Under natural viewing conditions the input to the retina is a complex spatiotemporal signal that depends on both the scene and the way the observer moves. It is commonly assumed that the retina processes this input si...
详细信息
Under natural viewing conditions the input to the retina is a complex spatiotemporal signal that depends on both the scene and the way the observer moves. It is commonly assumed that the retina processes this input signal efficiently by taking into account the statistics of the natural world. It has recently been argued that incessant microscopic eye movements contribute to this process by decorrelating the input to the retina. Here we tested this theory by measuring the responses of the salamander retina to stimuli replicating the natural input signals experienced by the retina in the presence and absence of fixational eye movements. Contrary to the predictions of classic theories of efficient encoding that do not take behavior into account, we show that the response characteristics of retinal ganglion cells are not sufficient in themselves to disrupt the broad correlations of natural scenes. Specifically, retinal ganglion cells exhibited strong and extensive spatial correlations in the absence of fixational eye movements. However, the levels of correlation in the neural responses dropped in the presence of fixational eye movements, resulting in effective decorrelation of the channels streaming information to the brain. These observations confirm the predictions that microscopic eye movements act to reduce correlations in retinal responses and contribute to visual information processing.
Stochastic and reduced biophysical models of synaptic transmission are formulated and evaluated. The synaptic transmission involves presynaptic facilitation of neurotransmitter release, depletion and recovery of the p...
详细信息
Stochastic and reduced biophysical models of synaptic transmission are formulated and evaluated. The synaptic transmission involves presynaptic facilitation of neurotransmitter release, depletion and recovery of the presynaptic pool of readily releasable vesicles containing neurotransmitter molecules and saturation of postsynaptic receptors of both fast non-NMDA and slow NMDA types. The models are shown to display the principal dynamical characteristics experimentally observed of synaptic transmission. The two main types of neural coding, i.e. rate and temporal coding, can be distinguished by means of different dynamical properties of synaptic transmission determined by initial neurotransmitter release probability and presynaptic firing rate. From the temporal evolution of the postsynaptic membrane potential response to a train of presynaptic action potentials at a sustained firing rate, in particular the steady-state amplitude and steady-state average level of postsynaptic membrane potentials are determined as functions of both initial release probability and presynaptic firing rate. The models are applicable to studies of the primary stages of learning processes and can be extended to incorporate short-term and long-term potentiation in memory consolidation processes.
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. Fir...
详细信息
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
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...
详细信息
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.
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....
详细信息
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.
When a rat moves, grid cells in its entorhinal cortex become active in multiple regions of the external world that form a hexagonal lattice. As the animal traverses one such "firing field," spikes tend to oc...
详细信息
When a rat moves, grid cells in its entorhinal cortex become active in multiple regions of the external world that form a hexagonal lattice. As the animal traverses one such "firing field," spikes tend to occur at successively earlier theta phases of the local field potential. This phenomenon is called phase precession. Here, we show that spike phases provide 80% more spatial information than spike counts and that they improve position estimates from single neurons down to a few centimeters. To understand what limits the resolution and how variable spike phases are across different field traversals, we analyze spike trains run by run. We find that the multiple firing fields of a grid cell operate as independent elements for encoding physical space. In addition, phase precession is significantly stronger than the pooled-run data suggest. Despite the inherent stochasticity of grid-cell firing, phase precession is therefore a robust phenomenon at the single-trial level, making a theta-phase code for spatial navigation feasible.
It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmissi...
详细信息
It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmission of information coherently related to the context in which it occurs, thus forming synchronized population codes. This coordination involves contextual field (CF) connections that link processors within and between cortical regions. The effects of CF connections are distinguished from those mediating receptive field (RF) input;it is shown how CFs can guide both learning and processing without becoming confused with the transmission of RF information. Simulations explore the capabilities of networks built from local processors with both RF and CF connections. Physiological evidence for synchronization, CFs, and plasticity of the RF and CF connections is described. Coordination via CFs is related to perceptual grouping, the effects of context on contrast sensitivity, amblyopia, implicit influences of color in achromotopsia, object and word perception, and the discovery of distal environmental variables and their interactions through self-organization. Cortical computation could thus involve the flexible evaluation of relations between input signals by locally specialized but adaptive processors whose activity is dynamically associated and coordinated within the between regions through specialized contextual connections.
Manual dexterity requires proprioceptive feedback about the state of the hand. To date, study of the neural basis of proprioception in the cortex has focused primarily on reaching movements to the exclusion of hand-sp...
详细信息
Manual dexterity requires proprioceptive feedback about the state of the hand. To date, study of the neural basis of proprioception in the cortex has focused primarily on reaching movements to the exclusion of hand-specific behaviors such as grasping. To fill this gap, we record both time-varying hand kinematics and neural activity evoked in somatosensory and motor cortices as monkeys grasp a variety of objects. We find that neurons in the somatosensory cortex, as well as in the motor cortex, preferentially track time-varying postures of multi-joint combinations spanning the entire hand. This contrasts with neural responses during reaching movements, which preferentially track time-varying movement kinematics of the arm, such as velocity and speed of the limb, rather than its time-varying postural configuration. These results suggest different representations of arm and hand movements suited to the different functional roles of these two effectors.
Understanding how the nervous system achieves reliable performance using unreliable components is important for many disciplines of science and engineering, in part because it can suggest ways to lower the energetic c...
详细信息
Understanding how the nervous system achieves reliable performance using unreliable components is important for many disciplines of science and engineering, in part because it can suggest ways to lower the energetic cost of computing. In vision, retinal ganglion cells partition visual space into approximately circular regions termed receptive fields (RFs). Average RF shapes are such that they would provide maximal spatial resolution if they were centered on a perfect lattice. However, individual shapes have fine-scale irregularities. Here, we find that irregular RF shapes increase the spatial resolution in the presence of lattice irregularities from approximate to 60% to approximate to 92% of that possible for a perfect lattice. Optimization of RF boundaries around their fixed center positions reproduced experimental observations neuron-by-neuron. Our results suggest that lattice irregularities determine the shapes of retinal RFs and that similar algorithms can improve the performance of retinal prosthetics where substantial irregularities arise at their interface with neural tissue.
To understand how information is coded in the primary somatosensory cortex (S I) we need to decipher the relationship between neural activity and tactile stimuli. Such a relationship can be formally measured by mutual...
详细信息
To understand how information is coded in the primary somatosensory cortex (S I) we need to decipher the relationship between neural activity and tactile stimuli. Such a relationship can be formally measured by mutual information. The present study was designed to determine how S1 neuronal populations code for the multidimensional kinetic features (i.e. random, time-varying patterns of force) of complex tactile stimuli, applied at different locations of the rat forepaw. More precisely, the stimulus localization and feature extraction were analyzed as two independent processes, using both rate coding and temporal coding strategies. To model the process of stimulus kinetic feature extraction, multidimensional stimuli were projected onto lower dimensional subspace and then clustered according to their similarity. Different combinations of stimuli clustering were applied to differentiate each stimulus identification process. Information analyses show that both processes are synergistic, this synergy is enhanced within the temporal coding framework. The stimulus localization process is faster than the stimulus feature extraction process. The latter provides more information quantity with rate coding strategy, whereas the localization process maximizes the mutual information within the temporal coding framework. Therefore, combining mutual information analysis with robust clustering of complex stimuli provides a framework to study neural coding mechanisms related to complex stimuli discrimination. (C) 2007 Elsevier Ltd. All rights reserved.
暂无评论