One of the central questions in neuroscience concerns the basic code for information processing in the brain. Much experimental evidence and theoretical consideration have suggested that single-neuron coding is no lon...
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One of the central questions in neuroscience concerns the basic code for information processing in the brain. Much experimental evidence and theoretical consideration have suggested that single-neuron coding is no longer a tenable hypothesis. The present review explains why population neuronal coding is valid and discusses how it is carried out in the brain. The main context is experimental access to real features of the coding in working brains as deduced from experimental research. Several recent studies recording neuronal activities from behaving animals have shown that ensemble activity of neurons represents specific information, indicating the reality of population coding by many neurons. The key concept which can integrate the experimental evidence is the 'cell assembly', i.e., overlapped populations of neurons with flexible functional connections within and among the populations. Correlated activity among the neurons constructs the functional connection. In order to see features of the cell-assembly coding, two main properties of cell assemblies in processing several different kinds of information must be investigated, that is, the overlapping of neurons and the dynamics of synaptic connections. This manner of coding can provide both the experimental and theoretical framework to detect the real dynamic features of information processing by the brain.
In two previous studies, we had demonstrated the influence of eye position on neuronal discharges in the middle temporal area, medial superior temporal area, lateral intraparietal area and area 7A of the awake monkey ...
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In two previous studies, we had demonstrated the influence of eye position on neuronal discharges in the middle temporal area, medial superior temporal area, lateral intraparietal area and area 7A of the awake monkey (Bremmer et al., 1997a,b), Eye position effects also have been found in visual cortical areas V3A and V6 and even in the premotor cortex and the supplementary eye field. These effects are generally discussed in light of a coordinate transformation of visual signals into a non-retinocentric frame of reference. Neural network studies dealing with the eye position effect succeeded in constructing such non-retinocentric representations by using model neurones whose response characteristics resembled those of 'real' neurones. However, to our knowledge, response properties of real neurones never acted as input into these neural networks. In the present study, we thus investigated whether, theoretically, eye position could be estimated from the population discharge of the (previously) recorded neurones and, if so, we intended to develop an encoding algorithm for the position of the eyes in the orbit. The optimal linear estimator proved the capability of the ensemble activity for determining correctly eye position. We then developed the so-called subpopulation encoding of eye position. This algorithm is based on the partition of the ensemble of neurones into two pairs of subpopulations. Eye position is represented by the differences of activity levels within each pair of subpopulations. Considering this result, encoding of the location of an object relative to the head could easily be accomplished by combining eye position information with the intrinsic knowledge about the retinal location of a visual stimulus. Taken together, these results show that throughout the monkey's visual cortical system information is available which can be used in a fairly simple manner in order to generate a non-retinocentric representation of visual information.
Rate coding and temporal coding are two extremes of the neural coding process. The concept of a stationary state corresponds to the information processing approach that views the brain as a decision maker, adopts rate...
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Rate coding and temporal coding are two extremes of the neural coding process. The concept of a stationary state corresponds to the information processing approach that views the brain as a decision maker, adopts rate coding as its main strategy and endorses the single-or few neuron approach. If information derived from sensory stimulation is used to continuously update the brain's internal representation of the world, then neural codes may change with time through learning. As a consequence, the same spike sequence may be interpreted differently (or evoke a different behavior) later in the day. This non-stationary viewpoint is embodied hi the representational model of brain function that stresses learning and plasticity and employs temporal coding in neural assemblies. We argue that the switching between quasi-stable brain states as a result of learning is more relevant than the neuronal patterns, and the correlations between them, that are found during stationary states. The neural code likely resides in the activity patterns that cause this state-switching. (C) 1998 Elsevier Science Ltd. All rights reserved.
We analyze a model of navigational map formation based on correlation-based, temporally asymmetric potentiation and depression of synapses between hippocampal place cells. We show that synaptic modification during ran...
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We analyze a model of navigational map formation based on correlation-based, temporally asymmetric potentiation and depression of synapses between hippocampal place cells. We show that synaptic modification during random exploration of an environment shifts the location encoded by place cell activity in such a way that it indicates the direction from any location to a fixed target avoiding walls and other obstacles. Multiple maps to different targets can be simultaneously stored if we introduce target-dependent modulation of place cell activity. Once maps to a number of target locations in a given environment have been stored, novel maps to previously unknown target locations are automatically constructed by interpolation between existing maps.
