Neuronal Mechanisms of Visual Attention

Covert Attention Increases the Gain of Stimulus-Evoked Population Codes

Covert spatial attention has a variety of effects on the responses of individual neurons. However, relatively little is known about the net effect of these changes on sensory population codes, even though perception ultimately depends on population activity. Here, we measured the EEG in human observers (male and female), and isolated stimulus-evoked activity that was phase-locked to the onset of attended and ignored visual stimuli. Using an encoding model, we reconstructed spatially selective population tuning functions from the pattern of stimulus-evoked activity across the scalp. Our EEG-based approach allowed us to measure very early visually evoked responses occurring ∼100 ms after stimulus onset. In Experiment 1, we found that covert attention increased the amplitude of spatially tuned population responses at this early stage of sensory processing. In Experiment 2, we parametrically varied stimulus contrast to test how this effect scaled with stimulus contrast. We found that the effect of attention on the amplitude of spatially tuned responses increased with stimulus contrast, and was well described by an increase in response gain (i.e., a multiplicative scaling of the population response). Together, our results show that attention increases the gain of spatial population codes during the first wave of visual processing.SIGNIFICANCE STATEMENT We know relatively little about how attention improves population codes, even though perception is thought to critically depend on population activity. In this study, we used an encoding-model approach to test how attention modulates the spatial tuning of stimulus-evoked population responses measured with EEG. We found that attention multiplicatively scales the amplitude of spatially tuned population responses. Furthermore, this effect was present within 100 ms of stimulus onset. Thus, our results show that attention improves spatial population codes by increasing their gain at this early stage of processing.

How developmental neuroscience can help address the problem of child poverty

Nearly 1 in 5 children in the United States lives in a household whose income is below the official federal poverty line, and more than 40% of children live in poor or near-poor households. Research on the effects of poverty on children's development has been a focus of study for many decades and is now increasing as we accumulate more evidence about the implications of poverty. The American Academy of Pediatrics recently added "Poverty and Child Health" to its Agenda for Children to recognize what has now been established as broad and enduring effects of poverty on child development. A recent addition to the field has been the application of neuroscience-based methods. Various techniques including neuroimaging, neuroendocrinology, cognitive psychophysiology, and epigenetics are beginning to document ways in which early experiences of living in poverty affect infant brain development. We discuss whether there are truly worthwhile reasons for adding neuroscience and related biological methods to study child poverty, and how might these perspectives help guide developmentally based and targeted interventions and policies for these children and their families.

Alpha oscillations do not implement gain control in early visual cortex but rather gating in parieto-occipital regions

Spatial attention provides a mechanism for, respectively, enhancing relevant and suppressing irrelevant information. While it is well established that attention modulates oscillations in the alpha band, it remains unclear if alpha oscillations are involved in directly modulating the neuronal excitability associated with the allocation of spatial attention. In this study, in humans, we utilized a novel broadband frequency (60-70 Hz) tagging paradigm to quantify neuronal excitability in relation to alpha oscillations in a spatial attention paradigm. We used magnetoencephalography to characterize ongoing brain activity as it allows for localizing the sources of both the alpha and frequency tagging responses. We found that attentional modulation of alpha power and the frequency tagging response are uncorrelated over trials. Importantly, the neuronal sources of the tagging response were localized in early visual cortex (V1) whereas the sources of the alpha activity were identified around parieto-occipital sulcus. Moreover, we found that attention did not modulate the latency of the frequency tagged responses. Our findings point to alpha band oscillations serving a downstream gating role rather than implementing gain control of excitability in early visual regions.

Low rank mechanisms underlying flexible visual representations

Neuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex have heterogeneous dependence on stimulus properties (e.g., contrast), processes that affect all stages of visual processing (e.g., adaptation), and cognitive processes (e.g., attention or task switching). Understanding whether these processes affect similar neuronal populations and whether they have similar effects on entire populations can provide insight into whether they utilize analogous mechanisms. In particular, it has recently been demonstrated that attention has low rank effects on the covariability of populations of visual neurons, which impacts perception and strongly constrains mechanistic models. We hypothesized that measuring changes in population covariability associated with other sensory and cognitive processes could clarify whether they utilize similar mechanisms or computations. Our experimental design included measurements in multiple visual areas using four distinct sensory and cognitive processes. We found that contrast, adaptation, attention, and task switching affect the variability of responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit may use similar mechanisms to perform many forms of modulation and likely reflects a general principle that applies to a wide range of brain areas and sensory, cognitive, and motor processes.

Slow Drift of Neural Activity as a Signature of Impulsivity in Macaque Visual and Prefrontal Cortex

An animal's decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This state embodies multiple cognitive factors, such as arousal and fatigue, but it is unclear how these factors influence the neural processes that encode sensory stimuli and form a decision. We discovered that, unprompted by task conditions, animals slowly shifted their likelihood of detecting stimulus changes over the timescale of tens of minutes. Neural population activity from visual area V4, as well as from prefrontal cortex, slowly drifted together with these behavioral fluctuations. We found that this slow drift, rather than altering the encoding of the sensory stimulus, acted as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in population activity across multiple brain areas and sheds further light on how internal states contribute to the decision-making process.

Separable Influences of Reward on Visual Processing and Choice

Primate vision is characterized by constant, sequential processing and selection of visual targets to fixate. Although expected reward is known to influence both processing and selection of visual targets, similarities and differences between these effects remain unclear mainly because they have been measured in separate tasks. Using a novel paradigm, we simultaneously measured the effects of reward outcomes and expected reward on target selection and sensitivity to visual motion in monkeys. Monkeys freely chose between two visual targets and received a juice reward with varying probability for eye movements made to either of them. Targets were stationary apertures of drifting gratings, causing the end points of eye movements to these targets to be systematically biased in the direction of motion. We used this motion-induced bias as a measure of sensitivity to visual motion on each trial. We then performed different analyses to explore effects of objective and subjective reward values on choice and sensitivity to visual motion to find similarities and differences between reward effects on these two processes. Specifically, we used different reinforcement learning models to fit choice behavior and estimate subjective reward values based on the integration of reward outcomes over multiple trials. Moreover, to compare the effects of subjective reward value on choice and sensitivity to motion directly, we considered correlations between each of these variables and integrated reward outcomes on a wide range of timescales. We found that, in addition to choice, sensitivity to visual motion was also influenced by subjective reward value, although the motion was irrelevant for receiving reward. Unlike choice, however, sensitivity to visual motion was not affected by objective measures of reward value. Moreover, choice was determined by the difference in subjective reward values of the two options, whereas sensitivity to motion was influenced by the sum of values. Finally, models that best predicted visual processing and choice used sets of estimated reward values based on different types of reward integration and timescales. Together, our results demonstrate separable influences of reward on visual processing and choice, and point to the presence of multiple brain circuits for the integration of reward outcomes.

