Charles M. Gray

Bio: Charles M. Gray is an academic researcher from Montana State University. The author has contributed to research in topics: Visual cortex & Orientation column. The author has an hindex of 36, co-authored 60 publications receiving 17794 citations. Previous affiliations of Charles M. Gray include Baylor College of Medicine & Max Planck Society.

Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties.

Abstract: A FUNDAMENTAL step in visual pattern recognition is the establishment of relations between spatially separate features. Recently, we have shown that neurons in the cat visual cortex have oscillatory responses in the range 40–60 Hz (refs 1,2) which occur in synchrony for cells in a functional column and are tightly correlated with a local oscillatory field potential. This led us to hypothesize that the synchronization of oscillatory responses of spatially distributed, feature selective cells might be a way to establish relations between features in different parts of the visual field2,3. In support of this hypothesis, we demonstrate here that neurons in spatially separate columns can synchronize their oscillatory responses. The synchronization has, on average, no phase difference, depends on the spatial separation and the orientation preference of the cells and is influenced by global stimulus properties.

Visual feature integration and the temporal correlation hypothesis

Abstract: The mammalian visual system is endowed with a nearly infinite capacity for the recognition of patterns and objects. To have acquired this capability the visual system must have solved what is a fundamentally combinatorial prob­ lem. Any given image consists of a collection of features, consisting of local contrast borders of luminance and wavelength, distributed across the visual field. For one to detect and recognize an object within a scene, the features comprising the object must be identified and segregated from those comprising other objects. This problem is inherently difficult to solve because of the combinatorial nature of visual images. To appreciate this point, consider a simple local feature such as a small vertically oriented line segment placed within a fixed location of the visual field. When combined with other line segments, this feature can form a nearly infinite number of geometrical objects. Any one of these objects may coexist with an equally large number of other

Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex

Abstract: In areas 17 and 18 of the cat visual cortex the firing probability of neurons, in response to the presentation of optimally aligned light bars within their receptive field, oscillates with a peak frequency near 40 Hz. The neuronal firing pattern is tightly correlated with the phase and amplitude of an oscillatory local field potential recorded through the same electrode. The amplitude of the local field-potential oscillations are maximal in response to stimuli that match the orientation and direction preference of the local cluster of neurons. Single and multiunit recordings from the dorsal lateral geniculate nucleus of the thalamus showed no evidence of oscillations of the neuronal firing probability in the range of 20-70 Hz. The results demonstrate that local neuronal populations in the visual cortex engage in stimulus-specific synchronous oscillations resulting from an intracortical mechanism. The oscillatory responses may provide a general mechanism by which activity patterns in spatially separate regions of the cortex are temporally coordinated.

Chattering cells: superficial pyramidal neurons contributing to the generation of synchronous oscillations in the visual cortex.

Abstract: In response to visual stimulation, a subset of neurons in the striate and prestriate cortex displays synchronous rhythmic firing in the gamma frequency band (20 to 70 hertz) This finding has raised two fundamental questions: What is the functional significance of synchronous gamma-band activity and how is it generated? This report addresses the second of these two questions By means of intracellular recording and staining of single cells in the cat striate cortex in vivo, a biophysically distinct class of pyramidal neuron termed “chattering cells” is described These neurons are located in the superficial layers of the cortex, intrinsically generate 20- to 70-hertz repetitive burst firing in response to suprathreshold depolarizing current injection, and exhibit pronounced oscillations in membrane potential during visual stimulation that are largely absent during periods of spontaneous activity These properties suggest that chattering cells may make a substantial intracortical contribution to the generation of synchronous cortical oscillations and thus participate in the recruitment of large populations of cells into synchronously firing assemblies

Collective dynamics of small-world networks

Abstract: Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Neural Mechanisms of Selective Visual Attention

Abstract: The two basic phenomena that define the problem of visual attention can be illustrated in a simple example. Consider the arrays shown in each panel of Figure 1. In a typical experiment, before the arrays were presented, subjects would be asked to report letters appearing in one color (targets, here black letters), and to disregard letters in the other color (nontargets, here white letters). The array would then be briefly flashed, and the subjects, without any opportunity for eye movements, would give their report. The display mimics our. usual cluttered visual environment: It contains one or more objects that are relevant to current behavior, along with others that are irrelevant. The first basic phenomenon is limited capacity for processing information. At any given time, only a small amount of the information available on the retina can be processed and used in the control of behavior. Subjectively, giving attention to any one target leaves less available for others. In Figure 1, the probability of reporting the target letter N is much lower with two accompa­ nying targets (Figure la) than with none (Figure Ib). The second basic phenomenon is selectivity-the ability to filter out un­ wanted information. Subjectively, one is aware of attended stimuli and largely unaware of unattended ones. Correspondingly, accuracy in identifying an attended stimulus may be independent of the number of nontargets in a display (Figure la vs Ie) (see Bundesen 1990, Duncan 1980).

Neurophysiological investigation of the basis of the fMRI signal

Abstract: Functional magnetic resonance imaging (fMRI) is widely used to study the operational organization of the human brain, but the exact relationship between the measured fMRI signal and the underlying neural activity is unclear. Here we present simultaneous intracortical recordings of neural signals and fMRI responses. We compared local field potentials (LFPs), single- and multi-unit spiking activity with highly spatio-temporally resolved blood-oxygen-level-dependent (BOLD) fMRI responses from the visual cortex of monkeys. The largest magnitude changes were observed in LFPs, which at recording sites characterized by transient responses were the only signal that significantly correlated with the haemodynamic response. Linear systems analysis on a trialby-trial basis showed that the impulse response of the neurovascular system is both animal- and site-specific, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses. These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output.