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J Neurophysiol 94: 1469-1497, 2005. First published April 7, 2005; doi:10.1152/jn.00064.2005
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Neuronal Activity Dependent on Anticipated and Elapsed Delay in Macaque Prefrontal Cortex, Frontal and Supplementary Eye Fields, and Premotor Cortex

Matthew R. Roesch and Carl R. Olson

Center for the Neural Basis of Cognition, Mellon Institute; and Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania

Submitted 19 January 2005; accepted in final form 27 March 2005


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
In macaque monkeys performing a memory-guided saccade task for a reward of variable size, neuronal activity in several areas of frontal cortex is stronger when the monkey anticipates a larger reward. This effect might depend on either the size or the value of the reward. To distinguish between these possibilities, we recorded from neurons in frontal cortex while controlling value through a manipulation of time rather than amount. A cue presented at the beginning of each trial, predicted the length of the delay during which the monkey would have to maintain fixation before performing a saccade and receiving a reward of fixed size. Predicting a short delay had effects closely similar to those of predicting a large reward: 1) monkeys were more motivated when working for a reward at short delay, 2) neurons tended to fire more strongly before a short delay, 3) individual neurons firing more strongly before a short delay tended also to fire more strongly before a large reward, and 4) the tendency to fire more strongly before a short delay was far more pronounced in premotor areas caudal to the arcuate sulcus than in association areas rostral to it. The association areas, in contrast, were marked by a tendency for neurons to fire more strongly at the end of the long delay. We conclude that predicting a short delay, like predicting a large reward, induces an enhancement of neuronal activity related to motivational modulation of the monkey's preparatory state.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
The anticipation of reward is thought to lead to motivated behavior through a series of steps originating in the limbic system and terminating in the motor system (Hikosaka et al. 2000Go; Kalivas and Nakamura 1999Go; Mogenson et al. 1980Go; Ono et al. 2000). The limbic system is crucial for the initial stage of evaluating rewards (Roesch and Olson 2004Go; Tremblay and Schultz 1999Go, 2000Go). The transition from evaluating a reward to initiating action in pursuit of it is thought to depend on structures interposed functionally between the limbic system and motor system. Areas that may play a role in this transition include the dorsolateral prefrontal cortex (PFC), the frontal eye field (FEF), the supplementary eye field (SEF), the premotor cortex (PM), and the supplementary motor area (SMA). Neuronal activity in all of these areas is influenced both by the nature of the action the monkey is planning and by the value of the reward to which it will lead (Coe et al. 2002Go; Hikosaka and Watanabe 2000Go; Hikosaka et al. 1989Go; Kobayashi et al. 2002Go; Leon and Shadlen 1999Go; Matsumoto et al. 2003Go; Roesch and Olson 2003Go; Wallis and Miller 2003Go; Watanabe 1990Go, 1992Go, 1996Go; Watanabe et al. 2002Go). Thus it makes sense to think of them as a potential watershed between limbic evaluative functions and motor output.

The PFC, FEF, SEF, PM, and SMA are thought to serve a variety of functions with cognitive, oculomotor, and skeletomotor components. It would be surprising, for that reason, if reward-related activity took the same form or had the same significance in all of them. To test for possible differences among these areas with respect to the nature of reward-related activity, we recently carried out a comparative study in which we recorded from neurons in all of them while monkeys performed a memory-guided saccade task in which a cue presented early in each trial indicated whether the reward delivered on successful completion of the trial would be large or small (Roesch and Olson 2003Go). We found that the tendency for neurons to fire more strongly when a large reward was expected substantially increased as the recording site moved posteriorly (from PFC to FEF to PM in the lateral frontal lobe and from SEF to SMA in the medial frontal lobe).

The pattern of interareal differences observed in the previous study was of interest because it cast light on the possible significance of reward-related activity. This might either 1) represent the value of the anticipated reward in the service of an economic decision process or 2) reflect motivational modulation of the state of motor preparation, motor output, arousal, or attention. To distinguish definitively between these possibilities is not possible in experiments that manipulate only the value of the predicted reward because, under this manipulation, perceived value and motivational state are correlated (Maunsell 2004Go; Roesch and Olson 2004Go). Nevertheless, in light of the fact that reward-related activity was strongest by far in PM and SMA, which is to say in motor areas, the second interpretation, based on motivational modulation of the monkey's preparatory state, carries greatest weight.

We were concerned that these results might be specific to manipulations of value based on reward size. To address this issue, we devised an alternate approach in which the size of the reward was the same on every trial but the monkey was informed by an early cue whether the delay before delivery of the reward would be long or short. It is well known that inserting a longer anticipated delay before an anticipated reward reduces its perceived value, a phenomenon known as time-discounting (Lowenstein and Elster 1992Go). We report here that varying the delay before delivery of a constant reward had very much the same effect on neuronal activity as varying the size of a reward delivered at a constant delay. In particular, the tendency for neurons to fire more strongly after a cue that predicted a short delay was much more robust in areas behind the arcuate sulcus (FEF/PM, PM, and SMAr) than in areas in front of it (PFC, FEF, and SEF).


    METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects

Four adult male rhesus monkeys were used (Macaca mulatta; laboratory designations N, P, A, and F). Experimental procedures were approved by the Carnegie Mellon University Animal Care and Use Committee and were in compliance with the guidelines set forth in the United States Public Health Service Guide for the Care and Use of Laboratory Animals.

Preparatory surgery

At the outset of the training period, each monkey underwent sterile surgery under general anesthesia maintained with isofluorane inhalation. The top of the skull was exposed, bone screws were inserted around the perimeter of the exposed area, a continuous cap of rapidly hardening acrylic was laid down so as to cover the skull and embed the heads of the screws, a head-restraint bar was embedded in the cap, and scleral search coils were implanted on the eyes, with the leads directed subcutaneously to plugs on the acrylic cap (Robinson 1963). After initial training, recording chambers were implanted into the acrylic. At each selected site, a 2-cm-diameter disk of acrylic and skull was removed. A cylindrical recording chamber was cemented into the hole with its base just above the exposed dural membrane.