Extinguishing Exogenous Attention via Transcranial Magnetic Stimulation

Orienting covert exogenous (involuntary) attention to a target location improves performance in many visual tasks [1, 2]. It is unknown whether early visual cortical areas are necessary for this improvement. To establish a causal link between these areas and attentional modulations, we used transcranial magnetic stimulation (TMS) to briefly alter cortical excitability and determine whether early visual areas mediate the effect of exogenous attention on performance. Observers performed an orientation discrimination task. After a peripheral valid, neutral, or invalid cue, two cortically magnified gratings were presented, one in the stimulated region and the other in the symmetric region in the opposite hemifield. Observers received two successive TMS pulses around their occipital pole while the stimuli were presented. Shortly after, a response cue indicated the grating whose orientation observers had to discriminate. The response cue either matched-target stimulated-or did not match-distractor stimulated-the stimulated side. Grating contrast was varied to measure contrast response functions (CRF) for all combinations of attention and TMS conditions. When the distractor was stimulated, exogenous attention yielded response gain-performance benefits in the valid-cue condition and costs in the invalid-cue condition compared with the neutral condition at the high contrast levels. Crucially, when the target was stimulated, this response gain was eliminated. Therefore, TMS extinguished the effect of exogenous attention. These results establish a causal link between early visual areas and the modulatory effect of exogenous attention on performance.

Selection history is relative

Visual attention can be tuned to specific features to aid in visual search. The way in which these search strategies are established and maintained is flexible, reflecting goal-directed attentional control, but can exert a persistent effect on selection that remains even when these strategies are no longer advantageous, reflecting an attentional bias driven by selection history. Apart from feature-specific search, recent studies have shown that attention can be tuned to target-nontarget relationships. Here we tested whether a relational search strategy continues to bias attention in a subsequent task, where the relationally better color and former target color both serve as distractors (Experiment 1) or as potential targets (Experiment 2). We demonstrate that a relational bias can persist in a subsequent task in which color serves as a task-irrelevant feature, both impairing and facilitating visual search performance. Our findings extend our understanding of the relational account of attentional control and the nature of selection history effects on attention.

Visual Functions of Primate Area V4

Area V4-the focus of this review-is a mid-level processing stage along the ventral visual pathway of the macaque monkey. V4 is extensively interconnected with other visual cortical areas along the ventral and dorsal visual streams, with frontal cortical areas, and with several subcortical structures. Thus, it is well poised to play a broad and integrative role in visual perception and recognition-the functional domain of the ventral pathway. Neurophysiological studies in monkeys engaged in passive fixation and behavioral tasks suggest that V4 responses are dictated by tuning in a high-dimensional stimulus space defined by form, texture, color, depth, and other attributes of visual stimuli. This high-dimensional tuning may underlie the development of object-based representations in the visual cortex that are critical for tracking, recognizing, and interacting with objects. Neurophysiological and lesion studies also suggest that V4 responses are important for guiding perceptual decisions and higher-order behavior.

Parallel Neural Multiprocessing with Gamma Frequency Latencies

The Poisson variability in cortical neural responses has been typically modeled using spike averaging techniques, such as trial averaging and rate coding, since such methods can produce reliable correlates of behavior. However, mechanisms that rely on counting spikes could be slow and inefficient and thus might not be useful in the brain for computations at timescales in the 10 millisecond range. This issue has motivated a search for alternative spike codes that take advantage of spike timing and has resulted in many studies that use synchronized neural networks for communication. Here we focus on recent studies that suggest that the gamma frequency may provide a reference that allows local spike phase representations that could result in much faster information transmission. We have developed a unified model (gamma spike multiplexing) that takes advantage of a single cycle of a cell's somatic gamma frequency to modulate the generation of its action potentials. An important consequence of this coding mechanism is that it allows multiple independent neural processes to run in parallel, thereby greatly increasing the processing capability of the cortex. System-level simulations and preliminary analysis of mouse cortical cell data are presented as support for the proposed theoretical model.

Computational and neurophysiological principles underlying auditory perceptual decisions

A fundamental scientific goal in auditory neuroscience is identifying what mechanisms allow the brain to transform an unlabeled mixture of auditory stimuli into distinct perceptual representations. This transformation is accomplished by a complex interaction of multiple neurocomputational processes, including Gestalt grouping mechanisms, categorization, attention, and perceptual decision-making. Despite a great deal of scientific energy devoted to understanding these principles of hearing, we still do not understand either how auditory perception arises from neural activity or the causal relationship between neural activity and auditory perception. Here, we review the contributions of cortical and subcortical regions to auditory perceptual decisions with an emphasis on those studies that simultaneously measure behavior and neural activity. We also put forth challenges to the field that must be faced if we are to further our understanding of the relationship between neural activity and auditory perception.

Coding Perceptual Decisions: From Single Units to Emergent Signaling Properties in Cortical Circuits

Spiking activity in single neurons of the primate visual cortex has been tightly linked to perceptual decisions. Any mechanism that reads out these perceptual signals to support behavior must respect the underlying neuroanatomy that shapes the functional properties of sensory neurons. Spatial distribution and timing of inputs to the next processing levels are critical, as conjoint activity of precursor neurons increases the spiking rate of downstream neurons and ultimately drives behavior. I set out how correlated activity might coalesce into a micropool of task-sensitive neurons signaling a particular percept to determine perceptual decision signals locally and for flexible interarea transmission depending on the task context. As data from more and more neurons and their complex interactions are analyzed, the space of computational mechanisms must be constrained based on what is plausible within neurobiological limits. This review outlines experiments to test the new perspectives offered by these extended methods.

