Representation of an Abstract Perceptual Decision in Macaque Superior Colliculus

Abstract deliberation by visuomotor neurons in prefrontal cortex

During visually guided behavior, the prefrontal cortex plays a pivotal role in mapping sensory inputs onto appropriate motor plans. When the sensory input is ambiguous, this involves deliberation. It is not known whether the deliberation is implemented as a competition between possible stimulus interpretations or between possible motor plans. Here we study neural population activity in the prefrontal cortex of macaque monkeys trained to flexibly report perceptual judgments of ambiguous visual stimuli. We find that the population activity initially represents the formation of a perceptual choice before transitioning into the representation of the motor plan. Stimulus strength and prior expectations both bear on the formation of the perceptual choice, but not on the formation of the action plan. These results suggest that prefrontal circuits involved in action selection are also used for the deliberation of abstract propositions divorced from a specific motor plan, thus providing a crucial mechanism for abstract reasoning.

Brain-wide arousal signals are segregated from movement planning in the superior colliculus

The superior colliculus (SC) is traditionally considered a brain region that functions as an interface between processing visual inputs and generating eye movement outputs. Although its role as a primary reflex center is thought to be conserved across vertebrate species, evidence suggests that the SC has evolved to support higher-order cognitive functions including spatial attention. When it comes to oculomotor areas such as the SC, it is critical that high precision fixation and eye movements are maintained even in the presence of signals related to ongoing changes in cognition and brain state, both of which have the potential to interfere with eye position encoding and movement generation. In this study, we recorded spiking responses of neuronal populations in the SC while monkeys performed a memory-guided saccade task and found that the activity of some of the neurons fluctuated over tens of minutes. By leveraging the statistical power afforded by high-dimensional neuronal recordings, we were able to identify a low-dimensional pattern of activity that was correlated with the subjects' arousal levels. Importantly, we found that the spiking responses of deep-layer SC neurons were less correlated with this brain-wide arousal signal, and that neural activity associated with changes in pupil size and saccade tuning did not overlap in population activity space with movement initiation signals. Taken together, these findings provide a framework for understanding how signals related to cognition and arousal can be embedded in the population activity of oculomotor structures without compromising the fidelity of the motor output.

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants' choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.

Abstract perceptual choice signals during action-linked decisions in the human brain

Humans can make abstract choices independent of motor actions. However, in laboratory tasks, choices are typically reported with an associated action. Consequentially, knowledge about the neural representation of abstract choices is sparse, and choices are often thought to evolve as motor intentions. Here, we show that in the human brain, perceptual choices are represented in an abstract, motor-independent manner, even when they are directly linked to an action. We measured MEG signals while participants made choices with known or unknown motor response mapping. Using multivariate decoding, we quantified stimulus, perceptual choice, and motor response information with distinct cortical distributions. Choice representations were invariant to whether the response mapping was known during stimulus presentation, and they occupied a distinct representational space from motor signals. As expected from an internal decision variable, they were informed by the stimuli, and their strength predicted decision confidence and accuracy. Our results demonstrate abstract neural choice signals that generalize to action-linked decisions, suggesting a general role of an abstract choice stage in human decision-making.

Visuo-vestibular heading perception: a model system to study multi-sensory decision making

Integrating noisy signals across time as well as sensory modalities, a process named multi-sensory decision making (MSDM), is an essential strategy for making more accurate and sensitive decisions in complex environments. Although this field is just emerging, recent extraordinary works from different perspectives, including computational theory, psychophysical behaviour and neurophysiology, begin to shed new light onto MSDM. In the current review, we focus on MSDM by using a model system of visuo-vestibular heading. Combining well-controlled behavioural paradigms on virtual-reality systems, single-unit recordings, causal manipulations and computational theory based on spiking activity, recent progress reveals that vestibular signals contain complex temporal dynamics in many brain regions, including unisensory, multi-sensory and sensory-motor association areas. This challenges the brain for cue integration across time and sensory modality such as optic flow which mainly contains a motion velocity signal. In addition, new evidence from the higher-level decision-related areas, mostly in the posterior and frontal/prefrontal regions, helps revise our conventional thought on how signals from different sensory modalities may be processed, converged, and moment-by-moment accumulated through neural circuits for forming a unified, optimal perceptual decision. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

A neural mechanism for terminating decisions

The brain makes decisions by accumulating evidence until there is enough to stop and choose. Neural mechanisms of evidence accumulation are established in association cortex, but the site and mechanism of termination are unknown. Here, we show that the superior colliculus (SC) plays a causal role in terminating decisions, and we provide evidence for a mechanism by which this occurs. We recorded simultaneously from neurons in the lateral intraparietal area (LIP) and SC while monkeys made perceptual decisions. Despite similar trial-averaged activity, we found distinct single-trial dynamics in the two areas: LIP displayed drift-diffusion dynamics and SC displayed bursting dynamics. We hypothesized that the bursts manifest a threshold mechanism applied to signals represented in LIP to terminate the decision. Consistent with this hypothesis, SC inactivation produced behavioral effects diagnostic of an impaired threshold sensor and prolonged the buildup of activity in LIP. The results reveal the transformation from deliberation to commitment.

Primate superior colliculus is engaged in abstract higher-order cognition

Categorization is a fundamental cognitive process by which the brain assigns stimuli to behaviorally meaningful groups. Investigations of visual categorization in primates have identified a hierarchy of cortical areas that are involved in the transformation of sensory information into abstract category representations. However, categorization behaviors are ubiquitous across diverse animal species, even those without a neocortex, motivating the possibility that subcortical regions may contribute to abstract cognition in primates. One candidate structure is the superior colliculus (SC), an evolutionarily conserved midbrain region that, although traditionally thought to mediate only reflexive spatial orienting, is involved in cognitive tasks that require spatial orienting. Here, we reveal a novel role of the primate SC in abstract, higher-order visual cognition. We compared neural activity in the SC and the posterior parietal cortex (PPC), a region previously shown to causally contribute to category decisions, while monkeys performed a visual categorization task in which they report their decisions with a hand movement. The SC exhibits stronger and shorter-latency category encoding than the PPC, and inactivation of the SC markedly impairs monkeys' category decisions. These results extend SC's established role in spatial orienting to abstract, non-spatial cognition.

