Neuronal Activity Dependent on Anticipated and Elapsed Delay in Macaque Prefrontal Cortex, Frontal and Supplementary Eye Fields, and Premotor Cortex

Neural dynamics underlying self-control in the primate subthalamic nucleus

The subthalamic nucleus (STN) is hypothesized to play a central role in neural processes that regulate self-control. Still uncertain, however, is how that brain structure participates in the dynamically evolving estimation of value that underlies the ability to delay gratification and wait patiently for a gain. To address that gap in knowledge, we studied the spiking activity of neurons in the STN of monkeys during a task in which animals were required to remain motionless for varying periods of time in order to obtain food reward. At the single-neuron and population levels, we found a cost-benefit integration between the desirability of the expected reward and the imposed delay to reward delivery, with STN signals that dynamically combined both attributes of the reward to form a single integrated estimate of value. This neural encoding of subjective value evolved dynamically across the waiting period that intervened after instruction cue. Moreover, this encoding was distributed inhomogeneously along the antero-posterior axis of the STN such that the most dorso-posterior-placed neurons represented the temporal discounted value most strongly. These findings highlight the selective involvement of the dorso-posterior STN in the representation of temporally discounted rewards. The combination of rewards and time delays into an integrated representation is essential for self-control, the promotion of goal pursuit, and the willingness to bear the costs of time delays.

Working Memory Is Complex and Dynamic, Like Your Thoughts

Working memory is where thoughts are held and manipulated. For many years, the dominant model was that working memory relied on steady-state neural dynamics. A neural representation was activated and then held in that state. However, as often happens, the more we examine working memory (especially with new technology), the more complex it looks. Recent discoveries show that working memory involves multiple mechanisms, including discontinuous bouts of spiking. Memories are also dynamic, evolving in a task-dependent manner. Cortical rhythms may control those dynamics, thereby endowing top-down "executive" control over our thoughts.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Functional and Neuropathological Evidence for a Role of the Brainstem in Autism

The brainstem includes many nuclei and fiber tracts that mediate a wide range of functions. Data from two parallel approaches to the study of autistic spectrum disorder (ASD) implicate many brainstem structures. The first approach is to identify the functions affected in ASD and then trace the neural systems mediating those functions. While not included as core symptoms, three areas of function are frequently impaired in ASD: (1) Motor control both of the limbs and body and the control of eye movements; (2) Sensory information processing in vestibular and auditory systems; (3) Control of affect. There are critical brainstem nuclei mediating each of those functions. There are many nuclei critical for eye movement control including the superior colliculus. Vestibular information is first processed in the four nuclei of the vestibular nuclear complex. Auditory information is relayed to the dorsal and ventral cochlear nuclei and subsequently processed in multiple other brainstem nuclei. Critical structures in affect regulation are the brainstem sources of serotonin and norepinephrine, the raphe nuclei and the locus ceruleus. The second approach is the analysis of abnormalities from direct study of ASD brains. The structure most commonly identified as abnormal in neuropathological studies is the cerebellum. It is classically a major component of the motor system, critical for coordination. It has also been implicated in cognitive and language functions, among the core symptoms of ASD. This structure works very closely with the cerebral cortex; the cortex and the cerebellum show parallel enlargement over evolution. The cerebellum receives input from cortex via relays in the pontine nuclei. In addition, climbing fiber input to cerebellum comes from the inferior olive of the medulla. Mossy fiber input comes from the arcuate nucleus of the medulla as well as the pontine nuclei. The cerebellum projects to several brainstem nuclei including the vestibular nuclear complex and the red nucleus. There are thus multiple brainstem nuclei distributed at all levels of the brainstem, medulla, pons, and midbrain, that participate in functions affected in ASD. There is direct evidence that the cerebellum may be abnormal in ASD. The evidence strongly indicates that analysis of these structures could add to our understanding of the neural basis of ASD.

Single caudate neurons encode temporally discounted value for formulating motivation for action

The term 'temporal discounting' describes both choice preferences and motivation for delayed rewards. Here we show that neuronal activity in the dorsal part of the primate caudate head (dCDh) signals the temporally discounted value needed to compute the motivation for delayed rewards. Macaque monkeys performed an instrumental task, in which visual cues indicated the forthcoming size and delay duration before reward. Single dCDh neurons represented the temporally discounted value without reflecting changes in the animal's physiological state. Bilateral pharmacological or chemogenetic inactivation of dCDh markedly distorted the normal task performance based on the integration of reward size and delay, but did not affect the task performance for different reward sizes without delay. These results suggest that dCDh is involved in encoding the integrated multi-dimensional information critical for motivation.

Representation of the observer's predicted outcome value in mirror and nonmirror neurons of macaque F5 ventral premotor cortex

In the search for the function of mirror neurons, a previous study reported that F5 mirror neuron responses are modulated by the value that the observing monkey associates with the grasped object. Yet we do not know whether mirror neurons are modulated by the expected reward value for the observer or also by other variables, which are causally dependent on value (e.g., motivation, attention directed at the observed action, arousal). To clarify this, we trained two rhesus macaques to observe a grasping action on an object kept constant, followed by four fully predictable outcomes of different values (2 outcomes with positive and 2 with negative emotional valence). We found a consistent order in population activity of both mirror and nonmirror neurons that matches the order of the value of this predicted outcome but that does not match the order of the above-mentioned value-dependent variables. These variables were inferred from the probability not to abort a trial, saccade latency, modulation of eye position during action observation, heart rate, and pupil size. Moreover, we found subpopulations of neurons tuned to each of the four predicted outcome values. Multidimensional scaling revealed equal normalized distances of 0.25 between the two positive and between the two negative outcomes suggesting the representation of a relative value, scaled to the task setting. We conclude that F5 mirror neurons and nonmirror neurons represent the observer's predicted outcome value, which in the case of mirror neurons may be transferred to the observed object or action.NEW & NOTEWORTHY Both the populations of F5 mirror neurons and nonmirror neurons represent the predicted value of an outcome resulting from the observation of a grasping action. Value-dependent motivation, arousal, and attention directed at the observed action do not provide a better explanation for this representation. The population activity's metric suggests an optimal scaling of value representation to task setting.

