Graded Neuronal Modulations Related to Visual Spatial Attention

Dissociation of attentional state and behavioral outcome using local field potentials

Successful behavior depends on attentional state and other factors related to decision-making, which may modulate neuronal activity differently. Here, we investigated whether attentional state and behavioral outcome (i.e., whether a target is detected or missed) are distinguishable using the power and phase of local field potential (LFP) recorded bilaterally from area V4 of monkeys performing a cued visual attention task. To link each trial's outcome to pairwise measures of attention that are typically averaged across trials, we used several methods to obtain single-trial estimates of spike count correlation and phase consistency. Surprisingly, while attentional location was best discriminated using gamma and high-gamma power, behavioral outcome was best discriminated by alpha power and steady-state visually evoked potential. Power outperformed absolute phase in attentional/behavioral discriminability, although single-trial gamma phase consistency provided reasonably high attentional discriminability. Our results suggest a dissociation between the neuronal mechanisms that regulate attentional focus and behavioral outcome.

Microsaccades are directed toward the midpoint between targets in a variably cued attention task

Reliable, noninvasive biomarkers that reveal the internal state of a subject are an invaluable tool for neurological diagnoses. Small fixational eye movements, called microsaccades, are a candidate biomarker thought to reflect a subject's focus of attention [Z. M. Hafed, J. J. Clark, VisionRes. 42, 2533-2545 (2002); R. Engbert, R. Kliegl, VisionRes. 43, 1035-1045 (2003)]. The linkage between the direction of microsaccades and attention has mainly been demonstrated using explicit and unambiguous attentional cues. However, the natural world is seldom predictable and rarely provides unambiguous information. Thus, a useful biomarker must be robust to such changes in environmental statistics. To determine how well microsaccades reveal visual-spatial attention across behavioral contexts, we analyzed these fixational eye movements in monkeys performing a conventional change detection task. The task included two stimulus locations and variable cue validities across blocks of trials. Subjects were adept at the task, showing precise and graded modulations of visual attention for subtle target changes and performing better and faster when the cue was more reliable [J. P. Mayo, J. H. R. Maunsell, J. Neurosci. 36, 5353 (2016)]. However, over tens of thousands of microsaccades, we found no difference in microsaccade direction between cued locations when cue variability was high nor between hit and miss trials. Instead, microsaccades were made toward the midpoint of the two target locations, not toward individual targets. Our results suggest that the direction of microsaccades should be interpreted with caution and may not be a reliable measure of covert spatial attention in more complex viewing conditions.

Microsaccades are directed towards the midpoint between targets in a variably cued attention task

Reliable, non-invasive biomarkers that reveal the internal state of a subject are an invaluable tool for neurological diagnoses. Small fixational eye movements, called microsaccades, are a candidate biomarker thought to reflect a subject's focus of attention (1, 2). The linkage between the direction of microsaccades and attention has mainly been demonstrated using explicit and unambiguous attentional cues. However, the natural world is seldom predictable and rarely provides unambiguous information. Thus, a useful biomarker must be robust to such changes in environmental statistics. To determine how well microsaccades reveal visual-spatial attention across behavioral contexts, we analyzed these fixational eye movements in monkeys performing a conventional change detection task. The task included two stimulus locations and variable cue validities across blocks of trials. Subjects were adept at the task, showing precise and graded modulations of visual attention for subtle target changes and performing better and faster when the cue was more reliable (3). However, over tens of thousands of microsaccades, we found no difference in microsaccade direction between cued locations when cue variability was high nor between hit and miss trials. Instead, microsaccades were made towards the midpoint of the two target locations, not towards individual targets. Our results suggest that the direction of microsaccades should be interpreted with caution and may not be a reliable measure of covert spatial attention in more complex viewing conditions.