Nicotinic Receptor Subunit Distribution in Auditory Cortex: Impact of Aging on Receptor Number and Function

The presence of novel or degraded communication sounds likely results in activation of basal forebrain cholinergic neurons increasing release of ACh onto presynaptic and postsynaptic nAChRs in primary auditory cortex (A1). nAChR subtypes include high-affinity heteromeric nAChRs commonly composed of α4 and β2 subunits and low-affinity homomeric nAChRs composed of α7 subunits. In young male FBN rats, we detail the following: (1) the distribution/expression of nAChR subunit transcripts in excitatory (VGluT1) and inhibitory (VGAT) neurons across A1 layers; (2) heteromeric nAChR binding across A1 layers; and (3) nAChR excitability in A1 layer (L) 5 cells. In aged rats, we detailed the impact of aging on A1 nAChR subunit expression across layers, heteromeric nAChR receptor binding, and nAChR excitability of A1 L5 cells. A majority of A1 cells coexpressed transcripts for β2 and α4 with or without α7, while dispersed subpopulations expressed β2 and α7 or α7 alone. nAChR subunit transcripts were expressed in young excitatory and inhibitory neurons across L2-L6. Transcript abundance varied across layers, and was highest for β2 and α4. Significant age-related decreases in nAChR subunit transcript expression (message) and receptor binding (protein) were observed in L2-6, most pronounced in infragranular layers. In vitro patch-clamp recordings from L5B pyramidal output neurons showed age-related nAChR subunit-selective reductions in postsynaptic responses to ACh. Age-related losses of nAChR subunits likely impact ways in which A1 neurons respond to ACh release. While the elderly require additional resources to disambiguate degraded speech codes, resources mediated by nAChRs may be compromised with aging.SIGNIFICANCE STATEMENT When attention is required, cholinergic basal forebrain neurons may trigger increased release of ACh onto auditory neurons in primary auditory cortex (A1). Laminar and phenotypic differences in neuronal nAChR expression determine ways in which A1 neurons respond to release of ACh in challenging acoustic environments. This study detailed the distribution and expression of nAChR subunit transcript and protein across A1 layers in young and aged rats. Results showed a differential distribution of nAChR subunits across A1 layers. Age-related decreases in transcript/protein expression were reflected in age-related subunit specific functional loss of nAChR signaling to ACh application in A1 layer 5. Together, these findings could reflect the age-related decline in selective attention observed in the elderly.

Attention amplifies neural representations of changes in sensory input at the expense of perceptual accuracy

Attention enhances the neural representations of behaviorally relevant stimuli, typically by a push-pull increase of the neuronal response gain to attended vs. unattended stimuli. This selectively improves perception and consequently behavioral performance. However, to enhance the detectability of stimulus changes, attention might also distort neural representations, compromising accurate stimulus representation. We test this hypothesis by recording neural responses in the visual cortex of rhesus monkeys during a motion direction change detection task. We find that attention indeed amplifies the neural representation of direction changes, beyond a similar effect of adaptation. We further show that humans overestimate such direction changes, providing a perceptual correlate of our neurophysiological observations. Our results demonstrate that attention distorts the neural representations of abrupt sensory changes and consequently perceptual accuracy. This likely represents an evolutionary adaptive mechanism that allows sensory systems to flexibly forgo accurate representation of stimulus features to improve the encoding of stimulus change.

Exogenous spatial attention shortens perceived depth

Although spatial attention has been found to alter the subjective appearance of visual stimuli in several perceptual dimensions, no research has explored whether exogenous spatial attention can affect depth perception, which is a fundamental dimension in perception that allows us to effectively interact with the environment. Here, we used an experimental paradigm adapted from Gobell and Carrasco (Psychological Science, 16[8], 644-651, 2005) to investigate this question. A peripheral cue preceding two line stimuli was used to direct exogenous attention to either location of the two lines. The two lines were separated by a certain relative disparity, and participants were asked to judge the perceived depth of two lines while attention was manipulated. We found that a farther stereoscopic depth at the attended location was perceived to be equally distant as a nearer depth at the unattended location. No such effect was found in a control experiment that employed a postcue paradigm, suggesting that our findings could not be attributed to response bias. Therefore, our study shows that exogenous spatial attention shortens perceived depth. The apparent change in stereoscopic depth may be regulated by a mechanism involving direct neural enhancement on those tuned to disparity, or be modulated by an attentional effect on apparent contrast. This finding shows that attention can change not only visual appearance but also the perceived spatial relation between an object and an observer.

Attention in Psychology, Neuroscience, and Machine Learning

Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, and learning. It has also recently been applied in several domains in machine learning. The relationship between the study of biological attention and its use as a tool to enhance artificial neural networks is not always clear. This review starts by providing an overview of how attention is conceptualized in the neuroscience and psychology literature. It then covers several use cases of attention in machine learning, indicating their biological counterparts where they exist. Finally, the ways in which artificial attention can be further inspired by biology for the production of complex and integrative systems is explored.

Exogenous attention facilitates perceptual learning in visual acuity to untrained stimulus locations and features

Visual perceptual learning (VPL) refers to the improvement in performance on a visual task due to practice. A hallmark of VPL is specificity, as improvements are often confined to the trained retinal locations or stimulus features. We have previously found that exogenous (involuntary, stimulus-driven) and endogenous (voluntary, goal-driven) spatial attention can facilitate the transfer of VPL across locations in orientation discrimination tasks mediated by contrast sensitivity. Here, we investigated whether exogenous spatial attention can facilitate such transfer in acuity tasks that have been associated with higher specificity. We trained observers for 3 days (days 2-4) in a Landolt acuity task (Experiment 1) or a Vernier hyperacuity task (Experiment 2), with either exogenous precues (attention group) or neutral precues (neutral group). Importantly, during pre-tests (day 1) and post-tests (day 5), all observers were tested with neutral precues; thus, groups differed only in their attentional allocation during training. For the Landolt acuity task, we found evidence of location transfer in both the neutral and attention groups, suggesting weak location specificity of VPL. For the Vernier hyperacuity task, we found evidence of location and feature specificity in the neutral group, and learning transfer in the attention group-similar improvement at trained and untrained locations and features. Our results reveal that, when there is specificity in a perceptual acuity task, exogenous spatial attention can overcome that specificity and facilitate learning transfer to both untrained locations and features simultaneously with the same training. Thus, in addition to improving performance, exogenous attention generalizes perceptual learning across locations and features.