Working Memory 2.0

Working memory is the fundamental function by which we break free from reflexive input-output reactions to gain control over our own thoughts. It has two types of mechanisms: online maintenance of information and its volitional or executive control. Classic models proposed persistent spiking for maintenance but have not explicitly addressed executive control. We review recent theoretical and empirical studies that suggest updates and additions to the classic model. Synaptic weight changes between sparse bursts of spiking strengthen working memory maintenance. Executive control acts via interplay between network oscillations in gamma (30-100 Hz) in superficial cortical layers (layers 2 and 3) and alpha and beta (10-30 Hz) in deep cortical layers (layers 5 and 6). Deep-layer alpha and beta are associated with top-down information and inhibition. It regulates the flow of bottom-up sensory information associated with superficial layer gamma. We propose that interactions between different rhythms in distinct cortical layers underlie working memory maintenance and its volitional control.

Encoding of Reward and Decoding Movement from the Frontal Eye Field during Smooth Pursuit Eye Movements

Expectation of reward potentiates sensorimotor transformations to drive vigorous movements. One of the main challenges in studying reward is to determine how representations of reward interact with the computations that drive behavior. We recorded activity in smooth pursuit neurons in the frontal eye field (FEF) of two male rhesus monkeys while controlling the eye speed by manipulating either reward size or target speed. The neurons encoded the different reward conditions more strongly than the different target speed conditions. This pattern could not be explained by differences in the eye speed, since the eye speed sensitivity of the neurons was also larger for the reward conditions. Pooling the responses by the preferred direction of the neurons attenuated the reward modulation and led to a tighter association between neural activity and behavior. Therefore, a plausible decoder such as the population vector could explain how the FEF both drives behavior and encodes reward beyond behavior.SIGNIFICANCE STATEMENT Motor areas combine sensory and reward information to drive movement. To disambiguate these sources, we manipulated the speed of smooth pursuit eye movements by controlling either the size of the reward or the speed of the visual motion signals. We found that the relationship between activity in frontal eye field and eye kinematics varied: the eye speed sensitivity was larger for the different reward conditions than for the different target speed conditions. Decoders that pooled signals by the preferred direction of the neurons attenuated the reward modulations. These decoders may indicate how reward can be both encoded beyond eye kinematics at the single neuron level and drive movement at the population level.

Neurons in the crow nidopallium caudolaterale encode varying durations of visual working memory periods

Adaptive sequential behaviors rely on the bridging and integration of temporally separate information for the realization of prospective goals. Corvids' remarkable behavioral flexibility is thought to depend on the workings of the nidopallium caudolaterale (NCL), a high-level avian associative forebrain area. We trained carrion crows to remember visual items for three alternating delay durations in a delayed match-to-sample task and recorded single-unit activity from the NCL. Sample-selective delay activity, a correlate of visual working memory, was maintained throughout different working memory durations. Delay responses remained selective for the same preferred sample item across blocks with different delay durations. However, selectivity strength decreased with increasing delay durations, mirroring worsened behavioral performance with longer memory delays. Behavioral relevance of delay activity was further evidenced by reduced encoding of the preferred sample item during error trials. In addition, NCL neurons adapted their time-dependent discharges to blocks of different memory durations, so that delay duration could be successfully classified based on population activity a few trials after the delay duration switched. Therefore, NCL neurons not only maintain information from individual trials, but also keep track of the duration for which this information is needed in the context of the task. These results strengthen the role of corvid NCL in maintaining working memory for flexible control of temporally extended goal-directed behavior.

The necessity to choose causes reward-related anticipatory biasing: Parieto-occipital alpha-band oscillations reveal suppression of low-value targets

Positive outcome of actions can be maximized by choosing the option with the highest reward. For saccades, it has recently been suggested that the necessity to choose is, in fact, an important factor mediating reward effects: latencies to single low-reward targets increased with an increasing proportion of interleaved choice-trials, in which participants were free to choose between two targets to obtain either a high or low reward. Here, we replicate this finding for manual responses, demonstrating that this effect of choice is a more general, effector-independent phenomenon. Oscillatory activity in the alpha and beta band in the preparatory period preceding target onset was analysed for a parieto-occipital and a centrolateral region of interest to identify an anticipatory neural biasing mechanism related to visuospatial attention or motor preparation. When the proportion of interleaved choices was high, an increase in lateralized posterior alpha power indicated that the hemifield associated with a low reward was suppressed in preparation for reward-maximizing target selection. The larger the individual increase in lateralized alpha power, the slower the reaction times to low-reward targets. At a broader level, these findings support the notion that reward only affects responses when behaviour can be optimized to maximize positive outcome.

Cortical neurons multiplex reward-related signals along with sensory and motor information

Rewards are known to influence neural activity associated with both motor preparation and execution. This influence can be exerted directly upon the primary motor (M1) and somatosensory (S1) cortical areas via the projections from reward-sensitive dopaminergic neurons of the midbrain ventral tegmental areas. However, the neurophysiological manifestation of reward-related signals in M1 and S1 are not well understood. Particularly, it is unclear how the neurons in these cortical areas multiplex their traditional functions related to the control of spatial and temporal characteristics of movements with the representation of rewards. To clarify this issue, we trained rhesus monkeys to perform a center-out task in which arm movement direction, reward timing, and magnitude were manipulated independently. Activity of several hundred cortical neurons was simultaneously recorded using chronically implanted microelectrode arrays. Many neurons (9-27%) in both M1 and S1 exhibited activity related to reward anticipation. Additionally, neurons in these areas responded to a mismatch between the reward amount given to the monkeys and the amount they expected: A lower-than-expected reward caused a transient increase in firing rate in 60-80% of the total neuronal sample, whereas a larger-than-expected reward resulted in a decreased firing rate in 20-35% of the neurons. Moreover, responses of M1 and S1 neurons to reward omission depended on the direction of movements that led to those rewards. These observations suggest that sensorimotor cortical neurons corepresent rewards and movement-related activity, presumably to enable reward-based learning.

