Attentional Changes in Either Criterion or Sensitivity Are Associated with Robust Modulations in Lateral Prefrontal Cortex

Reward history cues focal attention in whisker somatosensory cortex

Prior reward is a potent cue for attentional capture, but the underlying neurobiology is largely unknown. In a novel whisker touch detection task, we show that mice flexibly shift attention between specific whiskers on a trial-by-trial timescale, guided by the recent history of stimulus-reward association. 2-photon calcium imaging and spike recordings revealed a robust neurobiological correlate of attention in somatosensory cortex (S1), boosting sensory responses to the attended whisker in L2/3 and L5, but not L4. Attentional boosting in L2/3 pyramidal cells was topographically precise and whisker-specific, and shifted receptive fields towards the attended whisker. L2/3 VIP interneurons were broadly activated by whisker stimuli, motion and arousal but did not carry a whisker-specific attentional signal, and thus did not mediate focal tactile attention. Thus, the history of stimuli and rewards in the recent past can dynamically engage local modulation in cortical sensory maps to guide flexible shifts in ongoing behavior.

Dorsal pulvinar inactivation leads to spatial selection bias without perceptual deficit

The dorsal pulvinar has been implicated in visuospatial attentional and perceptual confidence processing. Pulvinar lesions in humans and monkeys lead to spatial neglect symptoms, including an overt spatial saccade bias during free choices. However, it remains unclear whether disrupting the dorsal pulvinar during target selection that relies on a perceptual decision leads to a perceptual impairment or a more general spatial orienting and choice deficit. To address this question, we reversibly inactivated the unilateral dorsal pulvinar by injecting GABA-A agonist THIP while two macaque monkeys performed a color discrimination saccade task with varying perceptual difficulty. We used Signal Detection Theory and simulations to dissociate perceptual sensitivity (d-prime) and spatial selection bias (response criterion) effects. We expected a decrease in d-prime if dorsal pulvinar affects perceptual discrimination and a shift in response criterion if dorsal pulvinar is mainly involved in spatial orienting. After the inactivation, we observed response criterion shifts away from contralesional stimuli, especially when two competing stimuli in opposite hemifields were present. Notably, the d-prime and overall accuracy remained largely unaffected. Our results underline the critical contribution of the dorsal pulvinar to spatial orienting and action selection while showing it to be less important for visual perceptual discrimination.

Visuo-frontal interactions during social learning in freely moving macaques

Social interactions represent a ubiquitous aspect of our everyday life that we acquire by interpreting and responding to visual cues from conspecifics1. However, despite the general acceptance of this view, how visual information is used to guide the decision to cooperate is unknown. Here, we wirelessly recorded the spiking activity of populations of neurons in the visual and prefrontal cortex in conjunction with wireless recordings of oculomotor events while freely moving macaques engaged in social cooperation. As animals learned to cooperate, visual and executive areas refined the representation of social variables, such as the conspecific or reward, by distributing socially relevant information among neurons in each area. Decoding population activity showed that viewing social cues influences the decision to cooperate. Learning social events increased coordinated spiking between visual and prefrontal cortical neurons, which was associated with improved accuracy of neural populations to encode social cues and the decision to cooperate. These results indicate that the visual-frontal cortical network prioritizes relevant sensory information to facilitate learning social interactions while freely moving macaques interact in a naturalistic environment.

Dissociable components of attention exhibit distinct neuronal signatures in primate visual cortex

Attention can be deployed in multiple forms and facilitates behavior by influencing perceptual sensitivity and choice bias. Attention is also associated with a myriad of changes in sensory neural activity. Yet, the relationship between the behavioral components of attention and the accompanying changes in neural activity remains largely unresolved. We examined this relationship by quantifying sensitivity and bias in monkeys performing a task that dissociated eye movement responses from the focus of covert attention. Unexpectedly, bias, not sensitivity, increased at the focus of covert attention, whereas sensitivity increased at the location of planned eye movements. Furthermore, neuronal activity within visual area V4 varied robustly with bias, but not sensitivity, at the focus of covert attention. In contrast, correlated variability between neuronal pairs was lowest at the location of planned eye movements, and varied with sensitivity, but not bias. Thus, dissociable behavioral components of attention exhibit distinct neuronal signatures within the visual cortex.

Ga2O3 Bipolar Heterojunction-Based Optoelectronic Synapse Array with Visual Attention

The human brain efficiently processes only a fraction of visual information, a phenomenon termed attentional control, resulting in energy savings and heightened adaptability. Translating this mechanism into artificial visual neurons holds promise for constructing energy-efficient, bioinspired visual systems. Here, we propose a self-rectifying artificial visual neuron (SEVN) based on a NiO/Ga2O3 bipolar heterojunction with attentional control on patterns with a target color. The device exhibits short-term potentiation (STP) with quantum point contact (QPC) traits at low bias and transitions to long-term potentiation (LTP) at high bias, particularly facilitated by electron capture in deep defects upon ultraviolet (UV) exposure. With the utilization of two wavelengths of light upon the target and interference part of CAPTCHA to simulate top-down attentional control, the recognition accuracy is enhanced from 74 to 84%. These findings have the potential to augment the visual capability of neuromorphic systems with implications for diverse applications, including cybersecurity, healthcare, and machine vision.