Chambers were placed either at a medial location (over SEF and SMAr) or at a lateral location (over PFC, FEF, FEF/PM, and PM). Recording was carried out from a medial chamber in monkeys A, N, and F; a left lateral chamber in monkey P; and a right lateral chamber in monkeys F and N. The medial chambers placed over SEF and SMAr were centered on the midline of the brain approximately 21 mm anterior to the Horsley–Clarke interaural plane. The lateral chambers placed over PFC, FEF, and PM were centered approximately at anterior 23 mm and lateral 23 mm.

Memory-guided saccade task

The aim of this task was to allow initial characterization of the spatial selectivity of each neuron. The monkeys performed memory-guided saccades to six targets forming a hexagonal array at an eccentricity of 10° (Fig. 1A). Each trial began with the monkey's fixating a central spot. At 500 ms after attainment of fixation, the six targets appeared. After an additional 300 ms a cue was presented for 250 ms in superimposition on one of the targets. After a random delay in the range of 500 to 1,000 ms, the fixation spot was extinguished, whereupon the monkey had to make a saccade directly to the previously cued target. Trials involving the six targets were interleaved in random order subject to the constraint that each block of six successful trials had to contain one trial involving each target. Testing continued until it was possible to identify the target eliciting maximal activity. Subsequent testing in other tasks involved this target and the one diametrically opposite with respect to the fixation point (Fig. 1A: 1 and 1', 2 and 2', or 3 and 3').



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FIG. 1. Variable-delay task and variable-reward task. A: all potential targets were at 10° eccentricity. One pair of diametrically opposed targets was used during each recording session (1 and 1', 2 and 2', or 3 and 3'). Pair was selected to include the target at the neuron's preferred location. BI: panels represent the screen in front of the monkey during successive epochs of a single representative trial. Center of the dashed circle indicates the monkey's direction of gaze during the corresponding trial epoch; the arrow indicates the direction of the eye movement. All other items represent images visible to the monkey. B: white fixation spot appeared at the center of the screen and monkey achieved foveal fixation. C: after 50 ms, the fixation spot was replaced by a cue the shape and color of which signified the length of the upcoming delay period (C1) in the variable-delay task and the size of the upcoming reward (C2) in the variable-reward task. D: after 400 ms 2 targets appeared at diametrically opposed locations. E: A cue was then presented for 250 ms in superimposition on one of the targets. F1: a delay period of 500 ms (short) or 2,500 ms (long) ensued in the variable-delay task. F2: a fixed delay of 1,500 ms ensued in the variable-reward task. G: fixation spot was extinguished. H: monkey was required to make a saccade directly to the previously cued target. I: after maintaining fixation on the target for 300–450 ms, the monkey received a juice reward.

 
Variable-delay task

The monkeys performed a memory-guided saccade task in which a cue presented early in the trial predicted a short (500 ms) or a long (2,500 ms) delay period. Essential features of the task are summarized in Fig. 1. Each trial began with onset of a central fixation spot (Fig. 1B1). At a time 50 ms after attainment of fixation, the spot was transformed to a cue the shape and color of which signified the length of the upcoming delay period (Fig. 1C1). After 400 ms two targets appeared (Fig. 1D1) at diametrically opposed locations. A directional cue identical to the fixation cue except in size was then presented for 250 ms in superimposition on one of the targets (Fig. 1E1). After a 500 ms (or 2,500 ms) delay period (Fig. 1F1), the fixation spot was extinguished (Fig. 1G1), whereupon the monkey was required to make a saccade directly to the previously cued target (Fig. 1H1) and to maintain fixation on it for 300–450 ms after saccade completion until delivery of a juice reward (Fig. 1I1). The intertrial interval after a correct trial was set to 1,000 ms whereas, after an error, either a fixation break or a wrong choice, it was set to 5,000 ms. There were four conditions representing all possible combinations of delay length (short or long) and direction (preferred or antipreferred). The conditions were interleaved in random order subject to the constraint that one trial conforming to each condition had to be completed successfully before initiation of the next block of trials. Because of this constraint, no long-term advantage attached to breaking fixation on an undesirable (long-delay) trial. The rejected condition would simply be presented repeatedly until a trial was successfully completed. To prevent confounding activity related to delay length with selectivity for the visual properties of the cues, the cue convention was reversed after each block of 40 successful trials. The collection of data from a given neuron commonly continued until 80 trials had been completed successfully.

Stimuli in the variable-delay task

The fixation spot was a 0.38° white square presented at the center of the screen. Targets were 0.38° white squares presented 10° from central fixation. The central delay cues, which spanned 0.96°, were a red square and a blue circle. The directional cue shared all of the properties of the foveal delay cue with the exception that it spanned 1.32°. The background of the display had a luminance of 1.5 cd/m2 and CIE x and y chromaticity coefficients of 0.26 and 0.26. White stimuli had a luminance of 126.5 cd/m2 and CIE x and y chromaticity coefficients of 0.28 and 0.32. Red stimuli had a luminance of 112.5 cd/m2 and CIE x and y chromaticity coefficients of 0.27 and 0.61. Blue stimuli had a luminance of 110.2 cd/m2 and CIE x and y chromaticity coefficients of 0.15 and 0.17.

Variable-reward task

Many of the neurons studied in the context of the variable-delay task were also studied in the context of the variable-reward task. In the variable-reward task, the delay was fixed at 1,500 ms, whereas the cue at the beginning of the trial predicted a big (0.3 ml) or small (0.1 ml) juice reward. Essential features of the task are summarized in Fig. 1. For further details of task design, see Roesch and Olson (2003)Go. Data collected in the context of the variable-reward task were considered in a previous paper concerned with that task (Roesch and Olson 2003Go). Here, we consider data from the variable-reward task solely in connection with the question whether neurons sensitive to delay length were also sensitive to reward size.