Dialogue on economic choice, learning theory, and neuronal representations

In recent years, two distinct lines of work have focused on the substrates of associative learning and on the mechanisms of economic decisions. While experiments often focused the same brain regions - most notably the orbitofrontal cortex - the two literatures have remained largely distinct. Here we engage in a dialogue with the intent to clarify the relationship between the two frameworks. We identify a potential correspondence between the concept of outcome defined in learning theory and that of good defined in neuroeconomics, and we specifically discuss the concept of value defined in the two frameworks. While many differences remain unresolved, a common idea is that good/outcome values are subjective, devaluation-sensitive and computed on the fly, not "cached" or pre-computed.

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.

Theta oscillation and neuronal activity in rat hippocampus are involved in temporal discrimination of time in seconds

The discovery of time cells revealed that the rodent hippocampus has information regarding time. Previous studies have suggested that the role of hippocampal time cells is to integrate temporally segregated events into a sequence using working memory with time perception. However, it is unclear whether hippocampal cells contribute to time perception itself because most previous studies employed delayed matching-to-sample tasks that did not separately evaluate time perception from working memory processes. Here, we investigated the function of the rat hippocampus in time perception using a temporal discrimination task. In the task, rats had to discriminate between durations of 1 and 3 s to get a reward, and maintaining task-related information as working memory was not required. We found that some hippocampal neurons showed firing rate modulation similar to that of time cells. Moreover, theta oscillation of local field potentials (LFPs) showed a transient enhancement of power during time discrimination periods. However, there were little relationships between the neuronal activities and theta oscillations. These results suggest that both the individual neuronal activities and theta oscillations of LFPs in the hippocampus have a possibility to be engaged in seconds order time perception; however, they participate in different ways.

Signs of timing in motor cortex during movement preparation and cue anticipation

The capacity to accurately anticipate the timing of predictable events is essential for sensorimotor behavior. Motor cortex holds an established role in movement preparation and execution. In this chapter we review the different ways in which motor cortical activity is modulated by event timing in sensorimotor delay tasks. During movement preparation, both single neuron and population responses reflect the temporal constraints of the task. Anticipatory modulations prior to sensory cues are also observed in motor cortex when the cue timing is predictable. We propose that the motor cortical activity during cue anticipation and movement preparation is embedded in a timing network that facilitates sensorimotor processing. In this context, the pre-cue and post-cue activity may reflect a presetting mechanism, complementing processing during movement execution, while prohibiting premature responses in situations requiring delayed motor output.

Modulation of Alpha Activity in the Parieto-occipital Area by Distractors during a Visuospatial Working Memory Task: A Magnetoencephalographic Study

Oscillatory brain activity is known to play an essential role in information processing in working memory. Recent studies have indicated that alpha activity (8–13 Hz) in the parieto-occipital area is strongly modulated in working memory tasks. However, the function of alpha activity in working memory is open to several interpretations, such that alpha activity may be a direct neural correlate of information processing in working memory or may reflect disengagement from information processing in other brain areas. To examine the functional contribution of alpha activity to visuospatial working memory, we introduced visuospatial distractors during a delay period and examined neural activity from the whole brain using magnetoencephalography. The strength of event-related alpha activity was estimated using the temporal spectral evolution (TSE) method. The results were as follows: (1) an increase of alpha activity during the delay period as indicated by elevated TSE curves was observed in parieto-occipital sensors in both the working memory task and a control task that did not require working memory; and (2) an increase of alpha activity during the delay period was not observed when distractors were presented, although TSE curves were constructed only from correct trials. These results indicate that the increase of alpha activity is not directly related to information processing in working memory but rather reflects the disengagement of attention from the visuospatial input.

Neurophysiology of Reward-Guided Behavior: Correlates Related to Predictions, Value, Motivation, Errors, Attention, and Action

Many brain areas are activated by the possibility and receipt of reward. Are all of these brain areas reporting the same information about reward? Or are these signals related to other functions that accompany reward-guided learning and decision-making? Through carefully controlled behavioral studies, it has been shown that reward-related activity can represent reward expectations related to future outcomes, errors in those expectations, motivation, and signals related to goal- and habit-driven behaviors. These dissociations have been accomplished by manipulating the predictability of positively and negatively valued events. Here, we review single neuron recordings in behaving animals that have addressed this issue. We describe data showing that several brain areas, including orbitofrontal cortex, anterior cingulate, and basolateral amygdala signal reward prediction. In addition, anterior cingulate, basolateral amygdala, and dopamine neurons also signal errors in reward prediction, but in different ways. For these areas, we will describe how unexpected manipulations of positive and negative value can dissociate signed from unsigned reward prediction errors. All of these signals feed into striatum to modify signals that motivate behavior in ventral striatum and guide responding via associative encoding in dorsolateral striatum.

Timing in reward and decision processes

Sensitivity to time, including the time of reward, guides the behaviour of all organisms. Recent research suggests that all major reward structures of the brain process the time of reward occurrence, including midbrain dopamine neurons, striatum, frontal cortex and amygdala. Neuronal reward responses in dopamine neurons, striatum and frontal cortex show temporal discounting of reward value. The prediction error signal of dopamine neurons includes the predicted time of rewards. Neurons in the striatum, frontal cortex and amygdala show responses to reward delivery and activities anticipating rewards that are sensitive to the predicted time of reward and the instantaneous reward probability. Together these data suggest that internal timing processes have several well characterized effects on neuronal reward processing.

