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J Neurophysiol 91: 1381-1402, 2004. First published October 22, 2003; doi:10.1152/jn.00738.2003
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What the Brain Stem Tells the Frontal Cortex. I. Oculomotor Signals Sent From Superior Colliculus to Frontal Eye Field Via Mediodorsal Thalamus

Marc A. Sommer and Robert H. Wurtz

Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892-4435

Submitted 31 July 2003; accepted in final form 24 September 2003


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Neuronal processing in cerebral cortex and signal transmission from cortex to brain stem have been studied extensively, but little is known about the numerous feedback pathways that ascend from brain stem to cortex. In this study, we characterized the signals conveyed through an ascending pathway coursing from the superior colliculus (SC) to the frontal eye field (FEF) via mediodorsal thalamus (MD). Using antidromic and orthodromic stimulation, we identified SC source neurons, MD relay neurons, and FEF recipient neurons of the pathway in Macaca mulatta. The monkeys performed oculomotor tasks, including delayed-saccade tasks, that permitted analysis of signals such as visual activity, delay activity, and presaccadic activity. We found that the SC sends all of these signals into the pathway with no output selectivity, i.e., the signals leaving the SC resembled those found generally within the SC. Visual activity arrived in FEF too late to contribute to short-latency visual responses there, and delay activity was largely filtered out in MD. Presaccadic activity, however, seemed critical because it traveled essentially unchanged from SC to FEF. Signal transmission in the pathway was fast (~2 ms from SC to FEF) and topographically organized (SC neurons drove MD and FEF neurons having similarly eccentric visual and movement fields). Our analysis of identified neurons in one pathway from brain stem to frontal cortex thus demonstrates that multiple signals are sent from SC to FEF with presaccadic activity being prominent. We hypothesize that a major signal conveyed by the pathway is corollary discharge information about the vector of impending saccades.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Many studies in the past half-century have characterized the signals that course from retina to cerebral cortex and then down to the brain stem motor centers that control rapid or saccadic eye movements. This work has greatly advanced our understanding of sensorimotor transformations and their attendant cognitive processes. However, there are also pathways running in the reverse direction, from brain stem up to cortex. What roles do these ascending pathways play in vision, cognition, and movement, considering that they "go against the flow" of the normal sensorimotor transformation?

Anatomical work has indicated that one such pathway in monkeys ascends from midbrain to frontal cortex via a thalamic relay (Fig. 1A). Studies showed, first, that some projections from the intermediate layers of the superior colliculus (SC) terminate at the lateral edge of the mediodorsal nucleus (MD) of the thalamus (Benevento and Fallon 1975Go; Harting et al. 1980Go) and, second, that some neurons in this part of MD project to a prefrontal area important for oculomotor control, the frontal eye field (FEF) (Barbas and Mesulam 1981Go; Goldman-Rakic and Porrino 1985Go; Kievit and Kuypers 1975Go; Le Gros Clark and Boggon 1935Go; Walker 1940Go). Subsequent transynaptic retrograde tracing experiments using herpes virus injections in FEF found first-order labeling in thalamus, including in lateral MD, and second-order labeling in the SC intermediate layers (Lynch et al. 1994Go). Taken together, these results provided strong evidence for an SC-MD-FEF pathway. In the present study, we examined the signals sent through this pathway.



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FIG. 1. Identification of mediodorsal nucleus (MD) relay neurons. A: MD relay neurons were both orthodromically activated from the superior colliculus (SC) and antidromically activated from the frontal eye field (FEF). B: action potentials from an example MD relay neuron. Left: orthodromic activation from the SC. Top: stimulation in the SC at time 0 caused the MD neuron to fire 1.5-3 ms later (several trials superimposed). Stimulus artifact was erased for clarity. Bottom: failure of the collision test; when the SC was stimulated just after a spontaneous action potential of the MD neuron, activation still occurred. Right: antidromic activation from the FEF. Top: FEF stimulation at time 0 caused the MD neuron to fire with a stable, short latency of ~1.2 ms. Bottom: success of the collision test; when the FEF was stimulated just after a spontaneous action potential of the MD neuron (within a collision interval of ~1.4 ms), activation failed to occur (no spikes appeared at time designated with *). C: relay collision test. Time 0 is when FEF is stimulated; the time of SC stimulation varies, as labeled (SC stim). Top: the neuron was activated orthodromically from the SC, but FEF stimulation still caused antidromic activation because it occurred at sufficient delay after the orthodromically activated spikes (i.e., beyond the collision interval). Bottom: when the delay between SC and FEF stimulation was decreased to within the collision interval, the orthodromically activated spikes prevented antidromic activation (i.e., spikes are absent at time designated by *). The orthodromically and antidromically activated action potentials therefore were produced by the same neuron.

 
Our first goal was to physiologically identify neurons throughout the pathway using the classic methods of antidromic and orthodromic activation. Antidromic activation (backfiring neurons with electrical stimulation) has been employed since the earliest experiments in behaving monkeys to identify neurons projecting out of a brain area (e.g., Bizzi 1968Go; Evarts 1968Go). To identify neurons that receive input from a specific brain area, investigators have used orthodromic activation (synaptically driving neurons with stimulation) (e.g., Raybourn and Keller 1977Go). In the present study, we used these methods as follows. To identify SC neurons projecting into the ascending pathway, we antidromically activated them from MD. To identify FEF neurons receiving input from the pathway, we orthodromically activated them from the SC. To identify the crucial MD relay neurons linking the SC to the FEF, we orthodromically activated them from the SC and antidromically activated them from the FEF. The use of antidromic and orthodromic activation techniques yielded two further benefits as well: by analyzing activation latencies, we could determine the speed of signal transmission in the pathway, and by comparing the ability to activate MD or FEF neurons from different parts of the SC, we could establish whether neurons along the pathway were connected logically as a function of the well-known topography in the SC (rostral SC represents small and caudal SC large saccades) (Robinson 1972Go).

Our second main goal was to characterize the signals conveyed through the pathway. Previous researchers hypothesized that the pathway might carry visual signals (Suzuki and Azuma 1983Go; Wurtz and Mohler 1976Go), activity related to cognitive processes (Leichnetz et al. 1981Go), and/or presaccadic activity (Goldberg and Bushnell 1981Go; Lynch et al. 1994Go). All of these hypotheses are plausible because recordings in the general populations of SC, MD, and FEF neurons showed that neurons in all three structures can have visual-, cognitive-, or saccade-related activity (FEF: reviewed by Schall 1997Go; MD: Schlag and Schlag-Rey 1984Go; Schlag-Rey and Schlag 1984Go; Tanibuchi and Goldman-Rakic 2003Go; Wyder et al. 2003Go; SC: reviewed by Wurtz et al. 2000Go). Our identification of the specific SC neurons that feed into the pathway, the specific MD neurons that serve as relays, and the specific FEF neurons that receive input from the pathway allows us to test these hypotheses by explicitly determining what signals are sent from SC to FEF and how they change along the way. To evaluate the signals, we recorded from identified neurons while monkeys performed tasks that included making delayed saccades to visual or remembered targets. We focused our analyses on visual responses, delay activity, and saccade-related activity.

