Traditional views of visual processing suggest that early visual neurons in areas V1 and V2 are static spatiotemporal filters that extract local features from a visual scene. The extracted information is then channeled through a feedforward chain of modules in successively higher visual areas for further analysis. Recent electrophysiological recordings from early visual neurons in awake behaving monkeys reveal that there are many levels of complexity in the information processing of the early visual cortex, as seen in the long-latency responses of its neurons. These new findings suggest that activity in the early visual cortex is tightly coupled and highly interactive with the rest of the visual system. They lead us to propose a new theoretical setting based on the mathematical framework of hierarchical Bayesian inference for reasoning about the visual system. In this framework, the recurrent feedforward/feedback loops in the cortex serve to integrate top-down contextual priors and bottom-up observations so as to implement concurrent probabilistic inference along the visual hierarchy. We suggest that the algorithms of particle filtering and Bayesian-belief propagation might model these interactive cortical computations. We review some recent neurophysiological evidences that support the plausibility of these ideas.

In the classical feed-forward, modular view of visual processing, the primary visual cortex (area V1) is a module that serves to extract local features such as edges and bars. Representation and recognition of objects are thought to be functions of higher extrastriate cortical areas. This paper presents neurophysiological data that show the later part of V1 neurons' responses reflecting higher order perceptual computations related to Ullman's (Cognition 1984; 18:97-159) visual routines and Marr's (Vision NJ: Freeman 1982) full primal sketch, 2 1/2D sketch and 3D model. Based on theoretical reasoning and the experimental evidence, we propose a possible reinterpretation of the functional role of V1. In this framework, because of V1 neurons' precise encoding of orientation and spatial information, higher level perceptual computations and representations that involve high resolution details, fine geometry and spatial precision would necessarily involve V1 and be reflected in the later part of its neurons' activities.

To elucidate the roles of visual areas V1 and V2 and their interaction in early perceptual processing, we studied the responses of V1 and V2 neurons to statically displayed Kanizsa figures. We found evidence that V1 neurons respond to illusory contours of the Kanizsa figures. The illusory contour signals in V1 are weaker than in V2, but are significant, particularly in the superficial layers. The population averaged response to illusory contours emerged 100 msec after stimulus onset in the superficial layers of V1, and around 120 -190 msec in the deep layers. The illusory contour response in V2 began earlier, occurring at 70 msec in the superficial layers and at 95 msec in the deep layers. The temporal sequence of the events suggests that the computation of illusory contours involves intercortical interaction, and that early perceptual organization is likely to be an interactive process. W hen viewing the Kanizsa display shown in Fig. 1a, we perceive the borders of a square even in regions of the image where there is no direct visual evidence for them. This is one example of the phenomenon of illusory or subjective contours (1). This perceptual phenomenon has been reported by von der Heydt and colleagues (2, 3) to possess a direct physiological correlate in macaque area V2, where some neurons were found to respond to an illusory contour moving across their receptive fields. In contrast, they failed to observe responses to illusory contours in area V1. The apparent absence of illusory-contour responses in area V1 is puzzling both because there are recurrent pathways from V2 to V1 and because interaction between modules is a key feature of many models for early perceptual organization (4-7). Moreover, other groups have shown that neurons in area V1 do detect subjective contours defined indirectly in other ways, for example by the fracture line where lines or out of phase sine wave gratings abut (8, 9). Because of the nature of their stimuli, these studies (8, 9) did not resolve the question of whether their results would apply to the illusory contours as studied by Von der Heydt and colleagues. In light of these considerations, we decided to reexamine the issue of neural responses to illusory contours in areas V1 and V2. By using a technique designed to call attention to the illusory square and employing a static display that allowed tracking the temporal evolution of responses, we have found that neurons in area V1 do respond to illusory contours, although at a latency greater than that in V2.We conducted the following neurophysiological experiment on two awake behaving rhesus monkeys. In each trial, while the monkey was fixating a red dot on the screen within a 0.5°fixation window, a sequence of four stimuli was presented. The presentation of each stimulus in the sequence lasted for 400 msec. On completion of the sequence, the monkey had to make a saccadic eye movement to another red dot that appeared at a random position on the screen to complete the trial. The set of test stimuli included a Kanizsa figure with...

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Successful application of two-photon imaging with genetic tools in awake macaque monkeys will enable fundamental advances in our understanding of higher cognitive function at the level of molecular and neuronal circuits. Here we report techniques for long-term two-photon imaging in awake macaque monkeys. Using genetically encoded indicators including GCaMP5 and GCaMP6s delivered by AAV2/1 into the visual cortex, we demonstrate that high-quality two-photon imaging of large neuronal populations can be achieved and maintained in awake monkeys for months. Simultaneous intracellular recording and two-photon calcium imaging confirm that fluorescence activity is linearly proportional to neuronal spiking activity across a wide range of firing rates (10 Hz to 150 Hz). By providing two-photon imaging access to cortical neuronal populations at single-cell or single dendritic spine resolution in awake monkeys, the techniques reported can help bridge the use of modern genetic and molecular tools and the study of higher cognitive function.

Multineuronal recordings have revealed that neurons in primary visual cortex (V1) exhibit coordinated fluctuations of spiking activity in the absence and in the presence of visual stimulation. From the perspective of understanding a single cell’s spiking activity relative to a behavior or stimulus, these network flutuations are typically considered to be noise. We show that these events are highly correlated with another commonly recorded signal, the local field potential (LFP), and are also likely related to global network state phenomena which have been observed in a number of neural systems. Moreover, we show that attributing a component of cell firing to these network fluctuations via explicit modeling of the LFP improves the recovery of cell properties. This suggests that the impact of network fluctuations may be estimated using the LFP, and that a portion of this network activity is unrelated to the stimulus and instead reflects ongoing cortical activity. Thus, the LFP acts as an easily accessible bridge between the network state and the spiking activity.

Inferring depth from binocular disparities is a difficult problem for the visual system because local features in the left- and right-eye images must be matched correctly to solve this “stereo correspondence problem.” Cortical architecture and computational studies suggest that lateral interactions among neurons could help resolve local uncertainty about disparity encoded in individual neurons by incorporating contextual constraints. We found that correlated activity among pairs of neurons in primary visual cortex depended both on disparity-tuning relationships and the stimuli displayed within the receptive fields of the neurons. Nearby pairs of neurons with distinct disparity tuning exhibited a decrease in spike correlation at competing disparities soon after response onset. Distant neuronal pairs of similar disparity tuning exhibited an increase in spike correlation at mutually preferred disparities. The observed correlated activity and response dynamics suggests that local competitive and distant cooperative interactions improve disparity tuning of individual neurons over time. Such interactions could represent a neural substrate for the principal constraints underlying cooperative stereo algorithms.