Searching for the holy grail: temporally informative firing patterns in the rat

This chapter reviews our work from the past decade investigating cortical and striatal firing patterns in rats while they time intervals in the multi-seconds range. We have found that both cortical and striatal firing rates contain information that the rat can use to identify how much time has elapsed both from trial onset and from the onset of an active response state. I describe findings showing that the striatal neurons that are modulated by time are also modulated by overt behaviors, suggesting that time modulates the strength of motor coding in the striatum, rather than being represented as an abstract quantity in isolation. I also describe work showing that there are a variety of temporally informative activity patterns in pre-motor cortex, and argue that the heterogeneity of these patterns can enhance an organism's temporal estimate. Finally, I describe recent behavioral work from my lab in which the simultaneous cueing of multiple durations leads to a scalar temporal expectation at an intermediate time, providing strong support for a monotonic representation of time.

Updating dopamine reward signals

Recent work has advanced our knowledge of phasic dopamine reward prediction error signals. The error signal is bidirectional, reflects well the higher order prediction error described by temporal difference learning models, is compatible with model-free and model-based reinforcement learning, reports the subjective rather than physical reward value during temporal discounting and reflects subjective stimulus perception rather than physical stimulus aspects. Dopamine activations are primarily driven by reward, and to some extent risk, whereas punishment and salience have only limited activating effects when appropriate controls are respected. The signal is homogeneous in terms of time course but heterogeneous in many other aspects. It is essential for synaptic plasticity and a range of behavioural learning situations.

Is working more costly than waiting in monkeys?

We studied how value for instrumental action is discounted by predicted effort and delay. The monkeys were trained to perform instrumental trials that required a bar release when a visual target changed from red-to-green. There were two trial conditions. In delay trials, after the monkeys performed one instrumental trial correctly a reward was delivered 0-7 seconds later. In work trials, the monkeys had to perform 0, 1, or 2 additional instrumental trials to obtain a reward. The lengths of trials in delay matched the time it took to complete work trials. The length of delay or number of trials was indicated by a visual cue presented throughout the trial. Our hypothesis was that the monkeys would all show temporal discounting of reward in the delay trials, and that in the work trials the monkeys' performance might reflect an additional cost due to working. The error rate increased linearly as remaining cost increased for all 8 monkeys. For 4 monkeys the error rate was significantly larger in work trials than in delay trials (effort sensitive monkeys). For the other 4 monkeys there was no significant difference in error rate (effort insensitive monkeys). Since the error rate has an inverse relation with value for action, these results suggest that value is discounted hyperbolically by effort as well as by delay. Error rates generally increased as the testing sessions progressed and the total reward accumulated (i.e., effect of reward devaluation). The relative impact of delay and effort on error rates was reasonably stable within subjects. Thus, within the monkey population there seems to be a significant dichotomy in the sensitivity governing whether working is more costly than waiting, possibly arising from a constitutional or genetic trait.

The temporal derivative of expected utility: a neural mechanism for dynamic decision-making

Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, the neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making.

Evidence for a link between the experiential allocation of saccade preparation and visuospatial attention

Whether a link exists between the two orienting processes of saccade preparation and visuospatial attention has typically been studied by using either sensory cues or predetermined rules that instruct subjects where to allocate these limited resources. In the real world, explicit instructions are not always available and presumably expectations shaped by previous experience play an important role in the allocation of these processes. Here we examined whether manipulating two experiential factors that clearly influence saccade preparation--the probability and timing of saccadic responses--also influences the allocation of visuospatial attention. Occasionally, a visual probe was presented whose spatial location and time of presentation varied relative to those of the saccade target. The proportion of erroneous saccades directed toward this probe indexed saccade preparation, and the proportion of correct discriminations of probe orientation indexed visuospatial attention. Overall, preparation and attention were significantly correlated to each other across these manipulations of saccade probability and timing. Saccade probability influenced both preparation and attention processes, whereas saccade timing influenced only preparation processes. Unexpectedly, discrimination ability was not improved in those trials in which the probe triggered an erroneous saccade despite particularly heightened levels of saccade preparation. To account for our results, we propose a conceptual dual-purpose threshold model based on neurophysiological considerations that link the processes of saccade preparation and visuospatial attention. The threshold acts both as the minimum activity level required for eliciting saccades and a maximum level for which neural activity can provide attentional benefits.

Impact of size and delay on neural activity in the rat limbic corticostriatal system

A number of factors influence an animal’s economic decisions. Two most commonly studied are the magnitude of and delay to reward. To investigate how these factors are represented in the firing rates of single neurons, we devised a behavioral task that independently manipulated the expected delay to and size of reward. Rats perceived the differently delayed and sized rewards as having different values and were more motivated under short delay and big-reward conditions than under long delay and small reward conditions as measured by percent choice, accuracy, and reaction time. Since the creation of this task, we have recorded from several different brain areas including, orbitofrontal cortex, striatum, amygdala, substantia nigra pars reticulata, and midbrain dopamine neurons. Here, we review and compare those data with a substantial focus on those areas that have been shown to be critical for performance on classic time discounting procedures and provide a potential mechanism by which they might interact when animals are deciding between differently delayed rewards. We found that most brain areas in the cortico-limbic circuit encode both the magnitude and delay to reward delivery in one form or another, but only a few encode them together at the single neuron level.

Prefrontal cortex and impulsive decision making

Impulsivity refers to a set of heterogeneous behaviors that are tuned suboptimally along certain temporal dimensions. Impulsive intertemporal choice refers to the tendency to forego a large but delayed reward and to seek an inferior but more immediate reward, whereas impulsive motor responses also result when the subjects fail to suppress inappropriate automatic behaviors. In addition, impulsive actions can be produced when too much emphasis is placed on speed rather than accuracy in a wide range of behaviors, including perceptual decision making. Despite this heterogeneous nature, the prefrontal cortex and its connected areas, such as the basal ganglia, play an important role in gating impulsive actions in a variety of behavioral tasks. Here, we describe key features of computations necessary for optimal decision making and how their failures can lead to impulsive behaviors. We also review the recent findings from neuroimaging and single-neuron recording studies on the neural mechanisms related to impulsive behaviors. Converging approaches in economics, psychology, and neuroscience provide a unique vista for better understanding the nature of behavioral impairments associated with impulsivity.