Studying the visual brain in its natural rhythm

How the brain fluidly orchestrates visual behavior is a central question in cognitive neuroscience. Researchers studying neural responses in humans and nonhuman primates have mapped out visual response profiles and cognitive modulation in a large number of brain areas, most often using pared down stimuli and highly controlled behavioral paradigms. The historical emphasis on reductionism has placed most studies at one pole of an inherent trade-off between strictly controlled experimental variables and open designs that monitor the brain during its natural modes of operation. This bias toward simplified experiments has strongly shaped the field of visual neuroscience, with little guarantee that the principles and concepts established within that framework will apply more generally. In recent years, a growing number of studies have begun to relax strict experimental control with the aim of understanding how the brain responds under more naturalistic conditions. In this article, we survey research that has explicitly embraced the complexity and rhythm of natural vision. We focus on those studies most pertinent to understanding high-level visual specializations in brains of humans and nonhuman primates. We conclude that representationalist concepts borne from conventional visual experiments fall short in their ability to capture the real-life visual operations undertaken by the brain. More naturalistic approaches, though fraught with experimental and analytic challenges, provide fertile ground for neuroscientists seeking new inroads to investigate how the brain supports core aspects of our daily visual experience.

Neuromodulation of Brain State and Behavior

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

How exogenous spatial attention affects visual representation

Orienting covert spatial attention to a target location enhances visual sensitivity and benefits performance in many visual tasks. How these attention-related improvements in performance affect the underlying visual representation of low-level visual features is not fully understood. Here we focus on characterizing how exogenous spatial attention affects the feature representations of orientation and spatial frequency. We asked observers to detect a vertical grating embedded in noise and performed psychophysical reverse correlation. Doing so allowed us to make comparisons with previous studies that utilized the same task and analysis to assess how endogenous attention and presaccadic modulations affect visual representations. We found that exogenous spatial attention improved performance and enhanced the gain of the target orientation without affecting orientation tuning width. Moreover, we found no change in spatial frequency tuning. We conclude that covert exogenous spatial attention alters performance by strictly boosting gain of orientation-selective filters, much like covert endogenous spatial attention.

Neural dynamics of the attentional blink revealed by encoding orientation selectivity during rapid visual presentation

The human brain is inherently limited in the information it can make consciously accessible. When people monitor a rapid stream of visual items for two targets, they typically fail to see the second target if it occurs within 200–500 ms of the first, a phenomenon called the attentional blink (AB). The neural basis for the AB is poorly understood, partly because conventional neuroimaging techniques cannot resolve visual events displayed close together in time. Here we introduce an approach that characterises the precise effect of the AB on behaviour and neural activity. We employ multivariate encoding analyses to extract feature-selective information carried by randomly-oriented gratings. We show that feature selectivity is enhanced for correctly reported targets and suppressed when the same items are missed, whereas irrelevant distractor items are unaffected. The findings suggest that the AB involves both short- and long-range neural interactions between visual representations competing for access to consciousness.

People often fail to perceive the second of two brief visual targets, a phenomenon known as the attentional blink (AB). Here the authors modelled behaviour and brain activity to show that the AB arises from short- and long-range interactions between representations of elementary visual features.

Mechanisms underlying gain modulation in the cortex

Cortical gain regulation allows neurons to respond adaptively to changing inputs. Neural gain is modulated by internal and external influences, including attentional and arousal states, motor activity and neuromodulatory input. These influences converge to a common set of mechanisms for gain modulation, including GABAergic inhibition, synaptically driven fluctuations in membrane potential, changes in cellular conductance and changes in other biophysical neural properties. Recent work has identified GABAergic interneurons as targets of neuromodulatory input and mediators of state-dependent gain modulation. Here, we review the engagement and effects of gain modulation in the cortex. We highlight key recent findings that link phenomenological observations of gain modulation to underlying cellular and circuit-level mechanisms. Finally, we place these cellular and circuit interactions in the larger context of their impact on perception and cognition.

Spatial Attentional Selection Modulates Early Visual Stimulus Processing Independently of Visual Alpha Modulations

The capacity-limited human brain is constantly confronted with a huge amount of sensory information. Selective attention is needed for biasing neural processing towards relevant information and consequently allows meaningful interaction with the environment. Activity in the alpha-band has been proposed to be related to top-down modulation of neural inhibition and could thus represent a viable candidate to control the priority of stimulus processing. It is, however, unknown whether modulations in the alpha-band directly relate to changes in the sensory gain control of the early visual cortex. Here, we used a spatial cueing paradigm while simultaneously measuring ongoing alpha-band oscillations and steady-state visual evoked potentials (SSVEPs) as a marker of continuous early sensory processing in the human visual cortex. Thereby, the effects of spatial attention for both of these signals and their potential interactions were assessed. As expected, spatial attention modulated both alpha-band and SSVEP responses. However, their modulations were independent of each other and the corresponding activity profiles differed across task demands. Thus, our results challenge the view that modulations of alpha-band activity represent a mechanism that directly alters or controls sensory gain. The potential role of alpha-band oscillations beyond sensory processing will be discussed in light of the present results.

Attention can be subdivided into neurobiological components corresponding to distinct behavioral effects

Attention is a common but highly complex term associated with a large number of distinct behavioral and perceptual phenomena. In the brain, attention-related changes in neuronal activity are observed in widespread structures. The many distinct behavioral and neuronal phenomena related to attention suggest that it might be subdivided into components corresponding to distinct biological mechanisms. Recent neurophysiological studies in monkeys have isolated behavioral changes related to attention along the 2 indices of signal detection theory and found that these 2 behavioral changes are associated with distinct neuronal changes in different brain areas. These results support the view that attention is made up of distinct neurobiological mechanisms.

