Intermediate-level visual processing requires sharing of information from throughout the visual field. The interconnections within the primary visual cortex and the relationship of these connections to the functional architecture of this area suggest that they mediate contour integration.
Cortical circuits include a plexus of long-range horizontal connections, running parallel to the cortical surface, formed by the axons of pyramidal neurons. Horizontal connections exist in every area of the cerebral cortex, but their function varies from one area to the next depending on the functional architecture of each area. In the visual cortex these connections mediate interactions between orientation columns of similar specificity thus integrating information over a large area of visual cortex that represents a great expanse of the visual field (see Figure 25–14).
The combination of this like-to-like rule of connections and the fact that the horizontal connections link distant locations in the visual field suggest these connections have a role in contour integration. Contour integration and the related property of contour saliency reflect the Gestalt principle of good continuation. Contour integration and saliency are mediated by the horizontal connections in V1 (see Figure 27–6).
A final feature of cortical connectivity important for visuospatial integration is feedback projection from higher-order cortical areas. Feedback connections are as extensive as the feed-forward connections that originate in the thalamus or at earlier stages of cortical processing. Little is known about the function of these feedback projections. They likely play a role in mediating the top-down influences of attention, expectation, and perceptual task, all of which are known to affect early stages in cortical processing.
Perceptual Learning Requires Plasticity in Cortical Connections
The synaptic connections in ocular-dominance columns are adaptable to experience only during a critical period in development (see Chapter 57). This suggests that the functional properties of visual cortex neurons are fixed in adulthood. Nevertheless, many properties of cortical neurons remain mutable throughout life. For example, changes in the visual cortex can occur following retinal lesions.
When focal lesions occur in corresponding positions on the two retinas, the corresponding part of the cortical map, referred to as the lesion projection zone, is initially deprived of visual input. Over a period of several months, however, the receptive fields of cells within this region shift from the lesioned part of the retina to the functioning area surrounding the lesion. As a result, the cortical representation of the lesioned part of the retina shrinks while that of the surrounding region expands (Figure 27–13).
Adult cortical plasticity.
When corresponding positions in both eyes are lesioned, the cortical area receiving input from the lesioned areas—the lesion projection zone—is initially silenced. The receptive fields of neurons in the lesion projection zone eventually shift from the area of the lesion to the surrounding, intact retina. This occurs because neurons surrounding the lesion projection zone sprout collaterals that form synaptic connections with neurons inside the zone. As a result, the cortical representation of the lesioned part of the retina shrinks while that of the surrounding retina expands.
The plasticity of cortical maps and connections did not evolve as a response to lesions. Instead, plasticity is the neural mechanism for improving our perceptual skills. Many of the attributes analyzed by the visual cortex, including stereoscopic acuity, direction of movement, and orientation, become sharper with practice. Hermann von Helmholtz stated in 1866 that "the judgment of the senses may be modified by experience and by training derived under various circumstances, and may be adapted to the new conditions. Thus, persons may learn in some measure to utilize details of the sensation which otherwise would escape notice and not contribute to obtaining any idea of the object." This perceptual learning is a variety of implicit learning that does not involve conscious processes (see Chapter 65).
Perceptual learning involves repeating a discrimination task many times and does not require error feedback to improve performance. Improvement manifests itself as a decrease in the threshold for discriminating small differences in the attributes of a target stimulus or in the ability to detect a target in a complex environment. Several areas of visual cortex, including the primary visual cortex, participate in perceptual learning.
An important aspect of perceptual learning is its specificity: Training on one task does not transfer to other tasks. For example, in a three-line bisection task the subject must determine whether the centermost of three parallel lines is closer to the line on the left or the one on the right. The amount of offset from the central position required for accurate responses decreases substantially after repeated practice (Figure 27–14A).
Perceptual learning is a form of implicit learning. With practice one can learn to discriminate smaller differences in orientation, position, depth, and direction of movement of objects.
A. The improvement is seen as a reduction in the amount of change required to reliably detect a tilted line or one positioned to the left or right of a nearly collinear line (vernier task). Perceptual learning is highly specific, so that training on a three-line bisection task leads to substantial improvement in that task (left pair of bars in the bar graph) without affecting performance on the vernier discrimination task (central pair of bars). However, training specifically on vernier discrimination does enhance performance on that task (right pair of bars).
