John H. R. Maunsell

The connections of the middle temporal visual area (MT) and their relationship to a cortical hierarchy in the macaque monkey

The cortical and subcortical connections of the middle temporal visual area (MT) of the macaque monkey were investigated using combined injections of [3H]proline and horseradish peroxidase within MT. Cortical connections were assigned to specific visual areas on the basis of their relationship to the pattern of interhemispheric connections, revealed by staining for degeneration following callosal transection. MT was shown to be reciprocally connected with many topographically organized cortical visual areas, including V1, V2, V3, and V4. These pathways link regions representing corresponding portions of the visual field in the different areas. In addition, MT has reciprocal connections with two previously unidentified cortical areas, which we have designated the medial superior temporal area (MST) and the ventral intraparietal area (VIP). The laminar distribution of terminals and cell bodies in cortical areas connected with MT follows a consistent pattern. In areas V1, V2, and V3, the projections to MT arise largely or exclusively from cells in supragranular layers, and the reciprocal connections from MT terminate mainly in supragranular and infragranular layers. In contrast, the projections to MST and VIP terminate mainly in layer IV, and the reciprocal pathways originate from cells in both superficial and deep layers. On the basis of this pattern, each connection can be designated as forward or feedback in nature, and a hierarchical arrangement of visual areas can be determined. In this hierarchy, MT is at a higher level than V1, V2, and V3, and at a lower level than MST and VIP. Subcortical projections were seen from MT to the claustrum, the putamen, the caudate nucleus, the inferior and lateral subdivisions of the pulvinar complex, the ventral lateral geniculate nucleus, the reticular nucleus of the thalamus, the superior colliculus, and the pontine nuclei.

Effects of Attention on Orientation-Tuning Functions of Single Neurons in Macaque Cortical Area V4

We examined how attention affected the orientation tuning of 262 isolated neurons in extrastriate area V4 and 135 neurons in area V1 of two rhesus monkeys. The animals were trained to perform a delayed match-to-sample task in which oriented stimuli were presented in the receptive field of the neuron being recorded. On some trials the animals were instructed to pay attention to those stimuli, and on other trials they were instructed to pay attention to other stimuli outside the receptive field. In this way, orientation-tuning curves could be constructed from neuronal responses collected in two behavioral states: one in which those stimuli were attended by the animal and one in which those stimuli were ignored by the animal. We fit Gaussians to the neuronal responses to twelve different orientations for each behavioral state. Although attention enhanced the responses of V4 neurons (median 26% increase) and V1 neurons (median 8% increase), selectivity, as measured by the width of its orientation-tuning curve, was not systematically altered by attention. The effects of attention were consistent with a multiplicative scaling of the driven response to all orientations. We also found that attention did not cause systematic changes in the undriven activity of the neurons.

Hierarchical organization and functional streams in the visual cortex

Abstract In the macaque monkey, a dozen distinct visual areas have been identified in the cerebral cortex. These areas can be arranged in a well-defined hierarchy on the basis of their pattern of interconnections. Physiological recordings suggest that there are at least two major functional streams in this hierarchy, one related to the analysis of motion and the other to the analysis of form and color.

Coding of image contrast in central visual pathways of the macaque monkey.

Measurements of contrast sensitivity were obtained from isolated neurons in the lateral geniculate nucleus, striate cortex, and middle temporal visual area of macaque monkeys. Between the lateral geniculate nucleus and the middle temporal area contrast sensitivity functions become progressively steeper. Furthermore, many neurons in the middle temporal area are more sensitive than any cell encountered in early stages. Measurements made with stimuli of different sizes show that this high sensitivity depends on areal summation across the receptive field.

Feature-based attention in visual cortex

Although most studies of visual attention have examined the effects of shifting attention between different locations in the visual field, attention can also be directed to particular visual features, such as a color, orientation or a direction of motion. Single-unit studies have shown that attention to a feature modulates neuronal signals in a range of areas in monkey visual cortex. The location-independent property of feature-based attention makes it particularly well suited to modify selectively the neural representations of stimuli or parts within complex visual scenes that match the currently attended feature. This review is part of the TINS special issue on The Neural Substrates of Cognition.