Presaccadic attention does not facilitate the detection of changes in the visual field

Planning a rapid eye movement (saccade) changes how we perceive our visual world. Even before we move the eyes visual discrimination sensitivity improves at the impending target of eye movements, a phenomenon termed "presaccadic attention." Yet, it is unknown if such presaccadic selection merely affects perceptual sensitivity, or also affects downstream decisional processes, such as choice bias. We report a surprising lack of presaccadic perceptual benefits in a common, everyday setting-detection of changes in the visual field. Despite the lack of sensitivity benefits, choice bias for reporting changes increased reliably for the saccade target. With independent follow-up experiments, we show that presaccadic change detection is rendered more challenging because percepts at the saccade target location are biased toward, and more precise for, only the most recent of two successive stimuli. With a Bayesian model, we show how such perceptual and choice biases are crucial to explain the effects of saccade plans on change detection performance. In sum, visual change detection sensitivity does not improve presaccadically, a result that is readily explained by teasing apart distinct components of presaccadic selection. The findings may have critical implications for real-world scenarios, like driving, that require rapid gaze shifts in dynamically changing environments.

How to get rich from inflation

We seem to have rich experience across our visual field. Yet we are surprisingly poor at tasks involving the periphery and low spatial attention. Recently, Lau and collaborators have argued that a phenomenon known as "subjective inflation" allows us to reconcile these phenomena. I show inflation is consistent with multiple interpretations, with starkly different consequences for richness and for theories of consciousness more broadly. What's more, we have only weak reasons favouring any of these interpretations over the others. I provisionally argue for an interpretation on which subjective experience is genuinely rich, but (in peripheral/unattended areas) unreliable as a guide to the external world. The main challenge for this view is that it appears to imply that experience in the periphery is not just unreliable but unstable. However, I argue that this consequence, while initially appearing unintuitive, is in fact plausible.

Boundary updating as a source of history effect on decision uncertainty

When sorting a sequence of stimuli into binary classes, current choices are often negatively correlated with recent stimulus history. This phenomenon-dubbed the repulsive bias-can be explained by boundary updating, a process of shifting the class boundary to previous stimuli. This explanation implies that recent stimulus history can also influence "decision uncertainty," the probability of making incorrect decisions, because it depends on the location of the boundary. However, there have been no previous efforts to elucidate the impact of previous stimulus history on decision uncertainty. Here, from the boundary-updating process that accounts for the repulsive bias, we derived a prediction that decision uncertainty increases as current choices become more congruent with previous stimuli. We confirmed this prediction in behavioral, physiological, and neural correlates of decision uncertainty. Our work demonstrates that boundary updating offers a principled account of how previous stimulus history concurrently relates to choice bias and decision uncertainty.

Dissociable Neural Mechanisms Underlie the Effects of Attention on Visual Appearance and Response Bias

A prominent theoretical framework spanning philosophy, psychology, and neuroscience holds that selective attention penetrates early stages of perceptual processing to alter the subjective visual experience of behaviorally relevant stimuli. For example, searching for a red apple at the grocery store might make the relevant color appear brighter and more saturated compared with seeing the exact same red apple while searching for a yellow banana. In contrast, recent proposals argue that data supporting attention-related changes in appearance reflect decision- and motor-level response biases without concurrent changes in perceptual experience. Here, we tested these accounts by evaluating attentional modulations of EEG responses recorded from male and female human subjects while they compared the perceived contrast of attended and unattended visual stimuli rendered at different levels of physical contrast. We found that attention enhanced the amplitude of the P1 component, an early evoked potential measured over visual cortex. A linking model based on signal detection theory suggests that response gain modulations of the P1 component track attention-induced changes in perceived contrast as measured with behavior. In contrast, attentional cues induced changes in the baseline amplitude of posterior alpha band oscillations (∼9-12 Hz), an effect that best accounts for cue-induced response biases, particularly when no stimuli are presented or when competing stimuli are similar and decisional uncertainty is high. The observation of dissociable neural markers that are linked to changes in subjective appearance and response bias supports a more unified theoretical account and demonstrates an approach to isolate subjective aspects of selective information processing.SIGNIFICANCE STATEMENT Does attention alter visual appearance, or does it simply induce response bias? In the present study, we examined these competing accounts using EEG and linking models based on signal detection theory. We found that response gain modulations of the visually evoked P1 component best accounted for attention-induced changes in visual appearance. In contrast, cue-induced baseline shifts in alpha band activity better explained response biases. Together, these results suggest that attention concurrently impacts visual appearance and response bias, and that these processes can be experimentally isolated.

Topological insights into the neural basis of flexible behavior

It is widely accepted that there is an inextricable link between neural computations, biological mechanisms, and behavior, but it is challenging to simultaneously relate all three. Here, we show that topological data analysis (TDA) provides an important bridge between these approaches to studying how brains mediate behavior. We demonstrate that cognitive processes change the topological description of the shared activity of populations of visual neurons. These topological changes constrain and distinguish between competing mechanistic models, are connected to subjects' performance on a visual change detection task, and, via a link with network control theory, reveal a tradeoff between improving sensitivity to subtle visual stimulus changes and increasing the chance that the subject will stray off task. These connections provide a blueprint for using TDA to uncover the biological and computational mechanisms by which cognition affects behavior in health and disease.