We found that the pathway from SC to MD to FEF is fast conducting, topographically connected, and rich in many types of signals from purely visual to purely saccadic. The saccade-related activity seemed especially important because unlike the other signals it coursed through the pathway with no detectable change in its strength or timing. We conclude that a major role of the pathway from SC to FEF may be to provide feedback of saccadic commands, or corollary discharge, to cerebral cortex. In the accompanying paper (Sommer and Wurtz 2004b), we describe experiments in which we tested this hypothesized function by transiently inactivating the pathway.

Some of these results were previously reported in brief articles and abstracts (Sommer and Wurtz 1998Go, 2000aGo, 2002Go; Wurtz and Sommer 2000Go).


    METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Identifying neurons in the pathway

The first main goal of this study was to physiologically identify neurons throughout the pathway from SC to MD to FEF. In three 5-10 kg monkeys (Macaca mulatta), we implanted scleral search coils for measuring eye position, recording cylinders for accessing the brain, and a post for immobilizing the head during experiments (see Sommer and Wurtz 2000bGo for details). All procedures were approved by the Institute for Animal Care and Use Committee and complied with Public Health Service Policy on the humane care and use of laboratory animals. In one monkey (C), we studied identified neurons at all three levels of the pathway, in another (B), we studied identified neurons in SC and MD only, and in the third (H), we studied identified neurons in FEF only. Data were collected from within the left hemisphere of monkeys C and H and from within the right hemisphere of monkey B. We found the FEF and SC using recording and stimulation criteria (presaccadic activity and <50 µA current thresholds for evoking saccades) and confirmed the localizations with magnetic resonance imaging (MRI). To find MD, we used anatomical studies (Barbas and Mesulam 1981Go; Goldman-Rakic and Porrino 1985Go; Lynch et al. 1994Go) and stereotaxic coordinates (Martin and Bowden 1997Go; Olszewski 1952Go) as guides. We positioned MD cylinders at A8, L3 and searched in them until we found identified relay neurons (the process of identification is described next). We always inserted recording and stimulating electrodes through guide tubes (23 gauge) aimed using a grid (Crist et al. 1988Go) having holes 1 mm apart (even finer resolution was achieved in some recordings using grids with holes offset 0.5 mm from the normal pattern).

ANTIDROMIC AND ORTHODROMIC STIMULATION. We used standard techniques to record extracellularly from single neurons (Sommer and Wurtz 2000bGo). After isolating a neuron, we identified its connections using antidromic and/or orthodromic activation (for reviews, see Lemon 1984Go; Lipski 1981Go). Activation means that a neuron produced an action potential shortly after we electrically stimulated a distant structure (for examples see Fig. 1B, top row). Antidromic activation, or backfiring a neuron through its own axon, indicated that the neuron projected to the distant structure. Orthodromic activation, or synaptically driving the neuron, indicated that the neuron received input from the distant structure. We distinguished anti-from orthodromic activation primarily with the collision test in which electrical stimulation is timed to occur just after a spontaneous action potential of the neuron (Fig. 1B, bottom). If the neuron projects to the area containing the stimulating electrode, then the spontaneous action potential moving forward in the axon will meet the stimulation-evoked action potential moving backward in the same axon, and neither will travel further because the axon will be in its absolute refractory period on both sides of the meeting point. Hence the stimulation-evoked action potential will not appear at the recording electrode (Fig. 1B, bottom right, *), whereas normally it would (Fig. 1B, top right). If the delay between onset of the spontaneous action potential and onset of stimulation is increased past a certain interval, ~0.2-0.6 ms longer than the activation latency, then the collision effect ceases (not shown). If all this occurs, then the activation passes the collision test, and the neuron is considered to be antidromically activated; it projects to the distant structure holding the stimulating electrode. If the activation fails the collision test (Fig. 1B, compare top left and bottom left), then the neuron is considered to be orthodromically activated; it receives input from the distant structure. To complement the collision test, we also examined whether the activation latency was stable or not; stable activation latencies, exhibiting a range <=0.1 ms (Fig. 1B, top right), are typical of antidromic activation, but jittery latencies, range >0.1 ms (Fig. 1B, top left), are typical of orthodromic activation. In rare cases when we were unsure whether the activation was antidromic versus orthodromic, we abandoned the neuron and searched for a new one.

Neurons were identified as belonging to the ascending pathway according to the following criteria: SC neurons had to be antidromically activated from MD, MD neurons had to be orthodromically activated from the SC and antidromically activated from the FEF, and FEF neurons had to be orthodromically activated from the SC. To activate neurons, we stimulated through tungsten microelectrodes (~100 k{Omega} at 1,000 Hz; Frederick-Haer) using single, biphasic, negative-positive current pulses of 0.15 ms/phase. We implanted these monopolar stimulating electrodes semi-chronically for several weeks except during some experiments (as mentioned in RESULTS) in which we used moveable electrodes. Accurate placement of the stimulating electrodes was critical to this study, and therefore details about this are provided next.

SC-STIMULATING ELECTRODES. We implanted stimulating electrodes in the SC (for orthodromically activating MD or FEF neurons) with their tips in the intermediate layers in all three monkeys. We always implanted a pair of SC-stimulating electrodes with one relatively rostral (in or near the "fixation" zone; Munoz and Wurtz 1993Go) and one relatively caudal (typically 10-20° eccentricity on the SC topographic map) (Robinson 1972Go), except in a few experiments when we used a single, moveable electrode to find the current threshold profile as a function of depth into the SC (e.g., Fig. 4, E and F). To confine stimulating currents as much as possible to the SC, we positioned stimulating electrodes on or near the representation of the horizontal meridian that runs through the center of the SC map (see Fig. 4C, 0° direction contour). Before epoxying an electrode in place, we always recorded through it to ensure that its tip was amid neurons having fixation-related, foveal visual, and/or small-saccade-related activity (for the rostral electrode) or peripheral visual responses and large-saccade-related activity (for the caudal electrode), and we stimulated through the electrode using trains of pulses to ensure that low currents (<20 µA at 350 Hz for 70 ms using biphasic pulses having durations of 0.25 ms/phase) fixed the eyes in place or evoked small saccades (for the rostral electrode) or evoked larger saccades (for the caudal electrode). After several weeks, the implanted electrodes became unusable (they failed to pass current reliably), at which time we replaced them with new electrodes at slightly different SC locations. Over the course of the study, we used a total of 10 SC electrode pairs in the three monkeys. On average, we placed rostral electrode tips at 1.7° eccentricity on the SC map and 1.8 mm depth below the SC surface and caudal electrode tips at 13.0° eccentricity and 1.7 mm depth. The current thresholds for orthodromically activating neurons using these SC electrodes were on average 264 µA (range: 7-718 µA, n = 45) for MD neurons and 110 µA (range: 16-540 µA, n = 47) for FEF neurons. The difference in these averages probably was not important; it may have been an artifact of slightly different SC stimulating electrode placements in each of the three monkeys.



