A typical scene contains many different objects that compete for neural representation due to the limited processing capacity of the visual system. At the neural level, competition among multiple stimuli is evidenced by the mutual suppression of their visually evoked responses and occurs most strongly at the level of the receptive field. The competition among multiple objects can be biased by both bottom-up sensory-driven mechanisms, such as stimulus salience, and top-down influences, such as selective attention. Although the competition among stimuli for representation is ultimately resolved within visual cortex, the source of top-down biasing signals likely derives from a distributed network of areas in frontal and parietal cortex. Recently, we reported that monkeys with lesions of prefrontal cortex (PFC) are selectively impaired in their ability to switch top-down control. In the past year, we asked whether monkeys with lesions of posterior parietal cortex (PPC) would show similar or different behavioral effects. Our results showed that, unlike monkeys with PFC lesions, those with PPC lesions are not selectively impaired in their ability to switch top-down control. Rather, they have a selective impairment in spatially locating targets they are required to discriminate. Thus, the PFC plays a critical role in the ability to switch attentional control on the basis of changing task demands, whereas the PPC plays a critical role in allocating attentional resources to behaviorally relevant spatial locations. These findings are being prepared for publication.

 During the past year, we also aimed to better characterize the nature of distractibility in ADHD by testing hypotheses about whether distractibility arises from increased sensory-driven interference or from inefficient top-down control. We employed an attentional filtering paradigm in which discrimination difficulty and distractor salience were parametrically manipulated. Increased discrimination difficulty should add to the load of top-down processes, whereas increased distractor salience should result in stronger sensory interference. We found a striking interaction of discrimination difficulty and distractor salience: For difficult discriminations, ADHD children filtered distractors as efficiently as healthy children and adults, and all groups were slower to respond with high vs. low salience distractors. In contrast, for easy discriminations, ADHD children were much slower and made more errors than healthy children and adults. For easy discriminations, healthy children and adults filtered out high salience distractors as easily as low salience distractors, but ADHD children were slower to respond on trials with low salience distractors than they on trials with high salience distractors. The fact that ADHD children exhibit efficient attentional filtering when task demands are high, but show deficient and atypical distractor filtering under low task demands suggests that filtering mechanisms remain intact in these children but the trigger for activating attention is selectively impaired.

 Perceptual learning refers to improved detection and discrmination of visual stimuli as a result of repeated experience with such stimuli. There is conflicting evidence in the literature regarding the role played by attention in perceptual learning. To further examine this issue, we independently manipulated exogenous (involuntary) and endogenous (voluntary) attention and measured the rate of perceptual learning of oriented stimuli presented in different quadrants of the visual field. In this way, we could track learning at attended, divided-attended, and unattended locations. We also measured contrast thresholds of the stimuli before and after training. Our results showed that, for both exogenous and endogenous attention, accuracy in performing the orientation discrimination improved to a greater extent at attended than at unattended locations. Importantly, however, only exogenous attention resulted in improved contrast thresholds. These findings suggest that both exogenous and endogenous attention facilitate perceptual learning, but that only exogenous attention enhances sensitivity to a trained visual stimulus. 
 Retinotopic selectivity, as measured by neuronal activity patterns that vary consistently with the location of visual stimuli, has been documented in many human brain regions, notably occipital visual cortex and frontal and parietal regions associated with endogenous (voluntary) attention. We hypothesized that retinotopic selectivity also exists in regions active during exogenous (involuntary) attention. To test this hypothesis, we acquired fMRI data while subjects maintained fixation on a central cross. At unpredictable time intervals, stimuli consisting of an array of rapidly expanding circles appeared at one of six spatial locations. Positive fMRI activations to the stimulus presentations were identified in multiple brain regions including the temporoparietal junction (TPJ), a region previously implicated in exogenous attention. The TPJ activations did not appear to be organized as a map across the cortical surface. However, multivoxel pattern recognition analysis successfully predicted fMRI responses to every one of the fifteen stimulus location pairs, demonstrating that patterns of activity in TPJ depend on the retinotopic stimulus location. This is the first demonstration that spatial locations are represented in a brain region associated with exogenous attention.

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Kaskan, P M; Costa, V D; Eaton, H P et al. (2016) Learned Value Shapes Responses to Objects in Frontal and Ventral Stream Networks in Macaque Monkeys. Cereb Cortex :
Bell, Andrew H; Summerfield, Christopher; Morin, Elyse L et al. (2016) Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex. Curr Biol 26:2280-90
Gattass, Ricardo; Lima, Bruss; Soares, Juliana G M et al. (2015) Controversies about the visual areas located at the anterior border of area V2 in primates. Vis Neurosci 32:E019
Zachariou, Valentinos; Nikas, Christine V; Safiullah, Zaid N et al. (2015) Common Dorsal Stream Substrates for the Mapping of Surface Texture to Object Parts and Visual Spatial Processing. J Cogn Neurosci 27:2442-61
Japee, Shruti; Holiday, Kelsey; Satyshur, Maureen D et al. (2015) A role of right middle frontal gyrus in reorienting of attention: a case study. Front Syst Neurosci 9:23
Avidan, Galia; Tanzer, Michal; Hadj-Bouziane, Fadila et al. (2014) Selective dissociation between core and extended regions of the face processing network in congenital prosopagnosia. Cereb Cortex 24:1565-78
Gattass, Ricardo; Galkin, Thelma W; Desimone, Robert et al. (2014) Subcortical connections of area V4 in the macaque. J Comp Neurol 522:1941-65
Yue, Xiaomin; Pourladian, Irene S; Tootell, Roger B H et al. (2014) Curvature-processing network in macaque visual cortex. Proc Natl Acad Sci U S A 111:E3467-75
Morin, Elyse L; Hadj-Bouziane, Fadila; Stokes, Mark et al. (2014) Hierarchical Encoding of Social Cues in Primate Inferior Temporal Cortex. Cereb Cortex :
Gattass, Ricardo; Soares, Juliana G M; Desimone, Robert et al. (2014) Connectional subdivision of the claustrum: two visuotopic subdivisions in the macaque. Front Syst Neurosci 8:63

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