Posterior Parietal Cortex Plays a Causal Role in Abstract Memory-Based Visual Categorical Decisions

Neural activity in the lateral intraparietal cortex (LIP) correlates with both sensory evaluation and motor planning underlying visuomotor decisions. We previously showed that LIP plays a causal role in visually-based perceptual and categorical decisions, and preferentially contributes to evaluating sensory stimuli over motor planning. In that study, however, monkeys reported their decisions with a saccade to a colored target associated with the correct motion category or direction. Since LIP is known to play a role in saccade planning, it remains unclear whether LIP's causal role in such decisions extend to decision-making tasks which do not involve saccades. Here, we employed reversible pharmacological inactivation of LIP neural activity while two male monkeys performed delayed match to category (DMC) and delayed match to sample (DMS) tasks. In both tasks, monkeys needed to maintain gaze fixation throughout the trial and report whether a test stimulus was a categorical match or nonmatch to the previous sample stimulus by releasing a touch bar. LIP inactivation impaired monkeys' behavioral performance in both tasks, with deficits in both accuracy and reaction time (RT). Furthermore, we recorded LIP neural activity in the DMC task targeting the same cortical locations as in the inactivation experiments. We found significant neural encoding of the sample category, which was correlated with monkeys' categorical decisions in the DMC task. Taken together, our results demonstrate that LIP plays a generalized role in visual categorical decisions independent of the task-structure and motor response modality.SIGNIFICANCE STATEMENT Neural activity in the lateral intraparietal cortex (LIP) correlates with perceptual and categorical decisions, in addition to its role in mediating saccadic eye movements. Past work found that LIP is causally involved in visual decisions that are rapidly reported by saccades in a reaction time based decision making task. Here we use reversible inactivation of LIP to test whether LIP is also causally involved in visual decisions when reported by hand movements during delayed matching tasks. Here we show that LIP inactivation impaired monkeys' task performance during both memory-based discrimination and categorization tasks. These results demonstrate that LIP plays a generalized role in visual categorical decisions independent of the task-structure and motor response modality.

Dorsolateral Striatum is a Bottleneck for Responding to Task-Relevant Stimuli in a Learned Whisker Detection Task in Mice

A learned sensory-motor behavior engages multiple brain regions, including the neocortex and the basal ganglia. How a target stimulus is detected by these regions and converted to a motor response remains poorly understood. Here, we performed electrophysiological recordings and pharmacological inactivations of whisker motor cortex and dorsolateral striatum to determine the representations within, and functions of, each region during performance in a selective whisker detection task in male and female mice. From the recording experiments, we observed robust, lateralized sensory responses in both structures. We also observed bilateral choice probability and preresponse activity in both structures, with these features emerging earlier in whisker motor cortex than dorsolateral striatum. These findings establish both whisker motor cortex and dorsolateral striatum as potential contributors to the sensory-to-motor (sensorimotor) transformation. We performed pharmacological inactivation studies to determine the necessity of these brain regions for this task. We found that suppressing the dorsolateral striatum severely disrupts responding to task-relevant stimuli, without disrupting the ability to respond, whereas suppressing whisker motor cortex resulted in more subtle changes in sensory detection and response criterion. Together these data support the dorsolateral striatum as an essential node in the sensorimotor transformation of this whisker detection task.SIGNIFICANCE STATEMENT Selecting an item in a grocery store, hailing a cab - these daily practices require us to transform sensory stimuli into motor responses. Many decades of previous research have studied goal-directed sensory-to-motor transformations within various brain structures, including the neocortex and the basal ganglia. Yet, our understanding of how these regions coordinate to perform sensory-to-motor transformations is limited because these brain structures are often studied by different researchers and through different behavioral tasks. Here, we record and perturb specific regions of the neocortex and the basal ganglia and compare their contributions during performance of a goal-directed somatosensory detection task. We find notable differences in the activities and functions of these regions, which suggests specific contributions to the sensory-to-motor transformation process.

Fluoxetine degrades luminance perceptual thresholds while enhancing motivation and reward sensitivity

Selective serotonin reuptake inhibitors (SSRIs) increase serotonin activity in the brain. While they are mostly known for their antidepressant properties, they have been shown to improve visual functions in amblyopia and impact cognitive functions ranging from attention to motivation and sensitivity to reward. Yet, a clear understanding of the specific action of serotonin to each of bottom-up sensory and top-down cognitive control components and their interaction is still missing. To address this question, we characterize, in two adult male macaques, the behavioral effects of fluoxetine, a specific SSRI, on visual perception under varying bottom-up (luminosity, distractors) and top-down (uncertainty, reward biases) constraints while they are performing three different visual tasks. We first manipulate target luminosity in a visual detection task, and we show that fluoxetine degrades luminance perceptual thresholds. We then use a target detection task in the presence of spatial distractors, and we show that under fluoxetine, monkeys display both more liberal responses as well as a degraded perceptual spatial resolution. In a last target selection task, involving free choice in the presence of reward biases, we show that monkeys display an increased sensitivity to reward outcome under fluoxetine. In addition, we report that monkeys produce, under fluoxetine, more trials and less aborts, increased pupil size, shorter blink durations, as well as task-dependent changes in reaction times. Overall, while low level vision appears to be degraded by fluoxetine, performances in the visual tasks are maintained under fluoxetine due to enhanced top-down control based on task outcome and reward maximization.