Normalization governs attentional modulation within human visual cortex

Although attention is known to increase the gain of visuocortical responses, its underlying neural computations remain unclear. Here, we use fMRI to test the hypothesis that a neural population’s ability to be modulated by attention is dependent on divisive normalization. To do so, we leverage the feature-tuned properties of normalization and find that visuocortical responses to stimuli sharing features normalize each other more strongly. Comparing these normalization measures to measures of attentional modulation, we demonstrate that subpopulations which exhibit stronger normalization also exhibit larger attentional benefits. In a converging experiment, we reveal that attentional benefits are greatest when a subpopulation is forced into a state of stronger normalization. Taken together, these results suggest that the degree to which a subpopulation exhibits normalization plays a role in dictating its potential for attentional benefits.

Attention is known to enhance relevant information in our environment, yet its underlying neural computations remain unclear. Here, the authors provide evidence that the degree to which a neural population can normalize itself results in greater potential for attentional benefits.

The link between reading ability and visual spatial attention across development

Interacting with a cluttered and dynamic environment requires making decisions about visual information at relevant locations while ignoring irrelevant locations. Typical adults can do this with covert spatial attention: prioritizing particular visual field locations even without moving the eyes. Deficits of covert spatial attention have been implicated in developmental dyslexia, a specific reading disability. Previous studies of children with dyslexia, however, have been complicated by group differences in overall task ability that are difficult to distinguish from selective spatial attention. Here, we used a single-fixation visual search task to estimate orientation discrimination thresholds with and without an informative spatial cue in a large sample (N = 123) of people ranging in age from 5 to 70 years and with a wide range of reading abilities. We assessed the efficiency of attentional selection via the cueing effect: the difference in log thresholds with and without the spatial cue. Across our whole sample, both absolute thresholds and the cueing effect gradually improved throughout childhood and adolescence. Compared to typical readers, individuals with dyslexia had higher thresholds (worse orientation discrimination) as well as smaller cueing effects (weaker attentional selection). Those differences in dyslexia were especially pronounced prior to age 20, when basic visual function is still maturing. Thus, in line with previous theories, literacy skills are associated with the development of selective spatial attention.

Prefrontal Corticotectal Neurons Enhance Visual Processing through the Superior Colliculus and Pulvinar Thalamus

Top-down modulation of visual processing is mediated in part by direct prefrontal to visual cortical projections. Here, we show that the mouse cingulate cortex (Cg) regulates visual processing not only through corticocortical neurons projecting to the visual cortex but also through corticotectal neurons projecting subcortically. Bidirectional optogenetic manipulation demonstrated a prominent contribution of Cg corticotectal neurons to visually guided behavior, which is mediated by their collateral projections to both the motor-related layers of the superior colliculus (SC) and the lateral posterior nucleus of the thalamus (LP, analogous to the primate pulvinar). Whereas the Cg innervates the anterior LP (LPa), the SC innervates the posterior LP (LPp). Activating each stage of the Cg→SC→LPp or the Cg→LPa pathway strongly enhanced visual performance of the mouse and the sensory responses of visual cortical neurons. These results delineate two subcortical pathways by which a subtype of prefrontal pyramidal neurons exerts a powerful top-down influence on visual processing. VIDEO ABSTRACT.

Spatial attention alters visual appearance

It is well established that attention improves performance on many visual tasks. However, for more than 100 years, psychologists, philosophers, and neurophysiologists have debated its phenomenology-whether attention actually changes one's subjective experience. Here, we show that it is possible to objectively and quantitatively investigate the effects of attention on subjective experience. First, we review evidence showing that attention alters the appearance of many static and dynamic basic visual dimensions, which mediate changes in appearance of higher-level perceptual aspects. Then, we summarize current views on how attention alters appearance. These findings have implications for our understanding of perception and attention, illustrating that attention affects not only how we perform in visual tasks, but actually alters our experience of the visual world.

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.

Effects of Locomotion on Visual Responses in the Mouse Superior Colliculus

Visual responses are extensively shaped by internal factors. This effect is drastic in the primary visual cortex (V1), where locomotion profoundly increases visually-evoked responses. Here we investigate whether a similar effect exists in another major visual structure, the superior colliculus (SC). By performing two-photon calcium imaging of head-fixed male and female mice running on a treadmill, we find that only a minority of neurons in the most superficial lamina of the SC display significant changes during locomotion. This modulation includes both increase and decrease in response amplitude and is similar between excitatory and inhibitory neurons. The overall change in the SC is small, whereas V1 responses almost double during locomotion. Additionally, SC neurons display lower response variability and less spontaneous activity than V1 neurons. Together, these experiments indicate that locomotion-dependent modulation is not a widespread phenomenon in the early visual system and that the SC and V1 use different strategies to encode visual information.SIGNIFICANCE STATEMENT Visual information captured by the retina is processed in parallel through two major pathways, one reaching the primary visual cortex through the thalamus, and the other projecting to the superior colliculus. The two pathways then merge in the higher areas of the visual cortex. Recent studies have shown that behavioral state such as locomotion is an essential component of vision and can strongly affect visual responses in the thalamocortical pathway. Here we demonstrate that neurons in the mouse superior colliculus and primary visual cortex display striking differences in their modulation by locomotion, as well as in response variability and spontaneous activity. Our results reveal an important "division of labor" in visual processing between these two evolutionarily distinct structures.