A scale-dependent measure of system dimensionality

A fundamental problem in science is uncovering the effective number of degrees of freedom in a complex system: its dimensionality. A system’s dimensionality depends on its spatiotemporal scale. Here, we introduce a scale-dependent generalization of a classic enumeration of latent variables, the participation ratio. We demonstrate how the scale-dependent participation ratio identifies the appropriate dimension at local, intermediate, and global scales in several systems such as the Lorenz attractor, hidden Markov models, and switching linear dynamical systems. We show analytically how, at different limiting scales, the scale-dependent participation ratio relates to well-established measures of dimensionality. This measure applied in neural population recordings across multiple brain areas and brain states shows fundamental trends in the dimensionality of neural activity—for example, in behaviorally engaged versus spontaneous states. Our novel method unifies widely used measures of dimensionality and applies broadly to multivariate data across several fields of science.

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The scale-dependent dimensionality unifies widely used measures of dimensionality

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Dynamical systems show distinct dimensionality properties at different scales

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The scale-dependent dimensionality allows us to identify critical scales of the system

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Fundamental trends in dimensionality of neural activity depend on the brain state

Data mining is based on the discovery of structure within data. However, such a structure is often complex. The fact that the properties of data distributions vary depending on the scale at which they are examined is a fundamental component of this complexity. For example, a manifold may appear smooth at small scales but jagged or even fractal at larger scales. This scale dependence is critical, yet it is commonly overlooked. We introduce a fundamental approach for analyzing the properties of data distributions at all scales. This single scale-dependent description enables simultaneous examination of how characteristics vary across all scales, offering insight into the structure of the data distribution. This will help us gain a better grasp of data structures and pave the way for future theoretical advances in data science.

Deficits in decision-making induced by parietal cortex inactivation are compensated at two timescales

Perceptual decisions arise through the transformation of samples of evidence into a commitment to a proposition or plan of action. Such transformation is thought to involve cortical circuits capable of computation over timescales associated with working memory, attention, and planning. Neurons in the lateral intraparietal area (LIP) play a role in these functions, and much of what is known about the neurobiology of decision-making has been influenced by studies of LIP and its network of connections. However, the causal role of LIP remains controversial. In this study, we used pharmacological and chemogenetic methods to inactivate LIP in one brain hemisphere of four rhesus monkeys. This inactivation produced biases in decisions, but the effects dissipated despite persistent neural inactivation, implying compensation by unaffected areas. Compensation occurred rapidly within an experimental session and more gradually across sessions. These findings resolve disparate studies and inform the interpretation of focal perturbations of brain function.

Sequential sampling from memory underlies action selection during abstract decision-making

The study of perceptual decision-making in monkeys has provided insights into the process by which sensory evidence is integrated toward a decision. When monkeys make decisions with the knowledge of the motor actions the decisions bear upon, the process of evidence integration is instantiated by neurons involved in the selection of said actions. It is less clear how monkeys make decisions when unaware of the actions required to communicate their choice-what we refer to as "abstract" decisions. We investigated this by training monkeys to associate the direction of motion of a noisy random-dot display with the color of two targets. Crucially, the targets were displayed at unpredictable locations after the motion stimulus was extinguished. We found that the monkeys postponed decision formation until the targets were revealed. Neurons in the parietal association area LIP represented the integration of evidence leading to a choice, but as the stimulus was no longer visible, the samples of evidence must have been retrieved from short-term memory. Our results imply that when decisions are temporally unyoked from the motor actions they bear upon, decision formation is protracted until they can be framed in terms of motor actions.

Collicular circuits for flexible sensorimotor routing

Context-based sensorimotor routing is a hallmark of executive control. Pharmacological inactivations in rats have implicated the midbrain superior colliculus (SC) in this process. But what specific role is this, and what circuit mechanisms support it? Here we report a subset of rat SC neurons that instantiate a specific link between the representations of context and motor choice. Moreover, these neurons encode animals' choice far earlier than other neurons in the SC or in the frontal cortex, suggesting that their neural dynamics lead choice computation. Optogenetic inactivations revealed that SC activity during context encoding is necessary for choice behavior, even while that choice behavior is robust to inactivations during choice formation. Searches for SC circuit models matching our experimental results identified key circuit predictions while revealing some a priori expected features as unnecessary. Our results reveal circuit mechanisms within the SC that implement response inhibition and context-based vector inversion during executive control.

Causal role for the primate superior colliculus in the computation of evidence for perceptual decisions

Trained monkeys performed a two-choice perceptual decision-making task in which they reported the perceived orientation of a dynamic Glass pattern, before and after unilateral, reversible, inactivation of a brainstem area-the superior colliculus (SC)-involved in preparing eye movements. We found that unilateral SC inactivation produced significant decision biases and changes in reaction times consistent with a causal role for the primate SC in perceptual decision-making. Fitting signal detection theory and sequential sampling models to the data showed that SC inactivation produced a decrease in the relative evidence for contralateral decisions, as if adding a constant offset to a time-varying evidence signal for the ipsilateral choice. The results provide causal evidence for an embodied cognition model of perceptual decision-making and provide compelling evidence that the SC of primates (a brainstem structure) plays a causal role in how evidence is computed for decisions-a process usually attributed to the forebrain.

