Attentional modulations related to spatial gating but not to allocation of limited resources in primate V1

Oscillations in an artificial neural network convert competing inputs into a temporal code

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems.

Oculomotor feature discrimination is cortically mediated

Eye movements are often directed toward stimuli with specific features. Decades of neurophysiological research has determined that this behavior is subserved by a feature-reweighting of the neural activation encoding potential eye movements. Despite the considerable body of research examining feature-based target selection, no comprehensive theoretical account of the feature-reweighting mechanism has yet been proposed. Given that such a theory is fundamental to our understanding of the nature of oculomotor processing, we propose an oculomotor feature-reweighting mechanism here. We first summarize the considerable anatomical and functional evidence suggesting that oculomotor substrates that encode potential eye movements rely on the visual cortices for feature information. Next, we highlight the results from our recent behavioral experiments demonstrating that feature information manifests in the oculomotor system in order of featural complexity, regardless of whether the feature information is task-relevant. Based on the available evidence, we propose an oculomotor feature-reweighting mechanism whereby (1) visual information is projected into the oculomotor system only after a visual representation manifests in the highest stage of the cortical visual processing hierarchy necessary to represent the relevant features and (2) these dynamically recruited cortical module(s) then perform feature discrimination via shifting neural feature representations, while also maintaining parity between the feature representations in cortical and oculomotor substrates by dynamically reweighting oculomotor vectors. Finally, we discuss how our behavioral experiments may extend to other areas in vision science and its possible clinical applications.

The cost of divided attention for detection of simple visual features primarily reflects limits in post-perceptual processing

Covert spatial attention allows us to prioritize processing at relevant locations. Perception is generally poorer when attention is distributed across multiple locations than when attention is focused on a single location. However, while divided attention typically impairs performance, recent work suggests that divided attention does not seem to impair detection of simple visual features. Here, we re-examined this possibility. In two experiments, observers detected a simple target (a vertical Gabor), and we manipulated whether attention was focused at one location (focal-cue condition) or distributed across two locations (distributed-cue condition). In Experiment 1, targets could appear independently at each location, such that observers needed to judge target presence for each location separately in the distributed-cue condition. Under these conditions, we found a robust cost of dividing attention. Next, we further probed what stage of processing gave rise to this cost. In Experiment 1, the cost of dividing attention could reflect a limit in the ability to make concurrent judgments about target presence. In Experiment 2, we simplified the task to test whether this was the case: just one target could appear on each trial, such that observers made a single judgment ("was a target present?") in both the focal-cue and distributed-cue conditions. Here, we found a marginal cost of dividing attention that was weaker than the cost in Experiment 1. Together, our results suggest that divided attention does impair detection of simple visual features, but that this cost is primarily due to a limit in post-perceptual processes.

Task Context Modulates Feature-Selective Responses in Area V4

Feature selectivity of visual cortical responses measured during passive fixation provides only a partial view of selectivity because it does not account for the influence of cognitive factors. Here we focus on primate area V4 and ask how neuronal tuning is modulated by task engagement. We investigated whether responses to colored shapes during active shape discrimination are simple, stimulus-agnostic, scaled versions of responses during passive fixation, akin to results from attentional studies. Alternatively, responses could be subject to stimulus-specific scaling, that is, responses to different stimuli are modulated differently, resulting in changes in underlying shape/color selectivity. Among 83 well-isolated V4 neurons in two male macaques, only a minority (16 of 83), which were weakly tuned to both shape and color, displayed responses during fixation and discrimination tasks that could be related by stimulus-agnostic scaling. The majority (67 of 83), which were strongly tuned to shape, color, or both, displayed stimulus-dependent response changes during discrimination. For some of these neurons (39 of 83), the shape or color of the stimulus dictated the magnitude of the change, and for others (28 of 83) it was the combination of stimulus shape and color. Importantly, for neurons with one strong and one weak tuning dimension, stimulus-dependent response changes during discrimination were associated with a relative increase in selectivity along the stronger tuning dimension, without changes in tuning peak. These results reveal that more strongly tuned V4 neurons may also be more flexible in their selectivity, and imbalances in selectivity are amplified during active task contexts.SIGNIFICANCE STATEMENT Tuning for stimulus features is typically characterized by recording responses during passive fixation, but cognitive factors, including attention, influence responses in visual cortex. To determine how behavioral engagement influences neuronal responses in area V4, we compared responses to colored shapes during passive fixation and active behavior. For a large fraction of neurons, differences in responses between passive fixation and active behavior depended on the identity of the visual stimulus. For a subgroup of strongly feature-selective neurons, this response modulation was associated with enhanced selectivity for one feature at the expense of selectivity for the other. Such flexibility in tuning strength could improve performance in tasks requiring active judgment of stimuli.