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.

EEG Signals Index a Global Signature of Arousal Embedded in Neuronal Population Recordings

Electroencephalography (EEG) has long been used to index brain states, from early studies describing activity in the presence and absence of visual stimulation to modern work employing complex perceptual tasks. These studies have shed light on brain-wide signals but often lack explanatory power at the single neuron level. Similarly, single neuron recordings can suffer from an inability to measure brain-wide signals accessible using EEG. Here, we combined these techniques while monkeys performed a change detection task and discovered a novel link between spontaneous EEG activity and a neural signal embedded in the spiking responses of neuronal populations. This "slow drift" was associated with fluctuations in the subjects' arousal levels over time: decreases in prestimulus α power were accompanied by increases in pupil size and decreases in microsaccade rate. These results show that brain-wide EEG signals can be used to index modes of activity present in single neuron recordings, that in turn reflect global changes in brain state that influence perception and behavior.

Methylphenidate as a causal test of translational and basic neural coding hypotheses

Most systems neuroscience studies fall into one of two categories: basic science work aimed at understanding the relationship between neurons and behavior, or translational work aimed at developing treatments for neuropsychiatric disorders. Here we use these two approaches to inform and enhance each other. Our study both tests hypotheses about basic science neural coding principles and elucidates the neuronal mechanisms underlying clinically relevant behavioral effects of systemically administered methylphenidate (Ritalin). We discovered that orally administered methylphenidate, used clinically to treat attention deficit hyperactivity disorder (ADHD) and generally to enhance cognition, increases spatially selective visual attention, enhancing visual performance at only the attended location. Further, we found that this causal manipulation enhances vision in rhesus macaques specifically when it decreases the mean correlated variability of neurons in visual area V4. Our findings demonstrate that the visual system is a platform for understanding the neural underpinnings of both complex cognitive processes (basic science) and neuropsychiatric disorders (translation). Addressing basic science hypotheses, our results are consistent with a scenario in which methylphenidate has cognitively specific effects by working through naturally selective cognitive mechanisms. Clinically, our findings suggest that the often staggeringly specific symptoms of neuropsychiatric disorders may be caused and treated by leveraging general mechanisms.

Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation

Behavioral experience and flexibility are crucial for survival in a constantly changing environment. Despite evolutionary pressures to develop adaptive behavioral strategies in a dynamically changing sensory landscape, the underlying neural correlates have not been well explored. Here, we use genetically encoded voltage imaging to measure signals in primary somatosensory cortex (S1) during sensory learning and behavioral adaptation in the mouse. In response to changing stimulus statistics, mice adopt a strategy that modifies their detection behavior in a context dependent manner as to maintain reward expectation. Surprisingly, neuronal activity in S1 shifts from simply representing stimulus properties to transducing signals necessary for adaptive behavior in an experience dependent manner. Our results suggest that neuronal signals in S1 are part of an adaptive framework that facilitates flexible behavior as individuals gain experience, which could be part of a general scheme that dynamically distributes the neural correlates of behavior during learning.

Waiblinger et al. investigate the role of primary sensory cortex in flexible behaviors. They show that neuronal signals in S1 are part of an adaptive and dynamic framework that facilitates flexible behavior as an individual gains experience, indicating a role for S1 in long-term adaptive strategies.

Spatial and Feature-selective Attention Have Distinct, Interacting Effects on Population-level Tuning

Attention can be deployed in different ways: When searching for a taxi in New York City, we can decide where to attend (e.g., to the street) and what to attend to (e.g., yellow cars). Although we use the same word to describe both processes, nonhuman primate data suggest that these produce distinct effects on neural tuning. This has been challenging to assess in humans, but here we used an opportunity afforded by multivariate decoding of MEG data. We found that attending to an object at a particular location and attending to a particular object feature produced effects that interacted multiplicatively. The two types of attention induced distinct patterns of enhancement in occipital cortex, with feature-selective attention producing relatively more enhancement of small feature differences and spatial attention producing relatively larger effects for larger feature differences. An information flow analysis further showed that stimulus representations in occipital cortex were Granger-caused by coding in frontal cortices earlier in time and that the timing of this feedback matched the onset of attention effects. The data suggest that spatial and feature-selective attention rely on distinct neural mechanisms that arise from frontal-occipital information exchange, interacting multiplicatively to selectively enhance task-relevant information.