Slow Endogenous Fluctuations in Cortical fMRI Signals Correlate with Reduced Performance in a Visual Detection Task and Are Suppressed by Spatial Attention

Spatial attention improves performance on visual tasks, increases neural responses to attended stimuli, and reduces correlated noise in visual cortical neurons. In addition to being visually responsive, many retinotopic visual cortical areas exhibit very slow (<0.1 Hz) endogenous fluctuations in functional magnetic resonance imaging signals. To test whether these fluctuations degrade stimulus representations, thereby impairing visual detection, we recorded functional magnetic resonance imaging responses while human participants performed a target detection task that required them to allocate spatial attention to either a rotating wedge stimulus or a central fixation point. We then measured the effects of spatial attention on response amplitude at the frequency of wedge rotation and on the amplitude of endogenous fluctuations at nonstimulus frequencies. We found that, in addition to enhancing stimulus-evoked responses, attending to the wedge also suppressed slow endogenous fluctuations that were unrelated to the visual stimulus in topographically defined areas in early visual cortex, posterior parietal cortex, and lateral occipital cortex, but not in a nonvisual cortical control region. Moreover, attentional enhancement of response amplitude and suppression of endogenous fluctuations were dissociable across cortical areas and across time. Finally, we found that the amplitude of the stimulus-evoked response was not correlated with a perceptual measure of visual target detection. Instead, perceptual performance was accounted for by the amount of suppression of slow endogenous fluctuations. Our results indicate that the amplitude of slow fluctuations of cortical activity is influenced by spatial attention and suggest that these endogenous fluctuations may impair perceptual processing in topographically organized visual cortical areas.

Interneuronal correlations at longer time scales predict decision signals for bistable structure-from-motion perception

Perceptual decisions are thought to depend on the activation of task-relevant neurons, whose activity is often correlated in time. Here, we examined how the temporal structure of shared variability in neuronal firing relates to perceptual choices. We recorded stimulus-selective neurons from visual area V5/MT while two monkeys (Macaca mulatta) made perceptual decisions about the rotation direction of structure-from-motion cylinders. Interneuronal correlations for a perceptually ambiguous cylinder stimulus were significantly higher than those for unambiguous cylinders or for random 2D motion during passive viewing. Much of the difference arose from correlations at relatively long timescales (hundreds of milliseconds). Choice-related neural activity (quantified as choice probability; CP) for ambiguous cylinders was positively correlated with interneuronal correlations and was specifically associated with their long timescale component. Furthermore, the slope of the long timescale - but not the instantaneous - component of the correlation predicted higher CPs towards the end of the trial i.e. close to the decision. Our results suggest that the perceptual stability of structure-from-motion cylinders may be controlled by enhanced interneuronal correlations on longer timescales. We propose this as a potential signature of top-down influences onto V5/MT processing that shape and stabilize the appearance of 3D-motion percepts.

Representation of shape, space, and attention in monkey cortex

Attentional deficits are core to numerous developmental, neurological, and psychiatric disorders. At the single-cell level, much knowledge has been garnered from studies of shape and spatial properties, as well as from numerous demonstrations of attentional modulation of those properties. Despite this wealth of knowledge of single-cell responses across many brain regions, little is known about how these cellular characteristics relate to population level representations and how such representations relate to behavior; in particular, how these cellular responses relate to the representation of shape, space, and attention, and how these representations differ across cortical areas and streams. Here we will emphasize the role of population coding as a missing link for connecting single-cell properties with behavior. Using a data-driven intrinsic approach to population decoding, we show that both 'what' and 'where' cortical visual streams encode shape, space, and attention, yet demonstrate striking differences in these representations. We suggest that both pathways fully process shape and space, but that differences in representation may arise due to their differing functions and input and output constraints. Moreover, differences in the effects of attention on shape and spatial population representations in the two visual streams suggest two distinct strategies: in a ventral area, attention or task demands modulate the population representations themselves (perhaps to expand or enhance one part at the expense of other parts) while in a dorsal area, at a population representation level, attention effects are weak and nearly non-existent, perhaps in order to maintain veridical representations needed for visuomotor control. We show that an intrinsic approach, as opposed to theory-driven and labeled approaches, is useful for understanding how representations develop and differ across brain regions. Most importantly, these approaches help link cellular properties more tightly with behavior, a much-needed step to better understand and interpret cellular findings and key to providing insights to improve interventions in human disorders.

Neuromodulation of Attention

Attention is critical to high-level cognition and attention deficits are a hallmark of neurologic and neuropsychiatric disorders. Although years of research indicates that distinct neuromodulators influence attentional control, a mechanistic account that traverses levels of analysis (cells, circuits, behavior) is missing. However, such an account is critical to guide the development of next-generation pharmacotherapies aimed at forestalling or remediating the global burden associated with disorders of attention. Here, we summarize current neuroscientific understanding of how attention affects single neurons and networks of neurons. We then review key results that have informed our understanding of how neuromodulation shapes these neuron and network properties and thereby enables the appropriate allocation of attention to relevant external or internal events. Finally, we highlight areas where we believe hypotheses can be formulated and tackled experimentally in the near future, thereby critically increasing our mechanistic understanding of how attention is implemented at the cellular and network levels.

Visual Neuroscience: Locomotion Changes How Mice See

How sensory signals are processed by the visual cortex is not fixed but changes depending on our spatial goals and whether or not we are moving. New research helps explain why these two effects do not always work well together.

Neuronal Effects of Spatial and Feature Attention Differ Due to Normalization

Although spatial and feature attention have differing effects on neuronal responses in visual cortex, it remains unclear why. Response normalization has been implicated in both types of attention (Carandini and Heeger, 2011), and single-unit studies have demonstrated that the magnitude of spatial attention effects on neuronal responses covaries with the magnitude of normalization effects. However, the relationship between feature attention and normalization remains largely unexplored. We recorded from individual neurons in the middle temporal area of rhesus monkeys using a task that allowed us to isolate the effects of feature attention, spatial attention, and normalization on the responses of each neuron. We found that the magnitudes of neuronal response modulations due to spatial attention and feature attention are correlated; however, whereas modulations due to spatial attention are correlated with normalization strength, those due to feature attention are not. Additionally, spatial attention modulations are stronger with multiple stimuli in the receptive field, whereas feature attention modulations are not. These findings are captured by a model in which spatial and feature attention share common top-down attention signals that nonetheless result in differing sensory neuron response modulations because of a spatially tuned sensory normalization mechanism. This model explains previously reported commonalities and differences between these two types of attention by clarifying the relationship between top-down attention signals and sensory normalization. We conclude that similar top-down signals to visual cortex can have distinct effects on neuronal responses due to distinct interactions with sensory mechanisms.SIGNIFICANCE STATEMENT Subjects use attention to improve their visual perception in several ways, including by attending to a location in space or to a visual feature. Prior studies have found both commonalities and differences between the effects of spatial and feature attention on neuronal responses in visual cortex, although it is unclear what mechanisms could explain this range of effects. Normalization, a computation by which neuronal responses are modified by stimulus context, has been implicated in many neuronal mechanisms throughout the brain. Here we propose that normalization provides a simple explanation for how spatial and feature attention could share common top-down attention signals that still affect sensory neuron responses differently.

