Primary visual cortex straightens natural video trajectories

European Journal of Neuroscience, 2007

In normal vision, visual scenes are predictable, as they are both spatially and temporally redundant. Evidence suggests that the visual system may use the spatio-temporal regularities of the external world, available in the retinal signal, to extract information from the visual environment and better reconstruct current and future stimuli. We studied this by recording neuronal responses of primary visual cortex (area V1) in anaesthetized and paralysed macaques during the presentation of dynamic sequences of bars, in which spatio-temporal regularities and local information were independently manipulated. Most V1 neurons were significantly modulated by events prior to and distant from stimulation of their classical receptive fields (CRFs); many were more strongly tuned to prior and distant events than they were to CRFs bars; and several showed tuning to prior information without any CRF stimulation. Hence, V1 neurons do not simply analyse local contours, but impute local features to the visual world, on the basis of prior knowledge of a visual world in which useful information can be distributed widely in space and time.

Recently, several studies showed that fMRI BOLD responses to moving random dot stimuli are enhanced at the location of dot appearance, i.e., the motion trailing edge. Possibly, BOLD activity in human visual cortex reflects predictability of visual motion input. In the current study, we investigate to what extent fMRI BOLD responses reflect estimated predictions to visual motion. We varied motion displacement parameters (duration and velocity), while measuring BOLD amplitudes as a function of distance from the trailing edge. We have found that for all stimulus configurations, BOLD signals decrease with increasing distance from the trailing edge. This finding indicates that neural activity directly reflects the predictability of moving dots, rather than their appearance within classical receptive fields. However, different motion displacement parameters exerted only marginal effects on predictability, suggesting that early visual cortex does not literally predict motion trajectories. Rather, the results reveal a heuristic mechanism of motion suppression from trailing to leading edge, plausibly mediated through short-range horizontal connections. Simple heuristic suppression allows the visual system to recognize novel input among many motion signals, while being most energy efficient.

Cortex, 2015

The computation of texture and shape involves integration of features of various orientations. Orientation networks within V1 tend to involve cells which share similar orientation selectivity. However, emergent properties in V2 require the integration of multiple orientations. We now show that, unlike interactions within V1, V1-V2 orientation interactions are much less synchronized and are not necessarily orientation dependent. We find V1-V2 orientation networks are of two types: a more tightly synchronized, orientation-preserving network and a less synchronized orientation-diverse network. We suggest that such diversity of V1-V2 interactions underlies the spatial and functional integration required for computation of higher order contour and shape in V2.

PLoS Computational Biology, 2012

Understanding how populations of neurons encode sensory information is a major goal of systems neuroscience. Attempts to answer this question have focused on responses measured over several hundred milliseconds, a duration much longer than that frequently used by animals to make decisions about the environment. How reliably sensory information is encoded on briefer time scales, and how best to extract this information, is unknown. Although it has been proposed that neuronal response latency provides a major cue for fast decisions in the visual system, this hypothesis has not been tested systematically and in a quantitative manner. Here we use a simple 'race to threshold' readout mechanism to quantify the information content of spike time latency of primary visual (V1) cortical cells to stimulus orientation. We find that many V1 cells show pronounced tuning of their spike latency to stimulus orientation and that almost as much information can be extracted from spike latencies as from firing rates measured over much longer durations. To extract this information, stimulus onset must be estimated accurately. We show that the responses of cells with weak tuning of spike latency can provide a reliable onset detector. We find that spike latency information can be pooled from a large neuronal population, provided that the decision threshold is scaled linearly with the population size, yielding a processing time of the order of a few tens of milliseconds. Our results provide a novel mechanism for extracting information from neuronal populations over the very brief time scales in which behavioral judgments must sometimes be made.

The mechanism or microcircuitry behind orientation selectivity in primary visual cortex (V1), and the means by which it develops without supervision or visual input, both remain unresolved questions. Work on the developmental question has assumed the prevalent spatial convergence model of orientation selectivity as the target mechanism. Encouraged by growing evidence challenging both the completeness of this model and its developmental viability, we investigated an alternative scheme. Accordingly, we demonstrate computationally how a scheme in which orientation selectivity originates from the orientation biases already in the retina and lateral geniculate nucelus (LGN) can answer both the mechanistic and developmental questions. In this scheme, the divergence of outputs from the retina allows retinal spontaneous activity to create correlations within the LGN. These correlations in turn allow a Hebbian plasticity mechanism to strengthen those LGN inputs to V1 which carry similar orie...

