Results 1  10
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291
WITH AN APPENDIX ON RESULTS OF MARTIN BENDA
, 2006
"... Abstract. Let (Yn) be a sequence of i.i.d. real valued random variables. Reflected random walk (Xn) is defined recursively by X0 = x ≥ 0, Xn+1 = Xn − Yn+1. In this note, we study recurrence of this process, extending a previous criterion. This is obtained by determining an invariant measure of the ..."
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Abstract. Let (Yn) be a sequence of i.i.d. real valued random variables. Reflected random walk (Xn) is defined recursively by X0 = x ≥ 0, Xn+1 = Xn − Yn+1. In this note, we study recurrence of this process, extending a previous criterion. This is obtained by determining an invariant measure of the embedded process of reflections. 1.
Generalized IntegrateandFire Models of Neuronal Activity Approximate Spike Trains of a . . .
"... We demonstrate that singlevariable integrateandfire models can quantitatively capture the dynamics of a physiologicallydetailed model for fastspiking cortical neurons. Through a systematic set of approximations, we reduce the conductance based model to two variants of integrateandfire mode ..."
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Cited by 84 (16 self)
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We demonstrate that singlevariable integrateandfire models can quantitatively capture the dynamics of a physiologicallydetailed model for fastspiking cortical neurons. Through a systematic set of approximations, we reduce the conductance based model to two variants of integrateandfire models. In the first variant (nonlinear integrateandfire model), parameters depend on the instantaneous membrane potential whereas in the second variant, they depend on the time elapsed since the last spike (Spike Response Model). The direct reduction links features of the simple models to biophysical features of the full conductance based model. To quantitatively
Spikefrequency adaptation separates transient communication signals from background oscillations
 J Neurosci
, 2005
"... Spikefrequency adaptation is a prominent feature of many neurons. However, little is known about its computational role in processing behaviorally relevant natural stimuli beyond filtering out slow changes in stimulus intensity. Here we present a more complex example where we demonstrate how spike ..."
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Cited by 38 (15 self)
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on the probability of a fish emitting chirps as a function of beat frequency. These results demonstrate how spikefrequency adaptation in general can facilitate extraction of signals of different time scales, specifically highfrequency signals embedded in slower oscillations. 1 Jan Benda et al.: Temporal Signal
Autosomal recessive primary microcephaly (MCPH): a review of clinical, molecular, and evolutionary findings
 Am. J. Hum. Genet
, 2005
"... Autosomal recessive primary microcephaly (MCPH) is a neurodevelopmental disorder. It is characterized by two principal features, microcephaly present at birth and nonprogressive mental retardation. The microcephaly is the consequence of a small but architecturally normal brain, and it is the cerebra ..."
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Cited by 38 (0 self)
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Autosomal recessive primary microcephaly (MCPH) is a neurodevelopmental disorder. It is characterized by two principal features, microcephaly present at birth and nonprogressive mental retardation. The microcephaly is the consequence of a small but architecturally normal brain, and it is the cerebral cortex that shows the greatest size reduction. There are at least seven MCPH loci, and four of the genes have been identified: MCPH1, encoding Microcephalin; MCPH3, encoding CDK5RAP2; MCPH5, encoding ASPM; and MCPH6, encoding CENPJ. These findings are starting to have an impact on the clinical management of families affected with MCPH. Present data suggest that MCPH is the consequence of deficient neurogenesis within the neurogenic epithelium. Evolutionary interest in MCPH has been sparked by the suggestion that changes in the MCPH genes might also be responsible for the increase in brain size during human evolution. Indeed, evolutionary analyses of Microcephalin and ASPM reveal evidence for positive selection during human and great ape evolution. So an understanding of this rare genetic disorder may offer us significant insights into neurogenic mitosis and the evolution of the most striking differences between us and our closest living relatives: brain size and cognitive ability.
The supplemental IRAS minor planet survey
 The Astronomical Journal
, 2002
"... A ThU document has been ciP~loved tepu l iease and sale; its distriuton is uniimitec. Q)PHILLIPS LABORATORY ..."
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Cited by 28 (0 self)
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A ThU document has been ciP~loved tepu l iease and sale; its distriuton is uniimitec. Q)PHILLIPS LABORATORY
A synchronizationdesynchronization code for natural communication signals. Neuron 52
, 2006
"... Synchronous spiking of neural populations is hypothesized to play important computational roles in forming neural assemblies and solving the binding problem. Although the opposite phenomenon of desynchronization is well known from EEG studies, it is largely neglected on the neuronal level. We here p ..."
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Cited by 20 (10 self)
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Synchronous spiking of neural populations is hypothesized to play important computational roles in forming neural assemblies and solving the binding problem. Although the opposite phenomenon of desynchronization is well known from EEG studies, it is largely neglected on the neuronal level. We here provide an example of in vivo recordings from weaklyelectric fish demonstrating that, depending on the social context, different types of natural communication signals elicit transient desynchronization as well as synchronization of the electroreceptor population without changing the mean firing rate. We conclude that, in general, both positive and negative changes in the degree of synchrony can be the relevant signals for neural information processing.
ALMOST SURE THEORIES
, 1980
"... If 'Jl is a model with universe t ' and O!>'~t~ " where q ix a llxcd positixc integer, we put 'JI(Q) for the expansion of ~1 with the new relation O. We stud ~ sets of rdations defined by xx, hcre tr ix a)hxto~xter sentence with equality of the appropriate type and tUI ~ ..."