A Novel Three-Choice Touchscreen Task to Examine Spatial Attention and Orienting Responses in Rodents

Mammalian orienting behavior consists of coordinated movements of the eyes, head, pinnae, vibrissae, or body to attend to an external stimulus. The present study aimed to develop a novel operant task using a touch-screen system to measure spatial attention. In this task, rats were trained to nose-poke a light stimulus presented in one of three locations. The stimulus was presented more frequently in the center location to develop spatial attention bias toward the center stimulus. Changes in orienting responses were detected by measuring the animals' response accuracy and latency to stimuli at the lateral locations, following reversible unilateral chemogenetic inactivation of the superior colliculus (SC). Additionally, spontaneous turning and rotation behavior was measured using an open-field test (OFT). Our results show that right SC inactivation significantly increased the whole body turn angle in the OFT, in line with previous literature that indicated an ipsiversive orientating bias and the presence of contralateral neglect following unilateral SC lesions. In the touch screen orienting task, unilateral SC inactivation significantly increased bias toward the ipsilateral side, as measured by response frequency in various experimental conditions, and a very large left-shift of a respective psychometric function. Our results demonstrate that this novel touchscreen task is able to detect changes in spatial attention and orienting responses because of e.g. experimental manipulations or injury with very high sensitivity, while taking advantage of the touch screen technology that allows for high transferability of the task between labs and for open-source data sharing through https://www.mousebytes.ca.

Unraveling circuits of visual perception and cognition through the superior colliculus

The superior colliculus is a conserved sensorimotor structure that integrates visual and other sensory information to drive reflexive behaviors. Although the evidence for this is strong and compelling, a number of experiments reveal a role for the superior colliculus in behaviors usually associated with the cerebral cortex, such as attention and decision-making. Indeed, in addition to collicular outputs targeting brainstem regions controlling movements, the superior colliculus also has ascending projections linking it to forebrain structures including the basal ganglia and amygdala, highlighting the fact that the superior colliculus, with its vast inputs and outputs, can influence processing throughout the neuraxis. Today, modern molecular and genetic methods combined with sophisticated behavioral assessments have the potential to make significant breakthroughs in our understanding of the evolution and conservation of neuronal cell types and circuits in the superior colliculus that give rise to simple and complex behaviors.

Tuned inhibition in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior

Current dominant views hold that perceptual confidence reflects the probability that a decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being correct can be dissociated. An alternative hypothesis suggests that confidence instead reflects the magnitude of evidence in favor of a decision while being relatively insensitive to the evidence opposing the decision. We considered how this alternative hypothesis might be biologically instantiated by developing a simple neural network model incorporating a known property of sensory neurons: tuned inhibition. The key idea of the model is that the level of inhibition that each accumulator unit receives from units with the opposite tuning preference, i.e. its inhibition 'tuning', dictates its contribution to perceptual decisions versus confidence judgments, such that units with higher tuned inhibition (computing relative evidence for different perceptual interpretations) determine perceptual discrimination decisions, and units with lower tuned inhibition (computing absolute evidence) determine confidence. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature where confidence and decision accuracy dissociate. By comparing model fits, we further demonstrate that a full complement of behavioral data across several previously published experimental results-including accuracy, reaction time, mean confidence, and metacognitive sensitivity-is best accounted for when confidence is computed from units without, rather than units with, tuned inhibition. Finally, we discuss predictions of our results and model for future neurobiological studies. These findings suggest that the brain has developed and implements this alternative, heuristic theory of perceptual confidence computation by relying on the diversity of neural resources available.

Variable Statistical Structure of Neuronal Spike Trains in Monkey Superior Colliculus

Popular models of decision-making propose that noisy sensory evidence accumulates until reaching a bound. Behavioral evidence as well as trial-averaged ramping of neuronal activity in sensorimotor regions of the brain support this idea. However, averaging activity across trials can mask other processes, such as rapid shifts in decision commitment, calling into question the hypothesis that evidence accumulation is encoded by delay period activity of individual neurons. We mined two sets of data from experiments in four monkeys in which we recorded from superior colliculus neurons during two different decision-making tasks and a delayed saccade task. We applied second-order statistical measures and spike train simulations to determine whether spiking statistics were similar or different in the different tasks and monkeys, despite similar trial-averaged activity across tasks and monkeys. During a motion direction discrimination task, single-trial delay period activity behaved statistically consistent with accumulation. During an orientation detection task, the activity behaved superficially like accumulation, but statistically consistent with stepping. Simulations confirmed both findings. Importantly, during a simple saccade task, with similar trial-averaged activity, neither process explained spiking activity, ruling out interpretations based on differences in attention, reward, or motor planning. These results highlight the need for exploring single-trial spiking dynamics to understand cognitive processing and raise the interesting hypothesis that the superior colliculus participates in different aspects of decision-making depending on task differences.SIGNIFICANCE STATEMENT How are decisions based on sensory information transformed into actions? We report that single-trial neuronal activity dynamics in the superior colliculus of monkeys show differences in decision-making tasks depending on task idiosyncrasies and requirements and despite similar trial-averaged ramping activity. These results highlight the importance of exploring single-trial spiking dynamics to understand cognitive processing and raise the interesting hypothesis that the superior colliculus participates in different aspects of decision-making depending on task requirements.

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.

Distributed coding of choice, action and engagement across the mouse brain

Vision, choice, action and behavioural engagement arise from neuronal activity that may be distributed across brain regions. Here we delineate the spatial distribution of neurons underlying these processes. We used Neuropixels probes1,2 to record from approximately 30,000 neurons in 42 brain regions of mice performing a visual discrimination task3. Neurons in nearly all regions responded non-specifically when the mouse initiated an action. By contrast, neurons encoding visual stimuli and upcoming choices occupied restricted regions in the neocortex, basal ganglia and midbrain. Choice signals were rare and emerged with indistinguishable timing across regions. Midbrain neurons were activated before contralateral choices and were suppressed before ipsilateral choices, whereas forebrain neurons could prefer either side. Brain-wide pre-stimulus activity predicted engagement in individual trials and in the overall task, with enhanced subcortical but suppressed neocortical activity during engagement. These results reveal organizing principles for the distribution of neurons encoding behaviourally relevant variables across the mouse brain.

