Unilateral prefrontal lesions impair memory-guided comparisons of contralateral visual motion

Cognitive independence and interactions between cerebral hemispheres

The two cerebral hemispheres can often operate independently. But interactions between them are critical for cognition and have been implicated in a number of neuropsychiatric disorders. Neurophysiological studies have long focused on a single hemisphere. Here, we review recent studies showing neurophysiological evidence showing both independence and interactions between the hemispheres during complex behavior.

Redundant, weakly connected prefrontal hemispheres balance precision and capacity in spatial working memory

How the prefrontal hemispheres coordinate to adapt to spatial working memory (WM) demands remains an open question. Recently, two models have been proposed: A specialized model, where each hemisphere governs contralateral behavior, and a redundant model, where both hemispheres equally guide behavior in the full visual space. To explore these alternatives, we analyzed simultaneous bilateral prefrontal cortex recordings from three macaque monkeys performing a visuo-spatial WM task. Each hemisphere represented targets across the full visual field and equally predicted behavioral imprecisions. Furthermore, memory errors were weakly correlated between hemispheres, suggesting that redundant, weakly coupled prefrontal hemispheres support spatial WM. Attractor model simulations showed that the hemispheric redundancy improved precision in simple tasks, whereas weak inter-hemispheric coupling allowed for specialized hemispheres in complex tasks. This interhemispheric architecture reconciles previous findings thought to support distinct models into a unified architecture, providing a versatile interhemispheric architecture that adapts to varying cognitive demands.

Patient-specific visual neglect severity estimation for stroke patients with neglect using EEG

Objective.We aim to assess the severity of spatial neglect (SN) through detailing patients' field of view (FOV) using EEG. Spatial neglect, a prevalent neurological syndrome in stroke patients, typically results from unilateral brain injuries, leading to inattention to the contralesional space. Commonly used Neglect detection methods like the Behavioral Inattention Test-conventional lack the capability to assess the full extent and severity of neglect. Although the Catherine Bergego Scale provides valuable clinical information, it does not detail the specific FOV affected in neglect patients.Approach.Building on our previously developed EEG-based brain-computer interface system, AR-guided EEG-based neglect detection, assessment, and rehabilitation system (AREEN), we aim to map neglect severity across a patient's FOV. We have demonstrated that AREEN can assess neglect severity in a patient-agnostic manner. However, its effectiveness in patient-specific scenarios, which is crucial for creating a generalizable plug-and-play system, remains unexplored. This paper introduces a novel EEG-based combined spatio-temporal network (ESTNet) that processes both time and frequency domain data to capture essential frequency band information associated with SN. We also propose a FOV correction system using Bayesian fusion, leveraging AREEN's recorded response times for enhanced accuracy by addressing noisy labels within the dataset.Main results.Extensive testing of ESTNet on our proprietary dataset has demonstrated its superiority over benchmark methods, achieving 79.62% accuracy, 76.71% sensitivity, and 86.36% specificity. Additionally, we provide saliency maps to enhance model explainability and establish clinical correlations.Significance.These findings underscore ESTNet's potential combined with Bayesian fusion-based FOV correction as an effective tool for generalized neglect assessment in clinical settings.

Single trial variability in neural activity during a working memory task reveals multiple distinct information processing sequences

Successful encoding, maintenance, and retrieval of information stored in working memory requires persistent coordination of activity among multiple brain regions. It is generally assumed that the pattern of such coordinated activity remains consistent for a given task. Thus, to separate this task-relevant signal from noise, multiple trials of the same task are completed, and the neural response is averaged across trials to generate an event-related potential (ERP). However, from trial to trial, the neuronal activity recorded with electroencephalogram (EEG) is actually spatially and temporally diverse, conflicting with the assumption of a single pattern of activity for a given task. Here, we show that variability in neuronal activity among single time-locked trials arises from the presence of multiple forms of stimulus dependent synchronized activity (i.e., distinct ERPs). We develop a data-driven classification method based on community detection to identify three discrete spatio-temporal clusters, or subtypes, of trials with different patterns of activation that are further associated with differences in decision-making processes. These results demonstrate that differences in the patterns of neural activity during working memory tasks represent fluctuations in the engagement of distinct brain networks and cognitive processes, suggesting that the brain can choose from multiple mechanisms to perform a given task.