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FIG. 4. Identification and location of SC source neurons. A: all of the SC source neurons were antidromically activated from sites of previously recorded MD relay neurons. B: action potentials from a SC source neuron. Top: MD stimulation at time 0 caused the SC neuron to fire with a stable, short latency of ~0.8 ms. Bottom: success of the collision test. C: mediolateral and rostrocaudal locations of the neurons. Using information from the visual field and/or movement field of each SC neuron, along with results of electrically evoking saccades, we estimated all the neuron locations ({bullet}) on the standard SC map of Robinson (1972Go). Ecc., eccentricity (size of electrically evoked saccades increases along this axis); Dir., direction (angle of electrically evoked saccades changes along this axis, with positive angles upward and negative angles downward). R, rostral; C, caudal; M, medial; L, lateral. Some sites fall slightly outside of Robinson's map, e.g., those representing saccades with more of a downward direction than he tested (directions from -60 to -90°). Data from monkey B were collected from the right SC but for simplicity are represented here on the left SC for combination with data from monkey C. D: depths of the neurons relative to the top of the SC. E: for comparison with neuronal depth data in D, an example current threshold profile for orthodromically activating an MD relay neuron is shown. Current threshold (abscissa) is plotted against the depth of the stimulating electrode tip in the SC (ordinate). Recordings through the stimulating electrode revealed the depth range where neurons had only visual responses ("vis. only" region, i.e., the superficial layers) and the depth range where neurons had visual- and saccade-related activity ("vis. and sacc." region, i.e., the intermediate and deep layers). Just below the SC, neurons had no visual- or saccade-related activity ("not vis. or sacc." region). The current threshold minimum ({triangleup}) was 265 µA, at 2.8 mm deep. F: results of all 8 tests in which the current threshold for driving MD relay neurons was evaluated as a function of electrode tip depth in the SC.

 
FEF-STIMULATING ELECTRODES. We implanted stimulating electrodes in the FEF (for antidromically activating MD neurons) in two monkeys, using slightly different methods to place them in each animal. In one monkey, we positioned an array of three electrodes with their tips at the sites of FEF neurons that we previously found to be activated orthodromically from the SC; that is, the electrodes were positioned as closely as possible to the target zone of the ascending pathway. In the other monkey, we simply positioned arrays of three or four electrodes with their tips in the middle layers of the FEF as indicated by recordings and MRI. Both methods were successful, although the former method was superior in that it yielded markedly lower current thresholds for antidromically activating MD neurons (average: 317 µA, range: 43-836 µA, n = 30 neurons) as compared with the latter method (average: 1,298 µA, range: 335-1,850 µA, n = 16 neurons). Although current thresholds using the latter method were relatively high, it is unlikely that the stimulation activated axons outside of the FEF. Using the relation distance = (current/K)0.5 (Tehovnik 1996Go), the average threshold of 1,298 µA at a pulse duration of 0.15 ms should activate low-threshold axons (K {approx} 381 µA/mm2) only within 1.8 mm and high-threshold axons (K {approx} 4,844 µA /mm2) only within 0.5 mm of the electrode tip.

MD-STIMULATING ELECTRODES. We implanted stimulating electrodes in MD (for antidromically activating SC neurons) in two monkeys at sites of previously recorded MD relay neurons. To minimize damage to the relay neurons and permit further experiments in the region (i.e., reversible inactivations; Sommer and Wurtz 2004b), we used only a single stimulating electrode in the MD of each monkey. We placed it at the most posterior site found to contain relay neurons, reasoning that SC afferents follow a posterior-anterior trajectory so that most should pass near this electrode before terminating in MD. Current thresholds for antidromically activating SC neurons from MD were on average 270 µA (range: 35-1,284 µA, n = 48).

TOPOGRAPHY OF PROJECTIONS. We also used orthodromic activation to search for projection topographies in the pathway. The concept was to see if stimulation in rostral (or caudal) SC preferentially drove MD or FEF neurons that represented small (or large) saccades as would be logical according to the SC map (Robinson 1972Go). This required measuring the visual and/or movement field of each MD or FEF neuron, and our procedure for doing this is described in the VISUAL AND MOVEMENT FIELDS section. We also had to estimate what part of the SC provided input to the neuron, and to do this, we calculated for each MD or FEF neuron a contrast ratio called the electrode preference index (EPI). The principle behind the EPI was as follows. Because we typically used two stimulating electrodes in the SC, one rostral and one caudal, we could compare the ability to drive an MD or FEF neuron from rostral versus caudal SC. If stimulation through one electrode activated the MD or FEF neuron at a lower current threshold than did stimulation through the other, then the former, "better" electrode was probably located nearer to those SC neurons that drove the MD or FEF neuron. EPI = (Ir - Ic)/(Ir + Ic), where Ir and Ic were the current thresholds for activating the recorded neuron from rostral and caudal SC (threshold was defined as the current causing activation in 50% of trials). An EPI closer to -1 or +1 suggested that the neuron was preferentially driven from projections originating closer to rostral or caudal SC, respectively.

Characterizing signals in the pathway

Our second main goal was to evaluate the signals sent from SC to MD to FEF. After physiologically identifying a neuron as belonging to the pathway as described in the preceding text, we analyzed its signals by having the monkey perform a series of tasks. Details of the testing apparatus were described previously (Sommer and Wurtz 2000bGo). Briefly, the monkey faced a tangent screen on which visual stimuli were projected by an LCD monitor. Visual stimuli were 0.3 x 0.3° blue or red spots (0.6 cd/m2) presented on a dark background (0.1 cd/m2) with dim ambient room light. Personal computers controlled the presentation of visual stimuli and recorded at 1 kHz the eye position, the occurrence of action potentials, and the timing of task events.

DELAYED-SACCADE TASKS. The purpose of these tasks was to search for visual responses, presaccadic activity, and tonic activity known as delay activity that seems related to cognitive processes such as memory or planning (e.g., see Sommer and Wurtz 2001Go). The delayed-saccade tasks are diagrammed in Fig. 10A. All trials began with a fixation point appearing in the center of the screen. After the monkey foveated it for 500-800 ms (pseudorandomly varied, like all task timings in this study), a target appeared at the estimated center of the visual and/or movement field. In visual trials of the task (Fig. 10A, Vis.), the target remained lit for the rest of the trial; in memory trials (Fig. 10A, Mem.), the target disappeared after 100 ms. In all trials, after a delay period of 500-1,000 ms the fixation spot disappeared, cueing the monkey to make a saccade to the location of the target after which a water reward was delivered.



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FIG. 10. Signals conveyed in the ascending pathway as determined using the delayed-saccade tasks. A: timeline of the tasks. The monkey foveated a fixation spot (Fix Spot) and then a peripheral target appeared. In the visual (Vis.) version of the task, the target remained on during an extended delay period, and in the memory (Mem.) version, it appeared for 100 ms and then was absent during the delay period. Disappearance of the fixation spot was the cue to make a saccade to the target location. Eye position (Eye Pos.) is shown in the fourth trace from the top. Base, baseline; Vis, visual; Del, delay; Pr, presaccadic; Po, postsaccadic. Time scale is at bottom, with ticks separated by 100 ms. B: examples of visual neurons. Depicted are spike density functions (Gaussian width 10 ms) (MacPherson and Aldridge 1979Go) showing the average firing rates of example FEF recipient, MD relay, and SC source neurons during the visual and memory trials. Data aligned to target onset (left), to fixation spot offset (cue to move; middle); and to saccade onset (right). Labels at lower left of each graph are identifying codes for each neuron. Further examples show visuomovement (C) and movement neurons (D).

