Researchers studying neural coding have speculated that populations of neurons would more effectively represent the stimulus if the neurons "cooperated:" by interacting through lateral connections, the neuro...
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Researchers studying neural coding have speculated that populations of neurons would more effectively represent the stimulus if the neurons "cooperated:" by interacting through lateral connections, the neurons would process and represent information better than if they functioned independently. We apply our new theory of information processing to determine the fidelity limits of simple population structures to encode stimulus features. We focus on noncooperative populations, which have no lateral connections. We show that they always exhibit positively correlated responses and that as population size increases, they perfectly represent the information conveyed by their inputs regardless of the individual neuron's coding scheme. Cooperative populations, which do have lateral connections, can, depending on the nature of the connections, perform better or worse than their noncooperative counterparts. We further show that common notions of synergy fail to capture the level of cooperation and to reflect the information processing properties of populations.
We analysed spike trains from the descending contralateral movement detector (DCMD) neuron of locusts. The locusts either performed jumps or did not jump in response to visual looming stimuli. An evolutionary algorith...
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We analysed spike trains from the descending contralateral movement detector (DCMD) neuron of locusts. The locusts either performed jumps or did not jump in response to visual looming stimuli. An evolutionary algorithm (EA) was employed to sort spike trains into the correct behavioural categories by optimising threshold parameters, so jump behaviour occurred if the spike-train data exceeded the threshold parameters from the EA. A candidate behavioural trigger appeared to be prolonged high-frequency spikes at a relatively early stage in the approach of the stimulus. This technique provides a useful precursor to a full biological analysis of the escape jump mechanism. (c) 2006 Elsevier B.V. All rights reserved.
This paper investigates the neural processes associated with bat sonar vocal production and their relationship with spatial orientation. The bat's heavy reliance on sound processing is reflected in specializations...
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This paper investigates the neural processes associated with bat sonar vocal production and their relationship with spatial orientation. The bat's heavy reliance on sound processing is reflected in specializations of auditory and motor neural structures. These specializations were utilized by investigating the mammalian superior colliculus (SC);a midbrain sensory motor nucleus mediating orientating behaviours in mammals, including vocal motor orientating. Behavioural and neurophysiological experiments were conducted in the insectivorous echolocating bat, Eptesicus fuscus. Chronic neural recording techniques were specifically developed to study neuronal activity. Potential application of the results on control systems is also addressed. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.
This paper presents an investigation into the responses of neurons to errors in presynaptic spike trains. Errors are viewed, in nonlinear dynamical terms, as brief-duration changes in stationary presynaptic spike trai...
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This paper presents an investigation into the responses of neurons to errors in presynaptic spike trains. Errors are viewed, in nonlinear dynamical terms, as brief-duration changes in stationary presynaptic spike trains which induce transient responses in the postsynaptic cell. As these are generally large-magnitude transients, linearized neural models are not helpful. Instead, the responses of a full, nonlinear physiological model of a neuron that includes the recognized living prototype of an inhibitory synapse are analyzed. More specifically, the transients are examined in the context of the stationary behaviors that precede and succeed each error. It is shown that one and two dimensional bifurcation diagrams can be constructed from the transient responses-that there are marked changes in the transient responses at points that correspond to bifurcations in the stationary responses, qualitative changes in transients on either side of bifurcations, and only quantitative changes in transients between bifurcations. (C) 2007 Elsevier Ireland Ltd. All rights reserved.
Slow N-Methyl-D-aspartic acid (NMDA) synaptic currents are assumed to strongly contribute to the persistently elevated firing rates observed in prefrontal cortex (PFC) during working memory. During persistent activity...
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Slow N-Methyl-D-aspartic acid (NMDA) synaptic currents are assumed to strongly contribute to the persistently elevated firing rates observed in prefrontal cortex (PFC) during working memory. During persistent activity, spiking of many neurons is highly irregular. Here we report that highly irregular firing can be induced through a combination of NMDA- and dopamine D1 receptor agonists applied to adult PFC neurons in vitro. The highest interspike-interval (ISI) variability occurred in a transition regime where the subthreshold membrane potential distribution shifts from mono- to bimodality, while neurons with clearly mono- or bimodal distributions fired much more regularly. Predictability within irregular ISI series was significantly higher than expected from a noise-driven linear process, indicating that it might best be described through complex (potentially chaotic) nonlinear deterministic processes. Accordingly, the phenomena observed in vitro could be reproduced in purely deterministic biophysical model neurons. High spiking irregularity in these models emerged within a chaotic, close-to-bifurcation regime characterized by a shift of the membrane potential distribution from mono- to bimodality and by similar ISI return maps as observed in vitro. The nonlinearity of NMDA conductances was crucial for inducing this regime. NMDA-induced irregular dynamics may have important implications for computational processes during working memory and neural coding.
In crickets, auditory information about ultrasound is carried bilaterally to the brain by the AN2 neurons. The ON1 neuron provides contralateral inhibitory input to AN2, thereby enhancing bilateral contrast between th...
