Networks In Visual Cortex Research Articles

A nonlinear identification method to study effective connectivity in functional MRI

In this paper we propose a novel approach for characterizing effective connectivity in functional magnetic resonance imaging (fMRI) data. Unlike most other methods, our approach is nonlinear and does not rely on a priori specification of a model that contains structural information of neuronal populations. Instead, it relies on a nonlinear autoregressive exogenous model and nonlinear system identification theory; the model's nonlinear connectivities are determined using a least squares method. A statistical test was developed to quantify the significance of the influence that regions exert on one another. We compared this approach with a linear method and applied it to the human visual cortex network. Results show that this method can be used to model nonlinear interaction between different regions for fMRI data.

Perceptual Learning Modifies Resting Directional Interaction between Visual Cortex and Dorsal Attention Network

Perceptual Learning Modifies Resting Directional Interaction between Visual Cortex and Dorsal Attention Network

Multiscale modeling of the primary visual cortex

Unifying the results obtained from the large-scale, physiologically realistic, yet minimal computational primary visual cortex (V1) network models and identifying the single cortical operating state, namely, an intermittent desuppressed state (IDS) with fluctuation-controlled criticality are presented. The study suggests a possible operating state of V1 characterised by high total conductance with strong inhibition, large synaptic fluctuation, and the important role played by the N-methyl-D-aspartic acid conductance in long-range, orientation-specific interactions. The model cortex has the ability to quantitatively and qualitatively reproduce a host of dynamical phenomena exhibited by the real cortex, and the network mechanisms as revealed in the IDS state with fluctuation-controlled criticality in the model V1 dynamics offers suggestions for the physiological underpinnings of the neuronal dynamics in real V1.

Neuronal Selectivity and Local Map Structure in Visual Cortex

The organization of primary visual cortex (V1) into functional maps makes individual cells operate in a variety of contexts. For instance, some neurons lie in regions of fairly homogeneous orientation preference (iso-orientation domains), while others lie in regions with a variety of preferences (e.g., pinwheel centers). We asked whether this diversity in local map structure correlates with the degree of selectivity of spike responses. We used a combination of imaging and electrophysiology to reveal that neurons in regions of homogeneous orientation preference have much sharper tuning. Moreover, in both monkeys and cats, a common principle links the structure of the orientation map, on the spatial scale of dendritic integration, to the degree of selectivity of individual cells. We conclude that neural computation is not invariant across the cortical surface. This finding must factor into future theories of receptive field wiring and map development.

Different Dynamics of Performance and Brain Activation in the Time Course of Perceptual Learning

Perceptual learning is regarded as a manifestation of experience-dependent plasticity in the sensory systems, yet the underlying neural mechanisms remain unclear. We measured the dynamics of performance on a visual task and brain activation in the human primary visual cortex (V1) across the time course of perceptual learning. Within the first few weeks of training, brain activation in a V1 subregion corresponding to the trained visual field quadrant and task performance both increased. However, while performance levels then saturated and were maintained at a constant level, brain activation in the corresponding areas decreased to the level observed before training. These findings indicate that there are distinct temporal phases in the time course of perceptual learning, related to differential dynamics of BOLD activity in visual cortex.

Emergence of population synchrony in a layered network of the cat visual cortex

Recently, a quantitative wiring diagram for the local neuronal network of cat visual cortex was described [T. Binzegger, R.J. Douglas, K.A.C. Martin, A quantitative map of the circuit of the cat primary visual cortex, J. Neurosci. 39 (24) (2004) 8441–8453.] giving the first complete estimate of synaptic connectivity among various types of neurons in different cortical layers. Here we numerically studied the activity dynamics of the resulting heterogeneous layered network of spiking integrate-and-fire neurons, connected with conductance-based synapses. The layered network exhibited, among other states, an interesting asynchronous activity with intermittent population-wide synchronizations. These population bursts (PB) were initiated by a network hot spot, and then spread into the other parts of the network. The cause of this PB is the correlation amplifying nature of recurrent connections, which becomes significant in densely coupled networks. The hot spot was located in layer 2 / 3 , the part of the network with the highest number of excitatory recurrent connections. We conclude that in structured networks, regions with a high degree of recurrence and many out-going fibres may be a source for population-wide synchronization.

Coding the presence of visual objects in a recurrent neural network of visual cortex

Before we can recognize a visual object, our visual system has to segregate it from its background. This requires a fast mechanism for establishing the presence and location of objects independently of their identity. Recently, border-ownership neurons were recorded in monkey visual cortex which might be involved in this task [Zhou, H., Friedmann, H., von der Heydt, R., 2000. Coding of border ownership in monkey visual cortex. J. Neurosci. 20 (17), 6594–6611]. In order to explain the basic mechanisms required for fast coding of object presence, we have developed a neural network model of visual cortex consisting of three stages. Feed-forward and lateral connections support coding of Gestalt properties, including similarity, good continuation, and convexity. Neurons of the highest area respond to the presence of an object and encode its position, invariant of its form. Feedback connections to the lowest area facilitate orientation detectors activated by contours belonging to potential objects, and thus generate the experimentally observed border-ownership property. This feedback control acts fast and significantly improves the figure-ground segregation required for the consecutive task of object recognition.

