Attention and Visual Perception

Attention is critical for optimal behavior. We study how neurons change the way they represented the visual world when attention shifts from one object to another. Typically, signals from neurons that encode visual information are stronger and less noise when a subject pays attention to the  objects that those neurons represent. Our current projects are directed at two important questions about neuronal correlates of attention.

First, what is attention? Studies of attention have always used operational definitions.  Attention takes different forms, and we have been working to break down attention into well defined components that map onto contributions from different brain structures.  We have found that attention-related changes in neurons in area V4 in visual cortex are specifically related to behavioral improvements in the ability to discriminate stimuli, while changes in prefrontal cortex are related to changes in eagerness to respond to target stimuli (Luo & Maunsell 2015, 2018, 2019).  Our current experiments are directed at determining which brain structures  contribute to changes in discrimination power and which contribute to the overall intensity of attention.

Readout of Signals from Cerebral Cortex

The cerebral cortex provides the brain's best and most complete representation its environment and state: sensory stimuli, current goals, task rules, cognitive set, motor state and more are all represented in cerebral cortex. At any moment, some of this information will be absolutely critical, while much will be irrelevant. Which representations are high-priority can change from moment to moment.  Working out how the brain selects and accesses specific cortical representations is one to the major challenges in systems-level neuroscience.  We currently have no comprehensive answers to questions such as how widely or narrowly cortical signals can be integrated in space and time, whether fine temporal patterns of spiking in cortex convey usable information, or how frequently and rapidly readout can shift from one set of neurons to another.

​​We have been approaching this issue using optogenetic perturbation of cortical neurons in mice that have been trained to perform visual detection and discrimination tasks (Cone et al, 2019, 2020).  Having animals give behavioral reports provides unambiguous evidence that the signals are capable of guiding behavior (that is, they can be read out).  Because the relevant signals are those we introduce, we know their location(s) and characteristics precisely.  Using optogenetics, we can limit perturbations to genetically identified sub-types of neurons.

Normalization in Sensory Representations

Sensory neurons respond differently when two or more stimuli appear at once. Typically, a neuron's response to multiple stimuli is not simply the sum of its responses to those stimuli when they appear individually.  Instead, responses are "normalized" to the context of how many stimuli are present.  Typically this produces a response that is closer to the average of the responses to the individual stimuli.

Normalization is ubiquitous in the nervous system. While the normalization is undoubtedly important for best using the dynamic range of neuronal responses, evidence suggests it serves other important functions.  In particular, it appears that much of the attention-related boost in sensory signals depends on normalization circuits to amplify signals (Ni & Maunsell 2019).  Normalization circuits can also reduce the noise in population signals (Verhoef & Maunsell 2017).  Additionally, normalization circuits might contribute to oscillations in the gamma frequency range in the local field potential (Ray et a. 2013). We are using multielectrode in mice and monkeys to characterize the specific cell-types that contribute to normalization, the circuits that they form, and the range of functional effects that they have on information processing in the brain.