Scalp-recorded N40 visual evoked potential: Sensory and attentional properties

N40 is a well-known component of evoked potentials with respect to the auditory and somatosensory modality but not much recognized with regard to the visual modality. To be detected with event-related potentials (ERPs), it requires an optimal signal-to-noise ratio. To investigate the nature of visual N40, we recorded EEG/ERP signals from 20 participants. Each of them was presented with 1800 spatial frequency gratings of 0.75, 1.5, 3 and 6 c/deg. Data were collected from 128 sites while participants were engaged in both passive viewing and attention conditions. N40 (30-55 ms) was modulated by alertness and selective attention; in fact, it was larger to targets than irrelevant and passively viewed spatial frequency gratings. Its strongest intracranial sources were the bilateral thalamic nuclei of pulvinar, according to swLORETA. The active network included precuneus, insula and inferior parietal lobule. An N80 component (60-90 ms) was also identified, which was larger to targets than irrelevant/passive stimuli and more negative to high than low spatial frequencies. In contrast, N40 was not sensitive to spatial frequency per se, nor did it show a polarity inversion as a function of spatial frequency. Attention, alertness and spatial frequency effects were also found for the later components P1, N2 and P300. The attentional effects increased in magnitude over time. The data showed that ERPs can pick up the earliest synchronized activity, deriving in part from thalamic nuclei, before the visual information has actually reached the occipital cortex.

Diminished Cortical Excitation and Elevated Inhibition During Perceptual Impairments in a Mouse Model of Autism

Sensory impairments are a core feature of autism spectrum disorder (ASD). These impairments affect visual perception and have been hypothesized to arise from imbalances in cortical excitatory and inhibitory activity. There is conflicting evidence for this hypothesis from several recent studies of transgenic mouse models of ASD; crucially, none have measured activity from identified excitatory and inhibitory neurons during simultaneous impairments of sensory perception. Here, we directly recorded putative excitatory and inhibitory population spiking in primary visual cortex (V1) while simultaneously measuring visual perceptual behavior in CNTNAP2-/- knockout (KO) mice. We observed quantitative impairments in the speed, accuracy, and contrast sensitivity of visual perception in KO mice. During these perceptual impairments, stimuli evoked more firing of inhibitory neurons and less firing of excitatory neurons, with reduced neural sensitivity to contrast. In addition, pervasive 3-10 Hz oscillations in superficial cortical layers 2/3 (L2/3) of KO mice degraded predictions of behavioral performance from neural activity. Our findings show that perceptual deficits relevant to ASD may be associated with elevated cortical inhibitory activity along with diminished and aberrant excitatory population activity in L2/3, a major source of feedforward projections to higher cortical regions.

Single trial neuronal activity dynamics of attentional intensity in monkey visual area V4

Understanding how activity of visual neurons represents distinct components of attention and their dynamics that account for improved visual performance remains elusive because single-unit experiments have not isolated the intensive aspect of attention from attentional selectivity. We isolated attentional intensity and its single trial dynamics as determined by spatially non-selective attentional performance in an orientation discrimination task while recording from neurons in monkey visual area V4. We found that attentional intensity is a distinct cognitive signal that can be distinguished from spatial selectivity, reward expectations and motor actions. V4 spiking on single trials encodes a combination of sensory and cognitive signals on different time scales. Attentional intensity and the detection of behaviorally relevant sensory signals are well represented, but immediate reward expectation and behavioral choices are poorly represented in V4 spiking. These results provide a detailed representation of perceptual and cognitive signals in V4 that are crucial for attentional performance.

During vigilance to painful stimuli: slower response rate is related to high trait anxiety, whereas faster response rate is related to high state anxiety

A pathological increase in vigilance, or hypervigilance, may be related to pain intensity in some clinical pain syndromes and may result from attention bias to salient stimuli mediated by anxiety. During a continuous performance task where subjects discriminated painful target stimuli from painful nontargets, we measured detected targets (hits), nondetected targets (misses), nondetected nontargets (correct rejections), and detected nontargets (false alarms). Using signal detection theory, we calculated response bias, the tendency to endorse a stimulus as a target, and discriminability, the ability to discriminate a target from nontarget. Owing to the relatively slow rate of stimulus presentation, our primary hypothesis was that sustained performance would result in a more conservative response bias reflecting a lower response rate over time on task. We found a more conservative response bias with time on task and no change in discriminability. We predicted that greater state and trait anxiety would lead to a more liberal response bias. A multivariable model provided partial support for our prediction; high trait anxiety related to a more conservative response bias (lower response rate), whereas high state anxiety related to a more liberal bias. This inverse relationship of state and trait anxiety is consistent with reports of effects of state and trait anxiety on reaction times to threatening stimuli. In sum, we report that sustained attention to painful stimuli was associated with a decrease in the tendency of the subject to respond to any stimulus over time on task, whereas the ability to discriminate target from nontarget remains unchanged.NEW & NOTEWORTHY During a series of painful stimuli requiring subjects to respond to targets, we separated response willingness from ability to discriminate targets from nontargets. Response willingness declined during the task, with no change in subjects' ability to discriminate, consistent with previous vigilance studies. High trait anxious subjects were less willing to respond and showed slower reaction times to hits than low anxious subjects. This study reveals an important role of trait anxiety in pain vigilance.

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.