Significance Statement

Small fixational eye movements called microsaccades are thought to "point" towards a location that is being attended in the visual periphery. This phenomenon has largely been studied using visual cues that unambiguously indicate the location of the upcoming stimulus change. Because the natural world is rarely unambiguous, we studied the relationship between microsaccade direction and spatial attention using less reliable cues. We found that monkeys' microsaccade directions in a standard visuospatial attention task did not indicate the animals' focus of attention, despite behavioral and neuronal evidence of spatial attention. Instead, microsaccades were made towards the midpoint between the target locations in both animals, suggesting a more complex relationship between microsaccades and attention in naturalistic settings.

Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish

Understanding how neural populations encode sensory stimuli remains a central problem in neuroscience. Here we performed multi-unit recordings from sensory neural populations in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus in response to stimuli located at different positions along the rostro-caudal axis. Our results reveal that the spatial dependence of correlated activity along receptive fields can help mitigate the deleterious effects that these correlations would otherwise have if they were spatially independent. Moreover, using mathematical modeling, we show that experimentally observed heterogeneities in the receptive fields of neurons help optimize information transmission as to object location. Taken together, our results have important implications for understanding how sensory neurons whose receptive fields display antagonistic center-surround organization encode location. Important similarities between the electrosensory system and other sensory systems suggest that our results will be applicable elsewhere.

Independent response modulation of visual cortical neurons by attentional and behavioral states

Sensory processing is influenced by cognitive and behavioral states, but how these states interact to modulate responses of individual neurons is unknown. We trained mice in a visual discrimination task wherein they attended to different locations within a hemifield while running or sitting still, enabling us to examine how visual responses are modulated by spatial attention and running behavior. We found that spatial attention improved discrimination performance and strengthened visual responses of excitatory neurons in the primary visual cortex whose receptive fields overlapped with the attended location. Although individual neurons were modulated by both spatial attention and running, the magnitudes of these influences were not correlated. While running-dependent modulation was stable across days, attentional modulation was dynamic, influencing individual neurons to different degrees after repeated changes in attentional states. Thus, despite similar effects on neural responses, spatial attention and running act independently with different dynamics, implying separable mechanisms for their implementation.

Decoding of attentional state using local field potentials

We review recent efforts to decode visual spatial attention from different types of brain signals, such as spikes and local field potentials (LFPs). Combining signals from more electrodes improves decoding, but the pattern of improvement varies considerably depending on the signal as well as the task (for example, decoding of sensory stimulus/motor intention versus location of attention). We argue that this pattern of results conveys important information not only about the usefulness of a particular brain signal for decoding attention, but also about the spatial scale over which attention operates in the brain. The spatial scale, in turn, likely depends on the extent of underlying mechanisms such as normalization, gain control via excitation-inhibition interactions, and neuromodulatory regulation of attention.

Neuronal correlates of selective attention and effort in visual area V4 are invariant of motivational context

Task demands can differentially engage two fundamental attention components: selectivity (spatial bias) and effort (total nonselective attentional intensity). The relative contributions and interactions of these components in modulating neuronal signals remain unknown. We recorded V4 neurons while monkeys' spatially selective attention and effort were independently controlled by adjusting either task difficulty or reward size at two locations. Neurons were robustly modulated by either selective attention or effort. Notably, increasing overall effort to improve performance at a distant site reduced neuronal responses even when performance was unchanged for receptive field stimuli. This interaction between attentional selectivity and effort was evident in single-trial spiking and can be explained by divisive normalization of spatially distributed behavioral performance at the single-neuron level. Changing motivation using task difficulty or reward produced indistinguishable effects. These results provide a cellular-level mechanism of how attention components integrate to modulate sensory processing in different motivational contexts.