Decoding the dynamic representation of facial expressions of emotion in explicit and incidental tasks

Faces transmit a wealth of important social signals. While previous studies have elucidated the network of cortical regions important for perception of facial expression, and the associated temporal components such as the P100, N170 and EPN, it is still unclear how task constraints may shape the representation of facial expression (or other face categories) in these networks. In the present experiment, we used Multivariate Pattern Analysis (MVPA) with EEG to investigate the neural information available across time about two important face categories (expression and identity) when those categories are either perceived under explicit (e.g. decoding facial expression category from the EEG when task is on expression) or incidental task contexts (e.g. decoding facial expression category from the EEG when task is on identity). Decoding of both face categories, across both task contexts, peaked in time-windows spanning 91-170 ms (across posterior electrodes). Peak decoding of expression, however, was not affected by task context whereas peak decoding of identity was significantly reduced under incidental processing conditions. In addition, errors in EEG decoding correlated with errors in behavioral categorization under explicit processing for both expression and identity, however under incidental conditions only errors in EEG decoding of expression correlated with behavior. Furthermore, decoding time-courses and the spatial pattern of informative electrodes showed consistently better decoding of identity under explicit conditions at later-time periods, with weak evidence for similar effects for decoding of expression at isolated time-windows. Taken together, these results reveal differences and commonalities in the processing of face categories under explicit Vs incidental task contexts and suggest that facial expressions are processed to a richer degree under incidental processing conditions, consistent with prior work indicating the relative automaticity by which emotion is processed. Our work further demonstrates the utility in applying multivariate decoding analyses to EEG for revealing the dynamics of face perception.

A Normalization Circuit Underlying Coding of Spatial Attention in Primate Lateral Prefrontal Cortex

Lateral prefrontal cortex (LPFC) neurons signal the allocation of voluntary attention; however, the neural computations underlying this function remain unknown. To investigate this, we recorded from neuronal ensembles in the LPFC of two Macaca fascicularis performing a visuospatial attention task. LPFC neural responses to a single stimulus were normalized when additional stimuli/distracters appeared across the visual field and were well-characterized by an averaging computation. Deploying attention toward an individual stimulus surrounded by distracters shifted neural activity from an averaging regime toward a regime similar to that when the attended stimulus was presented in isolation (winner-take-all; WTA). However, attentional modulation is both qualitatively and quantitatively dependent on a neuron's visuospatial tuning. Our results show that during attentive vision, LPFC neuronal ensemble activity can be robustly read out by downstream areas to generate motor commands, and/or fed back into sensory areas to filter out distracter signals in favor of target signals.

Attention Enhances the Efficacy of Communication in V1 Local Circuits

Attention is a critical component of visual perception; however, the mechanisms of attention at the granular level are poorly understood. One possible mechanism by which attention modulates neuronal activity is to control the efficacy of communication between connected neurons; however, it is unclear whether attention alters communication efficacy across a variety of neuronal circuits. In parallel, attentional modulation of neuronal firing rate is not uniform but depends upon the match between neuronal feature selectivity and the feature required for successful task completion. Here we tested whether modulation of communication efficacy is a viable mechanism of attention by assessing whether it is consistent across a variety of neuronal circuits and dependent upon the type of information conveyed in each circuit. We identified monosynaptically connected pairs of V1 neurons through cross-correlation of neuronal spike trains recorded in adult female macaque monkeys performing attention-demanding contrast-change detection tasks. Attention toward the stimulus in the receptive field of recorded neurons significantly facilitated the efficacy of communication among connected pairs of V1 neurons. The amount of attentional enhancement depended upon neuronal physiology, with larger facilitation for circuits conveying information about task-relevant features. Furthermore, presynaptic activity was more determinant of attentional enhancement of communication efficacy than postsynaptic activity, and feedforward local circuits often displayed the largest facilitation with attention. Together, these findings highlight attentional modulation of communication efficacy as a generalized mechanism of attention and demonstrate that attentional modulation at the granular level depends on the relevance of feature-specific information conveyed by neuronal circuits.SIGNIFICANCE STATEMENT How we pay attention to objects and locations in the visual environment has a profound impact on visual perception. Individual neurons in the visual cortex are similarly regulated by shifts in visual attention; however, the rules that govern whether and how attention alters neuronal activity are not known. In this study, we explored whether attention regulates communication between connected pairs of neurons in the primary visual cortex. We observed robust attentional facilitation of communication among these circuits. Furthermore, the extent to which the circuits were facilitated by attention depended on whether the information they conveyed was relevant for the particular attention task.

Illuminating the Neural Circuits Underlying Orienting of Attention

Human neuroimaging has revealed brain networks involving frontal and parietal cortical areas as well as subcortical areas, including the superior colliculus and pulvinar, which are involved in orienting to sensory stimuli. Because accumulating evidence points to similarities between both overt and covert orienting in humans and other animals, we propose that it is now feasible, using animal models, to move beyond these large-scale networks to address the local networks and cell types that mediate orienting of attention. In this opinion piece, we discuss optogenetic and related methods for testing the pathways involved, and obstacles to carrying out such tests in rodent and monkey populations.