Seconds after a cutaneous deafferentation is induced in adult animals, a complex process of plastic reorganization is triggered in the subcortical and cortical structures that form the somatosensory system. This proce...
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Seconds after a cutaneous deafferentation is induced in adult animals, a complex process of plastic reorganization is triggered in the subcortical and cortical structures that form the somatosensory system. This process, which leads to the immediate unmasking of novel neuronal sensory responses, continues to evolve for many weeks and months until most of the neuronal tissue deprived of its original afferent input gains responsiveness to surrounding skin territories. Here, I propose that the existence of dynamic and distributed sensory representations throughout the somatosensory system offers the substrate for the occurrence of immediate plastic remapping of the body surface following either a peripheral injury or a change in sensory experience. (C) 1997 Academic Press.
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.
Cells in area TE of the inferotemporal cortex of the monkey brain selectively respond to various moderately complex object features, and those that cluster in a columnar region that runs perpendicular to the cortical ...
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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 cluster in a columnar region that runs perpendicular to the cortical surface respond to similar features. Although cells within a column respond to similar features, their selectivity is not necessarily identical. The data of optical imaging in TE have suggested that the borders between neighboring columns are not discrete;a continuous mapping of complex feature space within a larger region contains several partially overlapped columns. This continuous mapping may be used for various computations, such as production of the image of the object at different viewing angles, illumination conditions, and articulation poses.
Single-neuron responses in motor and premotor cortex were recorded during a movement-sequence delay task. On each trial the monkey viewed a randomly selected sequence of target lights arrayed in two-dimensional space,...
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Single-neuron responses in motor and premotor cortex were recorded during a movement-sequence delay task. On each trial the monkey viewed a randomly selected sequence of target lights arrayed in two-dimensional space, remembered the sequence during a delay period, and then generated a coordinated sequence of movements to the remembered targets. Of 307 neurons studied, 25% were tuned specifically for either the first or the second target, but not both. Iq particular, for neurons tuned during both target presentations, tuned activity related to a particular first target direction were maintained during the presentation of a second target in a different direction. During the delay period, 32% of the neurons were tuned fbr upcoming movement in a single direction. These delay period responses often reflected activity patterns that first developed during target presentations and may therefore act to maintain target period information during the delay. Neurons with tuned activity during both the delay and movement periods exhibited two patterns: the first exhibited tuned responses during the delay that were correlated with the tuning of first-movement responses, while the second pattern showed delay-period tuning that was better correlated with tuned responses during second movements. This indicates that, before movement, distinct neural populations are correlated with specific movements in a sequence. About half the neurons studied were not directionally tuned during the initiation, target, or delay periods, but did show systematic changes in activity during task performance. Some (34%) were exclusively tuned during movement and appear to be involved in the direct control of movement. Others (17%) showed changes in firing rate from period to period within a trial but showed no directional preference for a particular direction of movement. population analyses of tuned activity during the target and delay periods indicated that accurate directional information about both fi
Disparity-evoked vergence is studied in stereograms showing one or two depth planes which are defined by isolated dots of varying density and contrast. Vergence position immediately after stimulus presentation was mea...
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Disparity-evoked vergence is studied in stereograms showing one or two depth planes which are defined by isolated dots of varying density and contrast. Vergence position immediately after stimulus presentation was measured using dichoptic nonius lines. Since the stimulus was not visible after the onset of the vergence movement, the experiment accesses the initiation of vergence rather than its eventual result. In the unequivocal stimuli (one depth plane), elicited vergence tends to reduce disparity. Disparities of 0.5-1 deg are most effective which is in accordance with earlier findings. If two depth planes are presented, elicited vergence lies between the two planes, approaching the plane with higher dot density and/or dot contrast. In quantitative measurements, we show that the depth-averaging mechanism uses signal power per depth plane as a weight. Therefore, the relative pulling strength of dot density compared with dot contrast follows a power law with exponent 2. We propose a population code for vergence control based on disparity-tuned pools of units. Copyright (C) 1996 Elsevier Science Ltd.
Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of pha...
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Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition, The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns, The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern, The reverse transition mag be induced by the Hebbian unlearning process without input, The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input, To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stags near the critical state corresponding to the phase transition point.
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