Spike-Gamma Phase Relationship in the Visual Cortex

Gamma oscillations (30-70 Hz) have been hypothesized to play a role in cortical function. Most of the proposed mechanisms involve rhythmic modulation of neuronal excitability at gamma frequencies, leading to modulation of spike timing relative to the rhythm. I first show that the gamma band could be more privileged than other frequencies in observing spike-field interactions even in the absence of genuine gamma rhythmicity and discuss several biases in spike-gamma phase estimation. I then discuss the expected spike-gamma phase according to several hypotheses. Inconsistent with the phase-coding hypothesis (but not with others), the spike-gamma phase does not change with changes in stimulus intensity or attentional state, with spikes preferentially occurring 2-4 ms before the trough, but with substantial variability. However, this phase relationship is expected even when gamma is a byproduct of excitatory-inhibitory interactions. Given that gamma occurs in short bursts, I argue that the debate over the role of gamma is a matter of semantics. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A general decoding strategy explains the relationship between behavior and correlated variability

Improvements in perception are frequently accompanied by decreases in correlated variability in sensory cortex. This relationship is puzzling because overall changes in correlated variability should minimally affect optimal information coding. We hypothesize that this relationship arises because instead of using optimal strategies for decoding the specific stimuli at hand, observers prioritize generality: a single set of neuronal weights to decode any stimuli. We tested this using a combination of multineuron recordings in the visual cortex of behaving rhesus monkeys and a cortical circuit model. We found that general decoders optimized for broad rather than narrow sets of visual stimuli better matched the animals’ decoding strategy, and that their performance was more related to the magnitude of correlated variability. In conclusion, the inverse relationship between perceptual performance and correlated variability can be explained by observers using a general decoding strategy, capable of decoding neuronal responses to the variety of stimuli encountered in natural vision.

Attention improves information flow between neuronal populations without changing the communication subspace

Visual attention allows observers to change the influence of different parts of a visual scene on their behavior, suggesting that information can be flexibly shared between visual cortex and neurons involved in decision making. We investigated the neural substrate of flexible information routing by analyzing the activity of populations of visual neurons in the medial temporal area (MT) and oculo-motor neurons in the superior colliculus (SC) while rhesus monkeys switched spatial attention. We demonstrated that attention increases the efficacy of visuomotor communication: trial-to-trial variability in SC population activity could be better predicted by the activity of the MT population (and vice versa) when attention was directed toward their joint receptive fields. Surprisingly, this improvement in prediction was not explained by changes in the dimensionality of the shared subspace or in the magnitude of local or shared pairwise noise correlations. These results lay a foundation for future theoretical and experimental studies into how visual attention can flexibly change information flow between sensory and decision neurons.

Rhythmic sampling revisited: Experimental paradigms and neural mechanisms

Sampling of information is thought to be an important aspect of explorative behaviour. Evidence for it has been gained in behavioural assessments of a variety of overt and covert cognitive domains, including sensation, attention, memory, eye movements and dexterity. A common aspect across many findings is that sampling tends to exhibit a rhythmicity at low frequencies (theta, 4-8 Hz; alpha, 9-12 Hz). Neurophysiological investigations in a wide range of species, including rodents, non-human primates and humans have demonstrated the presence of sampling related neural oscillations in a number of brain areas ranging from early sensory cortex, hippocampus to high-level cognitive areas. However, to assess whether rhythmic sampling represents a general aspect of exploratory behaviour one must critically evaluate the task parameters, and their potential link with neural oscillations. Here we focus on sampling during attentive vision to present an overview on the experimental conditions that are used to investigate rhythmic sampling and associated oscillatory brain activity in this domain. This review aims to (1) provide guidelines to efficiently quantify behavioural rhythms, (2) compare results from human and non-human primate studies and (3) argue that the underlying neural mechanisms of sampling can co-occur in both sensory and high-level areas.

Revisiting Persistent Neuronal Activity During Covert Spatial Attention

Persistent activity has been observed in the prefrontal cortex (PFC), in particular during the delay periods of visual attention tasks. Classical approaches based on the average activity over multiple trials have revealed that such an activity encodes the information about the attentional instruction provided in such tasks. However, single-trial approaches have shown that activity in this area is rather sparse than persistent and highly heterogeneous not only within the trials but also between the different trials. Thus, this observation raised the question of how persistent the actually persistent attention-related prefrontal activity is and how it contributes to spatial attention. In this paper, we review recent evidence of precisely deconstructing the persistence of the neural activity in the PFC in the context of attention orienting. The inclusion of machine-learning methods for decoding the information reveals that attention orienting is a highly dynamic process, possessing intrinsic oscillatory dynamics working at multiple timescales spanning from milliseconds to minutes. Dimensionality reduction methods further show that this persistent activity dynamically incorporates multiple sources of information. This novel framework reflects a high complexity in the neural representation of the attention-related information in the PFC, and how its computational organization predicts behavior.