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Cited by 20 (1 self)
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If 'Jl is a model with universe t ' and O!>'~t~ " where q ix a llxcd positixc integer, we put 'JI(Q) for the expansion of ~1 with the new relation O. We stud ~ sets of rdations defined by xx, hcre tr ix a)hxto~xter sentence with equality of the appropriate type and tUI ~ R,,. For s,mae simple cou,ltablc struetm'cs ~1, we show tilat Nllr) ix almost all of *t~2 or almost none of it. f~r certain tope)ogles and nleasures. \V,2)lave alla]ogous results for the cardinaliiy of S(~r/for some finite strucnu'cs ~I with large enough U, Some of the structures xve cxanline, ill both the countable and finite case, arc sets with a successor relatioll arid cyclic groups.
The minimal model for the Batalin–Vilkovisky operad
 SELECTA MATHEMATICA NEW SERIES
, 2012
"... The purpose of this paper is to explain and to generalize, in a homotopical way, the result of Barannikov–Kontsevich and Manin, which states that the underlying homology groups of some Batalin–Vilkovisky algebras carry a Frobenius manifold structure. To this extent, we first make the minimal model ..."
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Cited by 16 (6 self)
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The purpose of this paper is to explain and to generalize, in a homotopical way, the result of Barannikov–Kontsevich and Manin, which states that the underlying homology groups of some Batalin–Vilkovisky algebras carry a Frobenius manifold structure. To this extent, we first make the minimal model for the operad encoding BValgebras explicit. Then, we prove a homotopy transfer theorem for the associated notion of homotopy BValgebra. The final result provides an extension of the action of the homology of the Deligne–Mumford–Knudsen moduli space of genus 0 curves on the homology of some BValgebras to an action via higher homotopical operations organized by the cohomology of the open moduli space of genus zero curves. Applications in Poisson geometry and Lie algebra cohomology and to the Mirror Symmetry conjecture are given.
Limits of Linear Rate Coding of Dynamic Stimuli by
, 2007
"... We estimated the frequencyintensity (fI) curves of Punit electroreceptors using 4Hz random amplitude modulations (RAMs) and using the covariance method (50Hz RAMs). Both methods showed that P units are linear encoders of stimulus amplitude with additive noise; the gain of the fI curve was, on ..."
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Cited by 5 (1 self)
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We estimated the frequencyintensity (fI) curves of Punit electroreceptors using 4Hz random amplitude modulations (RAMs) and using the covariance method (50Hz RAMs). Both methods showed that P units are linear encoders of stimulus amplitude with additive noise; the gain of the fI curve was, on average, 0.32 and 2.38 spikes�s �1 ��V �1 for the low and highfrequency cutoffs, respectively. There were two sources of apparent noise in the encoding process: the first was the variability of baseline Punit discharge and the second was the variation of receptor discharge due to variability of the stimulus slope independent of its intensity. The covariance method showed that a linear combination of eigenvectors representing the timeweighted stimulus intensity (E1) and its derivative (E2) could account for, on average, 92 % of the total response variability; E1 by itself accounted for 76 % of the variability. The low gain of the lowfrequency fI curve implies that detection of small (1 �V) signals would require integration over many receptors (�1,200) and time (200 ms); even then, signals that elicit behavioral responses could not be detected using rate coding with the estimated gain and noise levels. Weak signals at the limit of behavioral thresholds could be detected if the animal were able to extract E1 from the population of responding P units; we propose a tentative mechanism for this operation although there is no evidence as to whether it is actually implemented in the nervous system of these fish.
SpikeFrequency Adaptation Generates Intensity Invariance in a Primary Auditory Interneuron
"... Adaptation of the spikefrequency response to constant stimulation, as observed on various timescales in many neurons, reflects highpass filter properties of a neuron’s transfer function. Adaptation in general, however, is not sufficient to make a neuron’s response independent of the mean intensity ..."
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Cited by 5 (1 self)
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Adaptation of the spikefrequency response to constant stimulation, as observed on various timescales in many neurons, reflects highpass filter properties of a neuron’s transfer function. Adaptation in general, however, is not sufficient to make a neuron’s response independent of the mean intensity of a sensory stimulus, since low frequency components of the stimulus are still transmitted, although with reduced gain. We here show, based on an analytically tractable model, that the response of a neuron is intensity invariant, if the fully adapted steadystate spikefrequency response to constant stimuli is independent of stimulus intensity. Electrophysiological recordings from the AN1, a primary auditory interneuron of crickets, show that for intensities above 60 dB SPL (sound pressure level) the AN1 adapted with a timeconstant of ∼ 40 ms to a steadystate firing rate of ∼ 100 Hz. Using identical random amplitudemodulation stimuli we verified that the AN1’s spikefrequency response is indeed invariant to the stimulus ’ mean intensity above 60 dB SPL. The transfer function of the AN1 is a band pass, resulting from a highpass filter (cutoff frequency at 4 Hz) due to adaptation and a lowpass filter (100 Hz) determined by the steadystate spike frequency. Thus, fast spikefrequency adaptation can generate intensity invariance already at the first level of neural processing.
Results 1  10
of
291