 
To analyze the data, we quantified and compared the mean firing rates during five periods (Fig. 10A, analysis epochs). The baseline epoch spanned 500-200 ms before target onset, the visual epoch 50-150 ms after target onset, the delay period epoch 300-0 ms before the cue to move, the presaccadic epoch 50-0 ms before saccade initiation, and the postsaccadic epoch 50-150 ms after saccade termination. To see if the neuronal activity changed at all during the task, we ran an ANOVA on the data. If significant (at P < 0.01), we performed an all-pairwise multiple comparison test (Student-Newman Keuls or Dunn's) to reveal whether firing rates in specific pairs of epochs differed from each other (at P < 0.05). We defined various types of signals according to comparisons between epochs, as follows. A phasic visual response occurred if the visual epoch activity exceeded the baseline epoch activity in either visual or memory trials. A tonic visual response occurred if the activity in the delay period of visual trials, during which time the receptive field was steadily illuminated, exceeded both the baseline activity in visual trials and the delay period activity in memory trials, two periods during which no visual stimuli were in the receptive field. Delay activity occurred if the delay period activity in memory trials exceeded the baseline activity in those trials; because the physical characteristics (fixation spot on, no peripheral visual stimulus) and the motor state (steady fixation) were identical in both of these epochs, differing activity between them must represent differences in the internal state of the animal presumably related to memory or other cognitive processes. Presaccadic activity occurred if presaccadic epoch activity exceeded both the delay period and the baseline activity in either visual or memory trials. Postsaccadic activity occurred if the postsaccadic epoch activity exceeded both the presaccadic and baseline epoch activities. We also performed other analyses on the firing rate data, such as determination of visual response latency, as will be described in the RESULTS.

GAP TASK. The purpose of this task was to look for "gap activity" during a brief period (the gap) after a fixation spot disappears but before a saccadic target appears. Such activity may be related to cognitive processes such as disengaging fixation or preparing to make a saccade (e.g., Dias and Bruce 1994Go; Munoz et al. 2000Go). In the gap task (Fig. 12A), the monkey fixated a spot for 500-800 ms and then the spot disappeared; the monkey had to maintain fixation on the blank screen, and then, after a 200-ms gap period, a target was presented at the estimated center of the visual and/or movement field; the monkey then looked at the target to receive its reward. We compared the mean firing rate during the gap period epoch, from 50 ms before target onset to 50 ms after (Fig. 12A), with the firing rate during a baseline epoch 500-200 ms before start of the gap. Gap activity occurred if the gap period activity exceeded the baseline activity.



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FIG. 12. Distributions of neurons having gap activity. A: timeline of the gap task. After the fixation spot was foveated, it disappeared and a gap period ensued for 200 ms, a target appeared in the periphery, and the monkey made a saccade to the target location. Time scale is at bottom, with ticks separated by 100 ms. B: neurons with gap activity. Gap activity (shaded boxes) was an elevated firing rate from the end of the gap period to just after target onset (before any visual response of the neuron began). The gap activity occurred regardless of whether the target eventually appeared in the contra- or ipsilateral hemifield (see legend; these 2 alternatives were randomized by trial). C: percentages of neurons along the pathway having gap activity. The pie charts represent 47 SC, 46 MD, and 37 FEF neurons (same neurons as in Fig. 11).

 
FIXATION BLINK TASK. The purpose of this task was to quantify foveal visual receptive fields and fixation-related activity in neurons that qualitatively appeared to exhibit these characteristics during the delayed-saccade and gap tasks. The task was very simple (diagram not shown): the monkey foveated a spot for 500-1,000 ms, the spot disappeared for 400-600 ms, and then the spot reappeared at the same place for 500-1,000 ms. The monkey was rewarded if it steadily fixated throughout the trial. We used three analysis epochs: a baseline epoch spanning 300-0 ms before fixation spot onset, a fixation epoch during the temporary disappearance of the fixation spot (300-0 ms before it reappeared), and a visual epoch just after the visual stimulus was flashed onto the fovea (100-300 ms after fixation spot reappearance). We compared the mean firing rates during these epochs using ANOVA and multiple comparison tests as described in the preceding text for the delayed-saccade task. A neuron carried a fixation signal if its activity in the fixation epoch was different from the baseline epoch activity and a foveal visual response if its activity in the visual epoch exceeded both the fixation and baseline epoch activities.

VISUAL AND MOVEMENT FIELDS. For every identified neuron, we measured the range of locations where visual stimuli caused it to fire (its visual field) and the range of saccadic vectors for which it fired presaccadically (its movement field). As with all testing in this study, we performed these measurements while the monkey's head was held stationary. We first estimated these fields on-line (see Fig. 7A, pink) by having the monkey make saccades to a variety of target locations while we inspected rasters of neuronal activity. For neurons having both visual and movement fields, it was clear by inspection that the fields were always highly coincident, so a single estimated field accurately represented both component fields. From this initial testing, we found the location of the target that evoked maximal activity, and we presented targets at this estimated best target location during the delayed-saccade and gap tasks described in the preceding text.



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FIG. 7. Visual and movement fields. Illustrated for 1 example MD relay neuron are the method for measuring its visual and movement fields (A), quantification of its visual field (B), and quantification of its movement field (C). In B and C, direction profiles are at left and eccentricity profiles are at right. D: open movement fields of 3 other MD relay neurons.

 
To permit off-line quantitative analysis of the visual and movement fields, we collected two data files while the monkey performed a visually guided saccade task in which it fixated a spot for 500-800 ms that then disappeared just as a peripheral target appeared. The monkey had to make a saccade to the target to receive a reward. First, we randomly presented targets in a direction series of eight possible locations around a circle having its radius equal to the estimated best eccentricity (Fig. 7A, orange). We set the directions to every 45° in angle starting from horizontal. Second, we randomly presented targets in an eccentricity series of eight possible locations along a line oriented at the estimated best direction (Fig. 7A, blue). We set the eccentricities to an array of [2.5, 5, 10, 20, 30, 40, 50, 60°] or adjusted them to better match the estimated range of the field(s) by multiplying this array by a scalar (e.g., by 0.5 for fields near the fovea). To optimize the accuracy of the eye position measurements, we arranged the fixation point and target so that most saccades in the eccentricity series traveled symmetrically across the center of the screen (Aizawa and Wurtz 1998Go; Munoz and Wurtz 1995Go), e.g., 20° leftward saccades were elicited by placing the fixation spot 10° right of center and the saccadic target 10° left of center. We did this for all target eccentricities except for the two smallest for which we used a central fixation spot.