Decoding of Attentional State Using High-Frequency Local Field Potential Is As Accurate As Using Spikes

Local field potentials (LFPs) in visual cortex are reliably modulated when the subject's focus of attention is cued into versus out of the receptive field of the recorded sites, similar to modulation of spikes. However, human psychophysics studies have used an additional attention condition, neutral cueing, for decades. The effect of neutral cueing on spikes was examined recently and found to be intermediate between cued and uncued conditions. However, whether LFPs are also precise enough to represent graded states of attention is unknown. We found in rhesus monkeys that LFPs during neutral cueing were also intermediate between cued and uncued conditions. For a single electrode, attention was more discriminable using high frequency (>30 Hz) LFP power than spikes, which is expected because LFP represents a population signal and therefore is expected to be less noisy than spikes. However, previous studies have shown that when multiple electrodes are used, spikes can outperform LFPs. Surprisingly, in our study, spikes did not outperform LFPs when discriminability was computed using multiple electrodes, even though the LFP activity was highly correlated across electrodes compared with spikes. These results constrain the spatial scale over which attention operates and highlight the usefulness of LFPs in studying attention.

The neural bases of spatial attention and perceptual rhythms

Attentional processes allow the brain to overcome its processing capacities limitations by enhancing relevant visual information and suppressing irrelevant information. Thus attention plays a critical role, shaping our perception of the world. Several models have been proposed to describe the neuronal bases of attention and its mechanistic underlyings. Recent electrophysiological evidence show that attentional processes rely on oscillatory brain activities that correlate with rhythmic changes in cognitive performance. In the present review, we first take a historical perspective on how attention is viewed, from the initial spotlight theory of attention to the recent dynamic view of attention selection and we review their supporting psychophysical evidence. Based on recent prefrontal electrophysiological evidence, we refine the most recent models of attention sampling by proposing a rhythmic and continuous model of attentional sampling. In particular, we show that attention involves a continuous exploration of space, shifting within and across visual hemifield at specific alpha and theta rhythms, independently of the current attentional load. In addition, we show that this prefrontal attentional spotlight implements conjointly selection and suppression mechanisms, and is captured by salient incoming items. Last, we argue that this attention spotlight implements a highly flexible alternation of attentional exploration and exploitation epochs, depending on ongoing task contingencies. In a last part, we review the local and network oscillatory mechanisms that correlate with rhythmic attentional sampling, describing multiple rhythmic generators and complex network interactions.

When Conflict Cannot be Avoided: Relative Contributions of Early Selection and Frontal Executive Control in Mitigating Stroop Conflict

When viewing familiar stimuli (e.g., common words), processing is highly automatized such that it can interfere with the processing of incompatible sensory information. At least two mechanisms may help mitigate this interference. Early selection accounts posit that attentional processes filter out distracting sensory information to avoid conflict. Alternatively, late selection accounts hold that all sensory inputs receive full semantic analysis and that frontal executive mechanisms are recruited to resolve conflict. To test how these mechanisms operate to overcome conflict induced by highly automatized processing, we developed a novel version of the color-word Stroop task, where targets and distractors were simultaneously flickered at different frequencies. We measured the quality of early sensory processing by assessing the amplitude of steady-state visually evoked potentials (SSVEPs) elicited by targets and distractors. We also indexed frontal executive processes by assessing changes in frontal theta oscillations induced by color-word incongruency. We found that target- and distractor-related SSVEPs were not modulated by changes in the level of conflict whereas frontal theta activity increased on high compared to low conflict trials. These results suggest that frontal executive processes play a more dominant role in mitigating cognitive interference driven by the automatic tendency to process highly familiar stimuli.