Single-trial neural dynamics are dominated by richly varied movements

When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape, and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered “noise”. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity.

Foraging as an evidence accumulation process

The patch-leaving problem is a canonical foraging task, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different “strategies”, for example an incremental, decremental, or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To describe sub-optimal decisions, we introduce an energy-dependent marginal utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch-leaving decisions.

Foraging is a ubiquitous animal behavior, performed by organisms as different as worms, birds, rats, and humans. Although the behavior has been extensively studied, it is not known how the brain processes information obtained during foraging activity to make subsequent foraging decisions. We form an evidence accumulation model of foraging decisions that describes the process through which an animal gathers information and uses it to make foraging decisions. By building on studies of the neural decision mechanisms within systems neuroscience, this model connects the foraging decision process with ecological models of patch-leaving decisions, such as the marginal value theorem. The model suggests the existence of different foraging strategies, which optimize for different environmental conditions and their potential implementation by neural decision making circuits. The model also shows how state-dependence, such as satiation level, can affect evidence accumulation to lead to sub-optimal foraging decisions. Our model provides a framework for future experimental studies which seek to elucidate how neural decision making mechanisms have been shaped by evolutionary forces in an animal’s surrounding environment.

Sequence-dependent sensitivity explains the accuracy of decisions when cues are separated with a gap

Most decisions require information gathering from a stimulus presented with different gaps. However, the neural mechanism underlying this integration is ambiguous. Recently, it has been claimed that humans can optimally integrate the information of two discrete pulses independent of the temporal gap between them. Interestingly, subjects' performance on such a task, with two discrete pulses, is superior to what a perfect accumulator can predict. Although numerous neuronal and descriptive models have been proposed to explain the mechanism of perceptual decision-making, none can explain human behavior on this two-pulse task. In order to investigate the mechanism of decision-making on the noted tasks, a set of modified drift-diffusion models based on different hypotheses were used. Model comparisons clarified that, in a sequence of information arriving at different times, the accumulated information of earlier evidence affects the process of information accumulation of later evidence. It was shown that the rate of information extraction depends on whether the pulse is the first or the second one. Moreover, our findings suggest that a drift diffusion model with a dynamic drift rate can also explain the stronger effect of the second pulse on decisions as shown by Kiani et al. (Journal of Neuroscience, 33 (42), 16483-16489, 2013).

A Role for the Superior Colliculus in Decision Criteria

Simple decisions arise from the evaluation of sensory evidence. But decisions are determined by more than just evidence. Individuals establish internal decision criteria that influence how they respond. Where or how decision criteria are established in the brain remains poorly understood. Here, we show that neuronal activity in the superior colliculus (SC) predicts changes in decision criteria. Using a novel "Yes-No" task that isolates changes in decision criterion from changes in decision sensitivity, and computing neuronal measures of sensitivity and criterion, we find that SC neuronal activity correlates with the decision criterion regardless of the location of the choice report. We also show that electrical manipulation of activity within the SC produces changes in decisions consistent with changes in decision criteria and are largely independent of the choice report location. Our correlational and causal results together provide strong evidence that SC activity signals the position of a decision criterion. VIDEO ABSTRACT.

Macaque dorsal premotor cortex exhibits decision-related activity only when specific stimulus-response associations are known

How deliberation on sensory cues and action selection interact in decision-related brain areas is still not well understood. Here, monkeys reached to one of two targets, whose colors alternated randomly between trials, by discriminating the dominant color of a checkerboard cue composed of different numbers of squares of the two target colors in different trials. In a Targets First task the colored targets appeared first, followed by the checkerboard; in a Checkerboard First task, this order was reversed. After both cues appeared in both tasks, responses of dorsal premotor cortex (PMd) units covaried with action choices, strength of evidence for action choices, and RTs- hallmarks of decision-related activity. However, very few units were modulated by checkerboard color composition or the color of the chosen target, even during the checkerboard deliberation epoch of the Checkerboard First task. These findings implicate PMd in the action-selection but not the perceptual components of the decision-making process in these tasks.

Visual Neurons in the Superior Colliculus Discriminate Many Objects by Their Historical Values

The superior colliculus (SC) is an important structure in the mammalian brain that orients the animal toward distinct visual events. Visually responsive neurons in SC are modulated by visual object features, including size, motion, and color. However, it remains unclear whether SC activity is modulated by non-visual object features, such as the reward value associated with the object. To address this question, three monkeys were trained (>10 days) to saccade to multiple fractal objects, half of which were consistently associated with large rewards while other half were associated with small rewards. This created historically high-valued (‘good’) and low-valued (‘bad’) objects. During the neuronal recordings from the SC, the monkeys maintained fixation at the center while the objects were flashed in the receptive field of the neuron without any reward. We found that approximately half of the visual neurons responded more strongly to the good than bad objects. In some neurons, this value-coding remained intact for a long time (>1 year) after the last object-reward association learning. Notably, the neuronal discrimination of reward values started about 100 ms after the appearance of visual objects and lasted for more than 100 ms. These results provide evidence that SC neurons can discriminate objects by their historical (long-term) values. This object value information may be provided by the basal ganglia, especially the circuit originating from the tail of the caudate nucleus. The information may be used by the neural circuits inside SC for motor (saccade) output or may be sent to the circuits outside SC for future behavior.