A neural correlate of the processing of multi-second time intervals in primate prefrontal cortex

Several areas of the brain are known to participate in temporal processing. Neurons in the prefrontal cortex (PFC) are thought to contribute to perception of time intervals. However, it remains unclear whether the PFC itself can generate time intervals independently of external stimuli. Here we describe a group of PFC neurons in area 9 that became active when monkeys recognized a particular elapsed time within the range of 1–7 seconds. Another group of area 9 neurons became active only when subjects reproduced a specific interval without external cues. Both types of neurons were individually tuned to recognize or reproduce particular intervals. Moreover, the injection of muscimol, a GABA agonist, into this area bilaterally resulted in an increase in the error rate during time interval reproduction. These results suggest that area 9 may process multi-second intervals not only in perceptual recognition, but also in internal generation of time intervals.

Relation of ordinal position signals to the expectation of reward and passage of time in four areas of the macaque frontal cortex

Neurons in several areas of the monkey frontal cortex exhibit rank selectivity, firing differentially as a function of the stage attained during the performance of a serial order task. The activity of these neurons is commonly thought to represent ordinal position within the trial. However, they might also be sensitive to factors correlated with ordinal position including time elapsed during the trial (which is greater for each successive stage) and the degree of anticipation of reward (which probably increases at each successive stage). To compare the influences of these factors, we monitored neuronal activity in the supplementary motor area (SMA), presupplementary motor area (pre-SMA), supplementary eye field (SEF), and dorsolateral prefrontal cortex during the performance of a serial order task (requiring a series of saccades in three specified directions), a variable reward task (in which a cue displayed early in the trial indicated whether the reward received at the end of the trial would be large or small), and a long delay task (in which the monkey had simply to maintain fixation during a period of time approximating the duration of an average trial in the serial order task). We found that rank signals were partially correlated with sensitivity to elapsed time and anticipated reward. The connection to elapsed time was strongest in the pre-SMA. The connection to anticipated reward was most pronounced in the SMA and SEF. However, critically, these factors could not fully explain rank selectivity in any of the areas tested.

Heterogeneous coding of temporally discounted values in the dorsal and ventral striatum during intertemporal choice

In choosing between different rewards expected after unequal delays, humans and animals often prefer the smaller but more immediate reward, indicating that the subjective value or utility of reward is depreciated according to its delay. Here, we show that neurons in the primate caudate nucleus and ventral striatum modulate their activity according to temporally discounted values of rewards with a similar time course. However, neurons in the caudate nucleus encoded the difference in the temporally discounted values of the two alternative targets more reliably than neurons in the ventral striatum. In contrast, neurons in the ventral striatum largely encoded the sum of the temporally discounted values, and therefore, the overall goodness of available options. These results suggest a more pivotal role for the dorsal striatum in action selection during intertemporal choice.

A heterogeneous population code for elapsed time in rat medial agranular cortex

The neural mechanisms underlying the temporal control of behavior are largely unknown. Here we recorded from medial agranular cortex neurons in rats while they freely behaved in a temporal production task, the peak-interval procedure. Due to variability in estimating the time of food availability, robust responding typically bracketed the expected duration, starting some time before and ending some time after the signaled delay. These response periods provided analytic "steady state" windows during which subjects actively indicated their temporal expectation of food availability. Remarkably, during these response periods, a variety of firing patterns were seen that could be broadly described as ramps, peaks, and dips, with different slopes, directions, and times at which maxima or minima occur. Regularized linear discriminant analysis indicated that these patterns provided sufficiently reliable information to discriminate the elapsed duration of responding within these response periods. Modeling this across neuron variability showed that the utilization of ramps, dips, and peaks, with different slopes and minimal/maximal rates at different times, led to a substantial improvement in temporal prediction errors, suggesting that heterogeneity in the neural representation of elapsed time may facilitate temporally controlled behavior.

Internal-time temporal difference model for neural value-based decision making

The temporal difference (TD) learning framework is a major paradigm for understanding value-based decision making and related neural activities (e.g., dopamine activity). The representation of time in neural processes modeled by a TD framework, however, is poorly understood. To address this issue, we propose a TD formulation that separates the time of the operator (neural valuation processes), which we refer to as internal time, from the time of the observer (experiment), which we refer to as conventional time. We provide the formulation and theoretical characteristics of this TD model based on internal time, called internal-time TD, and explore the possible consequences of the use of this model in neural value-based decision making. Due to the separation of the two times, internal-time TD computations, such as TD error, are expressed differently, depending on both the time frame and time unit. We examine this operator-observer problem in relation to the time representation used in previous TD models. An internal time TD value function exhibits the co-appearance of exponential and hyperbolic discounting at different delays in intertemporal choice tasks. We further examine the effects of internal time noise on TD error, the dynamic construction of internal time, and the modulation of internal time with the internal time hypothesis of serotonin function. We also relate the internal TD formulation to research on interval timing and subjective time.

A neural representation of sequential states within an instructed task

In the study of the neural basis of sensorimotor transformations, it has become clear that the brain does not always wait to sense external events and afterward select the appropriate responses. If there are predictable regularities in the environment, the brain begins to anticipate the timing of instructional cues and the signals to execute a response, revealing an internal representation of the sequential behavioral states of the task being performed. To investigate neural mechanisms that could represent the sequential states of a task, we recorded neural activity from two oculomotor structures implicated in behavioral timing--the supplementary eye fields (SEF) and the lateral intraparietal area (LIP)--while rhesus monkeys performed a memory-guided saccade task. The neurons of the SEF were found to collectively encode the progression of the task with individual neurons predicting and/or detecting states or transitions between states. LIP neurons, while also encoding information about the current temporal interval, were limited with respect to SEF neurons in two ways. First, LIP neurons tended to be active when the monkey was planning a saccade but not in the precue or intertrial intervals, whereas SEF neurons tended to have activity modulation in all intervals. Second, the LIP neurons were more likely to be spatially tuned than SEF neurons. SEF neurons also show anticipatory activity. The state-selective and anticipatory responses of SEF neurons support two complementary models of behavioral timing, state dependent and accumulator models, and suggest that each model describes a contribution SEF makes to timing at different temporal resolutions.