For every neuron having a significant visual response (as determined quantitatively using the delayed-saccade tasks), we reconstructed its visual field off-line by measuring average visual activity 50-150 ms after target onset in the direction and eccentricity series data. Similarly, for every neuron having significant presaccadic activity, we reconstructed its movement field by measuring average presaccadic activity 50-0 ms before the saccade in the direction and eccentricity series data. We fitted Gaussians to the direction series data (least-squares approximation) separately for the visual activity and the presaccadic activity, yielding direction cross-sections through the visual and movement fields (Fig. 7, B and C, left). We measured the direction range as the range of directions for which the Gaussian was >2 SDs above the mean baseline firing rate (we measured baselines 300-0 ms before target onset). The direction series data were shifted before fitting the Gaussian so that the fitted curve would peak near the center of the range; periodic curve fits, e.g., cosines, were attempted but the fields were too narrow to be well fit by them. We fitted splines to the eccentricity series data (Munoz and Wurtz 1995Go), yielding eccentricity cross-sections through the visual and movement fields (Fig. 7, B and C, right). We measured the eccentricity range as the range of eccentricities for which the spline was >2 SDs above the mean baseline firing rate. We used cubic spline fits except when they were clearly inadequate due to sharply varying data points (e.g., Fig. 7D, left and middle), in which case we used a ninth-order spline. We performed all curve fitting with Matlab (The MathWorks).

We note that for quantifying movement fields, activity was plotted against the actual direction or amplitude of each saccade, which is why data clusters in Fig. 7, C and D, exhibit scatter in both the x- and y-axis directions. For movement field eccentricity, therefore, spline fits were least-squares approximations. For visual fields, in contrast, we calculated the mean firing rate for each target location, which is why there is a single data point at each direction or eccentricity in Fig. 7B. Also, for simplicity we use the term "eccentricity" to describe radial extent for visual and movement fields, although "amplitude" would be more precise for movement fields.

DETECTION OF SACCADES AND FIXATIONS. On-line, we identified saccades and fixations using real-time detection software written in-house. A saccade was accurate if it landed in a rectangular virtual window surrounding the target location that ranged in size from 1° horizontally x 2° vertically for targets at small eccentricity (e.g., 4°) to 10 x 20° for targets located at large eccentricity (e.g., 40°). Windows for enforcing fixation were 2 x 2° squares around the fixation point. Off-line, we used software running a template-matching algorithm to automatically detect saccades in eye-position records. We verified the accuracy of saccade detection by visually inspecting the data from every trial.

STATISTICS. Unless explicitly noted otherwise, throughout this paper we compare data sets using Student's t-test, if judged normal by the Kolmogorov-Smirnov test and of equal variance by the Levene Median test, or else the Mann-Whitney rank sum test, and we analyze correlations using Pearson's test.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Identified neurons in the ascending pathway

We studied a total of 151 identified neurons: 48 SC source neurons projecting into the ascending pathway, 47 MD relay neurons linking SC to FEF, and 56 FEF recipient neurons targeted by the pathway.

MD RELAY NEURONS. Identification of MD relay neurons was the crucial first step in our study because it explicitly confirmed the presence of a pathway from SC to MD to FEF. Every time we isolated a neuron in MD, we tried to activate it using stimulating electrodes in the SC and the FEF (Fig. 1A). All 47 MD relay neurons in our sample (17 from monkey B, 30 from monkey C) were orthodromically activated from the SC as evidenced by activations that always failed the collision test (Fig. 1B, bottom left) and stimulation-evoked action potentials that nearly always had jittery latencies (Fig. 1B, top and bottom left). All the MD neurons also were antidromically activated from the FEF, as evidenced by activations that always passed the collision test (Fig. 1B, bottom right) and stimulation-evoked action potentials that always had stable latencies (Fig. 1B, top right). These individual MD neurons therefore received SC input and projected to the FEF, verifying the existence of a pathway from SC to MD to FEF.

We recorded only from well-isolated MD neurons and were always confident that both the orthodromically and antidromically activated action potentials were produced by the same neuron. To confirm this, when time permitted we also used the relay collision test (Fig. 1C), which has been used previously for identifying thalamic relay neurons of other pathways (e.g., Deschênes et al. 1982Go; Zhu and Lo 1998Go). Instead of waiting for the MD neuron to fire spontaneously to perform the collision test, we made it fire by orthodromically activating it from the SC. The orthodromically activated action potential could annihilate an action potential evoked antidromically from the FEF only if both sets of action potentials were produced by the same MD neuron. This always occurred; every neuron tested (11/11) passed the relay collision test.

In both monkeys, we found MD relay neurons ~3 mm lateral of the midline and ~7-9 mm anterior to the interaural line (Fig. 2A). In monkey B, we took particular care to search outside this narrow zone but found no other relay neurons (Fig. 2A, right). Many of the surrounding neurons could be orthodromically activated from the SC or antidromically activated from the FEF but not both (Fig. 2B); we do not know to where these SC-recipient neurons projected or from where these FEF-projecting neurons received their input, and we did not study their signals. We found MD relay neurons ~18-23 mm below the top of the brain, slightly deeper (by ~3 mm) in one monkey than in the other (Fig. 2C). The coordinates of the MD relay neurons corresponded well with the lateral edge of MD as described in stereotaxic atlases (Martin and Bowden 1997Go; Olszewski 1952Go) and as predicted by anatomical studies (Barbas and Mesulam 1981Go; Goldman-Rakic and Porrino 1985Go; Lynch et al. 1994Go). This lateral MD location was histologically verified in both monkeys (Fig. 3 shows the results from monkey C).



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FIG. 2. Locations of MD relay neurons. A: all recording sites in monkeys C (left) and B (right). Legend at left shows number of relay neurons found at each site. "Anterior" locations are stereotaxic AP coordinates, relative to interaural line. B: boundaries showing approximate ranges of relay neurons (activated from both SC and FEF) as compared with broader ranges of neurons activated from either SC or FEF but not both (legend at bottom). C: depths of relay neurons relative to the top of the brain.

 



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FIG. 3. Histological recovery of penetrations into the lateral edge of MD in monkey C. Sections (50 µ thick) were cut coronally and alternately stained for cell bodies (thionin) and myelin (modified protocol of Gallyas 1979Go). Scale bars are shown at right in all panels (1 mm/tick). A: a sketch of the general region. Guide tubes pierced the corpus collosum (cc) and electrodes entered the lateral edge of MD, just medial to the internal medullary lamina (IML). B: cell body stain, magnified from the area of detail in A. The black arrowhead points to a prominent penetration that yielded numerous relay neurons. C: myelin stain of the same area (from a nearby section), in which the IML can be seen along with the penetration (black arrowhead) just medial to it, i.e., at the lateral edge of MD. In both B and C, damage from the guide tube can be seen above the arrowhead in the corpus collosum. Cd, caudate nucleus; cgs, cingulate sulcus; Cl, claustrum; cs, central sulcus; Ins, insula; ips, intraparietal sulcus; LGN, lateral geniculate nucleus; Put, putamen; RTN, reticular nucleus of the thalamus. The region labeled lateral thalamic nuclei probably consisted of the ventrolateral and ventroposterolateral nuclei (see Olszewski 1952Go), but we did not attempt to verify this anatomically.