A synaptic threshold mechanism for computing escape decisions

Escaping from imminent danger is an instinctive behaviour that is fundamental for survival, and requires the classification of sensory stimuli as harmless or threatening. The absence of threat enables animals to forage for essential resources, but as the level of threat and potential for harm increases, they have to decide whether or not to seek safety 1 . Despite previous work on instinctive defensive behaviours in rodents2-11, little is known about how the brain computes the threat level for initiating  escape. Here we show that the probability and vigour of escape in mice scale with the saliency of innate threats, and are well described by a model that computes the distance between the threat level and an escape threshold. Calcium imaging and optogenetics in the midbrain of freely behaving mice show that the activity of excitatory neurons in the deep layers of the medial superior colliculus (mSC) represents the saliency of the threat stimulus and is predictive of escape, whereas glutamatergic neurons of the dorsal periaqueductal grey (dPAG) encode exclusively the choice to escape and control escape vigour. We demonstrate a feed-forward monosynaptic excitatory connection from mSC to dPAG neurons, which is weak and unreliable-yet required for escape behaviour-and provides a synaptic threshold for dPAG activation and the initiation of escape. This threshold can be overcome by high mSC network activity because of short-term synaptic facilitation and recurrent excitation within the mSC, which amplifies and sustains synaptic drive to the dPAG. Therefore, dPAG glutamatergic neurons compute escape decisions and escape vigour using a synaptic mechanism to  threshold threat information received from the mSC, and provide a biophysical model of how the brain performs a critical behavioural computation.

The Role of the Lateral Intraparietal Area in (the Study of) Decision Making

Over the past two decades, neurophysiological responses in the lateral intraparietal area (LIP) have received extensive study for insight into decision making. In a parallel manner, inferred cognitive processes have enriched interpretations of LIP activity. Because of this bidirectional interplay between physiology and cognition, LIP has served as fertile ground for developing quantitative models that link neural activity with decision making. These models stand as some of the most important frameworks for linking brain and mind, and they are now mature enough to be evaluated in finer detail and integrated with other lines of investigation of LIP function. Here, we focus on the relationship between LIP responses and known sensory and motor events in perceptual decision-making tasks, as assessed by correlative and causal methods. The resulting sensorimotor-focused approach offers an account of LIP activity as a multiplexed amalgam of sensory, cognitive, and motor-related activity, with a complex and often indirect relationship to decision processes. Our data-driven focus on multiplexing (and de-multiplexing) of various response components can complement decision-focused models and provides more detailed insight into how neural signals might relate to cognitive processes such as decision making.

Selective Optogenetic Control of Purkinje Cells in Monkey Cerebellum

Purkinje cells of the primate cerebellum play critical but poorly understood roles in the execution of coordinated, accurate movements. Elucidating these roles has been hampered by a lack of techniques for manipulating spiking activity in these cells selectively-a problem common to most cell types in non-transgenic animals. To overcome this obstacle, we constructed AAV vectors carrying the channelrhodopsin-2 (ChR2) gene under the control of a 1 kb L7/Pcp2 promoter. We injected these vectors into the cerebellar cortex of rhesus macaques and tested vector efficacy in three ways. Immunohistochemical analyses confirmed selective ChR2 expression in Purkinje cells. Neurophysiological recordings confirmed robust optogenetic activation. Optical stimulation of the oculomotor vermis caused saccade dysmetria. Our results demonstrate the utility of AAV-L7-ChR2 for revealing the contributions of Purkinje cells to circuit function and behavior, and they attest to the feasibility of promoter-based, targeted, genetic manipulations in primates.

Circuits for Action and Cognition: A View from the Superior Colliculus

The superior colliculus is one of the most well-studied structures in the brain, and with each new report, its proposed role in behavior seems to increase in complexity. Forty years of evidence show that the colliculus is critical for reorienting an organism toward objects of interest. In monkeys, this involves saccadic eye movements. Recent work in the monkey colliculus and in the homologous optic tectum of the bird extends our understanding of the role of the colliculus in higher mental functions, such as attention and decision making. In this review, we highlight some of these recent results, as well as those capitalizing on circuit-based methodologies using transgenic mice models, to understand the contribution of the colliculus to attention and decision making. The wealth of information we have about the colliculus, together with new tools, provides a unique opportunity to obtain a detailed accounting of the neurons, circuits, and computations that underlie complex behavior.

Auditory Processing in the Posterior Parietal Cortex

Goal-directed behavior can be characterized as a dynamic link between a sensory stimulus and a motor act. Neural correlates of many of the intermediate events of goal-directed behavior are found in the posterior parietal cortex. Although the parietal cortex’s role in guiding visual behaviors has received considerable attention, relatively little is known about its role in mediating auditory behaviors. Here, the authors review recent studies that have focused on how neurons in the lateral intraparietal area (area LIP) differentially process auditory and visual stimuli. These studies suggest that area LIP contains a modality-dependent representation that is highly dependent on behavioral context.

Cortical Components of Reaction-Time during Perceptual Decisions in Humans

The mechanisms of perceptual decision-making are frequently studied through measurements of reaction time (RT). Classical sequential-sampling models (SSMs) of decision-making posit RT as the sum of non-overlapping sensory, evidence accumulation, and motor delays. In contrast, recent empirical evidence hints at a continuous-flow paradigm in which multiple motor plans evolve concurrently with the accumulation of sensory evidence. Here we employ a trial-to-trial reliability-based component analysis of encephalographic data acquired during a random-dot motion task to directly image continuous flow in the human brain. We identify three topographically distinct neural sources whose dynamics exhibit contemporaneous ramping to time-of-response, with the rate and duration of ramping discriminating fast and slow responses. Only one of these sources, a parietal component, exhibits dependence on strength-of-evidence. The remaining two components possess topographies consistent with origins in the motor system, and their covariation with RT overlaps in time with the evidence accumulation process. After fitting the behavioral data to a popular SSM, we find that the model decision variable is more closely matched to the combined activity of the three components than to their individual activity. Our results emphasize the role of motor variability in shaping RT distributions on perceptual decision tasks, suggesting that physiologically plausible computational accounts of perceptual decision-making must model the concurrent nature of evidence accumulation and motor planning.

