one output (Shannon's mutual information), we argue that neural information processing crucially depends on the combination of multiple inputs to create the output of a processor. To account for this, we use a very recent extension of Shannon Information theory, called partial information decomposition (PID). PID allows to quantify the information that several inputs provide individually (unique information), redundantly (shared information) or only jointly (synergistic information) about the output. First, we review the framework of PID. Then we apply it to reevaluate and analyze several earlier proposals of information theoretic neural goal functions (predictive coding, infomax and coherent infomax, efficient coding). We find that PID allows to compare these goal functions in a common framework, and also provides a versatile approach to design new goal functions from first principles. Building on this, we design and analyze a novel goal function, called 'coding with synergy', which builds on combining external input and prior knowledge in a synergistic manner. We suggest that this

关键词： Information theory Unique information Shared information Synergy Redundancy Predictive coding neural coding Coherent infomax neural goal function

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Altered temporal pattern of mechanically evoked C-fiber activity in a model of diabetic neuropathy in the rat

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NEUROSCIENCE 2003年第4期121卷 1007-1015页

作者： Chen, X Levine, JD Univ Calif San Francisco NIH Pain Ctr Div NeurosciDept Anat San Francisco CA 94143 USA Univ Calif San Francisco NIH Pain Ctr Div NeurosciDept Med San Francisco CA 94143 USA Univ Calif San Francisco NIH Pain Ctr Div NeurosciDept Oral & Maxillofacial Surg San Francisco CA 94143 USA

While enhanced nociceptor activity has been demonstrated in models of painful peripheral neuropathy, analyses of activity pattern, which could play a role in the symptoms experienced as well as help elucidate underlying mechanism, are still limited. We evaluated the pattern of C-fiber activity, in response to mechanical and chemical stimuli, in a rat model of diabetes induced by a pancreatic P-cell toxin, streptozotocin (STZ). In diabetic rats the number of action potentials produced by threshold and suprathreshold (10 g) sustained (60 s) mechanical stimuli was elevated in approximately half of C-fibers. These high-firing C-fibers demonstrated a disproportionate increase in interspike intervals (ISIs) between 100 and 199 ms, compared with low-firing diabetic and control C-fibers. The co-efficient of variability (CV2), a frequency independent measure of ISI variability, was also greater in high-firing fibers, compared with control fibers. Unexpectedly, instantaneous frequency of the initial burst of activity during the first second was lower in high-firing fibers, even though the average frequency over the last 59 s was significantly higher. The number of action potentials evoked by a noxious chemical stimulus, 300 and 600 mM KCl, injected adjacent to the mechanical receptive field was also significantly increased in C-fibers from diabetic rats and mechanically high-firing fibers had more action potentials in response to KCI than control fibers and a disproportionate increase in ISIs between 100 and 199 ms for responses to chemical stimuli appeared only in mechanically high-firing C-fibers, compared with the mechanically low-firing diabetic or control C-fibers. There was, however, no corresponding change in CV2 or instantaneous frequency plots for the response to chemical stimulation in mechanically high-firing fibers, as there was in the response to mechanical stimulation. Our data demonstrate specific changes in firing pattern of high-firing C-fibers in the rat mod

关键词： STZ neuropathic pain peripheral nociceptor neural coding

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Touch is a team effort: interplay of submodalities in cutaneous sensibility

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TRENDS IN NEUROSCIENCES 2014年第12期37卷 689-697页

作者： Saal, Hennes P. Bensmaia, Sliman J. Univ Chicago Dept Organismal Biol & Anat Chicago IL 60637 USA Univ Chicago Comm Computat Neurosci Chicago IL 60637 USA

Traditionally, different classes of cutaneous mechanoreceptive afferents are ascribed different and largely non-overlapping functional roles (for example texture or motion) stemming from their different response properties. This functional segregation is thought to be reflected in cortex, where each neuron receives input from a single submodality. We summarize work that challenges this notion. First, while it is Possible to design artificial stimuli that preferentially excite a single afferent class, most natural stimuli excite all afferents and most tactile percepts are shaped by multiple submodalities. Second, closer inspection of cortical responses reveals that most neurons receive convergent input from multiple afferent classes. We argue that cortical neurons should be grouped based on their function rather than on their submodality composition.

关键词： somatosensory perception neural coding

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Impact and sources of neuronal variability in the fly's motion vision pathway

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JOURNAL OF PHYSIOLOGY-PARIS 2013年第1-2期107卷 26-40页

作者： Warzecha, Anne-Kathrin Rosner, Ronny Grewe, Jan Univ Bielefeld Dept Neurobiol D-33619 Bielefeld Germany Univ Marburg D-35032 Marburg Germany Univ Munich Dept Biol 2 D-82152 Martinsried Germany

Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations. Relevant sources of noise arising at different stages along the motion vision pathway have been investigated from the sensory input to the initiation of behavioral reactions. Here, we concentrate on the reliability of processing visual motion information in flies. Flies rely on visual motion information to guide their locomotion. They are among the best established model systems for the processing of visual motion information allowing us to bridge the gap between behavioral performance and underlying neuronal computations. It has been possible to directly assess the consequences of noise at major stages of the fly's visual motion processing system on the reliability of neuronal signals. Responses of motion sensitive neurons and their variability have been related to optomotor movements as indicators for the overall performance of visual motion computation. We address whether and how noise already inherent in the stimulus, e.g. photon noise for the visual system, influences later processing stages and to what extent variability at the output level of the sensory system limits behavioral performance. Recent advances in circuit analysis and the progress in monitoring neuronal activity in behaving animals should now be applied to understand how the animal meets the requirements of fast and reliable manoeuvres in naturalistic situations. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Motion vision Optomotor behavior Neuronal variability Fly neural coding Insect

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