 
SC SOURCE NEURONS. After collecting the sample of MD relay neurons in each monkey, we implanted a stimulating electrode with its tip amid these neurons and began recording in the SC (Fig. 4A). All 48 SC source neurons (33 from monkey B, 15 from monkey C) were antidromically activated from the MD electrode (Fig. 4B). We found source neurons in every site that we explored over a large range of the rostrocaudal and mediolateral extent of the SC (Fig. 4C). In each penetration, we started looking for SC source neurons at the top of the superficial layers and continued searching until we left the SC ~4-5 mm below. We found source neurons primarily 1-3 mm below the surface (Fig. 4D), corresponding approximately to the intermediate layers. To test this assessment that SC intermediate layer neurons drove the MD relay neurons, we also measured the optimal depths of stimulation within the SC for orthodromically activating MD relay neurons. We did this for eight MD relay neurons by moving a stimulating electrode through the SC and finding the depth of lowest current threshold for activation. Figure 4E shows a current threshold profile for one experiment: the minimum was in or near the intermediate layers where we found strong visual- and saccade-related activity during recordings in the same penetration. In most cases (7/8), threshold minima were in the intermediate layers (Fig. 4F), whereas in one case, the threshold minimum was deeper. We never found a threshold minimum in the purely visual superficial layers. These current threshold minima correspond well with the depths of the SC source neurons (cf. Fig. 4D), and therefore both lines of evidence agree that SC input to the MD relay neurons arises primarily from the intermediate layers.

FEF RECIPIENT NEURONS. All 56 FEF recipient neurons (13 from monkey C, 43 from monkey H) were orthodromically activated from the SC (Fig. 5, A and B), and, as we previously reported, current thresholds for driving them were lowest in the SC intermediate layers (Sommer and Wurtz 1998Go). Note that it was crucial to activate FEF recipient neurons from the SC, not from MD; as was shown in Fig. 2B (thin, solid-line boundaries), many MD neurons that project to the FEF do not seem to get input from the SC, and therefore stimulating MD instead of SC could mistakenly identify FEF neurons that are targeted by pathways other than that originating in the SC. Recipient neurons were located throughout most of the mediolateral range of the FEF (Fig. 5C) and from near the top of cortex to ~9 mm deep (as the electrode traversed the anterior bank of the arcuate sulcus; Fig. 5D). We often found FEF recipient neurons in the same penetrations that yielded FEF SC-projecting neurons (Sommer and Wurtz 2000bGo), but these two classes of neurons were not intermingled; they were always separated from each other by at least a few hundred microns in depth. The FEF recipient neurons were likely in layer IV, where most thalamic afferents terminate (Giguere and Goldman-Rakic 1988Go). FEF SC-projecting neurons are found only in layer V (Fries 1984Go; Leichnetz et al. 1981Go).



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FIG. 5. Identification and location of FEF recipient neurons. A: all of these neurons were orthodromically activated from the SC. B: action potentials from an FEF recipient neuron. Top: SC stimulation at time 0 caused the FEF neuron to fire with a jittery latency from ~1.7 to 2.7 ms. Bottom: failure of the collision test. C: mediolateral and anterioposterior locations of the neurons. Penetration sites yielding these neurons are shown relative to the arcuate sulcus (As, its superior limb; Ai, its inferior limb) and the posterior tip of the principal sulcus (Pr). Sulcal locations were determined by inspection during surgery, MRI, and for monkey H, histology. A, anterior; P, posterior. D: depths of the neurons.

 
SIGNAL SPEED IN THE PATHWAY. Activation latencies, the delays from stimulation onset to the earliest action potentials evoked in activated neurons, were very brief. SC to MD antidromic latencies (Fig. 6A, shaded histogram) had a median of 0.83 ms and MD to FEF antidromic latencies (inverted histogram) had a median of 1.0 ms. These two distributions were not significantly different (P > 0.05). SC to MD orthodromic activation latencies (dashed-line histogram) had a median of 1.4 ms, significantly longer than the antidromic activation latency for the same projection (cf. "SC to MD anti" histogram). The additional time (0.57 ms) was presumably the SC-MD synaptic delay.



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FIG. 6. Activation latencies of the neurons. A, upright histograms: for the SC to MD projection, the distributions of antidromic activation latencies obtained when stimulating MD and recording from SC ("SC to MD anti") and orthodromic activation latencies obtained when stimulating SC and recording from MD ("SC to MD ortho") are shown. Inverted histogram: for the MD to FEF projection, the distribution of antidromic activation latencies is shown ("MD to FEF anti"). Arrowheads show median latencies, and statistical results are indicated. B: the actual distribution of orthodromic latencies from SC to FEF ("SC to FEF ortho") compared with the predicted distribution found by summing the orthodromic activation latency from SC to MD with the antidromic activation latency from MD to FEF for every MD relay neuron ("Predicted SC to FEF ortho"). The distributions were not significantly different, n.s.d.

 
The SC to FEF orthodromic latencies are shown in Fig. 6B (dashed-line histogram); their median was 2.2 ms. Consistent with our assumption that the FEF recipient neurons were driven from the SC via MD relay neurons, this distribution of SC to FEF orthodromic latencies was not significantly different (P > 0.05) from the predicted distribution of the transmission time through the SC-MD-FEF pathway (Fig. 6B, shaded histogram), which had a median of 2.4 ms. The predicted distribution was derived by adding the time it takes for action potentials to travel from SC to MD (SC to MD orthodromic latency) to the time it takes for action potentials to travel from MD to FEF (MD to FEF antidromic latency) for each MD relay neuron. This distribution might be made more accurate by adding in the MD to FEF synaptic delay and subtracting out the FEF utilization time (the time it takes for stimulation to evoke an action potential), but these values are not known.

PROJECTION TOPOGRAPHY IN THE PATHWAY. We also used our activation methods to examine whether neurons in the pathway were linked together in a logical manner according to the topography of the SC. We expected MD and FEF neurons having small eccentricity fields to receive input primarily from rostral SC and those having large eccentricity fields to receive input primarily from caudal SC (see Fig. 4C for SC topography) (Robinson 1972Go). First we document the general characteristics of visual and movement fields throughout the pathway, and then we analyze the projection topography.

Figure 7, A-C, summarizes how we measured the visual and movement fields for one example MD relay neuron (see METHODS for details). It was clear from initial testing that the neuron had both visual- and saccade-related activity and that its visual and movement fields were almost perfectly coincident. After estimating the average location and size of the fields (Fig. 7A, pink), we had the monkey make saccades to targets in a direction series (Fig. 7A, orange) and eccentricity series (Fig. 7A, blue) that cut through the estimated fields. We plotted visual responses as a function of direction (Fig. 7B, left) and eccentricity (Fig. 7B, right) to reconstruct the visual field and similarly plotted presaccadic activity to reconstruct the movement field (Fig. 7C). This example neuron had a visual field (Fig. 7B) with best direction 35°, direction range 90°, best eccentricity 16°, and eccentricity range 37°. Its movement field was nearly identical (Fig. 7C), having a best direction of 27°, direction range of 128°, best eccentricity of 16°, and eccentricity range of 31°. The correspondence of this neuron's visual and movement fields was typical; similar overlap was seen in all of our MD, SC, and FEF neurons that had both visual and presaccadic activity.

