初级视皮层神经元非经典感受野研究的新进展

感觉皮层神经元的非经典感受野(简称"外周")对经典感受野(简称"中心")的调节作用广泛存在于哺乳动物中,被认为是感觉皮层神经元的基本特性.以初级视皮层神经元为例,刺激其外周能有效地调节刺激其中心引起的反应,这种作用主要是抑制性的.理解初级视皮层神经元的外周对中心的调节机制能够深入揭示哺乳动物的感觉皮层神经元信息处理的基本原则.本文综述了引起初级视皮层神经元非经典感受野对经典感受野调节作用的神经环路机制和计算模型研究的进展.     

Visual Receptive Field Properties of Neurons in the Mouse Lateral Geniculate Nucleus

The lateral geniculate nucleus (LGN) is increasingly regarded as a “smart-gating” operator for processing visual information. Therefore, characterizing the response properties of LGN neurons will enable us to better understand how neurons encode and transfer visual signals. Efforts have been devoted to study its anatomical and functional features, and recent advances have highlighted the existence in rodents of complex features such as direction/orientation selectivity. However, unlike well-researched higher-order mammals such as primates, the full array of response characteristics vis-à-vis its morphological features have remained relatively unexplored in the mouse LGN. To address the issue, we recorded from mouse LGN neurons using multisite-electrode-arrays (MEAs) and analysed their discharge patterns in relation to their location under a series of visual stimulation paradigms. Several response properties paralleled results from earlier studies in the field and these include centre-surround organization, size of receptive field, spontaneous firing rate and linearity of spatial summation. However, our results also revealed “high-pass” and “low-pass” features in the temporal frequency tuning of some cells, and greater average contrast gain than reported by earlier studies. In addition, a small proportion of cells had direction/orientation selectivity. Both “high-pass” and “low-pass” cells, as well as direction and orientation selective cells, were found only in small numbers, supporting the notion that these properties emerge in the cortex. ON- and OFF-cells showed distinct contrast sensitivity and temporal frequency tuning properties, suggesting parallel projections from the retina. Incorporating a novel histological technique, we created a 3-D LGN volume model explicitly capturing the morphological features of mouse LGN and localising individual cells into anterior/middle/posterior LGN. Based on this categorization, we show that the ON/OFF, DS/OS and linear response properties are not regionally restricted. Our study confirms earlier findings of spatial pattern selectivity in the LGN, and builds on it to demonstrate that relatively elaborate features are computed early in the visual pathway.     

Receptive Field Vectors of Genetically-Identified Retinal Ganglion Cells Reveal Cell-Type-Dependent Visual Functions

Sensory stimuli are encoded by diverse kinds of neurons but the identities of the recorded neurons that are studied are often unknown. We explored in detail the firing patterns of eight previously defined genetically-identified retinal ganglion cell (RGC) types from a single transgenic mouse line. We first introduce a new technique of deriving receptive field vectors (RFVs) which utilises a modified form of mutual information (“Quadratic Mutual Information”). We analysed the firing patterns of RGCs during presentation of short duration (~10 second) complex visual scenes (natural movies). We probed the high dimensional space formed by the visual input for a much smaller dimensional subspace of RFVs that give the most information about the response of each cell. The new technique is very efficient and fast and the derivation of novel types of RFVs formed by the natural scene visual input was possible even with limited numbers of spikes per cell. This approach enabled us to estimate the ''visual memory'' of each cell type and the corresponding receptive field area by calculating Mutual Information as a function of the number of frames and radius. Finally, we made predictions of biologically relevant functions based on the RFVs of each cell type. RGC class analysis was complemented with results for the cells’ response to simple visual input in the form of black and white spot stimulation, and their classification on several key physiological metrics. Thus RFVs lead to predictions of biological roles based on limited data and facilitate analysis of sensory-evoked spiking data from defined cell types.     

Reorganization of Receptive Fields of Cortical Field 21a Neurons and Formation of Responses to Moving Visual Stimuli

Using extracellular recording of spike activity from single neurons of field 21a of the cat neocortex, we examined in detail the spatial organization of receptive fields (RFs) of such cells after conditions of presentation of an immobile blinking light spot (a static RF) and moving visual stimuli (dynamic RFs). As was shown, the excitability of different RF subfields of a group of neurons possessing homogeneous on–off organization of the static RF changes significantly depended on the contrast, shape, dimension, orientation, and direction of movement of the applied mobile visual stimulus. This is manifested in changes in the number of discharge centers and shifts of their spatial localization. A hypothesis on the possible role of synchronous activation of the neurons neighboring the cell under study in the formation of an additional neuronal mechanism providing specialization of neuronal responses is proposed.     

Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding

Predictive coding has been previously introduced as a hierarchical coding framework for the visual system. At each level, activity predicted by the higher level is dynamically subtracted from the input, while the difference in activity continuously propagates further. Here we introduce modular predictive coding as a feedforward hierarchy of prediction modules without back-projections from higher to lower levels. Within each level, recurrent dynamics optimally segregates the input into novelty and familiarity components. Although the anatomical feedforward connectivity passes through the novelty-representing neurons, it is nevertheless the familiarity information which is propagated to higher levels. This modularity results in a twofold advantage compared to the original predictive coding scheme: the familiarity-novelty representation forms quickly, and at each level the full representational power is exploited for an optimized readout. As we show, natural images are successfully compressed and can be reconstructed by the familiarity neurons at each level. Missing information on different spatial scales is identified by novelty neurons and complements the familiarity representation. Furthermore, by virtue of the recurrent connectivity within each level, non-classical receptive field properties still emerge. Hence, modular predictive coding is a biologically realistic metaphor for the visual system that dynamically extracts novelty at various scales while propagating the familiarity information.     

Quantitative Studies of Stimulus Coding in First-Order Vibrissa Afferents of Rats. 1. Receptive Field Properties and Threshold Distributions

We examined stimulus-response relationships of vibrissa-activated mechanosensory neurons of the rat's fifth (trigeminal) ganglion. Single-unit activity was recorded with tungsten microelectrodes. The vibrissae were deflected with a variety of parametrically controlled stimulus waveforms.

We found that the receptive field of each vibrissa-activated neuron consisted of a single vibrissa. Few, if any, unambiguous examples of spontaneous activity were observed in these neurons. Even if true spontaneous activity was present, its observed incidence was low, as were the measured discharge rates.

Thresholds of individual neurons were usually quite discrete; often a 1-2% increase in pulse magnitude (angular displacement) above a level to which the neuron did not respond caused it to discharge on every trial. The distribution of thresholds for the sample was continuous with a median of about 1° and a range of over three orders of magnitude. The most sensitive neurons responded to deflections of less than 0.1°. Many neurons responded to a single suprathreshold pulse with more than one spike. We found no consistent relationships among the thresholds of the additional evoked discharges of an individual neuron other than that the total number of evoked spikes either increased or stayed the same, but never decreased, as stimulus magnitude increased.

About one-third of the neurons examined had velocity thresholds below 3°/sec. Above that value, thresholds were distributed continuously throughout a range of over three orders of magnitude. The median velocity threshold was about 100°/sec. The broad and continuous distributions of both magnitude and velocity thresholds suggest that a population of vibrissa-activated neurons can code stimulus strength smoothly and continuously over a wide range, even though individual neurons may be poorly suited to do so.     

Distribution Coding in the Visual Pathway

Although a variety of types of spike interval histograms have been reported, little attention has been given to the spike interval distribution as a neural code and to how different distributions are transmitted through neural networks. In this paper we present experimental results showing spike interval histograms recorded from retinal ganglion cells of the cat. These results exhibit a clear correlation between spike interval distribution and stimulus condition at the retinal ganglion cell level. The averaged mean rates of the cells studied were nearly the same in light as in darkness whereas the spike interval histograms were much more regular in light than in darkness. We present theoretical models which illustrate how such a distribution coding at the retinal level could be “interpreted” or recorded at some higher level of the nervous system such as the lateral geniculate nucleus. Interpretation is an essential requirement of a neural code which has often been overlooked in modeling studies. Analytical expressions are derived describing the role of distribution coding in determining the transfer characteristics of a simple interaction model and of a lateral inhibition network. Our work suggests that distribution coding might be interpreted by simply interconnected neural networks such as relay cell networks, in general, and the primary thalamic sensory nuclei in particular.     

Timing Precision in Population Coding of Natural Scenes in the Early Visual System

The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ~10-ms resolution is a crucial property of the neural code entering cortex.     

