Recent experimental evidence for temporal coding of cortical cell populations (Riehle, Grun, Diesmann, Aertsen, Science 278 (1997) 573-578, Donoghue, Sanes, Hatsopoulos, Gaal, J. Nuerophysiol. 79 (1998) 159-173). recu...
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Recent experimental evidence for temporal coding of cortical cell populations (Riehle, Grun, Diesmann, Aertsen, Science 278 (1997) 573-578, Donoghue, Sanes, Hatsopoulos, Gaal, J. Nuerophysiol. 79 (1998) 159-173). recurs to Hebb's classical cell assembly notion. Here the properties of columnar cell assemblies are estimated, using the assumptions about biological parameters of Wickens and Miller, Biol. Cybernet. 77 (1997) 351-358, but extending and correcting their predictions: Not the combinatorical constraint as they assume, but synaptic saturation and the requirement of low activation outside the assembly limit assembly size and number. As will be shown, (i) columnar assembly processing can be still information theoretically efficient, and (ii) at efficient parameter settings several assemblies can be ignited in a column at the same time. Feature (ii) allows faster and more flexible access to the information contained in the set of stored cell assemblies. (C) 2000 Elsevier Science B.V. All rights reserved.
Cells in area TE of the inferotemporal cortex of the monkey brain selectively respond to various moderately complex object features, and those that respond to similar features cluster in a columnar region elongated ve...
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Cells in area TE of the inferotemporal cortex of the monkey brain selectively respond to various moderately complex object features, and those that respond to similar features cluster in a columnar region elongated vertical to the cortical surface. Columns representing related but different features partially overlap, and at least in same cases they comprise a continuous map of a piece of complex feature space. This continuous mapping is likely used for various computations, such as production of the image of the object al different viewing angles, illumination conditions, and articulation poses. Copyright (C) 1996 Elsevier Science Ltd.
population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theor...
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population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains. (C) 2010 Elsevier Ltd. All rights reserved.
NMDA-mediated synaptic currents are believed to influence LTP. A recent model (Lisman et al., Nature Neurosci. (1993) 273-275) demonstrates that they can instead support short term memory based on rhythmic spike activ...
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NMDA-mediated synaptic currents are believed to influence LTP. A recent model (Lisman et al., Nature Neurosci. (1993) 273-275) demonstrates that they can instead support short term memory based on rhythmic spike activity. We examine this effect in a more realistic model that uses two-compartment neurons experiencing fatigue and also includes long-term memory by synaptic LTP. We find that the network does support both modes of operation without any parameter changes, but depending on the input patterns. Short term memory functionality might facilitate Hebbian learning through LTP by holding a new pattern while synaptic potentiation occurs. We also find that susceptibility of the short term memory against new input is time-dependent and reaches a maximum around the time constant of neuronal fatigue (200-400 ms). This corresponds well to the time scale of the syllabic rhythm and various psychophysical phenomena. (C) 2001 Elsevier Science B.V. All rights reserved.
A hierarchical vision system, inspired by the functional architecture of the cortical motion pathway, to provide motion interpretation and to guide real-time actions in the real-world, is proposed. Such a neuromimetic...
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A hierarchical vision system, inspired by the functional architecture of the cortical motion pathway, to provide motion interpretation and to guide real-time actions in the real-world, is proposed. Such a neuromimetic architecture exploits (i) log-polar mapping for data reduction, (ii) a population of motion energy neurons to compute the optic flow, and (iii) a population of adaptive templates in the cortical domain to gain the flow's affine description. The time-to-contact and the surface orientations of points of interest in the real-world are computed by directly combining the linear description of the cortical flow. The approach is validated through quantitative tests in synthetic environments, and in real-world automotive and robotics situations. (C) 2014 Elsevier Inc. All rights reserved.
Scene analysis in the mammalian visual system, conceived as a distributed and parallel process, faces the so-called binding problem. As a possible solution, the temporal correlation hypothesis has been suggested and i...
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Scene analysis in the mammalian visual system, conceived as a distributed and parallel process, faces the so-called binding problem. As a possible solution, the temporal correlation hypothesis has been suggested and implemented in phase-coding models. We propose an alternative model that reproduces experimental findings of synchronized and desynchronized fast oscillations more closely. This model is based on technical considerations concerning improved pattern separation in associative memories on the one hand, and on known properties of the visual cortex on the other. It consists of two reciprocally connected areas, one corresponding to a peripheral visual area (P), the other a central association area (C). P implements the orientation-selective subsystem of the primary visual cortex, while C was modeled as an associative memory with connections formed by Hebbian learning of all assemblies corresponding to stimulus objects. Spiking neurons including habituation and correlated noise were incorporated as well as realistic synaptic delays. Three learned stimuli were presented simultaneously and correlation analysis was performed on spike recordings. Generally, we found two states of activity: (i) relatively slow and unordered oscillations at about 20-25 Hz, synchronized only within small regions;and (ii) faster and more precise oscillations around 50-60 Hz, synchronized over the whole simulated area. The neuron groups representing one stimulus tended to be simultaneously in either the slow or the fast state. At each particular time, only one assembly was found to be in the fast state. Activation of the three assemblies switched on a time scale of 100 ms. This can be interpreted as self-generated attention switching. On the time scale corresponding to gamma oscillations, cross correlations between local neuron groups were either modulated or flat. Modulated correlograms resulted if the groups coded features corresponding to a common object. Otherwise, the correlograms
Recent advancements in multielectrode methods and spike-sorting algorithms enable the in vivo recording of the activities of many neurons at a high temporal resolution. These datasets offer new opportunities in the in...