The visual and movement fields for this example neuron were "closed", i.e., bounded in eccentricity (Fig. 7, B and C, right), but some other neurons had "open" visual or movement fields in that visual or presaccadic activity was significantly elevated even at the furthest eccentricity tested. Open fields have been described previously for SC and FEF neurons (Bruce and Goldberg 1985Go; Munoz and Wurtz 1995Go). We found open visual fields and movement fields, respectively, in 18% (6/33) and 53% (18/34) of SC neurons, 57% (16/28) and 76% (22/29) of MD neurons, and 18% (6/33) and 43% (10/23) of FEF neurons. There were three basic kinds of open visual or movement fields as illustrated by representative examples in Fig. 7D. In some neurons, activity rose and then stayed at a plateau level for as large of eccentricities that we could test (Fig. 7D, left); these fields had no distinct peak. In other neurons, there was a distinct peak, but the firing rate then never dropped below the significance criterion level even at very large eccentricities (Fig. 7D, middle). Finally, in some neurons, the firing rate increased monotonically with eccentricity (Fig. 7D, right).

Visual or movement fields having distinct peaks of activity (e.g., Fig. 7, B and C, and D, middle) appeared to encode a specific target location or saccadic vector, and those having firing rates that increased steadily with eccentricity (Fig. 7D, right) seemed to encode the distance of the target from the fovea (or the length of the saccade). Such visual and movement fields, carrying information about the target location or saccade vector, were found, respectively, in 100% (33/33) and 88% (30/34) of the SC source neurons, 61% (17/28) and 79% (23/29) of the MD relay neurons, and 100% (33/33) and 96% (22/23) of the FEF recipient neurons. Signals encoding the target location or saccadic vector therefore were abundant throughout the pathway.

Quantitative comparison of the sizes and spatial locations of the visual fields (Fig. 8A) and movement fields (Fig. 8B) showed that they remained similar throughout the pathway. Looking for differences from SC to MD and from MD to FEF, we found only that the best eccentricities of visual fields in MD were slightly larger than in the SC or the FEF (Fig. 8A, *; P < 0.025 criterion, corrected from P < 0.05 because the MD data were used in 2 comparisons). Throughout the pathway nearly all visual and movement fields had contralateral best directions (Fig. 8, A and B, far left).



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FIG. 8. Summary of best directions, direction ranges, best eccentricities, and eccentricity ranges for visual (A) and movement fields (B) for all 3 samples of neurons. Legend is in leftmost graph of A. {triangleup}, medians. The SC and FEF distributions were each compared with the MD distribution, and significant differences are indicated with asterisks. Best directions were angular data and thus required circular statistics analysis (Mardia-Watson-Wheeler test) (Batschelet 1981Go). For clarity, FEF distributions are inverted.

 
The next step in determining if there was a projection topography was to analyze which part of the SC provided input to each MD and FEF neuron. We did this by calculating an index called the EPI (see METHODS). EPI = -1 meant that a neuron seemed to receive only rostral SC input; EPI = +1 meant that it seemed to receive only caudal SC input; and intermediate EPI values indicated that it received input from intermediate rostrocaudal SC locations. MD and FEF neurons received input from a wide range of SC locations as shown by the pooled distribution of EPIs in Fig. 9A ( ; {square}, irrelevant here, is described in DISCUSSION).



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FIG. 9. Projection topographies from SC to MD and FEF. A: , the distribution of electrode preference indices (EPIs) for all the MD and FEF neurons pooled together. An EPI value indicates whether an MD or FEF neuron was activated preferentially from rostral SC (negative EPI) or caudal SC (positive EPI). For comparison (see DISCUSSION), {square} shows the distribution of EPIs for FEF neurons that project to the SC (from Sommer and Wurtz 2000bGo). Note that all neurons for which an EPI could be measured are included in these histograms, including some for which a best eccentricity did not exist or was not measured. B: for MD relay neurons (top) and FEF neurons (bottom), the best eccentricity (logarithmically transformed) of the visual and/or movement field of each neuron is plotted against the EPI of the neuron. If a neuron had both a visual and a movement field, we used the average best eccentricity of the fields. C: overall relationship between best eccentricity and EPI, created by pooling all the MD and FEF data from the graphs in B. D: diagram summarizing the projection topography. This illustration was derived from the regression line equation in C and the average rostral ("EPI -1") and caudal ("EPI +1") SC electrode placements plus interpolated midrange data ("EPI 0").

 
Finally, we evaluated whether there was a projection topography by plotting the best eccentricity of each MD or FEF neuron against its EPI. We used log10(best eccentricity) because eccentricity is represented logarithmically across the SC, but the same result was found using nontransformed best eccentricity. Log10(best eccentricity) was directly correlated with EPI for both MD relay neurons (Fig. 9B, top) and FEF recipient neurons (Fig. 9B, bottom). The appreciable scatter in the correlations was probably due to noise in the measurements of best eccentricity and current threshold (used to calculate EPI). Due to time constraints, best eccentricity was found using only limited quantification of the visual and movement fields (Fig. 7A) and current threshold for activating a neuron 50% of the time was found by iterating current levels over dozens of trials rather than the hundreds of trials that would have been preferable. Regardless, the significant correlations (Fig. 9B) did indicate that MD or FEF neurons having relatively small or large eccentricity fields were preferentially activated, respectively, from rostral or caudal SC, consistent with an orderly projection topography.

To summarize the results, we pooled all the data (Fig. 9C) and used the resulting regression equation and the average locations of the rostral and caudal stimulating electrodes (see METHODS) to illustrate the projection topography schematically (Fig. 9D). The topography was reasonably precise: projections from ~2° eccentricity on the SC map preferentially drove MD or FEF neurons having visual or movement fields of ~1° best eccentricity, projections from ~5° eccentricity preferentially drove neurons having fields of ~6° eccentricity, and projections from ~13° eccentricity preferentially drove neurons having fields of ~23° eccentricity.

Signals conveyed through the pathway

VARIETY OF SIGNAL TYPES CARRIED BY THE NEURONS. We evaluated the neuronal signals primarily with delayed-saccade tasks (Fig. 10A). After Bruce and Goldberg (1985Go), we classified neurons into three major categories: visual neurons (Fig. 10B) having phasic or tonic visual activity but no presaccadic activity, visuomovement neurons (Fig. 10C) having phasic or tonic visual activity plus presaccadic activity, and movement neurons (Fig. 10D) having presaccadic activity but no phasic or tonic visual activity. We found all three categories of neurons throughout the pathway, except that there were no movement neurons in the FEF recipient neuron sample (Fig. 10D).

Figure 11A shows the distributions of visual, visuomovement, and movement neurons at each stage of the pathway. Nearly every neuron in the pathway was active in the delayed-saccade tasks with only a small proportion at each stage unmodulated ("other" neurons). Visuomovement neurons were the most common type at every stage. We compared the distributions of neuron types from SC to MD and from MD to FEF ({chi}2 tests, P < 0.025 criterion because MD data were tested twice). From SC to MD, there was no significant change in the distribution of neuron types, but from MD to FEF, the distribution changed significantly: the FEF distribution was much more visual in nature than would be expected from its MD input.