Order of tasks

Neuronal activity was first monitored in the context of the memory-guided saccade task with reward size and delay length fixed and with targets at six locations spaced at 60° intervals around fixation (Fig. 1A). Any neuron appearing to exhibit task-related activity in this task was selected for study in the variable-delay task and the variable-reward task. In these tasks, the possible target locations were confined to the neuron's preferred direction (as determined in the memory-guided saccade task) and the opposite direction. The order in which the two tasks were run alternated across sessions. Some neurons were studied in the context of only one of the tasks because recording instability or satiation of the monkey prevented running both.

Single-neuron recording

At the beginning of each day's session, a varnish-coated tungsten microelectrode with an initial impedance of several megohms at 1 kHz (Frederick Haer, Bowdoinham, ME) was advanced vertically through the dura into the immediately underlying cortex. The dura was debrided at intervals commonly spanning a few months to ensure penetrability by the electrode. The electrode could be placed reproducibly at points forming a square grid with 1-mm spacing (Crist et al. 1988Go). The action potentials of a single neuron were isolated from the multineuronal trace by means of an online spike-sorting system using a template-matching algorithm (Signal Processing Systems, Prospect, Australia). The spike-sorting system, on detection of an action potential, generated a pulse the time of which was stored with 1-ms resolution.

Electromyographic measurements

Adhesive surface electrodes were placed on the shaved skin overlying the right splenius capitus and masseter muscles. The voltage threshold was set as low as possible subject to the constraint that the voltage did not cross threshold at rest. Muscle activity was stored as time-marked records of threshold crossings. From these, we constructed histograms representing the mean instantaneous threshold-crossing rate as a function of time during the trial under each condition.

Experimental control and data collection

All aspects of the behavioral experiment, including presentation of stimuli, monitoring of eye movements, monitoring of neuronal activity, and delivery of reward, were under the control of a Pentium-based computer running Cortex software provided by R. Desimone, Laboratory of Neuropsychology, National Institute of Mental Health. Eye position was monitored by means of a scleral search coil system (Riverbend Instruments, Birmingham, AL). The X and Y coordinates of eye position were stored with 4-ms resolution. Stimuli generated by an active matrix LCD projector were rear-projected on a frontoparallel screen 25 cm from the monkey's eyes.

Analysis of the dependency of behavior on delay length

We used paired t-tests to compare, across sessions, the session means of the following measures obtained on short-delay versus long-delay trials: reaction time, error rate, and fixation-break rate. Reaction time was defined as the delay from offset of the fixation spot to the moment when the eye left the central fixation window. Error rate was defined as the number of trials on which a saccade was directed to the wrong target expressed as a percentage of all trials on which a saccade was directed to either target. Fixation-break rate was defined as the percentage of all trials on which the eye left the central fixation window at any time before offset of the fixation spot.

Analysis of the dependency of firing rate on task factors

We used two-factor ANOVAs to analyze the dependency of the firing rate of each neuron on delay length and response direction. We independently analyzed data from seven trial epochs: 1) from delay cue onset to directional cue onset (700 ms), 2) from onset to offset of the directional cue (250 ms), 3) 250 ms beginning with directional cue offset, 4) 250 ms before fixation spot offset, 5) 200 ms before saccade initiation, 6) from saccade onset to 100 ms after saccade completion, 7) 100 ms before to 100 ms after initiation of reward delivery. In all tests, the criterion for statistical significance was taken as P ≤ 0.05.

Assessing contribution of reaction time to activity related to delay length

To determine whether neuronal activity continued to depend on delay length when the effects of behavioral reaction time were factored out, we performed a multivariate regression analysis, fitting three models

1) Y = a0 + a1RT

2)Y = a0 + a2DELAY

3)Y = a0 + a1RT + a2DELAY

where Y is the firing rate measured from onset of the delay cue to offset of the fixation spot and RT is the behavioral reaction time. The variable DELAY was set to 1 or 0 for trials with short or long delays, respectively. To determine whether adding the variable DELAY produced a significant improvement in performance, we compared model 3 to model 1. To determine whether adding the variable RT produced a significant improvement, we compared model 3 to model 2. Significance was assessed with an F-test using

where k = 1 is the difference in degrees of freedom between the two models, n = 1 is the number of neurons, and m is the number of trials on which the analysis was based. SSfull and SSred are the residual sums of squares resulting when the data were fitted with the full model (model 1) and the reduced model (model 2 or 3), respectively. The criterion for statistical significance was taken as P ≤ 0.05.

Localization of recording sites

To characterize the location of the recording sites relative to gross anatomical landmarks, we projected the sites onto structural magnetic resonance (MR) images (Fig. 2). The images were collected by use of a Bruker BioSpin 4.7 T magnet in which the anesthetized monkey was supported by an MR-compatible stereotaxic device. Fiducial marks made visible by means of a contrast agent included the centers of the ear bars and selected locations inside the recording chamber. Frontoparallel 2-mm-thick slices spanning the entire brain were collected. In addition, 2-mm-thick slices were collected parallel to the cortical surface underlying each lateral chamber. To determine the location of recording sites relative to functional divisions of cortex, we mapped out regions under each chamber from which motoric responses (eye, face, and limb movements) could be elicited at low threshold (≤40 µA) by electrical microstimulation (1.65-ms biphasic pulses delivered through the recording microelectrode at a frequency of 300 Hz in 200-ms-long trains).