Efficient allocation of attentional sensitivity gain in visual cortex reduces foveal sensitivity in visual search

The human visual system has a high-resolution fovea and a low-resolution periphery. When actively searching for a target, humans perform a covert search during each fixation, and then shift fixation (the fovea) to probable target locations. Previous studies of covert search under carefully controlled conditions provide strong evidence that for simple and small search displays, humans process all potential target locations with the same efficiency that they process those locations when individually cued on each trial. Here, we extend these studies to the case of large displays, in which the target can appear anywhere within the display. These more natural conditions reveal an attentional effect in which sensitivity in the fovea and parafovea is greatly diminished. We show that this "foveal neglect" is the expected consequence of efficiently allocating a fixed total attentional sensitivity gain across the retinotopic map in the visual cortex. We present a formal theory that explains our findings and the previous findings.

Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network

The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal–parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal–parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.

Reading: The Confluence of Vision and Language

The scientific study of reading has a rich history that spans disciplines from vision science to linguistics, psychology, cognitive neuroscience, neurology, and education. The study of reading can elucidate important general mechanisms in spatial vision, attentional control, object recognition, and perceptual learning, as well as the principles of plasticity and cortical topography. However, literacy also prompts the development of specific neural circuits to process a unique and artificial stimulus. In this review, we describe the sequence of operations that transforms visual features into language, how the key neural circuits are sculpted by experience during development, and what goes awry in children for whom learning to read is a struggle. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Is there a serial bottleneck in visual object recognition?

Divided attention has little effect for simple tasks, such as luminance detection, but it has large effects for complex tasks, such as semantic categorization of masked words. Here, we asked whether the semantic categorization of visual objects shows divided attention effects as large as those observed for words, or as small as those observed for simple feature judgments. Using a dual-task paradigm with nameable object stimuli, performance was compared with the predictions of serial and parallel models. At the extreme, parallel processes with unlimited capacity predict no effect of divided attention; alternatively, an all-or-none serial process makes two predictions: a large divided attention effect (lower accuracy for dual-task trials, compared to single-task trials) and a negative response correlation in dual-task trials (a given response is more likely to be incorrect when the response about the other stimulus is correct). These predictions were tested in two experiments examining object judgments. In both experiments, there was a large divided attention effect and a small negative correlation in responses. The magnitude of these effects was larger than for simple features, but smaller than for words. These effects were consistent with serial models, and rule out some but not all parallel models. More broadly, the results help establish one of the first examples of likely serial processing in perception.

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.

Advanced Circuit and Cellular Imaging Methods in Nonhuman Primates

Novel genetically encoded tools and advanced microscopy methods have revolutionized neural circuit analyses in insects and rodents over the last two decades. Whereas numerous technical hurdles originally barred these methodologies from success in nonhuman primates (NHPs), current research has started to overcome those barriers. In some cases, methodological advances developed with NHPs have even surpassed their precursors. One such advance includes new ultra-large imaging windows on NHP cortex, which are larger than the entire rodent brain and allow analysis unprecedented ultra-large-scale circuits. NHP imaging chambers now remain patent for periods longer than a mouse's lifespan, allowing for long-term all-optical interrogation of identified circuits and neurons over timeframes that are relevant to human cognitive development. Here we present some recent imaging advances brought forth by research teams using macaques and marmosets. These include technical developments in optogenetics; voltage-, calcium- and glutamate-sensitive dye imaging; two-photon and wide-field optical imaging; viral delivery; and genetic expression of indicators and light-activated proteins that result in the visualization of tens of thousands of identified cortical neurons in NHPs. We describe a subset of the many recent advances in circuit and cellular imaging tools in NHPs focusing here primarily on the research presented during the corresponding mini-symposium at the 2019 Society for Neuroscience annual meeting.