Modulation of synaptic integration by nitric oxide in a neuronal network of rat visual cortex

Modulation of synaptic integration by nitric oxide in a neuronal network of rat visual cortex

Local networks in visual cortex and their influence on neuronal responses and dynamics

Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks—the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

Recurrent networks in human visual cortex: psychophysical evidence.

To study the neuronal circuitry underlying visual spatial-integration processes, we measured the effect of short and long chains of proximal Gabor-signal (GS) flankers (sigma = lambda = 0.15 degrees) on the contrast-discrimination function of a foveal GS target. We found that the same pattern of lateral masks enhanced target detection with low-contrast pedestals and strongly suppressed the discrimination of a range of intermediate pedestal contrasts (pedestal contrast <30%). Increasing the number of the flankers reversed the suppressive effect. The data suggest that the main influence of the proximal flankers is maintained by activity-dependent interactions and not by linear spatial summation. With an increased number of flankers, we found a nonmonotonic relationship between the discrimination thresholds and the number of flankers, supporting the notion that the discrimination thresholds are mediated by excitatory-inhibitory recurrent networks that manifest the dynamics of large neuronal populations in the neocortex [Proc. Natl. Acad. Sci. USA 94, 10426 (1997)].

Chapter 21 GABA-mediated inhibition in the neural networks of visual cortex

This chapter illustrates the mechanisms of gamma-aminobutyric acid (GABA)-mediated synaptic inhibition. In the neocortex, there is no structural evidence for the pre-synaptic inhibitory mechanisms that were described by Eccles in the spinal cord. Therefore, it is assumed that cortical inhibition acts primarily through post-synaptic mechanisms. The action of the inhibitory synapses is to produce an outward current that opposes the inward current produced by the excitatory synapses. In theoretical analyses of post-synaptic inhibition, it has been convenient to divide the post-synaptic effects into two types: hyperpolarizing inhibition and shunting inhibition. Both act by increasing the permeability or conductance of the membrane to ions whose reversal potentials are near (shunting) or more negative (hyperpolarizing) than the resting membrane potential. This distinction between shunting and hyperpolarizing inhibition is to some extent artificial, particularly in whole animal recordings, where the concept of a resting membrane potential has to be considerably stretched to be an accurate description of the data.

Contrast adaptation and contrast masking in human vision

After a preliminary study of visual evoked potentials (VEPS) to a test grating seen in the presence of masks at different orientations, psychophysical data are presented showing the effects of adaptation and of masking on thresholds for detecting the same test grating. The test is a vertical grating of spatial frequency 2 cycles per degree; adapting and masking gratings differ from the test either in orientation or in spatial frequency. The effects of adaptation and masking are explained by a single mechanism model that assumes: (i) adaptation and masking both alter the contrast response (or transducer) function of the mechanism that detects the test; (ii) masks, but not adaptors, stimulate the mechanism that detects the test; and (iii) a test is detectable when it raises response level by a constant amount. The model incorporates two distinct tuning functions, a broad adaptive contrast function and a narrow effective contrast function. It accounts adequately for all the data, including the location and size of the facilitative dip found in some masking functions, the constant slopes of the threshold elevation segments of adaptation functions and the varying slopes of masking functions. It also predicts the sometimes surprising joint effects of adaptation followed by masking and of two masks operating simultaneously.

Quantitative analysis of the choline acetyltransferase‐immunoreactive axonal network in the cat primary visual cortex: I. Adult cats

The laminar distribution of cholinergic axons was analyzed quantitatively in the visual cortex of adult cats by using immunocytochemistry with a monoclonal antibody against choline acetyltransferase (ChAT). ChAT(+) fibers and varicosities were counted at different locations within area 17 and the distribution patterns in various animals were compared. Choline acetyltransferase-immunoreactivity was localized in fine, varicose fibers, which were present in all layers of the visual cortex. The density of labeled fibers was highest in layer I, which contained 14% of all fibers and 19.5% of all varicosities, and decreased toward deeper layers. The number of varicosities decreased more markedly toward deeper layers than the frequency of fibers. These distribution patterns were very consistent, showing only slight intra- and interindividual variability.

Quantitative analysis of the choline acetyltransferase-immunoreactive axonal network in the cat primary visual cortex: II. Pre- and postnatal development.

The pre- and postnatal development of cholinergic projections was investigated in the cat striate cortex by applying immunohistochemical methods based on a monoclonal antibody against choline acetyltransferase (ChAT). The earliest age investigated was gestational day 54. At this stage a sparse network of ChAT(+) fibers was distributed throughout the striate cortex. Subsequent postnatal maturation of ChAT(+) fibers was characterized by an increase in fiber density that started in layer VI and gradually progressed toward more superficial layers. By 4 weeks of age the density of ChAT(+) fibers and varicosities had reached adult levels in layers V and VI but was still subnormal in layers I-IV. The mature pattern of cholinergic innervation was established by 13 weeks of age. There was no evidence for developmental gradients in the anteroposterior and mediolateral directions within area 17. These results indicate that the cholinergic projection to striate cortex develops continuously in an inside-out sequence as is characteristic for most cortical maturation processes. There was no indication that striate cortex receives an especially dense cholinergic input during the critical period.