Eye movements reflect adaptive predictions and predictive precision

Successful decision-making depends on the ability to form predictions about uncertain future events. Existing evidence suggests predictive representations are not limited to point estimates but also include information about the associated level of predictive uncertainty. Estimates of predictive uncertainty have an important role in governing the rate at which beliefs are updated in response to new observations. It is not yet known, however, whether the same form of uncertainty-modulated learning occurs naturally and spontaneously when there is no task requirement to express predictions explicitly. Here, we used a gaze-based predictive inference paradigm to show that (a) predictive inference manifested in spontaneous gaze dynamics, (b) feedback-driven updating of spontaneous gaze-based predictions reflected adaptation to environmental statistics, and (c) anticipatory gaze variability tracked predictive uncertainty in an event-by-event manner. Our results demonstrate that sophisticated predictive inference can occur spontaneously and that oculomotor behavior can provide a multidimensional readout of internal predictive beliefs. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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.

The lateral prefrontal cortex of primates encodes stimulus colors and their behavioral relevance during a match-to-sample task

The lateral prefrontal cortex of primates (lPFC) plays a central role in complex cognitive behavior, in decision-making as well as in guiding top-down attention. However, how and where in lPFC such behaviorally relevant signals are computed is poorly understood. We analyzed neural recordings from chronic microelectrode arrays implanted in lPFC region 8Av/45 of two rhesus macaques. The animals performed a feature match-to-sample task requiring them to match both motion and color information in a test stimulus. This task allowed to separate the encoding of stimulus motion and color from their current behavioral relevance on a trial-by-trial basis. We found that upcoming motor behavior can be robustly predicted from lPFC activity. In addition, we show that 8Av/45 encodes the color of a visual stimulus, regardless of its behavioral relevance. Most notably, whether a color matches the searched-for color can be decoded independent of a trial's motor outcome and while subjects detect unique feature conjunctions of color and motion. Thus, macaque area 8Av/45 computes, among other task-relevant information, the behavioral relevance of visual color features. Such a signal is most critical for both the selection of responses as well as the deployment of top-down modulatory signals, like feature-based attention.

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.

Subcortical connectivity correlates selectively with attention's effects on spatial choice bias

Forebrain mechanisms of visuospatial attention have been widely studied. Yet, how the midbrain contributes to attention remains comparatively unknown. Here, we examined the role of the superior colliculus (SC), a vertebrate midbrain structure, in attention. Does the SC control sensitivity to attended information, or enable biasing choices toward attended information, or both? We mapped structural connections of the human SC with neocortical regions and found that the strengths of these connections correlated with, and were strongly predictive of, individuals’ choice bias, but not sensitivity. Taken together with previous animal studies, our results suggest that the human SC may play an evolutionarily conserved role in controlling choice bias during visual attention.

Neural mechanisms of attention are extensively studied in the neocortex; comparatively little is known about how subcortical regions contribute to attention. The superior colliculus (SC) is an evolutionarily conserved, subcortical (midbrain) structure that has been implicated in controlling visuospatial attention. Yet how the SC contributes mechanistically to attention remains unknown. We investigated the role of the SC in attention, combining model-based psychophysics, diffusion imaging, and tractography in human participants. Specifically, we asked whether the SC contributes to enhancing sensitivity (d′) to attended information, or whether it contributes to biasing choices (criteria) in favor of attended information. We tested human participants on a multialternative change detection task, with endogenous spatial cueing, and quantified sensitivity and bias with a recently developed multidimensional signal detection model (m-ADC model). At baseline, sensitivity and bias exhibited complementary patterns of asymmetries across the visual hemifields: While sensitivity was consistently higher for detecting changes in the left hemifield, bias was higher for reporting changes in the right hemifield. Remarkably, white matter connectivity of the SC with the neocortex mirrored this pattern of asymmetries. Specifically, the asymmetry in SC–cortex connectivity correlated with the asymmetry in choice bias, but not in sensitivity. In addition, SC–cortex connectivity strength could predict cueing-induced modulation of bias, but not of sensitivity, across individuals. In summary, the SC may be a key node in an evolutionarily conserved network for controlling choice bias during visuospatial attention.

Dissociable sensitivity and bias mechanisms mediate behavioral effects of exogenous attention

Attention can be directed endogenously, based on task-relevant goals, or captured exogenously, by salient stimuli. While recent studies have shown that endogenous attention can facilitate behavior through dissociable sensitivity (sensory) and choice bias (decisional) mechanisms, it is unknown if exogenous attention also operates through dissociable sensitivity and bias mechanisms. We tested human participants on a multialternative change detection task with exogenous attention cues, which preceded or followed change events in close temporal proximity. Analyzing participants’ behavior with a multidimensional signal detection model revealed clear dissociations between exogenous cueing effects on sensitivity and bias. While sensitivity was, overall, lower at the cued location compared to other locations, bias was highest at the cued location. With an appropriately designed post-cue control condition, we discovered that the attentional effect of exogenous pre-cueing was to enhance sensitivity proximal to the cue. In contrast, exogenous attention enhanced bias even for distal stimuli in the cued hemifield. Reaction time effects of exogenous cueing could be parsimoniously explained with a diffusion-decision model, in which drift rate was determined by independent contributions from sensitivity and bias at each location. The results suggest a mechanistic schema of how exogenous attention engages dissociable sensitivity and bias mechanisms to shape behavior.