Task dependence of decision- and choice-related activity in monkey oculomotor thalamus

Oculomotor signals circulate within putative recurrent feedback loops that include the frontal eye field (FEF) and the oculomotor thalamus (OcTh). To examine how OcTh contributes to visuomotor control, and perceptually informed saccadic choices in particular, neural correlates of perceptual judgment and motor selection in OcTh were evaluated and compared with those previously reported for FEF in the same subjects. Monkeys performed three tasks: a choice task in which perceptual decisions are urgent, a choice task in which identical decisions are made without time pressure, and a single-target, delayed saccade task. The OcTh yielded far fewer task-responsive neurons than the FEF, but across responsive pools, similar neuron types were found, ranging from purely visual to purely saccade related. Across such types, the impact of the perceptual information relevant to saccadic choices was qualitatively the same in FEF and OcTh. However, distinct from that in FEF, activity in OcTh was strongly task dependent, typically being most vigorous in the urgent task, less so in the easier choice task, and least in the single-target task. This was true for responsive and nonresponsive cells alike. Neurons with exclusively motor-related activity showed strong task dependence, fired less, and differed most patently from their FEF counterparts, whereas those that combined visual and motor activity fired most similarly to their FEF counterparts. The results suggest that OcTh activity is more distantly related to saccade production per se, because its degree of commitment to a motor choice varies markedly as a function of ongoing cognitive or behavioral demands.

Cortical and Subcortical Contributions to Short-Term Memory for Orienting Movements

Neural activity in frontal cortical areas has been causally linked to short-term memory (STM), but whether this activity is necessary for forming, maintaining, or reading out STM remains unclear. In rats performing a memory-guided orienting task, the frontal orienting fields in cortex (FOF) are considered critical for STM maintenance, and during each trial display a monotonically increasing neural encoding for STM. Here, we transiently inactivated either the FOF or the superior colliculus and found that the resulting impairments in memory-guided orienting performance followed a monotonically decreasing time course, surprisingly opposite to the neural encoding. A dynamical attractor model in which STM relies equally on cortical and subcortical regions reconciled the encoding and inactivation data. We confirmed key predictions of the model, including a time-dependent relationship between trial difficulty and perturbability, and substantial, supralinear, impairment following simultaneous inactivation of the FOF and superior colliculus during memory maintenance.

LIP activity in the interstimulus interval of a change detection task biases the behavioral response

When looking around at the world, we can only attend to a limited number of locations. The lateral intraparietal area (LIP) is thought to play a role in guiding both covert attention and eye movements. In this study, we tested the involvement of LIP in both mechanisms with a change detection task. In the task, animals had to indicate whether an element changed during a blank in the trial by making a saccade to it. If no element changed, they had to maintain fixation. We examine how the animal's behavior is biased based on LIP activity prior to the presentation of the stimulus the animal must respond to. When the activity was high, the animal was more likely to make an eye movement toward the stimulus, even if there was no change; when the activity was low, the animal either had a slower reaction time or maintained fixation, even if a change occurred. We conclude that LIP activity is involved in both covert and overt attention, but when decisions about eye movements are to be made, this role takes precedence over guiding covert attention.

A Multi-Area Stochastic Model for a Covert Visual Search Task

Decisions typically comprise several elements. For example, attention must be directed towards specific objects, their identities recognized, and a choice made among alternatives. Pairs of competing accumulators and drift-diffusion processes provide good models of evidence integration in two-alternative perceptual choices, but more complex tasks requiring the coordination of attention and decision making involve multistage processing and multiple brain areas. Here we consider a task in which a target is located among distractors and its identity reported by lever release. The data comprise reaction times, accuracies, and single unit recordings from two monkeys’ lateral interparietal area (LIP) neurons. LIP firing rates distinguish between targets and distractors, exhibit stimulus set size effects, and show response-hemifield congruence effects. These data motivate our model, which uses coupled sets of leaky competing accumulators to represent processes hypothesized to occur in feature-selective areas and limb motor and pre-motor areas, together with the visual selection process occurring in LIP. Model simulations capture the electrophysiological and behavioral data, and fitted parameters suggest that different connection weights between LIP and the other cortical areas may account for the observed behavioral differences between the animals.

Neuronal Reward and Decision Signals: From Theories to Data

Rewards are crucial objects that induce learning, approach behavior, choices, and emotions. Whereas emotions are difficult to investigate in animals, the learning function is mediated by neuronal reward prediction error signals which implement basic constructs of reinforcement learning theory. These signals are found in dopamine neurons, which emit a global reward signal to striatum and frontal cortex, and in specific neurons in striatum, amygdala, and frontal cortex projecting to select neuronal populations. The approach and choice functions involve subjective value, which is objectively assessed by behavioral choices eliciting internal, subjective reward preferences. Utility is the formal mathematical characterization of subjective value and a prime decision variable in economic choice theory. It is coded as utility prediction error by phasic dopamine responses. Utility can incorporate various influences, including risk, delay, effort, and social interaction. Appropriate for formal decision mechanisms, rewards are coded as object value, action value, difference value, and chosen value by specific neurons. Although all reward, reinforcement, and decision variables are theoretical constructs, their neuronal signals constitute measurable physical implementations and as such confirm the validity of these concepts. The neuronal reward signals provide guidance for behavior while constraining the free will to act.