Activity in LIP, But not V4, Matches Performance When Attention is Spread

The enhancement of neuronal responses in many visual areas while animals perform spatial attention tasks has widely been thought to be the neural correlate of visual attention, but it is unclear whether the presence or absence of this modulation contributes to our striking inability to notice changes in change blindness examples. We asked whether neuronal responses in visual area V4 and the lateral intraparietal area (LIP) in posterior parietal cortex could explain the limited ability of subjects to attend multiple items in a display. We trained animals to perform a change detection task in which they had to compare 2 arrays of stimuli separated briefly in time and found that each animal's performance decreased as function of set-size. Neuronal discriminability in V4 was consistent across set-sizes, but decreased for higher set-sizes in LIP. The introduction of a reward bias produced attentional enhancement in V4, but this could not explain the vast improvement in performance, whereas the enhancement in LIP responses could. We suggest that behavioral set-size effects and the marked improvement in performance with focused attention may not be related to response enhancement in V4 but, instead, may occur in or on the way to LIP.

Simultaneous multi-area recordings suggest that attention improves performance by reshaping stimulus representations

Visual attention dramatically improves individuals' ability to see and modulates the responses of neurons in every known visual and oculomotor area, but whether such modulations can account for perceptual improvements is unclear. We measured the relationship between populations of visual neurons, oculomotor neurons and behavior during detection and discrimination tasks. We found that neither of the two prominent hypothesized neuronal mechanisms underlying attention (which concern changes in information coding and the way sensory information is read out) provide a satisfying account of the observed behavioral improvements. Instead, our results are more consistent with the hypothesis that attention reshapes the representation of attended stimuli to more effectively influence behavior. Our results suggest a path toward understanding the neural underpinnings of perception and cognition in health and disease by analyzing neuronal responses in ways that are constrained by behavior and interactions between brain areas.

Modulations of emotional attention and spatial attention on human visual cortical activities

Background: Spatial attention could enhance the neural activities of attended locations in human visual cortex. As a salient stimulus, emotional image could enhance the responses in amygdala and visual areas. However, few studies examined the interaction of the attentional effects induced by emotional stimuli and spatial cues on the neural responses in visual areas.

Methods: In the present study, we used functional magnetic resonance imaging (fMRI) to examine the combined and separated effects of emotional image and spatial cue on the activities in human visual areas. A revised Posner cueing paradigm was utilized. Each participant viewed a fearful image and a peaceful image simultaneously in left and right visual fields. A spatial cue of two dots was then presented in one of the image positions. In this manner, the attentional effects for emotional image and spatial cue could be isolated and combined.

Results: The results showed that spatial cue enhanced the responses in V4, intraparietal sulcus (IPS) and lateral occipital area (LO), while emotional image could enhance the responses in V3, V4 and LO. Importantly, no significant interactions were found in any of the visual areas.

Conclusion: Our results indicate that the two kinds of attentional modulation might not be affected by each other. These findings shed light on the neural mechanism of the emotional attention.

Local and Global Influences of Visual Spatial Selection and Locomotion in Mouse Primary Visual Cortex

Sensory selection and movement locally and globally modulate neural responses in seemingly similar ways. For example, locomotion enhances visual responses in mouse primary visual cortex (V1), resembling the effects of spatial attention on primate visual cortical activity. However, interactions between these local and global mechanisms and the resulting effects on perceptual behavior remain largely unknown. Here, we describe a novel mouse visual spatial selection task in which animals either monitor one of two locations for a contrast change ("selective mice") or monitor both ("non-selective mice") and can run at will. Selective mice perform well only when their selected stimulus changes, giving rise to local electrophysiological changes in the corresponding hemisphere of V1 including decreased noise correlations and increased visual information. Non-selective mice perform well when either stimulus changes, giving rise to global changes across both hemispheres of V1. During locomotion, selective mice have worse behavioral performance, increased noise correlations in V1, and decreased visual information, while non-selective mice have decreased noise correlations in V1 but no change in performance or visual information. Our findings demonstrate that mice can locally or globally enhance visual information, but the interaction of the global effect of locomotion with local selection impairs behavioral performance. Moving forward, this mouse model will facilitate future studies of local and global sensory modulatory mechanisms and their effects on behavior.