Sensory and decisional components of endogenous attention are dissociable

Endogenous cueing of attention enhances sensory processing of the attended stimulus (perceptual sensitivity) and prioritizes information from the attended location for guiding behavioral decisions (spatial choice bias). Here, we test whether sensitivity and bias effects of endogenous spatial attention are under the control of common or distinct mechanisms. Human observers performed a multialternative visuospatial attention task with probabilistic spatial cues. Observers' behavioral choices were analyzed with a recently developed multidimensional signal detection model (the m-ADC model). The model effectively decoupled the effects of spatial cueing on sensitivity from those on spatial bias and revealed striking dissociations between them. Sensitivity was highest at the cued location and not significantly different among uncued locations, suggesting a spotlight-like allocation of sensory resources at the cued location. On the other hand, bias varied systematically with cue validity, suggesting a graded allocation of decisional priority across locations. Cueing-induced modulations of sensitivity and bias were uncorrelated within and across subjects. Bias, but not sensitivity, correlated with key metrics of prioritized decision-making, including reaction times and decision optimality indices. In addition, we developed a novel metric, differential risk curvature, for distinguishing bias effects of attention from those of signal expectation. Differential risk curvature correlated selectively with m-ADC model estimates of bias but not with estimates of sensitivity. Our results reveal dissociable effects of endogenous attention on perceptual sensitivity and choice bias in a multialternative choice task and motivate the search for the distinct neural correlates of each.NEW & NOTEWORTHY Attention is often studied as a unitary phenomenon. Yet, attention can both enhance the perception of important stimuli (sensitivity) and prioritize such stimuli for decision-making (bias). Employing a multialternative spatial attention task with probabilistic cueing, we show that attention affects sensitivity and bias through dissociable mechanisms. Specifically, the effects on sensitivity alone match the notion of an attentional "spotlight." Our behavioral model enables quantifying component processes of attention, and identifying their respective neural correlates.

Dissecting Modulatory Effects of Visual Attention in Primate Lateral Prefrontal Cortex Using Signal Detection Theory

In this issue of Neuron, Luo and Maunsell (2018) use signal detection theory to demonstrate that the modulatory effects of attention on neuronal responses in the lateral prefrontal cortex during change detection can be due to changes in an observer's sensitivity or shifts in their response criterion.

Contribution of Sensory Encoding to Measured Bias

Signal detection theory (SDT) is a widely used theoretical framework that describes how variable sensory signals are integrated with a decision criterion to support perceptual decision-making. SDT provides two key measurements: sensitivity (d') and bias (c), which reflect the separability of decision variable distributions (signal and noise) and the position of the decision criterion relative to optimal, respectively. Although changes in the subject's decision criterion can be reflected in changes in bias, decision criterion placement is not the sole contributor to measured bias. Indeed, neuronal representations of bias have been observed in sensory areas, suggesting that some changes in bias are because of effects on sensory encoding. To directly test whether the sensory encoding process can influence bias, we optogenetically manipulated neuronal excitability in primary visual cortex (V1) in mice of both sexes during either an orientation discrimination or a contrast detection task. Increasing excitability in V1 significantly decreased behavioral bias, whereas decreasing excitability had the opposite effect. To determine whether this change in bias is consistent with effects on sensory encoding, we made extracellular recordings from V1 neurons in passively viewing mice. Indeed, we found that optogenetic manipulation of excitability shifted the neuronal bias in the same direction as the behavioral bias. Moreover, manipulating the quality of V1 encoding by changing stimulus contrast or interstimulus interval also resulted in consistent changes in both behavioral and neuronal bias. Thus, changes in sensory encoding are sufficient to drive changes in bias measured using SDT.SIGNIFICANCE STATEMENT Perceptual decision-making involves sensory integration followed by application of a cognitive criterion. Using signal detection theory, one can extract features of the underlying decision variables and rule: sensitivity (d') and bias (c). Because bias is measured as the difference between the optimal and actual criterion, it is sensitive to both the sensory encoding processes and the placement of the decision criterion. Here, we use behavioral and electrophysiological approaches to demonstrate that measures of bias depend on sensory processes. Optogenetic manipulations of V1 in mice bidirectionally affect both behavioral and neuronal measures of bias with little effect on sensitivity. Thus, changes in sensory encoding influence bias, and the absence of changes in sensitivity do not preclude changes in sensory encoding.