Visual Attention in the Prefrontal Cortex

Voluntary attention selects behaviorally relevant signals for further processing while filtering out distracter signals. Neural correlates of voluntary visual attention have been reported across multiple areas of the primate visual processing streams, with the earliest and strongest effects isolated in the prefrontal cortex. In this article, I review evidence supporting the hypothesis that signals guiding the allocation of voluntary attention emerge in areas of the prefrontal cortex and reach upstream areas to modulate the processing of incoming visual information according to its behavioral relevance. Areas located anterior and dorsal to the arcuate sulcus and the frontal eye fields produce signals that guide the allocation of spatial attention. Areas located anterior and ventral to the arcuate sulcus produce signals for feature-based attention. Prefrontal microcircuits are particularly suited to supporting voluntary attention because of their ability to generate attentional template signals and implement signal gating and their extensive connectivity with the rest of the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Linking Neuronal Direction Selectivity to Perceptual Decisions About Visual Motion

Psychophysical and neurophysiological studies of responses to visual motion have converged on a consistent set of general principles that characterize visual processing of motion information. Both types of approaches have shown that the direction and speed of target motion are among the most important encoded stimulus properties, revealing many parallels between psychophysical and physiological responses to motion. Motivated by these parallels, this review focuses largely on more direct links between the key feature of the neuronal response to motion, direction selectivity, and its utilization in memory-guided perceptual decisions. These links were established during neuronal recordings in monkeys performing direction discriminations, but also by examining perceptual effects of widespread elimination of cortical direction selectivity produced by motion deprivation during development. Other approaches, such as microstimulation and lesions, have documented the importance of direction-selective activity in the areas that are active during memory-guided direction comparisons, area MT and the prefrontal cortex, revealing their likely interactions during behavioral tasks.

Decoding and mapping task states of the human brain via deep learning

Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requires careful feature selection/extraction according to expert knowledge. In this study, we propose a deep neural network (DNN) for directly decoding multiple brain task states from fMRI signals of the brain without any burden for feature handcrafts. We trained and tested the DNN classifier using task fMRI data from the Human Connectome Project's S1200 dataset (N = 1,034). In tests to verify its performance, the proposed classification method identified seven tasks with an average accuracy of 93.7%. We also showed the general applicability of the DNN for transfer learning to small datasets (N = 43), a situation encountered in typical neuroscience research. The proposed method achieved an average accuracy of 89.0 and 94.7% on a working memory task and a motor classification task, respectively, higher than the accuracy of 69.2 and 68.6% obtained by the SVM-MVPA. A network visualization analysis showed that the DNN automatically detected features from areas of the brain related to each task. Without incurring the burden of handcrafting the features, the proposed deep decoding method can classify brain task states highly accurately, and is a powerful tool for fMRI researchers.

The role of prefrontal cortex in the control of feature attention in area V4

When searching for an object in a cluttered scene, we can use our memory of the target object features to guide our search, and the responses of neurons in multiple cortical visual areas are enhanced when their receptive field contains a stimulus sharing target object features. Here we tested the role of the ventral prearcuate region (VPA) of prefrontal cortex in the control of feature attention in cortical visual area V4. VPA was unilaterally inactivated in monkeys performing a free-viewing visual search for a target stimulus in an array of stimuli, impairing monkeys' ability to find the target in the array in the affected hemifield, but leaving intact their ability to make saccades to targets presented alone. Simultaneous recordings in V4 revealed that the effects of feature attention on V4 responses were eliminated or greatly reduced while leaving the effects of spatial attention on responses intact. Altogether, the results suggest that feedback from VPA modulates processing in visual cortex during attention to object features.

Persistent Spiking Activity Underlies Working Memory

Persistent activity generated in the PFC during the delay period of working memory tasks represents information about stimuli held in memory and determines working memory performance. Alternative models of working memory, depending on the rhythmicity of discharges or exclusively on short-term synaptic plasticity, are inconsistent with the neurophysiological data.Dual Perspectives Companion Paper:Working Memory: Delay Activity, Yes! Persistent Activity? Maybe Not, by Mikael Lundqvist, Pawel Herman, and Earl K. Miller.

Association of salivary alpha-amylase and salivary flow rate with working memory functioning in healthy children

The aim of this study was to examine the association between auditory and visual working memory (WM) performance and salivary alpha-amylase (sAA) and salivary flow rate (SFR) in a sample of 63 children (38 boys). WM was assessed by means of WISC-V subtests: four auditory subtests (Digit Span and Letter-Number Sequencing) and one visual subtest (Picture Span). SAA activity, output, and SFR were measured at baseline (10 min prior to testing), one minute prior to testing, one minute after the end of the auditory WM subtests and one minute after the end of the visual WM subtest. Our statistical analyses showed an association among SAA activity, output and SFR levels and the number of recalled digits in the last attempt score in Letter-Number Sequencing subtest. Specifically, our results showed that working performance in this task was associated with a concurrent decrease in SFR (r(63) = -0.423, p < .05). This salivary measure was the best predictor of this specific index of working memory performance (β = -0.423, p < .05). These results show that the changes in SFR, which represents changes in parasympathetic tone, could be employed in future studies as a noninvasive marker of working memory performance in child studies.