The neural instantiation of a priority map

The term priority map is commonly used to describe a map of the visual scene, in which objects and locations are represented by their attentional priority, which itself is a combination of low-level salience and top-down control. The aim of this review is to examine how such a map may be represented at the neuronal level. We propose that there is not a single, common map in the brain, but that a number of cortical areas work together to generate the resultant behavior. Specifically, we suggest that the lateral intraparietal area (LIP) of posterior parietal cortex provides a simple representation of attentional priority, which remaps across saccades, so that there is an apparent allocentric map in a region with retinocentric encoding scheme. We propose that the frontal eye field (FEF) of prefrontal cortex receives the responses from LIP, but can suppress them to control the flow of eye movement behavior, and that the intermediate layers of the superior colliculus (SCi) reflect the final saccade goal. Together, these areas function to guide eye movements and may play a similar role in allocating covert visual attention.

Prediction error and repetition suppression have distinct effects on neural representations of visual information

Predictive coding theories argue that recent experience establishes expectations in the brain that generate prediction errors when violated. Prediction errors provide a possible explanation for repetition suppression, where evoked neural activity is attenuated across repeated presentations of the same stimulus. The predictive coding account argues repetition suppression arises because repeated stimuli are expected, whereas non-repeated stimuli are unexpected and thus elicit larger neural responses. Here, we employed electroencephalography in humans to test the predictive coding account of repetition suppression by presenting sequences of visual gratings with orientations that were expected either to repeat or change in separate blocks of trials. We applied multivariate forward modelling to determine how orientation selectivity was affected by repetition and prediction. Unexpected stimuli were associated with significantly enhanced orientation selectivity, whereas selectivity was unaffected for repeated stimuli. Our results suggest that repetition suppression and expectation have separable effects on neural representations of visual feature information.

Bridging Neural and Computational Viewpoints on Perceptual Decision-Making

Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.

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.

Brain regions modulated during covert visual attention in the macaque

Neurophysiological studies of covert visual attention in monkeys have emphasized the modulation of sensory neural responses in the visual cortex. At the same time, electrophysiological correlates of attention have been reported in other cortical and subcortical structures, and recent fMRI studies have identified regions across the brain modulated by attention. Here we used fMRI in two monkeys performing covert attention tasks to reproduce and extend these findings in order to help establish a more complete list of brain structures involved in the control of attention. As expected from previous studies, we found attention-related modulation in frontal, parietal and visual cortical areas as well as the superior colliculus and pulvinar. We also found significant attention-related modulation in cortical regions not traditionally linked to attention - mid-STS areas (anterior FST and parts of IPa, PGa, TPO), as well as the caudate nucleus. A control experiment using a second-order orientation stimulus showed that the observed modulation in a subset of these mid-STS areas did not depend on visual motion. These results identify the mid-STS areas (anterior FST and parts of IPa, PGa, TPO) and caudate nucleus as potentially important brain regions in the control of covert visual attention in monkeys.

Sensory Processing Across Conscious and Nonconscious Brain States: From Single Neurons to Distributed Networks for Inferential Representation

Neuronal activity is markedly different across brain states: it varies from desynchronized activity during wakefulness to the synchronous alternation between active and silent states characteristic of deep sleep. Surprisingly, limited attention has been paid to investigating how brain states affect sensory processing. While it was long assumed that the brain was mostly disconnected from external stimuli during sleep, an increasing number of studies indicates that sensory stimuli continue to be processed across all brain states-albeit differently. In this review article, we first discuss what constitutes a brain state. We argue that-next to global, behavioral states such as wakefulness and sleep-there is a concomitant need to distinguish bouts of oscillatory dynamics with specific global/local activity patterns and lasting for a few hundreds of milliseconds, as these can lead to the same sensory stimulus being either perceived or not. We define these short-lasting bouts as micro-states. We proceed to characterize how sensory-evoked neural responses vary between conscious and nonconscious states. We focus on two complementary aspects: neuronal ensembles and inter-areal communication. First, we review which features of ensemble activity are conducive to perception, and how these features vary across brain states. Properties such as heterogeneity, sparsity and synchronicity in neuronal ensembles will especially be considered as essential correlates of conscious processing. Second, we discuss how inter-areal communication varies across brain states and how this may affect brain operations and sensory processing. Finally, we discuss predictive coding (PC) and the concept of multi-level representations as a key framework for understanding conscious sensory processing. In this framework the brain implements conscious representations as inferences about world states across multiple representational levels. In this representational hierarchy, low-level inference may be carried out nonconsciously, whereas high levels integrate across different sensory modalities and larger spatial scales, correlating with conscious processing. This inferential framework is used to interpret several cellular and population-level findings in the context of brain states, and we briefly compare its implications to two other theories of consciousness. In conclusion, this review article, provides foundations to guide future studies aiming to uncover the mechanisms of sensory processing and perception across brain states.

Linking V1 Activity to Behavior

A long-term goal of visual neuroscience is to develop and test quantitative models that account for the moment-by-moment relationship between neural responses in early visual cortex and human performance in natural visual tasks. This review focuses on efforts to address this goal by measuring and perturbing the activity of primary visual cortex (V1) neurons while nonhuman primates perform demanding, well-controlled visual tasks. We start by describing a conceptual approach-the decoder linking model (DLM) framework-in which candidate decoding models take neural responses as input and generate predicted behavior as output. The ultimate goal in this framework is to find the actual decoder-the model that best predicts behavior from neural responses. We discuss key relevant properties of primate V1 and review current literature from the DLM perspective. We conclude by discussing major technological and theoretical advances that are likely to accelerate our understanding of the link between V1 activity and behavior.

Comparing frontal eye field and superior colliculus contributions to covert spatial attention

The causal roles of the frontal eye fields (FEF) and superior colliculus (SC) in spatial selective attention have not been directly compared. Reversible inactivation is an established method for testing causality but comparing results between FEF and SC is complicated by differences in size and morphology of the two brain regions. Here we exploited the fact that inactivation of FEF and SC also changes the metrics of saccadic eye movements, providing an independent benchmark for the strength of the causal manipulation. Using monkeys trained to covertly perform a visual motion-change detection task, we found that inactivation of either FEF or SC could cause deficits in attention task performance. However, SC-induced attention deficits were found with saccade changes half the size needed to get FEF-induced attention deficits. Thus, performance in visual attention tasks is vulnerable to loss of signals from either structure, but suppression of SC activity has a more devastating effect.