Subjective neuronal coding of reward: temporal value discounting and risk

A key question in the neurobiology of reward relates to the nature of coding. Rewards are objects that are advantageous or necessary for the survival of individuals in a variety of environmental situations. Thus reward appears to depend on the individual and its environment. The question arises whether neuronal systems in humans and monkeys code reward in subjective terms, objective terms or both. The present review addresses this issue by dealing with two important reward processes, namely the individual discounting of reward value across temporal delays, and the processing of information about risky rewards that depends on individual risk attitudes. The subjective value of rewards decreases with the temporal distance to the reward. In experiments using neurophysiology and brain imaging, dopamine neurons and striatal systems discount reward value across temporal delays of a few seconds, despite unchanged objective reward value, suggesting subjective value coding. The subjective values of risky outcomes depend on the risk attitude of individual decision makers; these values decrease for risk-avoiders and increase for risk-seekers. The signal for risk and the signal for the value of risky reward covary with individual risk attitudes in regions of the human prefrontal cortex, suggesting subjective rather than objective coding of risk and risky value. These data demonstrate that important parameters of reward are coded in a subjective manner in key reward structures of the brain. However, these data do not rule out that other neurons or brain structures may code reward according to its objective value and risk.

A role for the ventral premotor cortex beyond performance monitoring

Depending on the circumstances, decision making requires either comparing current sensory information with that showed recently or with that recovered from long-term memory (LTM). In both cases, to learn from past decisions and adapt future ones, memories and outcomes have to be available after the report of a decision. The ventral premotor cortex (PMv) is a good candidate for integrating memory traces and outcomes because it is involved in working-memory, decision-making, and encoding the outcomes. To test this hypothesis we recorded the extracellular unit activity while monkeys performed 2 variants of a visual discrimination task. In one task, the decision was based on the comparison of the orientation of a current stimulus with that of another stimulus recently shown. In the other task, the monkeys had to compare the current orientation of the stimulus with the correct one retrieved from LTM. Here, we report that when the task required retrieval of the stimulus and its use in the following trials, the neurons continue encoding this internal representation together with the outcomes after the monkey has emitted the motor response. However, this codification did not occur when the stimulus was shown recently and updated every trial. These results suggest that the PMv activity represents the information needed to evaluate the consequences of a decision. We interpret these results as evidence that the PMv plays a role in evaluating the outcomes that can serve to learn and thus adapt future decision to environmental demands.

Decisions in changing conditions: the urgency-gating model

Several widely accepted models of decision making suggest that, during simple decision tasks, neural activity builds up until a threshold is reached and a decision is made. These models explain error rates and reaction time distributions in a variety of tasks and are supported by neurophysiological studies showing that neural activity in several cortical and subcortical regions gradually builds up at a rate related to task difficulty and reaches a relatively constant level of discharge at a time that predicts movement initiation. The mechanism responsible for this buildup is believed to be related to the temporal integration of sequential samples of sensory information. However, an alternative mechanism that may explain the neural and behavioral data is one in which the buildup of activity is instead attributable to a growing signal related to the urgency to respond, which multiplicatively modulates updated estimates of sensory evidence. These models are difficult to distinguish when, as in previous studies, subjects are presented with constant sensory evidence throughout each trial. To distinguish the models, we presented human subjects with a task in which evidence changed over the course of each trial. Our results are more consistent with "urgency gating" than with temporal integration of sensory samples and suggest a simple mechanism for implementing trade-offs between the speed and accuracy of decisions.

Temporal discounting and inter-temporal choice in rhesus monkeys

Humans and animals are more likely to take an action leading to an immediate reward than actions with delayed rewards of similar magnitudes. Although such devaluation of delayed rewards has been almost universally described by hyperbolic discount functions, the rate of this temporal discounting varies substantially among different animal species. This might be in part due to the differences in how the information about reward is presented to decision makers. In previous animal studies, reward delays or magnitudes were gradually adjusted across trials, so the animals learned the properties of future rewards from the rewards they waited for and consumed previously. In contrast, verbal cues have been used commonly in human studies. In the present study, rhesus monkeys were trained in a novel inter-temporal choice task in which the magnitude and delay of reward were indicated symbolically using visual cues and varied randomly across trials. We found that monkeys could extract the information about reward delays from visual symbols regardless of the number of symbols used to indicate the delay. The rate of temporal discounting observed in the present study was comparable to the previous estimates in other mammals, and the animal's choice behavior was largely consistent with hyperbolic discounting. Our results also suggest that the rate of temporal discounting might be influenced by contextual factors, such as the novelty of the task. The flexibility furnished by this new inter-temporal choice task might be useful for future neurobiological investigations on inter-temporal choice in non-human primates.

Interacting outcome retrieval, anticipation, and feedback processes in the human brain

Cognitive control is an inherently multivariate phenomenon, and its neural basis is currently unclear. Here we examined using functional magnetic resonance imaging how participants retrieve prelearnt information from memory, use this information to guide responses for an impending decision, and adjust their responses based on outcome feedback. We developed a behavioral task designed to manipulate memory outcome-retrieval load, outcome-anticipation interval, and outcome-feedback processes. This allowed us to understand the neural basis of these cognitive processes in isolation and how they interact. Extending previous work, we found a retrieval-load by outcome-feedback interaction in the left globus pallidus; an outcome-feedback by anticipation-interval interaction in the inferior prefrontal cortex; a retrieval-load by anticipation-interval interaction in the midcingulate gyrus and a load by interval by outcome interaction in the right frontal pole. These results further advance our knowledge of how fundamental cognitive processes interact physiologically to give rise to higher-level behavioral control.