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Recent advancements in multielectrode methods and spike-sorting algorithms enable the in vivo recording of the activities of many neurons at a high temporal resolution. These datasets offer new opportunities in the investigation of the biological neural code, including the direct testing of specific coding hypotheses, but they also reveal the limitations of present decoder algorithms. Classical methods rely on a manual feature extraction step, resulting in a feature vector, like the firing rates of an ensemble of neurons. In this paper, we present a recurrent neural-network-based decoder and evaluate its performance on experimental and artificial datasets. The experimental datasets were obtained by recording the auditory cortical responses of rats exposed to sound stimuli, while the artificial datasets represent preset encoding schemes. The task of the decoder was to classify the action potential timeseries according to the corresponding sound stimuli. It is illustrated that, depending on the coding scheme, the performance of the recurrent-network-based decoder can exceed the performance of the classical methods. We also show how randomized copies of the training datasets can be used to reveal the role of candidate spike-train features. We conclude that artificial neural network decoders can be a useful alternative to classical population vector-based techniques in studies of the biological neural code.
We examine the functional hypothesis of bidirectional associative memory in a pair of reciprocally projecting cortical cell groups. Our simulation model features two-compartment neurons and synaptic weights formed by ...
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We examine the functional hypothesis of bidirectional associative memory in a pair of reciprocally projecting cortical cell groups. Our simulation model features two-compartment neurons and synaptic weights formed by Hebbian learning of pattern pairs. After stimulation of a learned memory in one group we recorded the network activation. At high synaptic memory load (0.14 bit/synapse) we varied the number of cells receiving stimulation input (input activity). The network "recalled" patterns by synchronized regular gamma spiking. Stimulated cells also expressed bursts that fascilitated the recall with low input activity. Performance was evaluated for one-step retrieval based on monosynaptic transmission expressed after ca. 35 ms, and for bidirectional retrieval involving iterative activity propagation. One-step retrieval performed comparably to the technical Willshaw model with small input activity, but worse in other cases. In 80% of the trials with low one-step performance iterative retrieval improved the result. It achieved higher overall performance after recall times of 60-260 ms. (C) 2001 Elsevier Science B.V. All rights reserved.
Recently, we proposed an ensemble-coding scheme of the midbrain superior colliculus (SC) in which, during a saccade, each spike emitted by each recruited SC neuron contributes a fixed minivector to the gaze-control mo...
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Recently, we proposed an ensemble-coding scheme of the midbrain superior colliculus (SC) in which, during a saccade, each spike emitted by each recruited SC neuron contributes a fixed minivector to the gaze-control motor output. The size and direction of this 'spike vector' depend exclusively on a cell's location within the SC motor map (Goossens and Van Opstal, in J Neurophysiol 95: 2326-2341, 2006). According to this simple scheme, the planned saccade trajectory results from instantaneous linear summation of all spike vectors across the motor map. In our simulations with this model, the brainstem saccade generator was simplified by a linear feedback system, rendering the total model (which has only three free parameters) essentially linear. Interestingly, when this scheme was applied to actually recorded spike trains from 139 saccade-related SC neurons, measured during thousands of eye movements to single visual targets, straight saccades resulted with the correct velocity profiles and nonlinear kinematic relations ('main sequence properties' and 'component stretching'). Hence, we concluded that the kinematic nonlinearity of saccades resides in the spatial-temporal distribution of SC activity, rather than in the brainstem burst generator. The latter is generally assumed in models of the saccadic system. Here we analyze how this behaviour might emerge from this simple scheme. In addition, we will show new experimental evidence in support of the proposed mechanism.
A computational model for the control of horizontal vergence, based on a population of disparity tuned complex cells, is presented. Since the population is able to extract the disparity map only in a limited range, us...
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A computational model for the control of horizontal vergence, based on a population of disparity tuned complex cells, is presented. Since the population is able to extract the disparity map only in a limited range, using the map to drive vergence control means to limit its functionality inside this range. The model directly extracts the disparity-vergence response by combining the outputs of the disparity detectors without explicit calculation of the disparity map. The resulting vergence control yields to stable fixation and has small response time to a wide range of disparities. Experimental simulations with synthetic stimuli in depth validated the approach. (C) 2010 Elsevier B.V. All rights reserved.
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