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.

Exploring the role of task performance and learning style on prefrontal hemodynamics during a working memory task

Existing literature outlines the quality and location of activation in the prefrontal cortex (PFC) during working memory (WM) tasks. However, the effects of individual differences on the underlying neural process of WM tasks are still unclear. In this functional near infrared spectroscopy study, we administered a visual and auditory n-back task to examine activation in the PFC while considering the influences of task performance, and preferred learning strategy (VARK score). While controlling for age, results indicated that high performance (HP) subjects (accuracy > 90%) showed task dependent lower activation compared to normal performance subjects in PFC region Specifically HP groups showed lower activation in left dorsolateral PFC (DLPFC) region during performance of auditory task whereas during visual task they showed lower activation in the right DLPFC. After accounting for learning style, we found a correlation between visual and aural VARK score and level of activation in the PFC. Subjects with higher visual VARK scores displayed lower activation during auditory task in left DLPFC, while those with higher visual scores exhibited higher activation during visual task in bilateral DLPFC. During performance of auditory task, HP subjects had higher visual VARK scores compared to NP subjects indicating an effect of learning style on the task performance and activation. The results of this study show that learning style and task performance can influence PFC activation, with applications toward neurological implications of learning style and populations with deficits in auditory or visual processing.

Top-Down Control of Visual Attention by the Prefrontal Cortex. Functional Specialization and Long-Range Interactions

The ability to select information that is relevant to current behavioral goals is the hallmark of voluntary attention and an essential part of our cognition. Attention tasks are a prime example to study at the neuronal level, how task related information can be selectively processed in the brain while irrelevant information is filtered out. Whereas, numerous studies have focused on elucidating the mechanisms of visual attention at the single neuron and population level in the visual cortices, considerably less work has been devoted to deciphering the distinct contribution of higher-order brain areas, which are known to be critical for the employment of attention. Among these areas, the prefrontal cortex (PFC) has long been considered a source of top-down signals that bias selection in early visual areas in favor of the attended features. Here, we review recent experimental data that support the role of PFC in attention. We examine the existing evidence for functional specialization within PFC and we discuss how long-range interactions between PFC subregions and posterior visual areas may be implemented in the brain and contribute to the attentional modulation of different measures of neural activity in visual cortices.

Prefrontal Neurons Represent Motion Signals from Across the Visual Field But for Memory-Guided Comparisons Depend on Neurons Providing These Signals

Visual decisions often involve comparisons of sequential stimuli that can appear at any location in the visual field. The lateral prefrontal cortex (LPFC) in nonhuman primates, shown to play an important role in such comparisons, receives information about contralateral stimuli directly from sensory neurons in the same hemisphere, and about ipsilateral stimuli indirectly from neurons in the opposite hemisphere. This asymmetry of sensory inputs into the LPFC poses the question of whether and how its neurons incorporate sensory information arriving from the two hemispheres during memory-guided comparisons of visual motion. We found that, although responses of individual LPFC neurons to contralateral stimuli were stronger and emerged 40 ms earlier, they carried remarkably similar signals about motion direction in the two hemifields, with comparable direction selectivity and similar direction preferences. This similarity was also apparent around the time of the comparison between the current and remembered stimulus because both ipsilateral and contralateral responses showed similar signals reflecting the remembered direction. However, despite availability in the LPFC of motion information from across the visual field, these "comparison effects" required for the comparison stimuli to appear at the same retinal location. This strict dependence on spatial overlap of the comparison stimuli suggests participation of neurons with localized receptive fields in the comparison process. These results suggest that while LPFC incorporates many key aspects of the information arriving from sensory neurons residing in opposite hemispheres, it continues relying on the interactions with these neurons at the time of generating signals leading to successful perceptual decisions.

SIGNIFICANCE STATEMENT

Visual decisions often involve comparisons of sequential visual motion that can appear at any location in the visual field. We show that during such comparisons, the lateral prefrontal cortex (LPFC) contains accurate representation of visual motion from across the visual field, supplied by motion processing neurons. However, at the time of comparison, LPFC neurons can only use this information to compute the differences between the stimuli, if stimuli appear at the same retinal location, implicating neurons with localized receptive fields in the comparison process. These findings show that sensory comparisons rely on the interactions between LPFC and sensory neurons that not only supply sensory signals but also actively participate in the comparison of these signals at the time of the decision.