Monkey supplementary eye field neurons signal the ordinal position of both actions and objects

When a monkey executes a learned series of eye movements (for example, rightward followed by upward followed by leftward), neurons in the supplementary eye field (SEF) fire differentially in conjunction with the first, second, and third movements. It has not been clear whether such ordinal position signals are truly general, accompanying all forms of sequential behavior, or accompany only learned sequences of movements. To resolve this issue, we trained monkeys to perform both a serial action task (making saccades in a fixed sequence of directions) and a serial object task (making saccades to a fixed sequence of objects). We found concordant ordinal position selectivity in the two tasks. Neuronal selectivity for the passage of time and expectation of reward could not explain such concordance. We conclude that SEF neurons signal ordinal position consistently across different task contexts. These signals presumably underlie the ability of primates including humans to perform a broad range of serial order tasks.

Valuation of uncertain and delayed rewards in primate prefrontal cortex

Humans and animals often must choose between rewards that differ in their qualities, magnitudes, immediacy, and likelihood, and must estimate these multiple reward parameters from their experience. However, the neural basis for such complex decision making is not well understood. To understand the role of the primate prefrontal cortex in determining the subjective value of delayed or uncertain reward, we examined the activity of individual prefrontal neurons during an inter-temporal choice task and a computer-simulated competitive game. Consistent with the findings from previous studies in humans and other animals, the monkey's behaviors during inter-temporal choice were well accounted for by a hyperbolic discount function. In addition, the activity of many neurons in the lateral prefrontal cortex reflected the signals related to the magnitude and delay of the reward expected from a particular action, and often encoded the difference in temporally discounted values that predicted the animal's choice. During a computerized matching pennies game, the animals approximated the optimal strategy, known as Nash equilibrium, using a reinforcement learning algorithm. We also found that many neurons in the lateral prefrontal cortex conveyed the signals related to the animal's previous choices and their outcomes, suggesting that this cortical area might play an important role in forming associations between actions and their outcomes. These results show that the primate lateral prefrontal cortex plays a central role in estimating the values of alternative actions based on multiple sources of information.

Short-term temporal discounting of reward value in human ventral striatum

Delayed rewards lose their value for economic decisions and constitute weaker reinforcers for learning. Temporal discounting of reward value already occurs within a few seconds in animals, which allows investigations of the underlying neurophysiological mechanisms. However, it is difficult to relate these mechanisms to human discounting behavior, which is usually studied over days and months and may engage different brain processes. Our study aimed to bridge the gap by using very short delays and measuring human functional magnetic resonance responses in one of the key reward centers of the brain, the ventral striatum. We used psychometric methods to assess subjective timing and valuation of monetary rewards with delays of 4.0-13.5 s. We demonstrated hyperbolic and exponential decreases of striatal responses to reward predicting stimuli within this time range, irrespective of changes in reward rate. Lower reward magnitudes induced steeper behavioral and striatal discounting. By contrast, striatal responses following the delivery of reward reflected the uncertainty in subjective timing associated with delayed rewards rather than value discounting. These data suggest that delays of a few seconds affect the neural processing of predicted reward value in the ventral striatum and engage the temporal sensitivity of reward responses. Comparisons with electrophysiological animal data suggest that ventral striatal reward discounting may involve dopaminergic and orbitofrontal inputs.

Measuring and modeling the interaction among reward size, delay to reward, and satiation level on motivation in monkeys

Motivation is usually inferred from the likelihood or the intensity with which behavior is carried out. It is sensitive to external factors (e.g., the identity, amount, and timing of a rewarding outcome) and internal factors (e.g., hunger or thirst). We trained macaque monkeys to perform a nonchoice instrumental task (a sequential red-green color discrimination) while manipulating two external factors: reward size and delay-to-reward. We also inferred the state of one internal factor, level of satiation, by monitoring the accumulated reward. A visual cue indicated the forthcoming reward size and delay-to-reward in each trial. The fraction of trials completed correctly by the monkeys increased linearly with reward size and was hyperbolically discounted by delay-to-reward duration, relations that are similar to those found in free operant and choice tasks. The fraction of correct trials also decreased progressively as a function of the satiation level. Similar (albeit noiser) relations were obtained for reaction times. The combined effect of reward size, delay-to-reward, and satiation level on the proportion of correct trials is well described as a multiplication of the effects of the single factors when each factor is examined alone. These results provide a quantitative account of the interaction of external and internal factors on instrumental behavior, and allow us to extend the concept of subjective value of a rewarding outcome, usually confined to external factors, to account also for slow changes in the internal drive of the subject.

Prefrontal coding of temporally discounted values during intertemporal choice

Reward from a particular action is seldom immediate, and the influence of such delayed outcome on choice decreases with delay. It has been postulated that when faced with immediate and delayed rewards, decision makers choose the option with maximum temporally discounted value. We examined the preference of monkeys for delayed reward in an intertemporal choice task and the neural basis for real-time computation of temporally discounted values in the dorsolateral prefrontal cortex. During this task, the locations of the targets associated with small or large rewards and their corresponding delays were randomly varied. We found that prefrontal neurons often encoded the temporally discounted value of reward expected from a particular option. Furthermore, activity tended to increase with [corrected] discounted values for targets [corrected] presented in the neuron's preferred direction, suggesting that activity related to temporally discounted values in the prefrontal cortex might determine the animal's behavior during intertemporal choice.