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In crickets, auditory information about ultrasound is carried bilaterally to the brain by the AN2 neurons. The ON1 neuron provides contralateral inhibitory input to AN2, thereby enhancing bilateral contrast between the left and right AN2s, an important cue for sound localization. We examine how the structures of the spike trains of these neurons affect this inhibitory interaction. As previously shown for AN2, ON1 responds to salient peaks in stimulus amplitude with bursts of spikes. Spike bursts, but not isolated spikes, reliably signal the occurrence of specific features of the stimulus. ON1 and AN2 burst at similar times relative to the amplitude envelope of the stimulus, and bursts are more tightly time-locked to stimulus feature than the isolated spikes. As a consequence, spikes that, in the absence of contralateral inhibition, would occur within AN2 bursts are more likely to be preceded by spikes in ON1 (mainly also in bursts) than are isolated AN2 spikes. This leads to a large decrease in the burst rate of the inhibited AN2. We conclude that the match in coding properties of ON1 and AN2 allows contralateral inhibition to be most efficient for those portions of the response that carry the behaviourally relevant information, i.e. for bursts.
The function of any neural circuit is governed by connectivity of neurons in the circuit and the computations performed by the neurons. Recent research on retinal function has substantially advanced understanding in b...
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The function of any neural circuit is governed by connectivity of neurons in the circuit and the computations performed by the neurons. Recent research on retinal function has substantially advanced understanding in both areas. First, visual information is transmitted to the brain by at least 17 distinct retinal ganglion cell types defined by characteristic morphology, light response properties, and central projections. These findings provide a much more accurate view of the parallel visual pathways emanating from the retina than do previous models, and they highlight the importance of identifying distinct cell types and their connectivity in other neural circuits. Second, encoding of visual information involves significant temporal structure and interactions in the spike trains of retinal neurons. The functional importance of this structure is revealed by computational analysis of encoding and decoding, an approach that may be applicable to understanding the function of other neural circuits.
We derive a simple measure for quantifying the average accuracy with which a neuronal population can represent a stimulus. This quantity, the basis set eff or, has three key properties: (1) it makes no assumptions abo...
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We derive a simple measure for quantifying the average accuracy with which a neuronal population can represent a stimulus. This quantity, the basis set eff or, has three key properties: (1) it makes no assumptions about the form of the neuronal responses;(2) it depends only on their second order statistics, so although it is easy to compute, it does take noise correlations into account;(3) its magnitude has an intuitive interpretation in terms of the accuracy with which information can be extracted from the population using a simple method-"simple" meaning linear. We use the basis set error to characterize the efficacy of several types of population codes generated synthetically in a computer. In general, the basis set error typically ranks different encoding schemes in a way that is qualitatively similar to Shannon's mutual information, except when nonlinear readout methods are necessary. Because this measure is concerned with signals that can be read out easily (i.e., through linear operations), it provides a lower bound on coding accuracy relative to the computational capabilities that are accessible to a neuronal population. (C) 2006 Elsevier Ireland Ltd. All rights reserved.
General navigation requires a spatial map that is not anchored to one environment. The firing fields of the "grid cells" found in the rat dorsolateral medial entorhinal cortex (dMEC) could be such a map. dME...
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General navigation requires a spatial map that is not anchored to one environment. The firing fields of the "grid cells" found in the rat dorsolateral medial entorhinal cortex (dMEC) could be such a map. dMEC firing fields are also thought to be modeled well by a regular triangular grid (a grid with equilateral triangles as units). We use computational means to analyze and validate the regularity of the firing fields both quantitatively (using summary statistics for geometric and photometric regularity) and qualitatively (using symmetry group analysis). Upon quantifying the regularity of real dMEC firing fields, we find that there are two types of grid cells. We show rigorously that both are nearest to triangular grids using symmetry analysis. However, type III grid cells are far from regular, both in firing rate (highly non-uniform) and grid geometry. Type III grid cells are also more numerous. We investigate the implications of this for the role of grid cells in path integration. (c) 2006 Elsevier B.V. All rights reserved.
hi the vertebrate inner retina, the second stage of the visual system, different components of the visual scene are transformed, discarded, or selected before visual information is transmitted through the optic nerve....
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hi the vertebrate inner retina, the second stage of the visual system, different components of the visual scene are transformed, discarded, or selected before visual information is transmitted through the optic nerve. This review discusses the connections between higher-level functions of visual processing, mathematical descriptions of the neural code, inner retinal circuitry, and visual computations. In the inner plexiform layer, bipolar cells deliver spatially and temporally filtered input to approximately ten anatomical strata. These layers receive a unique combination of excitation and inhibition, causing cells in different layers to respond with different kinetics to visual input. These distinct temporal channels interact through amacrine cells, a diverse class of inhibitory interneurons, which transmit signals within and between layers. In particular, wide-field amacrine cells transmit transient inhibition over long distances within a layer. These mechanisms and properties are combined into computations to detect the presence of differential motion and suppress the visual effects of eye movements.
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