Prefrontal Neurons Encode a Solution to the Credit-Assignment Problem

To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects.SIGNIFICANCE STATEMENT Credit assignment is the process by which we infer the causes of our successes and failures. We found that neuronal activity in the dorsolateral prefrontal cortex conveyed the necessary information for performing credit assignment. Importantly, while there are various potential mechanisms to retain a "trace" of the causal events over time, we observed that spiking activity was sufficiently stable to act as the link between causes and effects, in contrast to prior reports that suggested spiking representations were unstable over time. In addition, we observed that this stability varied as a function of learning, such that the neural code was more reliable over time during early learning, when it was most needed.

Mnemonic Encoding and Cortical Organization in Parietal and Prefrontal Cortices

Persistent activity within the frontoparietal network is consistently observed during tasks that require working memory. However, the neural circuit mechanisms underlying persistent neuronal encoding within this network remain unresolved. Here, we ask how neural circuits support persistent activity by examining population recordings from posterior parietal (PPC) and prefrontal (PFC) cortices in two male monkeys that performed spatial and motion direction-based tasks that required working memory. While spatially selective persistent activity was observed in both areas, robust selective persistent activity for motion direction was only observed in PFC. Crucially, we find that this difference between mnemonic encoding in PPC and PFC is associated with the presence of functional clustering: PPC and PFC neurons up to ∼700 μm apart preferred similar spatial locations, and PFC neurons up to ∼700 μm apart preferred similar motion directions. In contrast, motion-direction tuning similarity between nearby PPC neurons was much weaker and decayed rapidly beyond ∼200 μm. We also observed a similar association between persistent activity and functional clustering in trained recurrent neural network models embedded with a columnar topology. These results suggest that functional clustering facilitates mnemonic encoding of sensory information.SIGNIFICANCE STATEMENT Working memory refers to our ability to temporarily store and manipulate information. Numerous studies have observed that, during working memory, neurons in higher cortical areas, such as the parietal and prefrontal cortices, mnemonically encode the remembered stimulus. However, several recent studies have failed to observe mnemonic encoding during working memory, raising the question as to why mnemonic encoding is observed during some, but not all, conditions. In this study, we show that mnemonic encoding occurs when a cortical area is organized such that nearby neurons preferentially respond to the same stimulus. This result provides plausible neuronal conditions that allow for mnemonic encoding, and gives us further understanding of the brain's mechanisms that support working memory.

The Distributed Nature of Working Memory

Studies in humans and non-human primates have provided evidence for storage of working memory contents in multiple regions ranging from sensory to parietal and prefrontal cortex. We discuss potential explanations for these distributed representations: (i) features in sensory regions versus prefrontal cortex differ in the level of abstractness and generalizability; and (ii) features in prefrontal cortex reflect representations that are transformed for guidance of upcoming behavioral actions. We propose that the propensity to produce persistent activity is a general feature of cortical networks. Future studies may have to shift focus from asking where working memory can be observed in the brain to how a range of specialized brain areas together transform sensory information into a delayed behavioral response.

Human Dorsolateral Prefrontal Cortex Is Not Necessary for Spatial Working Memory

A dominant theory, based on electrophysiological and lesion evidence from nonhuman primate studies, posits that the dorsolateral prefrontal cortex (dlPFC) stores and maintains working memory (WM) representations. Yet, neuroimaging studies have consistently failed to translate these results to humans; these studies normally find that neural activity persists in the human precentral sulcus (PCS) during WM delays. Here, we attempt to resolve this discrepancy. To test the degree to which dlPFC is necessary for WM, we compared the performance of patients with dlPFC lesions and neurologically healthy controls on a memory-guided saccade task that was used in the monkey studies to measure spatial WM. We found that dlPFC damage only impairs the accuracy of memory-guided saccades if the damage impacts the PCS; lesions to dorsolateral dlPFC that spare the PCS have no effect on WM. These results identify the necessary subregion of the frontal cortex for WM and specify how this influential animal model of human cognition must be revised.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits

Neuronal activity in the lateral prefrontal cortex (LPFC) reflects the structure and cognitive demands of memory-guided sensory discrimination tasks. However, we still do not know how neuronal activity articulates in network states involved in perceiving, remembering, and comparing sensory information during such tasks. Oscillations in local field potentials (LFPs) provide fingerprints of such network dynamics. Here, we examined LFPs recorded from LPFC of macaques while they compared the directions or the speeds of two moving random-dot patterns, S1 and S2, separated by a delay. LFP activity in the theta, beta, and gamma bands tracked consecutive components of the task. In response to motion stimuli, LFP theta and gamma power increased, and beta power decreased, but showed only weak motion selectivity. In the delay, LFP beta power modulation anticipated the onset of S2 and encoded the task-relevant S1 feature, suggesting network dynamics associated with memory maintenance. After S2 onset the difference between the current stimulus S2 and the remembered S1 was strongly reflected in broadband LFP activity, with an early sensory-related component proportional to stimulus difference and a later choice-related component reflecting the behavioral decision buildup. Our results demonstrate that individual LFP bands reflect both sensory and cognitive processes engaged independently during different stages of the task. This activation pattern suggests that during elementary cognitive tasks, the prefrontal network transitions dynamically between states and that these transitions are characterized by the conjunction of LFP rhythms rather than by single LFP bands.

SIGNIFICANCE STATEMENT

Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks.

Multi-Voxel Decoding and the Topography of Maintained Information During Visual Working Memory

The ability to maintain representations in the absence of external sensory stimulation, such as in working memory, is critical for guiding human behavior. Human functional brain imaging studies suggest that visual working memory can recruit a network of brain regions from visual to parietal to prefrontal cortex. In this review, we focus on the maintenance of representations during visual working memory and discuss factors determining the topography of those representations. In particular, we review recent studies employing multi-voxel pattern analysis (MVPA) that demonstrate decoding of the maintained content in visual cortex, providing support for a “sensory recruitment” model of visual working memory. However, there is some evidence that maintained content can also be decoded in areas outside of visual cortex, including parietal and frontal cortex. We suggest that the ability to maintain representations during working memory is a general property of cortex, not restricted to specific areas, and argue that it is important to consider the nature of the information that must be maintained. Such information-content is critically determined by the task and the recruitment of specific regions during visual working memory will be both task- and stimulus-dependent. Thus, the common finding of maintained information in visual, but not parietal or prefrontal, cortex may be more of a reflection of the need to maintain specific types of visual information and not of a privileged role of visual cortex in maintenance.

Task-specific versus generalized mnemonic representations in parietal and prefrontal cortices

Our ability to learn a wide range of behavioral tasks is essential for responding appropriately to sensory stimuli according to behavioral demands, but the underlying neural mechanism has been rarely examined by neurophysiological recordings in the same subjects across learning. To understand how learning new behavioral tasks affects neuronal representations, we recorded from posterior parietal cortex (PPC) before and after training on a visual motion categorization task. We found that categorization training influenced cognitive encoding in PPC, with a marked enhancement of memory-related delay-period encoding during the categorization task that was absent during a motion discrimination task before categorization training. In contrast, the prefrontal cortex (PFC) exhibited strong delay-period encoding during both discrimination and categorization tasks. This reveals a dissociation between PFC's and PPC's roles in working memory, with general engagement of PFC across multiple tasks, in contrast with more task-specific mnemonic encoding in PPC.

The Role of Prefrontal Cortex in Working Memory: A Mini Review

A prominent account of prefrontal cortex (PFC) function is that single neurons within the PFC maintain representations of task-relevant stimuli in working memory. Evidence for this view comes from studies in which subjects hold a stimulus across a delay lasting up to several seconds. Persistent elevated activity in the PFC has been observed in animal models as well as in humans performing these tasks. This persistent activity has been interpreted as evidence for the encoding of the stimulus itself in working memory. However, recent findings have posed a challenge to this notion. A number of recent studies have examined neural data from the PFC and posterior sensory areas, both at the single neuron level in primates, and at a larger scale in humans, and have failed to find encoding of stimulus information in the PFC during tasks with a substantial working memory component. Strong stimulus related information, however, was seen in posterior sensory areas. These results suggest that delay period activity in the PFC might be better understood not as a signature of memory storage per se, but as a top down signal that influences posterior sensory areas where the actual working memory representations are maintained.

A Source for Feature-Based Attention in the Prefrontal Cortex

In cluttered scenes, we can use feature-based attention to quickly locate a target object. To understand how feature attention is used to find and select objects for action, we focused on the ventral prearcuate (VPA) region of prefrontal cortex. In a visual search task, VPA cells responded selectively to search cues, maintained their feature selectivity throughout the delay and subsequent saccades, and discriminated the search target in their receptive fields with a time course earlier than in FEF or IT cortex. Inactivation of VPA impaired the animals' ability to find targets, and simultaneous recordings in FEF revealed that the effects of feature attention were eliminated while leaving the effects of spatial attention in FEF intact. Altogether, the results suggest that VPA neurons compute the locations of objects with the features sought and send this information to FEF to guide eye movements to those relevant stimuli.