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FIG. 2. Recording sites in all monkeys were localized relative to gross morphological landmarks visible in structural magnetic resonance (MR) images and relative to regions from which motor responses could be elicited by low-threshold electrical microstimulation (200-ms, 300-Hz trains of 1.65-ms biphasic pulses at currents ≤40 µA). A: MR slice tangential to the surface of the cortex underlying the lateral chamber of monkey N. Black dots indicate MR-visible fiducial markers at known locations relative to the recording grid. Black rectangles indicate, for comparison, the approximate locations of fiducial markers in the midline chamber (this is for illustrative purposes only). Localization of midline recording sites was accomplished by use of a separate set of frontoparallel slices. AS, arcuate sulcus; PS, principal sulcus. B: results of microstimulation mapping in the lateral chamber of monkey N are projected onto an enlarged view of the cortex surrounding the arcuate (AS) and principal (PS) sulci. Symbols indicate particular patterns of motor response as defined in the legend at the bottom of the figure. Dashed perimeters enclose regions [dorsolateral prefrontal cortex (PFC), the frontal eye field (FEF), FEF/premotor cortex (PM), and PM] defined by stimulation-based criteria described in the text. C: results of microstimulation mapping in the midline chamber are projected onto an enlarged dorsal view of the underlying cortex. Anterior is to the right. Dashed perimeters enclose the SEF as defined by stimulation-based criteria described in the text. Black rectangles represent MR-visible fiducial markers at known locations relative to the recording grid in the midline chamber. Dashed vertical line indicates the frontal level of the genu of the arcuate sulcus.

 
We assigned recording sites to six areas according to the following criteria (Fig. 2). Dorsolateral prefrontal cortex (PFC): a region in front of the arcuate sulcus and surrounding and within the principal sulcus in which microstimulation did not elicit movements. Frontal eye field (FEF): a region rostral to and in the anterior bank of the arcuate sulcus in which microstimulation elicited saccades and not movements of the face or limbs. Recording sites in the FEF were all within 4 mm of the cortical surface at locations where microstimulation at the corresponding depth elicited eye movements. Premotor cortex (PM): a region caudal to the arcuate sulcus in which microstimulation elicited face or limb movements and not saccades. Transitional cortex (FEF/PM): a region immediately caudal to the arcuate sulcus and rostral to the pure face–limb zone in which electrical stimulation elicited both eye movements and movements of the face or limbs. Recording sites in FEF/PM were all within 4 mm of the cortical surface at locations where microstimulation at the corresponding depth elicited eye and face–limb movements. On the grounds of its location behind the arcuate sulcus, this cortex belongs to the premotor area. However, we have designated it as an independent zone with the possibility in mind that its distinct traits, as revealed by electrical stimulation, might be accompanied by some differential form of sensitivity to delay-predicting cues. The finding of an oculomotor representation in PM is not without precedent (Fujii et al. 1998Go, 2000Go). Supplementary eye field (SEF): a region, located rostral to the genu of the arcuate sulcus and extending 2–5 mm from the hemispheric midline, in which microstimulation elicited saccades. Rostral supplementary motor area (SMAr): a region immediately caudal to the SEF in which microstimulation elicited movements of the face and limbs.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Overview

In the following sections, we will describe the impact of delay length on behavior and neuronal activity in PFC, FEF, FEF/PM, PM, SEF, and SMAr. At each stage of analysis, we will consider (first) effects related to anticipated delay and (second) effects related to elapsed delay. We will examine the impact of anticipated delay by comparing short-delay to long-delay trials during epochs aligned on the delay-predicting cue and preceding the moment at which, in short-delay trials, the signal to respond was given. We will examine the impact of elapsed delay by comparing short-delay to long-delay trials during epochs near in time to the response and aligned on response initiation. The analyses concerned with anticipated and elapsed delay involve comparing roughly identical periods of neuronal activity, as observed on short-delay trials, to nonoverlapping early and late periods of activity, as observed on long-delay trials. Thus the two analyses are not entirely independent. However, as will be seen, they reveal qualitatively different effects.

Behavior: anticipated delay

To analyze the impact of anticipated delay on behavior we assessed how fixation breaks were distributed across time during the early part of the trial under short- versus long-delay conditions. The results, shown in Fig. 3C, indicate 1) that fixation breaks were more frequent under long- than under short-delay conditions and 2) that the tendency to break fixation declined over the course of the trial under both conditions. To determine whether the impact of anticipated delay length was significant, we compared the fixation-break frequencies (number of trials prematurely terminated by cessation of fixation expressed as a percentage of all trials) observed under short- and long-delay conditions in each monkey during the first 1,000 ms beginning at the presentation of the delay cue (Fig. 3D). This analysis epoch spans a period in which equivalent events occurred at equivalent times on short- and long-delay trials, with the only difference between them ascribed to anticipation. The tendency for fixation breaks to occur more often in anticipation of a long delay was present and significant in every monkey (two-tailed paired t-test, P < 0.05) and was highly significant in data collapsed across monkeys (P < 0.001). We conclude that the monkeys were less motivated to perform the task when anticipating a long delay than when anticipating a short delay.



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FIG. 3. Impact of the duration of the delay on behavior. A: error rate. Height of each bar indicates the mean across all recording sessions in all monkeys of the error rates on short-delay (black) and long-delay (gray) trials. Each value was obtained by first computing the mean for each session and then taking the average of the session means. Error bars indicate SE for the latter step. *P < 0.0001. B: mean behavioral reaction times on short-delay (black) and long-delay (gray) trials were computed similarly. *P < 0.0001. C: distribution of fixation breaks across the 4,000 ms period extending from initiation of fixation (B in Fig. 1) to offset of the fixation spot (G in Fig. 1). For each 500-ms epoch in short-delay (black square) and long-delay (gray circle) trials, the height of the symbol indicates the percentage of all fixation breaks that occurred during that epoch. Each value was obtained by first computing the mean for each session and then taking the average of the session means. Error bars indicate SE for the latter step. D: means across all recording sessions for individual monkeys. Error rate and reaction time were computed as above. Fixation-break rate, computed independently for short- and long-delay conditions, was the percentage of trials on which the monkey broke fixation at any point during the first 1,000 ms period extending from fixation attainment to offset of the fixation spot. An asterisk next to any value in the short-delay column indicates that this value differed significantly from the juxtaposed value in the long-delay column (t-test comparing the distributions of session means, P < 0.05).