A flexible readout mechanism of human sensory representations

Attention can both enhance and suppress cortical sensory representations. However, changing sensory representations can also be detrimental to behavior. Behavioral consequences can be avoided by flexibly changing sensory readout, while leaving the representations unchanged. Here, we asked human observers to attend to and report about either one of two features which control the visibility of motion while making concurrent measurements of cortical activity with BOLD imaging (fMRI). We extend a well-established linking model to account for the relationship between these measurements and find that changes in sensory representation during directed attention are insufficient to explain perceptual reports. Adding a flexible downstream readout is necessary to best explain our data. Such a model implies that observers should be able to recover information about ignored features, a prediction which we confirm behaviorally. Thus, flexible readout is a critical component of the cortical implementation of human adaptive behavior.

Spiking Suppression Precedes Cued Attentional Enhancement of Neural Responses in Primary Visual Cortex

Attending to a visual stimulus increases its detectability, even if gaze is directed elsewhere. This covert attentional selection is known to enhance spiking across many brain areas, including the primary visual cortex (V1). Here we investigate the temporal dynamics of attention-related spiking changes in V1 of macaques performing a task that separates attentional selection from the onset of visual stimulation. We found that preceding attentional enhancement there was a sharp, transient decline in spiking following presentation of an attention-guiding cue. This disruption of V1 spiking was not observed in a task-naïve subject that passively observed the same stimulus sequence, suggesting that sensory activation is insufficient to cause suppression. Following this suppression, attended stimuli evoked more spiking than unattended stimuli, matching previous reports of attention-related activity in V1. Laminar analyses revealed a distinct pattern of activation in feedback-associated layers during both the cue-induced suppression and subsequent attentional enhancement. These findings suggest that top-down modulation of V1 spiking can be bidirectional and result in either suppression or enhancement of spiking responses.

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.

Uncovering the Spatial Profile of Contour Integration from Fixational Saccades: Evidence for Widespread Processing in V1

During contour integration, neuronal populations in the primary visual cortex (V1) enhance their responses to the contour while suppressing their responses to the noisy background. However, the spatial extent and profile of these responses are not fully understood. To investigate this question, 2 monkeys were trained on a contour detection task while we measured population responses in V1 using voltage-sensitive dyes. During stimulus presentation the animals made few fixational saccades, and we used their changing gaze position to image and analyze neuronal responses from large part of the stimulus, encoding multiple contour/background elements. We found that contour enhancement was present over the entire contour-mapped areas. The background suppression increased with distance from the contour, extending into background-mapped areas remotely located from the contour. The spatial profile of enhancement and suppression fitted well with a Gaussian model. These results imply that the divergent cortical responses to contour integration are modulated independently and extend over large areas in V1.

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.

The impact of early visual cortex transcranial magnetic stimulation on visual working memory precision and guess rate

Neuroimaging studies have demonstrated that activity patterns in early visual areas predict stimulus properties actively maintained in visual working memory. Yet, the mechanisms by which such information is represented remain largely unknown. In this study, observers remembered the orientations of 4 briefly presented gratings, one in each quadrant of the visual field. A 10Hz Transcranial Magnetic Stimulation (TMS) triplet was applied directly at stimulus offset, or midway through a 2-second delay, targeting early visual cortex corresponding retinotopically to a sample item in the lower hemifield. Memory for one of the four gratings was probed at random, and participants reported this orientation via method of adjustment. Recall errors were smaller when the visual field location targeted by TMS overlapped with that of the cued memory item, compared to errors for stimuli probed diagonally to TMS. This implied topographic storage of orientation information, and a memory-enhancing effect at the targeted location. Furthermore, early pulses impaired performance at all four locations, compared to late pulses. Next, response errors were fit empirically using a mixture model to characterize memory precision and guess rates. Memory was more precise for items proximal to the pulse location, irrespective of pulse timing. Guesses were more probable with early TMS pulses, regardless of stimulus location. Thus, while TMS administered at the offset of the stimulus array might disrupt early-phase consolidation in a non-topographic manner, TMS also boosts the precise representation of an item at its targeted retinotopic location, possibly by increasing attentional resources or by injecting a beneficial amount of noise.