Distinct population codes for attention in the absence and presence of visual stimulation

Visual neurons respond more vigorously to an attended stimulus than an unattended one. How the brain prepares for response gain in anticipation of that stimulus is not well understood. One prominent proposal is that anticipation is characterized by gain-like modulations of spontaneous activity similar to gains in stimulus responses. Here we test an alternative idea: anticipation is characterized by a mixture of both increases and decreases of spontaneous firing rates. Such a strategy would be adaptive as it supports a simple linear scheme for disentangling internal, modulatory signals from external, sensory inputs. We recorded populations of V4 neurons in monkeys performing an attention task, and found that attention states are signaled by different mixtures of neurons across the population in the presence or absence of a stimulus. Our findings support a move from a stimulation-invariant account of anticipation towards a richer view of attentional modulation in a diverse neuronal population.

Attention affects stimulus response gain, but its impact without sensory drive is less known. Here, the authors show that attention is coded diversely in a population and is distinct between unstimulated and stimulated contexts, providing a contrast to normalized gain models of attention.

How biological attention mechanisms improve task performance in a large-scale visual system model

How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.

Having More Choices Changes How Human Observers Weight Stable Sensory Evidence

Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds.SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.

Theta Rhythmic Neuronal Activity and Reaction Times Arising from Cortical Receptive Field Interactions during Distributed Attention

Growing evidence suggests that distributed spatial attention may invoke theta (3-9 Hz) rhythmic sampling processes. The neuronal basis of such attentional sampling is, however, not fully understood. Here we show using array recordings in visual cortical area V4 of two awake macaques that presenting separate visual stimuli to the excitatory center and suppressive surround of neuronal receptive fields (RFs) elicits rhythmic multi-unit activity (MUA) at 3-6 Hz. This neuronal rhythm did not depend on small fixational eye movements. In the context of a distributed spatial attention task, during which the monkeys detected a spatially and temporally uncertain target, reaction times (RTs) exhibited similar rhythmic fluctuations. RTs were fast or slow depending on the target occurrence during high or low MUA, resulting in rhythmic MUA-RT cross-correlations at theta frequencies. These findings show that theta rhythmic neuronal activity can arise from competitive RF interactions and that this rhythm may result in rhythmic RTs potentially subserving attentional sampling.

Attentional fluctuations induce shared variability in macaque primary visual cortex

Variability in neuronal responses to identical stimuli is frequently correlated across a population. Attention is thought to reduce these correlations by suppressing noisy inputs shared by the population. However, even with precise control of the visual stimulus, the subject’s attentional state varies across trials. While these state fluctuations are bound to induce some degree of correlated variability, it is currently unknown how strong their effect is, as previous studies generally do not dissociate changes in attentional strength from changes in attentional state variability. We designed a novel paradigm that does so and find both a pronounced effect of attentional fluctuations on correlated variability at long timescales and attention-dependent reductions in correlations at short timescales. These effects predominate in layers 2/3, as expected from a feedback signal such as attention. Thus, significant portions of correlated variability can be attributed to fluctuations in internally generated signals, like attention, rather than noise.

Attention reduces correlated variability in population activity, however the effect of fluctuations in attentional state has not been studied. Here, the authors report in a novel visual task that fluctuations in attentional allocation have a pronounced effect on correlated variability at longer timescales.

Cognition as a Window into Neuronal Population Space

Understanding how cognitive processes affect the responses of sensory neurons may clarify the relationship between neuronal population activity and behavior. However, tools for analyzing neuronal activity have not kept up with technological advances in recording from large neuronal populations. Here, we describe prevalent hypotheses of how cognitive processes affect sensory neurons, driven largely by a model based on the activity of single neurons or pools of neurons as the units of computation. We then use simple simulations to expand this model to a new conceptual framework that focuses on subspaces of population activity as the relevant units of computation, uses comparisons between brain areas or to behavior to guide analyses of these subspaces, and suggests that population activity is optimized to decode the large variety of stimuli and tasks that animals encounter in natural behavior. This framework provides new ways of understanding the ever-growing quantity of recorded population activity data.