 
Behavior: elapsed delay

We will refer to effects occurring at the end of the trial (and revealed by comparing measures from short- and long-delay trials taken around the time of the behavioral response) as related to "elapsed delay." This is an expositional tool; it does not imply that the effects were a direct consequence of elapsed delay. There is no sure way of establishing whether effects present at the time of the response depended on the monkey's experiencing the antecedent delay or, alternatively, were a result of the monkey's having been put by the delay cue into a state that persisted until the end of the trial. With this qualification, we note that behavioral measures taken at the end of the trial were sensitive to the duration of the antecedent delay. This was evident in two behavioral measures computed for every neuronal data collection session. The error rate (percentage of trials when the incorrect target was selected relative to all trials when one target or the other was selected) was lower on short-delay (0.6%) than on long-delay (2.0%) trials (Fig. 3A). This trend was present in data from every monkey, achieving significance (two-tailed paired t-test, P < 0.05) in three out of four of them (Fig. 3D), and was highly significant in data collapsed across all monkeys (P < 0.0001). The average behavioral reaction time was faster on short-delay (233 ms) than on long-delay (248 ms) trials (Fig. 3B). This trend was present and achieved significance (two-tailed paired t-test, P < 0.05) in three out of four monkeys (Fig. 3D), and was highly significant in data collapsed across all monkeys (P < 0.0001). These results indicate that monkeys were in a state of heightened preparation (reflected by a simultaneous improvement of accuracy and speed) after a short delay as compared to a long delay.

Neuronal data analysis: anticipated delay

To determine whether neuronal activity was influenced by the length of the anticipated delay, we compared neuronal activity occurring before the imperative command (offset of the fixation spot) on short-delay trials to neuronal activity occurring during the identical period (at the end of which the fixation spot remained on) on long-delay trials. Neurons in many frontal areas exhibited activity related to the length of the expected delay. This activity commonly took the form of a main effect (with the net firing rate higher or lower on short-delay trials) and less frequently took the form of an interaction effect (with the strength of the directional signal stronger or weaker on short-delay trials). For the neurons illustrated in Fig. 4, A and B, the net firing rate during the "anticipated-delay" comparison period (time-locked to delay-cue onset and highlighted in yellow) was higher on short-delay trials (top row for each neuron) than on long-delay trials (bottom row for each neuron).



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FIG. 4. Data from 2 neurons exhibiting significant effects of delay length. Yellow: a period in which trials differed with respect to the length of the anticipated delay (data aligned on delay-cue onset). Green: a period around the time of the response when trials differed with respect to the duration of the antecedent elapsed delay (data aligned on saccade initiation). A: data from a neuron in PM that fired more strongly in anticipation of a short delay (yellow panels). Other functional attributes included firing more strongly after a short delay had elapsed (green panels) and exhibiting direction selectivity during the postsaccadic period. B: data from a neuron in the FEF that fired more strongly, on trials requiring a leftward response, at the end of a long delay (green panels). Other functional attributes included firing more strongly in anticipation of a short delay (yellow panels) and firing much more strongly throughout the delay period when the impending saccade was in a leftward directon.

 
In considering results from each cortical area, we will characterize the impact of anticipated delay on firing rate by proceeding through three steps. 1) Population histograms. The aim of this step is to indicate qualitatively how the length of predicted delay affected the population firing rate and the population directional signal. Population averaging, although informative, could lead to an underestimate of the strength of delay-selective activity if opposite signals carried by different neurons canceled out at the stage of averaging. The next steps of analysis address this issue. 2) Individual neurons by epoch. The aim of this step is to indicate whether effects evident at the level of the population were statistically significant at the level of individual neurons during successive epochs of the analysis period. We will assess how many neurons showed significant increases or decreases in firing rate on short-delay as compared with long-delay trials, and how many showed significant increases or decreases in the strength of the directional signal. The epochs of interest are: (I) from delay cue onset to directional cue onset (700 ms), (II) from onset to offset of the directional cue (250 ms), and (III) 250 ms beginning with directional cue offset. 3) Individual neurons across a long anticipatory epoch. To complement the analysis by short epochs, which gives good temporal resolution but low statistical sensitivity, we will also characterize the delay-related activity of each neuron by considering its firing rate during the period between onset of the delay cue and a point in time 250 ms after offset of the directional cue. This statistically robust but time-insensitive step will provide a single measure for each neuron to be used in comparing across areas the percentage of neurons sensitive to anticipated delay.

Neuronal data analysis: elapsed delay

On examination of histograms representing the activity of single neurons, it was evident that the firing rate at the end of the delay period, around the time of the saccade (epoch highlighted in green in Fig. 4), could differ according to whether the antecedent delay had been long or short. The neuron of Fig. 4A clearly fired more strongly at the end of a short than at the end of a long delay. In contrast, on trials requiring a response in the preferred (leftward) direction, the neuron of Fig. 4B fired more strongly at the end of a long delay. To analyze the nature and rate of incidence of effects dependent on elapsed delay, we will proceed through three steps of analysis. 1) Population histograms. These depict activity during a 1,500 ms epoch beginning 500 ms before saccade initiation (righthand column in Figs. 5 9). The beginning of this epoch coincides with a point in time about 250 ms after offset of the directional cue on short-delay trials and 2,250 ms after offset of the directional cue on long-delay trials. 2) Individual neurons by epoch. We will consider whether firing rate depended on delay length or its interaction with response direction during late epochs of the trial, including epoch IV (250 ms before fixation spot offset), epoch V (200 ms before saccade initiation), epoch VI (from saccade onset to 100 ms after saccade completion), and epoch VII (from 100 ms before to 100 ms after initiation of reward delivery). 3) Individual neurons across a long premovement epoch. To obtain one robust statistical measure for each neuron, to facilitate comparison across areas, we will determine whether the firing rate of each neuron depended significantly on delay length or its interaction with response direction during a long epoch beginning 250 ms before the imperative cue (offset of the fixation spot) and ending with saccade initiation.