Attention improves performance primarily by reducing interneuronal correlations

Visual attention can improve behavioral performance by allowing observers to focus on the important information in a complex scene. Attention also typically increases the firing rates of cortical sensory neurons. Rate increases improve the signal-to-noise ratio of individual neurons, and this improvement has been assumed to underlie attention-related improvements in behavior. We recorded dozens of neurons simultaneously in visual area V4 and found that changes in single neurons accounted for only a small fraction of the improvement in the sensitivity of the population. Instead, over 80% of the attentional improvement in the population signal was caused by decreases in the correlations between the trial-to-trial fluctuations in the responses of pairs of neurons. These results suggest that the representation of sensory information in populations of neurons and the way attention affects the sensitivity of the population may only be understood by considering the interactions between neurons.

Different Origins of Gamma Rhythm and High-Gamma Activity in Macaque Visual Cortex

High-gamma (80–200 Hz) activity can be dissociated from gamma rhythms in the monkey cortex, and appears largely to reflect spiking activity in the vicinity of the electrode.

Shape selectivity in primate lateral intraparietal cortex

The extrastriate visual cortex can be divided into functionally distinct temporal and parietal regions, which have been implicated in feature-related (‘what’) and spatial (‘where’) vision, respectively. Neuropsychological studies of patients with damage to either the temporal or the parietal regions provide support for this functional distinction. Given the prevailing modular theoretical framework and the fact that prefrontal cortex receives inputs from both temporal and parietal streams,, recent studies have focused on the role of prefrontal cortex in understanding where and how information about object identity is integrated with (or remains segregated from) information about object location. Here we show that many neurons in primate posterior parietal cortex (the ‘where’ pathway) show sensory shape selectivities to simple, two-dimensional geometric shapes while the animal performs a simple fixation task. In a delayed match-to-sample paradigm, many neuronal units also show significant differences in delay-period activity, and these differences depend on the shape of the sample. These results indicate that units in posterior parietal cortex contribute to attending to and remembering shape features in a way that is independent of eye movements, reaching, or object manipulation. These units show shape selectivity equivalent to any shown in the ventral pathway.

The Effect of Perceptual Learning on Neuronal Responses in Monkey Visual Area V4

Previous studies have shown that perceptual learning can substantially alter the response properties of neurons in the primary somatosensory and auditory cortices. Although psychophysical studies suggest that perceptual learning induces similar changes in primary visual cortex (V1), studies that have measured the response properties of individual neurons have failed to find effects of the size described for the other sensory systems. We have examined the effect of learning on neuronal response properties in a visual area that lies at a later stage of cortical processing, area V4. Adult macaque monkeys were trained extensively on orientation discrimination at a specific retinal location using a narrow range of orientations. During the course of training, the subjects achieved substantial improvement in orientation discrimination that was primarily restricted to the trained location. After training, neurons in V4 with receptive fields overlapping the trained location had stronger responses and narrower orientation tuning curves than neurons with receptive fields in the opposite, untrained hemifield. The changes were most prominent for neurons that preferred orientations close to the trained range of orientations. These results provide the first demonstration of perceptual learning modifying basic neuronal response properties at an intermediate level of visual cortex and give insights into the distribution of plasticity across adult visual cortex.

Neuronal representations of cognitive state: reward or attention?

The effects of spatial or featural attention on the activity of neurons have been studied in many experiments that have used a variety of neurophysiological approaches. Other experiments have examined how expectations about reward are represented in neuronal activity in various brain regions. Although attention and reward are distinct concepts, I argue here that many neurophysiological experiments on attention and reward do not permit a clean dissociation between the two. This problem arises in part because reward contingencies are the only parameter manipulated in any of these experiments. I describe how attention and reward expectations have been confounded, giving rise to uncertainty about how signals related to attention and reward are distributed in the brain.