B. The responses of neurons in V1 parallel perceptual learning. Subjects can detect collinear line segments embedded in a random background more easily as the number of segments is increased. The responses of neurons in V1 grow correspondingly stronger with the increase in the number of line segments. After practice, a line with fewer segments stands out more easily, and with this improvement the responses in V1 also increase. (Reproduced, with permission, from Crist et al. 2001; and Li et al. 2008.)
The learning in this task is specific to the location in the visual field and to the orientation of the lines. This specificity suggests that early stages of visual processing are responsible, for in the early stages receptive fields are smallest, visuotopic maps are most precise, and orientation tuning is sharpest. The learning is also specific for the stimulus configuration. Training on three-line bisection does not transfer to a vernier discrimination task in which the context is a line that is collinear with the target line (see Figure 27–14A).
The response properties of neurons in the primary visual cortex change during the course of perceptual learning in a way that tracks the perceptual improvement. An example of this is seen in contour saliency. With practice, subjects can more easily detect contours embedded in complex backgrounds. Detection improves with contour length, and the responses of neurons in V1 increase as well. With practice, subjects improve their ability to detect shorter contours and V1 neurons become correspondingly more sensitive to shorter contours (see Figure 27–14B).
Visual Search Relies on the Cortical Representation of Visual Attributes and Shapes
The detectability of features such as color, orientation, and shape is related to the process of visual search. Certain objects emerge or "pop out" from others in a complex image because the visual system processes simultaneously, in parallel pathways, the features of the target and the surrounding distractors (Figure 27–15). When the features of a target are complex, the target can be identified only through careful inspection of an entire image or scene (see Figure 21–5).
One object in a complex image stands out under certain conditions.
A. A differently colored object pops out.
B. A differently oriented line also pops out.
C. More complex shapes can pop out when they are very familiar, such as the numeral 2 embedded in a field of 5s. Rotating the image by 90° renders the elements of the figure less recognizable, making it more difficult to find the one figure that differs from the rest. (Reproduced, with permission, from Wang, Cavanagh, and Green 1994.)
The pop-out phenomenon can be influenced by training. A stimulus that initially cannot be found without effortful searching will pop out after training. The neuronal correlate of such a dramatic change is not certain. Parallel processing of the features of an object and its background is possible because feature information is encoded within retinotopically mapped areas at multiple locations in the visual cortex. Pop-out probably occurs early in the visual cortex. The pop-out of complex shapes such as numerals lends support to the idea that early in visual processing neurons can represent, and be selective for, shapes more complex than line segments with a particular orientation.
Cognitive Processes Influence Visual Perception
Scene segmentation—the parsing of a scene into different objects—involves a combination of bottom-up processes that follow the Gestalt rule of good continuation and top-down processes that create object expectation.
One strong top-down influence is spatial attention, which can change focus without any movement of an observer's eyes. Spatial attention is object-oriented in that it is distributed over the area occupied by the attended object, allowing the visual cortex to analyze the shape and attributes of objects one at a time.
Attentional mechanisms can solve the superposition problem. For us to recognize an object in a scene that includes multiple objects, we must determine which features correspond to which objects. Our sense that we identify multiple objects simultaneously is illusory. Instead, we serially process objects in rapid succession by shifting attention from one to the next. The results of each analysis build up the perception of a complex environment populated with many distinct objects. A dramatic demonstration of the importance of attention in object recognition is change blindness. If a subject rapidly shifts between two slightly different views of the same scene, he will not be able to detect the absence of an important component of the scene in one view without considerable scrutiny (see Figure 29–3).
Another top-down influence is perceptual task. At early stages in visual processing the properties of the same neuron vary with the type of visual discrimination being performed. Object identification itself involves a process of hypothesis testing in which internal representations of objects are compared with information arriving from the retina. This process is reflected in studies of visual imagery: Early stages in processing such as the primary visual cortex are activated when one imagines scenes in the absence of visual input.