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FIG. 5. Impact of delay length on 204 PFC neurons. A: curves representing mean population firing rate as a function of time under the 4 task conditions defined by 2 lengths of delay (short = blue, long = red) and 2 directions (preferred = thick, antipreferred = thin). Data to the left are aligned on the onset of the directional cue (Fig. 1E); data to the right are aligned on saccade initiation (Fig. 1H). B: difference in population firing rate between short-delay and long-delay conditions as a function of time during the trial. Positive (blue) values indicate that the firing rate was higher on short-delay trials. C: frequency of cases in which there was a significant main effect of delay length on neuronal firing rate (blue = stronger firing on short-delay trials; red = stronger firing on long-delay trials) during 7 trial epochs (I–VII) indicated at the bottom of the figure. D: difference in population directional signal between short-delay and long-delay conditions as a function of time during the trial. Positive (blue) values indicate that the directional signal was stronger on short-delay trials. Directional signal was taken as the firing rate on preferred-direction trials minus the firing rate on antipreferred-direction trials. E: frequency of cases in which firing rate depended significantly on the interaction between delay length and response direction (blue = stronger directional signal on short-delay trials; red = stronger directional signal on long-delay trials) during 7 trial epochs (I–VII) indicated at the bottom of the figure.

 


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FIG. 9. Impact of variable delay on 147 SEF neurons. Same conventions as in Fig. 5.

 
Prefrontal cortex (PFC): anticipated delay

POPULATION. We collected data from 204 neurons in the PFC of two monkeys (Table 1). As a basis for qualitative assessment of the effect of anticipated delay on the activity of these neurons, we constructed population curves representing firing rate as a function of time under the four trial conditions (Fig. 5A). Population histograms shown to the left (Fig. 5A1) represent activity subject to influence by the duration of the anticipated delay. In these displays, aligned on cue onset, thick and thin lines represent population activity on trials requiring responses in the preferred and antipreferred directions, respectively. Neuronal activity was strongly affected by response direction as indicated by the consistent elevation of thick above thin lines after appearance of the directional cue. Effects of anticipated delay length would be manifest as differences in firing rate between trials in which the response direction (indicated by line thickness) was the same but expected delay length (indicated by color) was different. It is evident from the close coincidence of red and blue curves that the impact of anticipated delay on firing rate was weak. To characterize the time course of activity modulated by anticipated delay length, we independently computed indices reflecting 1) the impact of expected delay length on net firing rate independent of direction and 2) the impact of expected delay length on the strength of the directional signal. The impact on net firing rate was measured with an index representing the average amount by which the firing rate increased under the short-delay condition. It was computed as (SP + SA – LP – LA)/2, where SP is the firing rate under the short-delay, preferred-direction condition; LA is the firing rate under the long-delay, antipreferred-direction condition; and so on. The impact of anticipated delay length on firing rate was variable over time and negligible in strength (Fig. 5B1). The effect of delay on the directional signal was represented by an index that corresponded to the average amount by which short-delay caused the difference in firing rate between preferred-direction and antipreferred-direction trials to increase. It was computed as (SP – SA – LP + LA)/2. This index hovered around zero before the directional signal and then became slightly positive (Fig. 5D1).


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TABLE 1. Anticipated delay: incidence of significant effects in the long anticipatory epoch

 
INDIVIDUAL NEURONS BY EPOCH. To determine whether effects present in the population were also observable at the level of individual neurons, we analyzed data from each neuron during three trial epochs (I–III) defined in METHODS and depicted along the timeline at the base of Fig. 5E1. For each epoch, we carried out an ANOVA with firing rate as the dependent variable and with delay length and response direction as factors.

   Main effect of delay.
Counts of neurons exhibiting a significant main effect of delay length on firing rate are shown in Fig. 5C1, where blue (or red) symbols represent the percentage of cases in which firing was increased (or decreased) for short compared with long delay trials. During each epoch (I–III), the full count of neurons exhibiting a main effect of delay (whether this took the form of significantly stronger or significantly weaker firing under the short-delay as compared with the long-delay condition) was significantly in excess of the frequency (0.05) expected by chance from type 1 errors ({chi}2 test, P < 0.05). This observation can be reconciled with the observation that there was little effect of delay on the average activity of the neuronal population (as indicated in the population histogram) by noting that neurons increasing and decreasing their firing rate on short-delay trials were equally common, so that the effects canceled at the population level. During no epoch was there a significant difference in number between neurons firing more strongly and those firing more weakly before a short delay ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
Counts of neurons exhibiting a significant interaction effect are shown in Fig. 5E1, where blue (or red) symbols represent the percentage of cases in which the directional signal was stronger (or weaker) on short-delay trials. Counts during epoch I necessarily represent type 1 errors because it was only after this epoch that the directional cue appeared. During epoch III, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity before a short delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG ANTICIPATORY EPOCH. To generate for each neuron a single statistical measure of the impact of predicted delay length on the neuronal firing rate, we carried out an ANOVA using, as the dependent variable, the mean firing rate across the entire period from onset of the delay cue to 250 ms after offset of the directional cue, taking as factors both expected delay length and instructed response direction. The results are presented in Table 1 and Fig. 11.



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FIG. 11. Frequency with which neuronal activity, as measured across the long anticipatory epoch (delay-cue onset to 250 ms after directional-cue offset), depended on delay length (A), direction (B), or their interaction (C). A: black (or gray) bars indicate the percentage of neurons in which the firing rate was significantly higher (or lower) under the short-delay condition. B: black (or gray) bars indicate the percentage of neurons in which the firing rate was significantly higher (or lower) on trials requiring a contraversive saccade. C: black (or gray) bars indicate the percentage of neurons in which there was a significant interaction such that the directional signal was stronger (or weaker) under the short-delay condition.

 
   Main effect of delay.
There was a significant main effect of expected delay in 10% of PFC neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The difference in frequency between neurons firing more strongly and those firing more weakly before a short delay was not significant ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). The difference in frequency between cases in which direction selectivity was stronger before a short delay and those in which it was weaker was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among PFC neurons, the length of the anticipated delay exerted a subtle influence on firing rate. A few neurons fired more strongly and a few more weakly in anticipation of a short delay.