Recruitment of a head-turning synergy by low-frequency activity in the primate superior colliculus

Low-frequency activity within the oculomotor system helps bridge sensation and action. Given ocular stability, low-frequency activity sustained by some neurons within the intermediate and deep superior colliculus (dSC) is assumed to be separated from motor output. However, the dSC is an orienting structure and the influence of low-frequency dSC activity at other effectors remains untested. We studied this by simultaneously recording activity from saccade-related dSC neurons and electromyographic (EMG) activity from neck muscles that turn the head. Monkeys performed a gap-saccade paradigm with varying levels of reward expectancy. Despite head restraint and even for relatively small target eccentricities (<or=10 degrees ), increasing reward expectancy for a given target increased the level of low-frequency activity on dSC neurons encoding saccades to the rewarded target and increased the recruitment of a neck muscle synergy that would turn the head toward the target. The magnitude of neck muscle recruitment correlated positively on a trial-by-trial basis with the level of low-frequency dSC activity, and such correlations were optimized when neck muscle activity was shifted about 20 ms later to account for delays in the tecto-reticulo-spinal pathway. Further, dSC activity discriminated about the side of target presentation approximately 11 ms earlier than neck EMG activity. Considered alongside neck EMG responses evoked causally by SC stimulation, our results are consistent with low-frequency dSC activity recruiting a head-turning synergy. Our results support a brain stem circuit wherein the magnitude of neck muscle recruitment reflects the difference in comparative low-frequency activation across both dSCs, perhaps because of mutually inhibitory interactions within downstream head premotor circuits.

Activity of primate orbitofrontal and dorsolateral prefrontal neurons: effect of reward schedule on task-related activity

Recent studies show that task-related activity in the dorsolateral prefrontal cortex (DLPFC) is modulated by the quality and quantity of the reward, suggesting that the subject's motivational state affects cognitive operations in the DLPFC. The orbito-frontal cortex (OFC) is a possible source of motivational inputs to the DLPFC. However, it is not well known whether these two areas exhibit similar motivational effects on task-related activity. We compared motivational effects on task-related activity in these areas while a monkey performed an oculomotor delayed-response (ODR) task under two reward schedules. In the ODR-1 schedule, reward was given only after the successful completion of four consecutive trials, whereas in the ODR-2 schedule, reward was given after every correct trial. Task-related activities in both areas showed spatial selectivity. The spatial characteristics of task-related activity remained constant in both schedules. Task-related activity in both areas, especially delay-period activity, was also affected by the reward schedule and the magnitude of the activity gradually increased depending on the proximity of the reward trial in the ODR-1 schedule. More task-related OFC activities were affected by reward schedules, whereas more task-related DLPFC activities were affected by spatial factors and reward schedules. These results indicate that the OFC plays a role in monitoring the proximity of the reward trial and detecting reward delivery, whereas the DLPFC plays a role in performing cognitive operations and integrating cognitive and motivational information. These results also indicate that spatial information and the animal's motivational state independently affect neuronal activity in both areas.

On the relationship between emotion and cognition

The current view of brain organization supports the notion that there is a considerable degree of functional specialization and that many regions can be conceptualized as either 'affective' or 'cognitive'. Popular examples are the amygdala in the domain of emotion and the lateral prefrontal cortex in the case of cognition. This prevalent view is problematic for a number of reasons. Here, I will argue that complex cognitive-emotional behaviours have their basis in dynamic coalitions of networks of brain areas, none of which should be conceptualized as specifically affective or cognitive. Central to cognitive-emotional interactions are brain areas with a high degree of connectivity, called hubs, which are critical for regulating the flow and integration of information between regions.

Order-dependent modulation of directional signals in the supplementary and presupplementary motor areas

To maximize reward and minimize effort, animals must often execute multiple movements in a timely and orderly manner. Such movement sequences must be usually discovered through experience, and during this process, signals related to the animal's action, its ordinal position in the sequence, and subsequent reward need to be properly integrated. To investigate the role of the primate medial frontal cortex in planning and controlling multiple movements, monkeys were trained to produce a series of hand movements instructed by visual stimuli. We manipulated the number of movements in a sequence across trials, making it possible to dissociate the effects of the ordinal position of a given movement and the number of remaining movements necessary to obtain reward. Neurons in the supplementary and presupplementary motor areas modulated their activity according to the number of remaining movements, more often than in relation to the ordinal position, suggesting that they might encode signals related to the timing of reward or its temporally discounted value. In both cortical areas, signals related to the number of remaining movements and those related to movement direction were often combined multiplicatively, suggesting that the gain of the signals related to movements might be modulated by motivational factors. Finally, compared with the supplementary motor area, neurons in the presupplementary motor area were more likely to increase their activity when the number of remaining movements is large. These results suggest that these two areas might play complementary roles in controlling movement sequences.

The representation of economic value in the orbitofrontal cortex is invariant for changes of menu

Economic choice entails assigning values to the available options and is impaired by lesions to the orbitofrontal cortex (OFC). Recent results show that some neurons in the OFC encode the values that monkeys (Macaca mulatta) assign to different goods when they choose between them. A broad and fundamental question is how this neuronal representation of value depends on the behavioral context. Here we show that neuronal responses in the OFC are typically invariant for changes of menu. In other words, the activity of a neuron in response to one particular good usually does not depend on what other goods are available at the same time. Neurons in the OFC encode economic value, not relative preference. The fact that their responses are menu invariant suggests that transitivity, a fundamental trait of economic choice, may be rooted in the activity of individual neurons.

Neuronal activity related to anticipated and elapsed time in macaque supplementary eye field

It is essential to sense anticipated and elapsed time in our daily life. Several areas of the brain including parietal cortex, prefrontal cortex, basal ganglia and olivo-cerebellar system are known to be related to this temporal processing. We now describe a number of cells in the supplementary eye field (SEF) with phasic, delay activity and postdelay activity modulation that varied with the length of the delay period. This variation occurred in two manners. First, cells became active with the shorter delay periods (GO signal presented earlier). We call these cells "short-delay cells". Second, cells became active with the longer delay periods (GO signal presented later). We call these cells "long-delay cells". However, such changed neuronal activity did not correlate with reaction time. These results suggest that the delay-dependent activity may reflect anticipated and elapsed time during performance of a delayed saccadic eye movement.