Proceedings of the National Academy of Sciences of the United States of America, 2012

Neurons in the medial superior temporal (MST) area of the primate visual cortex respond selectively to complex motion patterns defined by expansion, rotation, and deformation. Consequently they are often hypothesized to be involved in important behavioral functions, such as encoding the velocities of moving objects and surfaces relative to the observer. However, the computations underlying such selectivity are unknown. In this work we have developed a unique, naturalistic motion stimulus and used it to probe the complex selectivity of MST neurons. The resulting data were then used to estimate the properties of the feed-forward inputs to each neuron. This analysis yielded models that successfully accounted for much of the observed stimulus selectivity, provided that the inputs were combined via a nonlinear integration mechanism that approximates a multiplicative interaction among MST inputs. In simulations we found that this type of integration has the functional role of improving estimates of the 3D velocity of moving objects. As this computation is of general utility for detecting complex stimulus features, we suggest that it may represent a fundamental aspect of hierarchical sensory processing.

Nature neuroscience, 2001

Previous experiments indicate that the shape of maps of preferred orientation in the primary visual cortex does not depend on visual experience. We propose a network model that demonstrates that the orientation and direction selectivity of individual units and the structure of the corresponding angle maps could emerge from local recurrent connections. Our model reproduces the structure of preferred orientation and direction maps, and explains the origin of their interrelationship. The model also provides an explanation for the correlation between position shifts of receptive fields and changes of preferred orientations of single neurons across the surface of the cortex.

The Journal of Physiology, 2011

Non technical summary Neurones of the mammalian primary visual cortex have the remarkable property of being selective for the orientation of visual contours. It has been controversial whether this selectivity arises purely from mechanisms within the cortex itself, from the special way afferents from the thalamus project to the cortex or from the sharpening of a bias for orientation that already exists in the retina and the thalamus. Our experiments support the last of these three hypotheses. We used a special protocol to study both inhibitory and excitatory interactions within the cortex as well as in the thalamus and we find that the orientation selectivity may depend upon multiple mechanisms-including the thalamic biases for orientation and intracortical inhibition and excitation.

NeuroImage, 2009

Visual activity after eye-opening influences feature map structure in primary visual cortex (V1). For instance, rearing cats in an environment of stripes of one orientation yields an over-representation of that orientation in V1. However, whether such changes also affect the higher-order statistics of orientation maps is unknown. A statistical bias of orientation maps in normally raised animals is that the probability of the angular difference in orientation preference between each pair of points in the cortex depends on the angle of the line joining those points relative to a fixed but arbitrary set of axes. Natural images show an analogous statistical bias; however, whether this drives the development of comparable structure in V1 is unknown. We examined these statistics for normal, stripe-reared and dark-reared cats, and found that the biases present were not consistently related to those present in the input, or to genetic relationships. We compared these results with two computational models of orientation map development, an analytical model and a Hebbian model. The analytical model failed to reproduce the experimentally observed statistics. In the Hebbian model, while orientation difference statistics could be strongly driven by the input, statistics similar to those seen in experimental maps arose only when symmetry breaking was allowed to occur spontaneously. These results suggest that these statistical biases of orientation maps arise primarily spontaneously, rather than being governed by either input statistics or genetic mechanisms.

The Journal of Neuroscience, 2012

Neurons in primary visual cortex (V1) display substantial orientation selectivity even in species where V1 lacks an orientation map, such as in mice and rats. The mechanism underlying orientation selectivity in V1 with such a salt-and-pepper organization is unknown; it is unclear whether a connectivity that depends on feature similarity is required, or a random connectivity suffices. Here we argue for the latter. We study the response to a drifting grating of a network model of layer 2/3 with random recurrent connectivity and feedforward input from layer 4 neurons with random preferred orientations. We show that even though the total feedforward and total recurrent excitatory and inhibitory inputs all have a very weak orientation selectivity, strong selectivity emerges in the neuronal spike responses if the network operates in the balanced excitation/inhibition regime. This is because in this regime the (large) untuned components in the excitatory and inhibitory contributions approx...