Prefrontal cortex (PFC): elapsed delay

POPULATION. In curves representing the population firing rate as a function of time, it is evident that activity was enhanced after a long delay as compared to a short delay (Fig. 5A2). This was true both when the response was in the neuron's preferred direction (the thick red curve lies above thick blue curve) and when it was in the opposite direction (the thin red curve lies above the thin blue curve). The enhancement was present before saccade initiation but was most marked after the saccade (downward-directed red regions in the difference histogram of Fig. 5B). In contrast to the impact of elapsed delay on net firing rate, there was almost no effect on the strength of the directional signal (Fig. 5D2).

INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 5, C2 and E2, can be summarized in the following terms.

   Main effect of delay.
During each epoch (IV–VII), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During epochs IV and VI, the preponderance of neurons that fired more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During epochs IV, VI, and VII, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity after a long delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG PREMOVEMENT EPOCH. The results, presented in Table 3 and Fig. 17, can be summarized in the following terms.


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TABLE 3. Elapsed delay: incidence of significant effects in the long premovement epoch

 


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FIG. 17. Frequency with which neuronal activity at the end of the elapsed delay (epoch beginning 250 ms before fixation-spot offset and ending with saccade initiation) depended on delay length (A), response direction (B), or their interaction (C). Conventions as in Fig. 11.

 
   Main effect of delay.
There was a significant main effect of expected delay in 24% of PFC neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were significantly more common than expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons in which the directional signal was stronger after a long delay was significant ({chi}2 test, P < 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among PFC neurons, the length of the elapsed delay exerted a substantial influence on firing rate. A majority of delay-sensitive neurons fired more strongly after a long delay.

Frontal eye field (FEF): anticipated delay

POPULATION. We collected data from 124 neurons in the FEF of three monkeys (Table 1). Curves representing the activity of this population as a function of time during the trial indicate that the level of anticipated delay exerted only minor effects on neuronal activity early in the trial (Fig. 6A1).



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FIG. 6. Impact of variable delay on 124 FEF neurons. Same conventions as in Fig. 5.

 
INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 6, C1 and E1, can be summarized in the following terms.

   Main effect of delay.
During each epoch (I–III), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons firing more strongly and those firing more weakly before a short delay ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
During no epoch was the proportion of neurons exhibiting an interaction effect significantly in excess of the frequency expected by chance ({chi}2 test, P > 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity before a short delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG ANTICIPATORY EPOCH. The results, presented in Table 1 and Fig. 11, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 19% of FEF neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The difference in frequency between neurons firing more strongly and those firing more weakly before a short delay was not significant ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). The difference in frequency between cases in which direction selectivity was stronger before a short delay and those in which it was weaker was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among FEF neurons, the length of the anticipated delay exerted a moderate influence on firing rate. Some neurons fired more strongly and some more weakly in anticipation of a short delay.

Frontal eye field (FEF): elapsed delay

POPULATION. Population activity was enhanced after a long delay as compared to a short delay (Fig. 6A2). The time course of the enhancement is summarized in Fig. 6B2. There was no consistent effect of elapsed delay on the strength of the directional signal (Fig. 6D2).

Individual neurons by epoch. The results, presented in Fig. 6, C2 and E2, can be summarized in the following terms.

   Main effect of delay.
During each epoch (IV–VII), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During epochs IV and VI, the preponderance of neurons that fired more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During epochs IV–VI, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity after a long delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG PREMOVEMENT EPOCH. The results, presented in Table 3 and Fig. 17, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 43% of FEF neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were significantly more common than expected by chance ({chi}2 test, P < 0.05). The difference in number between neurons exhibiting stronger and weaker direction selectivity after a long delay was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among FEF neurons, the length of the elapsed delay exerted a substantial influence on firing rate. A majority of delay-sensitive neurons fired more strongly after a long delay.

FEF/PM: anticipated delay

POPULATION. We collected data from 34 neurons in FEF/PM of two monkeys (Table 1). Curves representing the activity of this population as a function of time during the trial indicate that the length of anticipated delay exerted a strong effect on neuronal activity (Fig. 7A1). The net firing rate was elevated shortly after the presentation of cues predicting short delays and the elevation persisted throughout the delay period (Fig. 7B1).



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FIG. 7. Impact of variable delay on 34 FEF/PM neurons. Same conventions as in Fig. 5.

 
INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 7, C1 and E1, can be summarized in the following terms.

   Main effect of delay.
During each epoch (I–III), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During each epoch, the preponderance of neurons firing more strongly before a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During no epoch was the proportion of neurons exhibiting an interaction effect significantly in excess of the frequency expected by chance ({chi}2 test, P > 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity before a short delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG ANTICIPATORY EPOCH. The results, presented in Table 1 and Fig. 11, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 24% of FEF/PM neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly before a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). The difference in frequency between cases in which direction selectivity was stronger before a short delay and those in which it was weaker was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among FEF/PM neurons, the length of the anticipated delay exerted a substantial influence on firing rate. Most delay-sensitive neurons fired more strongly in anticipation of a short delay.

FEF/PM: elapsed delay

POPULATION. Population activity was markedly enhanced toward the end of a short delay versus toward the end of a long delay (Fig. 7A2). The sign of the effect reversed after saccade completion, as indicated by the transition from an upward-directed blue region to a downward-directed red region in Fig. 7B2. There was an apparent slight tendency for the directional signal to be stronger after a short delay (Fig. 7D2).

Individual neurons by epoch. The results, presented in Fig. 7, C2 and E2, can be summarized in the following terms.

   Main effect of delay.
During epochs IV–VI, the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05) and the preponderance of neurons that fired more strongly after a short delay was significant ({chi}2 test, P < 0.05). During epoch VII, neurons that fired more strongly after a long delay were significantly preponderant.

   Interaction between delay and direction.
During epoch IV, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity after a long delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG PREMOVEMENT EPOCH. The results, presented in Table 3 and Fig. 17, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of elapsed delay in 38% of FEF/PM neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly after a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). There was no difference in number between neurons exhibiting stronger and weaker direction selectivity after a long delay. These results did not differ significantly between monkeys.