Spatial Distribution of Attentional Modulation at Columnar Resolution in Macaque Area V4

Attention to a location in a visual scene affects neuronal responses in visual cortical areas in a retinotopically specific manner. Optical imaging studies have revealed that cortical responses consist of two components of different sizes: the stimulus-nonspecific global signal and the stimulus-specific mapping signal (domain activity). It remains unclear whether either or both of these components are modulated by spatial attention. In this study, to determine the spatial distribution of attentional modulation at columnar resolution, we performed cerebral blood volume (CBV)-based optical imaging in area V4 of monkeys performing a color change detection task in which spatial attention was manipulated. We found that spatial attention enhanced global signals of the hemodynamic responses, but did not affect stimulus-selective domain activities. These results indicate the involvement of global signals in neural processing of spatial attention. We propose that global signals reflect the neural substrate of the normalization pool in normalization models of attention.

Sensory Prioritization in Rats: Behavioral Performance and Neuronal Correlates

Operating with some finite quantity of processing resources, an animal would benefit from prioritizing the sensory modality expected to provide key information in a particular context. The present study investigated whether rats dedicate attentional resources to the sensory modality in which a near-threshold event is more likely to occur. We manipulated attention by controlling the likelihood with which a stimulus was presented from one of two modalities. In a whisker session, 80% of trials contained a brief vibration stimulus applied to whiskers and the remaining 20% of trials contained a brief change of luminance. These likelihoods were reversed in a visual session. When a stimulus was presented in the high-likelihood context, detection performance increased and was faster compared with the same stimulus presented in the low-likelihood context. Sensory prioritization was also reflected in neuronal activity in the vibrissal area of primary somatosensory cortex: single units responded differentially to the whisker vibration stimulus when presented with higher probability compared with lower probability. Neuronal activity in the vibrissal cortex displayed signatures of multiplicative gain control and enhanced response to vibration stimuli during the whisker session. In conclusion, rats allocate priority to the more likely stimulus modality and the primary sensory cortex may participate in the redistribution of resources.

SIGNIFICANCE STATEMENT

Detection of low-amplitude events is critical to survival; for example, to warn prey of predators. To formulate a response, decision-making systems must extract minute neuronal signals from the sensory modality that provides key information. Here, we identify the behavioral and neuronal correlates of sensory prioritization in rats. Rats were trained to detect whisker vibrations or visual flickers. Stimuli were embedded in two contexts in which either visual or whisker modality was more likely to occur. When a stimulus was presented in the high-likelihood context, detection was faster and more reliable. Neuronal recording from the vibrissal cortex revealed enhanced representation of vibrations in the prioritized context. These results establish the rat as an alternative model organism to primates for studying attention.

Reward expectation differentially modulates attentional behavior and activity in visual area V4

Neural activity in visual area V4 is enhanced when attention is directed into neuronal receptive fields. However, the source of this enhancement is unclear, as most physiological studies have manipulated attention by changing the absolute reward associated with a particular location as well as its value relative to other locations. We trained monkeys to discriminate the orientation of two stimuli presented simultaneously in different hemifields while we independently varied the reward magnitude associated with correct discrimination at each location. Behavioral measures of attention were controlled by the relative value of each location. By contrast, neurons in V4 were consistently modulated by absolute reward value, exhibiting increased activity, increased gamma-band power and decreased trial-to-trial variability whenever receptive field locations were associated with large rewards. These data challenge the notion that the perceptual benefits of spatial attention rely on increased signal-to-noise in V4. Instead, these benefits likely derive from downstream selection mechanisms.

