Attention is essential for all daily tasks, and failure to control attention can have tragic consequences. An understanding of the neuronal mechanisms that guide attention will be needed for any comprehensive treatment of attention disorders, and is moreover likely to provide important new insights into the mechanisms of sensory processing and perception. The visual system is an ideal place to study attention, not only because optimal visual performance is critical for so many activities, but also because our relatively advanced understanding of the functional organization of the visual system makes it uniquely suited for addressing cutting-edge issues. The experiments proposed here capitalize on powerful new methods to address three pressing issues about the neuronal mechanisms underlying visual attention. The first concerns the mechanisms that control the distribution of attention across the visual field. Although attention is often described as a limited resource, recent neurophysiological measurements have revealed that the amount of attention directed to one visual stimulus can be independent of the amount of attention directed to another stimulus that is represented in the opposite cerebral hemisphere. To understand the mechanisms that control attention, it is important to know whether independent control exists only between the two hemispheres, or if attention can be relatively independent for stimuli represented within the same hemisphere. Although this question was previously unapproachable, it can now be answered with new techniques that use arrays of microelectrodes to monitor how much attention is allocated to individual stimuli represented by populations of neurons within one cerebral hemisphere.
The second aim i s to measure the causes of drifts in attention. Drift in attention might reflect unavoidable properties of brain organization, or might instead represent an adaptive mechanism for sampling the visual world optimally. Recordings from microelectrode arrays will allow us to measure fluctuations in attention on a behaviorally-relevant time scale under task conditions that are designed to either suppress or encourage drifts in attention. By comparing fluctuations in attention under different conditions, we will provide the first detailed assessment of the extent to which fluctuations in attention are under volitional control. The fina aim is to identify distinct neurophysiological components of attention. Attention is defined as the behavioral enhancements that arise from allocating resources to specific sensory signals, but several lines of evidence suggest that what we call attention is made up of separate elements that depend on distinct neurophysiological mechanisms. We will measure whether neuronal signals in visual and prefrontal cortex are specifically and differentially related to attention-related enhancements in sensory processing and attentional- related optimization of response criteria. The results could greatly advance our understanding of the nature of attention and its underlying mechanisms.
Attention dramatically influences perception and cognitive performance, and attention deficits are the most commonly diagnosed behavioral disorder of childhood, with attention deficit hyperactivity disorder (ADHD) affecting about 5% of children in the United States (1) and worldwide (2). Better understanding of basic neuronal mechanisms related to attention and their interaction with sensory signals is needed for guiding assessment, diagnosis and treatment of deficits of attention. The proposed research will investigate how attention affects visual processing in the nervous system, and in particular how control signals related to attention are distributed to different regions of visual cerebral cortex.
|Mayo, J Patrick; Maunsell, John H R (2016) Graded Neuronal Modulations Related to Visual Spatial Attention. J Neurosci 36:5353-61|
|Ray, Supratim; Maunsell, John H R (2015) Do gamma oscillations play a role in cerebral cortex? Trends Cogn Sci 19:78-85|
|Luo, Thomas Zhihao; Maunsell, John H R (2015) Neuronal Modulations in Visual Cortex Are Associated with Only One of Multiple Components of Attention. Neuron 86:1182-8|
|Mayo, J Patrick; Cohen, Marlene R; Maunsell, John H R (2015) A Refined Neuronal Population Measure of Visual Attention. PLoS One 10:e0136570|
|Histed, Mark H; Ni, Amy M; Maunsell, John H R (2013) Insights into cortical mechanisms of behavior from microstimulation experiments. Prog Neurobiol 103:115-30|
|Ray, Supratim; Ni, Amy M; Maunsell, John H R (2013) Strength of gamma rhythm depends on normalization. PLoS Biol 11:e1001477|
|Ni, Amy M; Ray, Supratim; Maunsell, John H R (2012) Tuned normalization explains the size of attention modulations. Neuron 73:803-13|
|Kang, Incheol; Maunsell, John H R (2012) Potential confounds in estimating trial-to-trial correlations between neuronal response and behavior using choice probabilities. J Neurophysiol 108:3403-15|
|Ghose, Kaushik; Maunsell, John H R (2012) A strong constraint to the joint processing of pairs of cortical signals. J Neurosci 32:15922-33|
|Cohen, Marlene R (2012) Eppendorf winner. When attention wanders. Science 338:58-9|
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