Sparse Spectro-Temporal Receptive Fields Based on Multi-Unit and High-Gamma Responses in Human Auditory Cortex

Spectro-Temporal Receptive Fields (STRFs) were estimated from both multi-unit sorted clusters and high-gamma power responses in human auditory cortex. Intracranial electrophysiological recordings were used to measure responses to a random chord sequence of Gammatone stimuli. Traditional methods for estimating STRFs from single-unit recordings, such as spike-triggered-averages, tend to be noisy and are less robust to other response signals such as local field potentials. We present an extension to recently advanced methods for estimating STRFs from generalized linear models (GLM). A new variant of regression using regularization that penalizes non-zero coefficients is described, which results in a sparse solution. The frequency-time structure of the STRF tends toward grouping in different areas of frequency-time and we demonstrate that group sparsity-inducing penalties applied to GLM estimates of STRFs reduces the background noise while preserving the complex internal structure. The contribution of local spiking activity to the high-gamma power signal was factored out of the STRF using the GLM method, and this contribution was significant in 85 percent of the cases. Although the GLM methods have been used to estimate STRFs in animals, this study examines the detailed structure directly from auditory cortex in the awake human brain. We used this approach to identify an abrupt change in the best frequency of estimated STRFs along posteromedial-to-anterolateral recording locations along the long axis of Heschl’s gyrus. This change correlates well with a proposed transition from core to non-core auditory fields previously identified using the temporal response properties of Heschl’s gyrus recordings elicited by click-train stimuli.     

Shaping of Receptive Fields in the Visual Cortex During Retinal Maturation

We present a computational study of the formation of simple-cell receptive field patterns in the primary visual cortex. Based on the observation that the spatial frequency of the retinal filter increases postnatally, our results explain differences in the time course of the development of orientation selectivity in binocularly deprived and normally reared kittens. Development after eye-opening in normal animals is modelled by training with natural images, whereas in the case of binocular deprivation noise-like stimulation continues. Further, it is shown that different orientation selectivities are obtained for network models trained with natural images in contrast to random phase images of identical second order statistics. The latter finding suggests that higher-order statistics of the inputs influences development of primary visual cortex. Finally, we search for quantities that identify possible signatures of natural image statistics in order to specify the amount of constructiveness that visual experience has on the formation of receptive fields.     

Predictive Coding of Dynamical Variables in Balanced Spiking Networks

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.     

Cellular Adaptation Facilitates Sparse and Reliable Coding in Sensory Pathways

Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.     

Covariation between Spike and LFP Modulations Revealed with Focal and Asynchronous Stimulation of Receptive Field Surround in Monkey Primary Visual Cortex

A focal visual stimulus outside the classical receptive field (RF) of a V1 neuron does not evoke a spike response by itself, and yet evokes robust changes in the local field potential (LFP). This subthreshold LFP provides a unique opportunity to investigate how changes induced by surround stimulation leads to modulation of spike activity. In the current study, two identical Gabor stimuli were sequentially presented with a variable stimulus onset asynchrony (SOA) ranging from 0 to 100 ms: the first (S1) outside the RF and the second (S2) over the RF of primary visual cortex neurons, while trained monkeys performed a fixation task. This focal and asynchronous stimulation of the RF surround enabled us to analyze the modulation of S2-evoked spike activity and covariation between spike and LFP modulation across SOA. In this condition, the modulation of S2-evoked spike response was dominantly facilitative and was correlated with the change in LFP amplitude, which was pronounced for the cells recorded in the upper cortical layers. The time course of covariation between the SOA-dependent spike modulation and LFP amplitude suggested that the subthreshold LFP evoked by the S1 can predict the magnitude of upcoming spike modulation.     

The Effects of Ageing and Visual Field Loss on Pointing to Visual Targets

Purpose

To investigate the effect of ageing on visuomotor function and subsequently evaluate the effect of visual field loss on such function in older adults.

Methods

Two experiments were performed: 1) to determine the effect of ageing on visual localisation and subsequent pointing precision, and 2) to determine the effect of visual field loss on these outcome measures. For Experiment 1, we measured visual localisation and pointing precision radially at visual eccentricities of 5, 10 and 15° in 25 older (60–72 years) and 25 younger (20–31 years) adults. In the pointing task, participants were asked to point to a target on a touchscreen at a natural pace that prioritised accuracy of the touch. In Experiment 2, a subset of these tasks were performed at 15° eccentricity under both monocular and binocular conditions, by 8 glaucoma (55–76 years) and 10 approximately age-matched controls (61–72 years).

Results

Visual localisation and pointing precision was unaffected by ageing (p>0.05) and visual field loss (p>0.05), although movement time was increased in glaucoma (p = 0.01).

Conclusion

Visual localisation and pointing precision to high contrast stimuli within the central 15° of vision are unaffected by ageing. Even in the presence of significant visual field loss, older adults with glaucoma are able perform such tasks with reasonable precision provided the target can be perceived and movement time is not restricted.