Action Planning and the Timescale of Evidence Accumulation

Perceptual decisions are based on the temporal integration of sensory evidence for different states of the outside world. The timescale of this integration process varies widely across behavioral contexts and individuals, and it is diagnostic for the underlying neural mechanisms. In many situations, the decision-maker knows the required mapping between perceptual evidence and motor response (henceforth termed “sensory-motor contingency”) before decision formation. Here, the integrated evidence can be directly translated into a motor plan and, indeed, neural signatures of the integration process are evident as build-up activity in premotor brain regions. In other situations, however, the sensory-motor contingencies are unknown at the time of decision formation. We used behavioral psychophysics and computational modeling to test if knowledge about sensory-motor contingencies affects the timescale of perceptual evidence integration. We asked human observers to perform the same motion discrimination task, with or without trial-to-trial variations of the mapping between perceptual choice and motor response. When the mapping varied, it was either instructed before or after the stimulus presentation. We quantified the timescale of evidence integration under these different sensory-motor mapping conditions by means of two approaches. First, we analyzed subjects’ discrimination threshold as a function of stimulus duration. Second, we fitted a dynamical decision-making model to subjects’ choice behavior. The results from both approaches indicated that observers (i) integrated motion information for several hundred ms, (ii) used a shorter than optimal integration timescale, and (iii) used the same integration timescale under all sensory-motor mappings. We conclude that the mechanisms limiting the timescale of perceptual decisions are largely independent from long-term learning (under fixed mapping) or rapid acquisition (under variable mapping) of sensory-motor contingencies. This conclusion has implications for neurophysiological and neuroimaging studies of perceptual decision-making.

Reach target selection in humans using ambiguous decision cues containing variable amounts of conflicting sensory evidence supporting each target choice

Human subjects chose between two color-coded reach targets using multicolored checkerboard-like decision cues (DCs) that presented variable amounts of conflicting sensory evidence supporting both target choices. Different DCs contained different numbers of small squares of the two target colors. The most ambiguous DCs contained nearly equal numbers of squares of both target colors. The subjects reached as soon as they selected a target after the appearance of the DC (“choose-and-go” task). The choice behavior of the subjects showed many similarities to prior studies using other stimulus properties (e.g., visual motion coherence, brightness), including progressively longer response times and higher target-choice error rates for more ambiguous DCs. However, certain trends in their choice behavior could not be fully captured by simple drift-diffusion models. Allowing the subjects to view the DCs for a period of time before presenting the targets (“match-to-sample” task) resulted in much shorter response times overall, but also revealed a reluctance of subjects to commit to a decision about the predominant color of the more ambiguous DCs during the initial extended observation period. Model processing and simulation analyses suggest that the subjects might adjust the dynamics of their decision-making process on a trial-to-trial basis in response to the variable level of ambiguous and conflicting evidence in different DCs between trials.

A mechanism for decision rule discrimination by supplementary eye field neurons

A decision to select an action from alternatives is often guided by rules that flexibly map sensory inputs to motor outputs when certain conditions are satisfied. However, the neural mechanisms underlying rule-based decision making remain poorly understood. Two complementary types of neurons in the supplementary eye field (SEF) of macaques have been identified that modulate activity differentially to interpret rules in an ocular go-nogo task, which stipulates that the animal either visually pursue a moving object if it intersects a visible zone ('go'), or maintain fixation if it does not ('nogo'). These neurons discriminate between go and nogo rule-states by increasing activity to signal their preferred (agonist) rule-state and decreasing activity to signal their non-preferred (antagonist) rule-state. In the current study, we found that SEF neurons decrease activity in anticipation of the antagonist rule-state, and do so more rapidly when the rule-state is easier to predict. This rapid decrease in activity could underlie a process of elimination in which trajectories that do not invoke the preferred rule-state receive no further computational resources. Furthermore, discrimination between difficult and easy trials in the antagonist rule-state occurs prior to when discrimination within the agonist rule-state occurs. A winner-take-all like model that incorporates a pair of mutually inhibited integrators to accumulate evidence in favor of either the decision to pursue or the decision to continue fixation accounts for the observed neural phenomena.

Modifying cognition and behavior with electrical microstimulation: implications for cognitive prostheses

A fundamental goal of cognitive neuroscience is to understand how brain activity generates complex mental states and behaviors. While neuronal activity may predict or correlate with behavioral responses in a cognitive task, the use of electrical microstimulation presents the possibility to augment such correlational findings with direct evidence for causal relationships. Although microstimulation has been used for many years as a tool for mapping sensory and motor function, its role in learning, memory and decision-making has emerged only recently. Focal microstimulation of higher cortical areas can produce complex mental states and sequences of action. However, the relationship between the locus of stimulation and the percepts or actions evoked is often stereotyped and inflexible. The challenge is to develop stimulation systems that do not have fixed output but can flexibly contribute to complex cognitive and behavioral tasks. We discuss how microstimulation has been instrumental in manipulating a wide spectrum of cognitive functions including working memory, perceptual decisions and executive control by enhancing attention, re-ordering temporal sequence of saccades, improving associative learning or cognitive performance. For example, stimulation in prefrontal, parietal and sensory cortices may establish causal effects on decision-making, while microstimulation of inferotemporal cortex or caudate nucleus enhances associative learning. Building cognitive prosthetics based on the insights gleaned from such studies may depend on the development of multiple-input, multiple-output (MIMO) devices that allow subjects to control stimulation with their own thoughts in a closed-loop system.