SUMMARY. Among FEF/PM neurons, the length of the elapsed delay exerted a substantial influence on firing rate. Before and during the saccade, a majority of delay-sensitive neurons fired more strongly after a short delay. During a period beginning after the saccade and extending through reward delivery, this pattern was reversed.

Premotor cortex (PM): anticipated delay

POPULATION. We collected data from 76 neurons in PM of two monkeys (Table 1). Curves representing the activity of this population as a function of time during the trial indicate that the length of the anticipated delay exerted a strong effect on neuronal activity (Fig. 8A1). The net firing rate was sharply elevated throughout the period after presentation of the short-delay cue (Fig. 8B1). The strength of the directional signal was also moderately elevated (Fig. 8D1).



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FIG. 8. Impact of variable delay on 76 PM neurons. Same conventions as in Fig. 5.

 
INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 8, C1 and E1, can be summarized in the following terms.

   Main effect of delay.
During each epoch (I–III), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During each epoch, the preponderance of neurons firing more strongly before a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During no epoch was the proportion of neurons exhibiting an interaction effect significantly in excess of the frequency expected by chance ({chi}2 test, P > 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity before a short delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG ANTICIPATORY EPOCH. The results, presented in Table 1 and Fig. 11, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 28% of PM neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly before a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). The difference in frequency between cases in which direction selectivity was stronger before a short delay and those in which it was weaker was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among PM neurons, the length of the anticipated delay exerted a dramatic influence on firing rate. Most delay-sensitive neurons fired more strongly in anticipation of a short delay.

Premotor cortex (PM): elapsed delay

POPULATION. Population activity was considerably enhanced toward the end of a short delay versus toward the end of a long delay (Fig. 8A2). There was an apparent slight tendency for the directional signal to be stronger after a short delay (Fig. 8D2).

INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 8, C2 and E2, can be summarized in the following terms.

   Main effect of delay.
During each epoch (IV–VII), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During epochs IV and V, the preponderance of neurons that fired more strongly after a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During epoch V, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity after a long delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG PREMOVEMENT EPOCH. The results, presented in Table 3 and Fig. 17, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of elapsed delay in 42% of PM neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly after a short delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). There was no difference in number between neurons exhibiting stronger and weaker direction selectivity after a long delay. These results did not differ significantly between monkeys.

SUMMARY. Among PM neurons, the length of the elapsed delay exerted a marked influence on firing rate. During the period leading up to the saccade, a majority of delay-sensitive neurons fired more strongly after a short delay.

Supplementary eye field (SEF): anticipated delay

POPULATION. We collected data from 147 neurons in the SEF of two monkeys (Table 1). Curves representing the activity of this population as a function of time during the trial indicate that the length of anticipated delay had only a minor impact on neuronal activity (Fig. 9, A1 and B1).

Individual neurons by epoch. The results, presented in Fig. 9, C1 and E1, can be summarized in the following terms.

   Main effect of delay.
During epoch II, the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons firing more strongly and those firing more weakly before a short delay ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
During no epoch was the proportion of neurons exhibiting an interaction effect significantly in excess of the frequency expected by chance ({chi}2 test, P > 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity before a short delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG ANTICIPATORY EPOCH. The results, presented in Table 1 and Fig. 11, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 12% of SEF neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The difference in frequency between neurons firing more strongly and those firing more weakly before a short delay was not significant ({chi}2 test, P > 0.05).

   Interaction between delay and direction.
Interaction effects were no more common than expected by chance ({chi}2 test, P > 0.05). The difference in frequency between cases in which direction selectivity was stronger before a short delay and those in which it was weaker was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among SEF neurons, the length of the anticipated delay exerted a very weak influence on firing rate. A few neurons fired more strongly and a few more weakly in anticipation of a short delay.

Supplementary eye field (SEF): elapsed delay

POPULATION. Population activity was enhanced after a long delay as compared to a short delay (Fig. 9A2). The enhancement was present during the late phase of the delay period and carried over into the saccadic period (Fig. 9B2). There was little or no apparent effect on the strength of the directional signal (Fig. 9D2).

INDIVIDUAL NEURONS BY EPOCH. The results, presented in Fig. 9, C2 and E2, can be summarized in the following terms.

   Main effect of delay.
During each epoch (IV–VII), the proportion of neurons exhibiting a main effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During epochs IV–VI, the preponderance of neurons that fired more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
During epoch IV, the proportion of neurons exhibiting an interaction effect was significantly in excess of the frequency expected by chance ({chi}2 test, P < 0.05). During no epoch was there a significant difference in number between neurons exhibiting stronger direction selectivity and those exhibiting weaker direction selectivity after a long delay ({chi}2 test, P > 0.05).

INDIVIDUAL NEURONS ACROSS A LONG PREMOVEMENT EPOCH. The results, presented in Table 3 and Fig. 17, can be summarized in the following terms.

   Main effect of delay.
There was a significant main effect of expected delay in 20% of SEF neurons. This percentage was significantly in excess of that expected by chance ({chi}2 test, P < 0.05). The preponderance of neurons firing more strongly after a long delay was significant ({chi}2 test, P < 0.05).

   Interaction between delay and direction.
Interaction effects were significantly more common than expected by chance ({chi}2 test, P < 0.05). The difference in number between neurons exhibiting stronger and weaker direction selectivity after a long delay was not significant ({chi}2 test, P > 0.05). These results did not differ significantly between monkeys.

SUMMARY. Among SEF neurons, the length of the elapsed delay exerted a dramatic influence on firing rate. A majority of delay-sensitive neurons fired more strongly after a long delay.

Rostral supplementary motor area (SMAr): anticipated delay

POPULATION. We collected data from 84 neurons in the SMAr of one monkey (Table 1). Curves representing the activity of this population as a function of time during the trial indicate that the length of the anticipated delay exerted a substantial effect on neuronal activity (Fig. 10A1). There was a considerable increase of firing rate beginning shortly after the delay cue on short-delay trials (Fig. 10B1).