Integrating Levels of Analysis in Systems and Cognitive Neurosciences: Selective Attention as a Case Study

Neuroscience is inherently interdisciplinary, rapidly expanding beyond its roots in biological sciences to many areas of the social and physical sciences. This expansion has led to more sophisticated ways of thinking about the links between brains and behavior and has inspired the development of increasingly advanced tools to characterize the activity of large populations of neurons. However, along with these advances comes a heightened risk of fostering confusion unless efforts are made to better integrate findings across different model systems and to develop a better understanding about how different measurement techniques provide mutually constraining information. Here we use selective visuospatial attention as a case study to highlight the importance of these issues, and we suggest that exploiting multiple measures can better constrain models that relate neural activity to animal behavior.

A case for human systems neuroscience

Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. Our approach has been to use a combination of psychophysics in which we can use human behavioral flexibility to make quantitative measurements of behavior and link those through computational models to measurements of cortical activity through magnetic resonance imaging. In particular, we have tested various computational hypotheses about what neural mechanisms could account for behavioral enhancement with spatial attention (Pestilli et al., 2011). Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans.

The marmoset monkey as a model for visual neuroscience

The common marmoset (Callithrix jacchus) has been valuable as a primate model in biomedical research. Interest in this species has grown recently, in part due to the successful demonstration of transgenic marmosets. Here we examine the prospects of the marmoset model for visual neuroscience research, adopting a comparative framework to place the marmoset within a broader evolutionary context. The marmoset's small brain bears most of the organizational features of other primates, and its smooth surface offers practical advantages over the macaque for areal mapping, laminar electrode penetration, and two-photon and optical imaging. Behaviorally, marmosets are more limited at performing regimented psychophysical tasks, but do readily accept the head restraint that is necessary for accurate eye tracking and neurophysiology, and can perform simple discriminations. Their natural gaze behavior closely resembles that of other primates, with a tendency to focus on objects of social interest including faces. Their immaturity at birth and routine twinning also makes them ideal for the study of postnatal visual development. These experimental factors, together with the theoretical advantages inherent in comparing anatomy, physiology, and behavior across related species, make the marmoset an excellent model for visual neuroscience.

Sensory gain outperforms efficient readout mechanisms in predicting attention-related improvements in behavior

Spatial attention has been postulated to facilitate perceptual processing via several different mechanisms. For instance, attention can amplify neural responses in sensory areas (sensory gain), mediate neural variability (noise modulation), or alter the manner in which sensory signals are selectively read out by postsensory decision mechanisms (efficient readout). Even in the context of simple behavioral tasks, it is unclear how well each of these mechanisms can account for the relationship between attention-modulated changes in behavior and neural activity because few studies have systematically mapped changes between stimulus intensity, attentional focus, neural activity, and behavioral performance. Here, we used a combination of psychophysics, event-related potentials (ERPs), and quantitative modeling to explicitly link attention-related changes in perceptual sensitivity with changes in the ERP amplitudes recorded from human observers. Spatial attention led to a multiplicative increase in the amplitude of an early sensory ERP component (the P1, peaking ∼80-130 ms poststimulus) and in the amplitude of the late positive deflection component (peaking ∼230-330 ms poststimulus). A simple model based on signal detection theory demonstrates that these multiplicative gain changes were sufficient to account for attention-related improvements in perceptual sensitivity, without a need to invoke noise modulation. Moreover, combining the observed multiplicative gain with a postsensory readout mechanism resulted in a significantly poorer description of the observed behavioral data. We conclude that, at least in the context of relatively simple visual discrimination tasks, spatial attention modulates perceptual sensitivity primarily by modulating the gain of neural responses during early sensory processing.

Encoding of graded changes in spatial specificity of prior cues in human visual cortex

Prior information about the relevance of spatial locations can vary in specificity; a single location, a subset of locations, or all locations may be of potential importance. Using a contrast-discrimination task with four possible targets, we asked whether performance benefits are graded with the spatial specificity of a prior cue and whether we could quantitatively account for behavioral performance with cortical activity changes measured by blood oxygenation level-dependent (BOLD) imaging. Thus we changed the prior probability that each location contained the target from 100 to 50 to 25% by cueing in advance 1, 2, or 4 of the possible locations. We found that behavioral performance (discrimination thresholds) improved in a graded fashion with spatial specificity. However, concurrently measured cortical responses from retinotopically defined visual areas were not strictly graded; response magnitude decreased when all 4 locations were cued (25% prior probability) relative to the 100 and 50% prior probability conditions, but no significant difference in response magnitude was found between the 100 and 50% prior probability conditions for either cued or uncued locations. Also, although cueing locations increased responses relative to noncueing, this cue sensitivity was not graded with prior probability. Furthermore, contrast sensitivity of cortical responses, which could improve contrast discrimination performance, was not graded. Instead, an efficient-selection model showed that even if sensory responses do not strictly scale with prior probability, selection of sensory responses by weighting larger responses more can result in graded behavioral performance benefits with increasing spatial specificity of prior information.