Stimulation of the substantia nigra influences the specification of memory-guided saccades

In the absence of sensory information, we rely on past experience or memories to guide our actions. Because previous experimental and clinical reports implicate basal ganglia nuclei in the generation of movement in the absence of sensory stimuli, we ask here whether one output nucleus of the basal ganglia, the substantia nigra pars reticulata (nigra), influences the specification of an eye movement in the absence of sensory information to guide the movement. We manipulated the level of activity of neurons in the nigra by introducing electrical stimulation to the nigra at different time intervals while monkeys made saccades to different locations in two conditions: one in which the target location remained visible and a second in which the target location appeared only briefly, requiring information stored in memory to specify the movement. Electrical manipulation of the nigra occurring during the delay period of the task, when information about the target was maintained in memory, altered the direction and the occurrence of subsequent saccades. Stimulation during other intervals of the memory task or during the delay period of the visually guided saccade task had less effect on eye movements. On stimulated trials, and only when the visual stimulus was absent, monkeys occasionally (∼20% of the time) failed to make saccades. When monkeys made saccades in the absence of a visual stimulus, stimulation of the nigra resulted in a rotation of the endpoints ipsilaterally (∼2°) and increased the reaction time of contralaterally directed saccades. When the visual stimulus was present, stimulation of the nigra resulted in no significant rotation and decreased the reaction time of contralaterally directed saccades slightly. Based on these measurements, stimulation during the delay period of the memory-guided saccade task influenced the metrics of saccades much more than did stimulation during the same period of the visually guided saccade task. Because these effects occurred with manipulation of nigral activity well before the initiation of saccades and in trials in which the visual stimulus was absent, we conclude that information from the basal ganglia influences the specification of an action as it is evolving primarily during performance of memory-guided saccades. When visual information is available to guide the specification of the saccade, as occurs during visually guided saccades, basal ganglia information is less influential.

Probing perceptual decisions in rodents

The study of perceptual decision-making offers insight into how the brain uses complex, sometimes ambiguous information to guide actions. Understanding the underlying processes and their neural bases requires that one pair recordings and manipulations of neural activity with rigorous psychophysics. Though this research has been traditionally performed in primates, it seems increasingly promising to pursue it at least partly in mice and rats. However, rigorous psychophysical methods are not yet as developed for these rodents as they are for primates. Here we give a brief overview of the sensory capabilities of rodents and of their cortical areas devoted to sensation and decision. We then review methods of psychophysics, focusing on the technical issues that arise in their implementation in rodents. These methods represent a rich set of challenges and opportunities.

Superior colliculus and visual spatial attention

The superior colliculus (SC) has long been known to be part of the network of brain areas involved in spatial attention, but recent findings have dramatically refined our understanding of its functional role. The SC both implements the motor consequences of attention and plays a crucial role in the process of target selection that precedes movement. Moreover, even in the absence of overt orienting movements, SC activity is related to shifts of covert attention and is necessary for the normal control of spatial attention during perceptual judgments. The neuronal circuits that link the SC to spatial attention may include attention-related areas of the cerebral cortex, but recent results show that the SC's contribution involves mechanisms that operate independently of the established signatures of attention in visual cortex. These findings raise new issues and suggest novel possibilities for understanding the brain mechanisms that enable spatial attention.

Optogenetic investigation of the role of the superior colliculus in orienting movements

In vivo studies have demonstrated that the superior colliculus (SC) integrates sensory information and plays a role in controlling orienting motor output. However, how the complex microcircuitry within the SC, as documented by slice studies, subserves these functions is unclear. Optogenetics affords the potential to examine, in behaving animals, the functional roles of specific neuron types that comprise heterogeneous nuclei. As a first step toward understanding how SC microcircuitry underlies motor output, we applied optogenetics to mice performing an odor discrimination task in which sensory decisions are reported by either a leftward or rightward SC-dependent orienting movement. We unilaterally expressed either channelrhodopsin-2 or halorhodopsin in the SC and delivered light in order to excite or inhibit motor-related SC activity as the movement was planned. We found that manipulating SC activity predictably affected the direction of the selected movement in a manner that depended on the difficulty of the odor discrimination. This study demonstrates that the SC plays a similar role in directional orienting movements in mice as it does in other species, and provides a framework for future investigations into how specific SC cell types contribute to motor control.

Prediction of economic choice by primate amygdala neurons

The amygdala is a key structure of the brain's reward system. Existing theories view its role in decision-making as restricted to an early valuation stage that provides input to decision mechanisms in downstream brain structures. However, the extent to which the amygdala itself codes information about economic choices is unclear. Here, we report that individual neurons in the primate amygdala predict behavioral choices in an economic decision task. We recorded the activity of amygdala neurons while monkeys chose between saving liquid reward with interest and spending the accumulated reward. In addition to known value-related responses, we found that activity in a group of amygdala neurons predicted the monkeys' upcoming save-spend choices with an average accuracy of 78%. This choice-predictive activity occurred early in trials, even before information about specific actions associated with save-spend choices was available. For a substantial number of neurons, choice-differential activity was specific for free, internally generated economic choices and not observed in a control task involving forced imperative choices. A subgroup of choice-predictive neurons did not show relationships to value, movement direction, or visual stimulus features. Choice-predictive activity in some amygdala neurons was preceded by transient periods of value coding, suggesting value-to-choice transitions and resembling decision processes in other brain systems. These findings suggest that the amygdala might play an active role in economic decisions. Current views of amygdala function should be extended to incorporate a role in decision-making beyond valuation.

A supramodal accumulation-to-bound signal that determines perceptual decisions in humans

In theoretical accounts of perceptual decision-making, a decision variable integrates noisy sensory evidence and determines action through a boundary-crossing criterion. Signals bearing these very properties have been characterized in single neurons in monkeys, but have yet to be directly identified in humans. Using a gradual target detection task, we isolated a freely evolving decision variable signal in human subjects that exhibited every aspect of the dynamics observed in its single-neuron counterparts. This signal could be continuously tracked in parallel with fully dissociable sensory encoding and motor preparation signals, and could be systematically perturbed mid-flight during decision formation. Furthermore, we found that the signal was completely domain general: it exhibited the same decision-predictive dynamics regardless of sensory modality and stimulus features and tracked cumulative evidence even in the absence of overt action. These findings provide a uniquely clear view on the neural determinants of simple perceptual decisions in humans.