Visual Selective Attention in Mice

Visual selective attention is a fundamental cognitive ability that allows us to process relevant visual stimuli while ignoring irrelevant distracters and has been extensively studied in human and non-human primate subjects. Mice have emerged as a powerful animal model for studying aspects of the visual system but have not yet been shown to exhibit visual selective attention. Differences in the organization of the visual systems of primates and mice raise the possibility that selective visual attention might not be present in mice, at least not in the forms that are well established in primates. Here, we tested for selective visual attention in mice by using three behavioral paradigms adapted from classic studies of attention. In a Posner-style cueing task, a spatial cue indicated the probable location of the relevant visual event, and we found that accuracy was higher and reaction times were shorter on validly cued trials. In a cue versus no-cue task, an informative spatial cue was provided on half the trials, and mice had higher accuracy and shorter reaction times with spatial cues and also lower detection thresholds measured from psychometric curves. In a filter task, the spatial cue indicated the location of the relevant visual event, and we found that mice could be trained to ignore irrelevant but otherwise identical visual events at uncued locations. Together, these results demonstrate that mice exhibit visual selective attention, paving the way to use classic attention paradigms in mice to study the genetic and neuronal circuit mechanisms of selective attention.

Evidence for unlimited capacity processing of simple features in visual cortex

Performance in many visual tasks is impaired when observers attempt to divide spatial attention across multiple visual field locations. Correspondingly, neuronal response magnitudes in visual cortex are often reduced during divided compared with focused spatial attention. This suggests that early visual cortex is the site of capacity limits, where finite processing resources must be divided among attended stimuli. However, behavioral research demonstrates that not all visual tasks suffer such capacity limits: The costs of divided attention are minimal when the task and stimulus are simple, such as when searching for a target defined by orientation or contrast. To date, however, every neuroimaging study of divided attention has used more complex tasks and found large reductions in response magnitude. We bridged that gap by using functional magnetic resonance imaging to measure responses in the human visual cortex during simple feature detection. The first experiment used a visual search task: Observers detected a low-contrast Gabor patch within one or four potentially relevant locations. The second experiment used a dual-task design, in which observers made independent judgments of Gabor presence in patches of dynamic noise at two locations. In both experiments, blood-oxygen level-dependent (BOLD) signals in the retinotopic cortex were significantly lower for ignored than attended stimuli. However, when observers divided attention between multiple stimuli, BOLD signals were not reliably reduced and behavioral performance was unimpaired. These results suggest that processing of simple features in early visual cortex has unlimited capacity.

Changes in perceptual sensitivity related to spatial cues depends on subcortical activity

Spatial cues allow animals to selectively attend to relevant visual stimuli while ignoring distracters. This process depends on a distributed neuronal network, and an important current challenge is to understand the functional contributions made by individual brain regions within this network and how these contributions interact. Recent findings point to a possible anatomical segregation, with cortical and subcortical brain regions contributing to different functional components of selective attention. Cortical areas, especially visual cortex, may be responsible for implementing changes in perceptual sensitivity by changing the signal-to-noise ratio, whereas other regions, such as the superior colliculus, may be involved in processes that influence selection between competing stimuli without regulating perceptual sensitivity. Such a segregation of function would predict that when activity in the superior colliculus is suppressed by reversible inactivation, animals should still show changes in perceptual sensitivity mediated by the intact cortical circuits. Contrary to this prediction, here we report that inactivation of the primate superior colliculus eliminates the changes in perceptual sensitivity made possible by spatial cues. These findings demonstrate changes in perceptual sensitivity depend not only on neuronal activity in cortex but also require interaction with signals from the superior colliculus.