Neural correlates of task switching in prefrontal cortex and primary auditory cortex in a novel stimulus selection task for rodents

Animals can selectively respond to a target sound despite simultaneous distractors, just as humans can respond to one voice at a crowded cocktail party. To investigate the underlying neural mechanisms, we recorded single-unit activity in primary auditory cortex (A1) and medial prefrontal cortex (mPFC) of rats selectively responding to a target sound from a mixture. We found that prestimulus activity in mPFC encoded the selection rule-which sound from the mixture the rat should select. Moreover, electrically disrupting mPFC significantly impaired performance. Surprisingly, prestimulus activity in A1 also encoded selection rule, a cognitive variable typically considered the domain of prefrontal regions. Prestimulus changes correlated with stimulus-evoked changes, but stimulus tuning was not strongly affected. We suggest a model in which anticipatory activation of a specific network of neurons underlies the selection of a sound from a mixture, giving rise to robust and widespread rule encoding in both brain regions.

A review of the mechanisms by which attentional feedback shapes visual selectivity

The glut of information available for the brain to process at any given moment necessitates an efficient attentional system that can 'pick and choose' what information receives prioritized processing. A growing body of work, spanning numerous methodologies and species, reveals that one powerful way in which attending to an item separates the wheat from the chaff is by altering a basic response property in the brain: neuronal selectivity. Selectivity is a cornerstone response property, largely dictating our ability to represent and interact with the environment. Although it is likely that selectivity is altered throughout many brain areas, here we focus on how directing attention to an item affects selectivity in the visual system, where this response property is generally more well characterized. First, we review the neural architecture supporting selectivity, and then discuss the various changes that could occur in selectivity for an attended item. In a survey of the literature, spanning neurophysiology, neuroimaging and psychophysics, we reveal that there is general convergence regarding the manner with which selectivity is shaped by attentional feedback. In a nutshell, the literature suggests that the type of changes in selectivity that manifest appears to depend on the type of attention being deployed: whereas directing spatial attention towards an item only alters spatial selectivity, directing feature-based attention can alter the selectivity of attended features.

Temporally-structured acquisition of multidimensional optical imaging data facilitates visualization of elusive cortical representations in the behaving monkey

Fundamental understanding of higher cognitive functions can greatly benefit from imaging of cortical activity with high spatiotemporal resolution in the behaving non-human primate. To achieve rapid imaging of high-resolution dynamics of cortical representations of spontaneous and evoked activity, we designed a novel data acquisition protocol for sensory stimulation by rapidly interleaving multiple stimuli in continuous sessions of optical imaging with voltage-sensitive dyes. We also tested a new algorithm for the "temporally structured component analysis" (TSCA) of a multidimensional time series that was developed for our new data acquisition protocol, but was tested only on simulated data (Blumenfeld, 2010). In addition to the raw data, the algorithm incorporates prior knowledge about the temporal structure of the data as well as input from other information. Here we showed that TSCA can successfully separate functional signal components from other signals referred to as noise. Imaging of responses to multiple visual stimuli, utilizing voltage-sensitive dyes, was performed on the visual cortex of awake monkeys. Multiple cortical representations, including orientation and ocular dominance maps as well as the hitherto elusive retinotopic representation of orientation stimuli, were extracted in only 10s of imaging, approximately two orders of magnitude faster than accomplished by conventional methods. Since the approach is rather general, other imaging techniques may also benefit from the same stimulation protocol. This methodology can thus facilitate rapid optical imaging explorations in monkeys, rodents and other species with a versatility and speed that were not feasible before.