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FIG. 11. Distributions of neuron classes, showing the percentages of visual, visuomovement, and movement neurons (A), neurons having delay activity (B), and neurons having tonic visual activity (C), at each stage in the ascending pathway. Larger arrows indicate significantly different distributions. The pie charts represent 47 SC neurons, 46 MD neurons, and 37 FEF neurons.

 
Many of the neurons also had delay activity, a signal occurring in memory trials after target disappearance and before saccade initiation that may be involved in higher-level functions such as working memory (Fuster 1997Go; Goldman-Rakic 1995Go). As examples, delay activity was present in all of the visuomovement neurons in Fig. 10C (see orange data representing memory trials). From SC to MD, the proportion of neurons with delay activity dropped significantly (Fig. 11B), but from MD to FEF, it did not change.

Because the proportions of visual, visuomovement, and movement neurons stayed the same from SC to MD (Fig. 11A), but the proportion of neurons having delay activity dropped (Fig. 11B), the connection from SC to MD seemed to act like a high-pass filter. That is, the connection seems to let bursts of action potentials through more readily than sustained activity (visual, visuomovement, and movement neurons nearly always had sharp visual- and saccade-related bursts of activity; see Fig. 10, B-D). To test this idea, we also examined whether the proportion of neurons carrying another sustained signal, tonic visual activity, similarly decreased from SC to MD. Figure 11C shows that it did. Moreover, we found that this was not a trivial result of delay activity and tonic visual activity tending to co-occur in the same neurons (analysis not shown).

Notably, however, the proportion of tonic visual signals increased from MD to FEF (Fig. 11C). Taken together with the result of Fig. 11A, that FEF recipient neurons are generally more visual than expected from their MD input, this suggests that FEF recipient neurons receive additional visual signals from elsewhere (probably from extrastriate cortex).

Many neurons in the SC and the FEF have gap activity presumably related to cognitive aspects of preparing to move or disengaging from fixation (Dias and Bruce 1994Go; Munoz et al. 2000Go), so we also used a gap task (Fig. 12A) to see if the pathway carried this signal. Gap activity is a slowly rising firing rate at the end of a gap period, occurring after a foveated spot disappears and before the neuron can possibly respond to the onset of the visual target for a saccade. Some neurons at every stage of the ascending pathway had gap activity (Fig. 12B). The occurrence of gap activity, however, diminished significantly from SC to MD (Fig. 12C). This provides even further evidence for a high-pass filter at the SC-MD synapse, given the slowly varying nature of gap activity (albeit not as sustained as delay or tonic visual activity, it nevertheless is a much more slowly varying signal than the visual or saccadic bursts). From MD to FEF, there was no significant change in the proportions of neurons having gap activity (Fig. 12C).

Finally, we also looked for two other kinds of signals that were relatively rare: fixation-related and postsaccadic activity. A few neurons clearly changed their firing rate at the start of fixation, and to further study them, we ran monkeys on a standard fixation blink task in which the fixation spot disappeared for ~400 ms, allowing us to distinguish activity related to the motor act of fixating from activity related to foveal visual responsiveness (for details, see Sommer and Wurtz 2000bGo). We found 5 SC neurons with foveal visual responses, 3 of which also had a fixation signal, 3 MD neurons with fixation signals, 2 of which had a foveal visual response, and 10 FEF neurons having the following distribution of signals: 2 had a foveal visual response but not a fixation signal, 4 had a fixation signal but not a foveal visual response, and 4 had both a foveal visual response and a fixation signal. We also searched for postsaccadic activity using the delayed-saccade tasks (see METHODS), and found three neurons in each of the SC, MD, and FEF samples that exhibited this activity.

STRENGTH AND TIMING OF SIGNALS. The preceding analyses were concerned with the percentages of various signals at different levels of the pathway; now we consider the activity profiles of the signals. We focused on visual- and saccade-related bursts of activity because these signals were plentiful throughout the pathway. For each neuron, we constructed spike density functions to summarize its firing rate in the visual version of the delayed-saccade task. To analyze visual bursts (Fig. 13A, left), we used Gaussians of width {sigma} = 2 ms for constructing spike density functions (narrower Gaussians resulted in data too noisy for reliably analyzing every neuron, and wider Gaussians resulted in unacceptable underestimates of the visual latency and visual burst magnitude). The latency of a visual burst was the duration from target onset until the spike density function crossed a significance threshold set to 2 SDs above mean baseline activity (measured from 40 ms before to 40 ms after target onset). The burst magnitude was the peak magnitude of the burst minus the mean baseline activity. The peak time was the duration from target onset until the peak magnitude of the burst. In this example (Fig. 13A, left), the visual burst latency was 75 ms, the burst magnitude was 475 spikes/s, and the peak time was 90 ms after target onset (also, the baseline activity had a mean of 8 spikes/s and an SD of 11 spikes/s, yielding a significance threshold of 30 spikes/s). To analyze saccadic bursts (Fig. 13A, right), we used similar methods and the same descriptors (latency, burst magnitude, and peak time) except that the spike density function Gaussian was set to 10 ms and the baseline activity was measured during the immediately preceding Delay epoch (see Fig. 10A). We tried narrower Gaussians but they often caused spurious, temporary rises above the baseline activity prior to the saccade. In this example (Fig. 13A, right), the saccadic burst latency was -96 ms, the burst magnitude was 194 spikes/s, and the peak time was -8 ms, where negative timing values represent periods before saccade initiation.



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FIG. 13. Strength and timing of signals. A: single neuron data illustrating the analyses. A visual burst is analyzed at left for 1 FEF recipient neuron and a saccadic burst is analyzed at right for another. Green dots show rasters of spikes from individual trials. See RESULTS for details. B: overall average visual bursts (left) and saccadic bursts (right). Thick lines are means, thin lines SEs. Data were aligned to target onset (left) or saccade onset (right) in the main graphs and to start of the bursts in the insets.

 
Table 1 lists all the quantitative results for the visual and saccadic bursts, and to allow a more qualitative appreciation of the data, Fig. 13B shows the grand average spike density functions (created by averaging the spike density functions from each neuron). A caveat of averaging together spike density functions is that burst latencies appear shorter than they actually are; for example, FEF recipient neurons had a median visual burst latency of 84 ms (Table 1, top row) even though in Fig. 13B (left) the latency appears to be ~65 ms. Thus although Fig. 13B accurately depicts the relative differences between the SC, MD, and FEF data, one should consult Table 1 for exact timing values. The most striking result in the visual burst data were that the FEF latencies occurred earlier than the MD latencies (Fig. 13B, left; Table 1, top row). In other words, the visual response of FEF recipient neurons preceded that of the MD neurons projecting to them, and therefore the primary visual drive of the FEF recipient neurons cannot be coming from the ascending pathway. In contrast, from SC to MD, the visual burst latencies were not different (