Stimulus Context and Reward Contingency Induce Behavioral Adaptation in a Rodent Tactile Detection Task

Behavioral adaptation is a prerequisite for survival in a constantly changing sensory environment, but the underlying strategies and relevant variables driving adaptive behavior are not well understood. Many learning models and neural theories consider probabilistic computations as an efficient way to solve a variety of tasks, especially if uncertainty is involved. Although this suggests a possible role for probabilistic inference and expectation in adaptive behaviors, there is little if any evidence of this relationship experimentally. Here, we investigated adaptive behavior in the rat model by using a well controlled behavioral paradigm within a psychophysical framework to predict and quantify changes in performance of animals trained on a simple whisker-based detection task. The sensory environment of the task was changed by transforming the probabilistic distribution of whisker deflection amplitudes systematically while measuring the animal's detection performance and corresponding rate of accumulated reward. We show that the psychometric function deviates significantly and reversibly depending on the probabilistic distribution of stimuli. This change in performance relates to accumulating a constant reward count across trials, yet it is exempt from changes in reward volume. Our simple model of reward accumulation captures the observed change in psychometric sensitivity and predicts a strategy seeking to maintain reward expectation across trials in the face of the changing stimulus distribution. We conclude that rats are able maintain a constant payoff under changing sensory conditions by flexibly adjusting their behavioral strategy. Our findings suggest the existence of an internal probabilistic model that facilitates behavioral adaptation when sensory demands change.SIGNIFICANCE STATEMENT The strategy animals use to deal with a complex and ever-changing world is a key to understanding natural behavior. This study provides evidence that rodent behavioral performance is highly flexible in the face of a changing stimulus distribution, consistent with a strategy to maintain a desired accumulation of reward.

Confirmation Bias through Selective Overweighting of Choice-Consistent Evidence

People's assessments of the state of the world often deviate systematically from the information available to them [1]. Such biases can originate from people's own decisions: committing to a categorical proposition, or a course of action, biases subsequent judgment and decision-making. This phenomenon, called confirmation bias [2], has been explained as suppression of post-decisional dissonance [3, 4]. Here, we provide insights into the underlying mechanism. It is commonly held that decisions result from the accumulation of samples of evidence informing about the state of the world [5-8]. We hypothesized that choices bias the accumulation process by selectively altering the weighting (gain) of subsequent evidence, akin to selective attention. We developed a novel psychophysical task to test this idea. Participants viewed two successive random dot motion stimuli and made two motion-direction judgments: a categorical discrimination after the first stimulus and a continuous estimation of the overall direction across both stimuli after the second stimulus. Participants' sensitivity for the second stimulus was selectively enhanced when that stimulus was consistent with the initial choice (compared to both, first stimuli and choice-inconsistent second stimuli). A model entailing choice-dependent selective gain modulation explained this effect better than several alternative mechanisms. Choice-dependent gain modulation was also established in another task entailing averaging of numerical values instead of motion directions. We conclude that intermittent choices direct selective attention during the evaluation of subsequent evidence, possibly due to decision-related feedback in the brain [9]. Our results point to a recurrent interplay between decision-making and selective attention.

Neural mechanisms of sensorimotor transformation and action selection

Ray Guillery made major contributions to our understanding of the development and function of the brain. One of his principal conceptual insights, developed together with Murray Sherman [S.M. Sherman & R.W. Guillery (2001) Exploring the Thalamus. Elsevier, Amstrerdam; S. Sherman & R. Guillery (2006) Exploring the Thalamus and Its Role in Cortical Functioning. Academic Press, New York, NY; S.M. Sherman & R.W. Guillery (2013) Functional Connections of Cortical Areas: A New View from the Thalamus. MIT Press, Cambridge, MA and then in his last book (R. Guillery (2017) The Brain as a Tool: A Neuroscientist's Account. Oxford University Press, Oxford, UK)], was that the brain is a 'tool' to understand the world. In this view, the brain does not passively process sensory information and use the result to inform motor outputs. Rather, sensory and motor signals are widely broadcast and inextricably linked, with ongoing sensorimotor transformations serving as the basis for interaction with the outside world. Here, we describe recent studies from our laboratory and others which demonstrate this astute framing of the link among sensation, perception, and action postulated by Guillery and others [G. Deco & E.T. Rolls (2005) Prog Neurobiol, 76, 236-256; P. Cisek & J.F. Kalaska (2010) Annu Rev Neurosci, 33, 269-298]. Guillery situated his understanding in the deeply intertwined relationship between the thalamus and cortex, and importantly in the feedback from cortex to thalamus which in turn influences feed-forward drive to cortex [S.M. Sherman & R.W. Guillery (2001) Exploring the Thalamus. Elsevier, Amstrerdam; S. Sherman & R. Guillery (2006) Exploring the Thalamus and Its Role in Cortical Functioning. Academic Press, New York, NY]. We extend these observations to argue that brain mechanisms for sensorimotor transformations involve cortical and subcortical circuits that create internal models as a substrate for action, that a key role of sensory inputs is to update such models, and that a major function of sensorimotor processing underlying cognition is to enable action selection and execution.

Neural Circuits That Mediate Selective Attention: A Comparative Perspective

Selective attention is central to cognition. Dramatic advances have been made in understanding the neural circuits that mediate selective attention. Forebrain networks, most elaborated in primates, control all forms of attention based on task demands and the physical salience of stimuli. These networks contain circuits that distribute top-down signals to sensory processing areas and enhance information processing in those areas. A midbrain network, most elaborated in birds, controls spatial attention. It contains circuits that continuously compute the highest priority stimulus location and route sensory information from the selected location to forebrain networks that make cognitive decisions. The identification of these circuits, their functions and mechanisms represent a major advance in our understanding of how the vertebrate brain mediates selective attention.