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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
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ABSTRACT |
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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. |
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INTRODUCTION |
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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 1975
; Harting et al. 1980) 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 1981; Goldman-Rakic and Porrino 1985; Kievit and Kuypers 1975; Le Gros Clark and Boggon 1935; Walker 1940). 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. 1994). 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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; Evarts 1968). 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 1977). 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 1972).
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 1983; Wurtz and Mohler 1976), activity related to cognitive processes (Leichnetz et al. 1981), and/or presaccadic activity (Goldberg and Bushnell 1981; Lynch et al. 1994). 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 1997; MD: Schlag and Schlag-Rey 1984; Schlag-Rey and Schlag 1984; Tanibuchi and Goldman-Rakic 2003; Wyder et al. 2003; SC: reviewed by Wurtz et al. 2000). 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 1998, 2000a, 2002; Wurtz and Sommer 2000).
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METHODS |
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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 2000b 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 1981; Goldman-Rakic and Porrino 1985; Lynch et al. 1994) and stereotaxic coordinates (Martin and Bowden 1997; Olszewski 1952) 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. 1988) 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 2000b). After isolating a neuron, we identified its connections using antidromic and/or orthodromic activation (for reviews, see Lemon 1984; Lipski 1981). 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
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 1993) and one relatively caudal (typically 10-20° eccentricity on the SC topographic map) (Robinson 1972), 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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), the average threshold of 1,298 µA at a pulse duration of 0.15 ms should activate low-threshold axons (K 
381 µA/mm2) only within 1.8 mm and high-threshold axons (K 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 1972). 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 2000b). 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 2001). 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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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 1994; Munoz et al. 2000). 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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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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; Munoz and Wurtz 1995), 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 1995), 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.
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RESULTS |
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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. 1982; Zhu and Lo 1998). 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 1997; Olszewski 1952) and as predicted by anatomical studies (Barbas and Mesulam 1981; Goldman-Rakic and Porrino 1985; Lynch et al. 1994). This lateral MD location was histologically verified in both monkeys (Fig. 3 shows the results from monkey C).
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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 1998). 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 2000b), 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 1988). FEF SC-projecting neurons are found only in layer V (Fries 1984; Leichnetz et al. 1981).
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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 1972). 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 1985; Munoz and Wurtz 1995). 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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, irrelevant here, is described in DISCUSSION).
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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 (1985), 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 (
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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; Goldman-Rakic 1995). 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 1994; Munoz et al. 2000), 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 2000b). 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 
= 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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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 (Fig. 13B, left; Table 1, top row), consistent with the SC providing the primary visual drive of the MD neurons. The peak times of visual bursts also were shorter in FEF than in MD, whereas they were not significantly different between SC and MD (Table 1, 2nd row from top). In terms of the strengths of the bursts, visual burst magnitudes were not significantly different from SC to MD or from MD to FEF (Table 1, 3rd row from top). However, the baseline activity significantly decreased from SC to MD and then significantly increased from MD to FEF (Table 1, 4th row from top). Note that these results, that the burst magnitude does not change from SC to MD but the baseline activity decreases, further support our conclusion from the previous section that the SC-MD synapse acts as a high-pass filter.
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In the insets of Fig. 13B, the grand average spike density functions are synchronized to the start of the bursts to reveal the bursts' average shapes. The average visual bursts (Fig. 13B, left inset) were bimodal with a major peak 20 ms into the burst, a secondary peak 50 ms later, and a total duration of 150 ms on average. This bimodality was conserved from SC to MD to FEF. The saccadic bursts (Fig. 13B, right inset) retained approximately the same width through the pathway (250 ms), although the average shapes of the bursts differed somewhat in SC, MD, and FEF.
In sum, these strength and timing analyses yielded three major results. First, the visual bursts of FEF recipient neurons occurred too early to result solely from ascending pathway input. These neurons must get substantial visual input from elsewhere. Second, the saccadic bursts seemed especially important as they appeared to pass unhindered through the pathway. Neither their strength nor their timing changed significantly from SC to MD to FEF. Third, all tonic activity (baseline levels prior to the bursts) decreased in strength from SC to MD, supporting the idea that this synapse acts as a high-pass filter.
GENERAL POPULATION OF SC NEURONS VERSUS THOSE PROJECTING UP TO MD. In addition to recording from identified SC source neurons, we also recorded from some unidentified single neurons (n = 17) and multi-unit sites (n = 23) in the SC intermediate layers. These neurons were "unidentified" in that we did not try activating them from any other brain structure; they are a sample of the general population of SC intermediate layer neurons. We found that the signals carried by SC source neurons were quite similar to the signals exhibited by this general sample of SC neurons as summarized in Fig. 14 and Table 2. The only differences were that SC source neurons had slightly longer latency visual responses, slightly earlier peaks in their saccadic bursts, and higher baseline firing rates. Overall there was no obvious output selectivity; the signals sent from SC to MD were representative of those generally found within the SC intermediate layers.
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DISCUSSION |
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PREEMINENCE OF SACCADIC ACTIVITY IN THE PATHWAY. Many types of signals flow through the SC-MD-FEF pathway, but information about impending saccades seems to be particularly important. This conclusion is based on multiple lines of evidence: throughout the pathway 60-80% of the neurons have presaccadic activity (Fig. 11A, visuomovement + movement neurons), this activity is strong (Table 1, 7th row), it begins well before saccade initiation (Table 1, 5th row), and it peaks at or just before saccade initiation (Table 1, 6th row). Also, at every level of the pathway, the movement fields are similar (Fig. 8B), most are contraversively directed, and most carry information about the saccadic vector. Figure 15B summarizes the crux of our argument. Presaccadic activity passes unimpeded from SC up to FEF and arrives just at the right time to contribute to FEF presaccadic activity, while for other signals it is a matter of "too little, too late." Too little delay activity makes it through the MD relay node for it to be a candidate as a crucial signal in the pathway, and visual signals arrive too late to be the primary cause of FEF visual responses.
What is the function of the presaccadic activity sent from SC to FEF? It is not proprioceptive because it starts before the eyes move. Also, it is unlikely to directly contribute to saccade generation for two reasons. First, the activity travels away from the saccade generating circuits of the pons and midbrain and instead goes up to cortex. Second, the activity does not impinge on pure movement neurons in the FEF, even though such neurons are common in the general population there (Bruce and Goldberg 1985; Schall 1991); instead, it selectively targets FEF neurons having visual responses (visual and visuomovement neurons). These three lines of evidence—that the activity is presaccadic, that it ascends into cortex, and that it influences visual-related neurons—are, however, compatible with a hypothesis that the activity is a corollary discharge. The term corollary discharge (Sperry 1950) refers to copies of movement commands used solely as information (reviewed by Bell 1984; McCloskey 1981). We hypothesize that presaccadic activity in the SC-MD-FEF pathway acts to inform the FEF about saccadic movement commands produced by the SC. By impinging on visual-related neurons, the activity may help prepare the visual system for the abrupt changes in visual input that occur when saccades suddenly rotate the retinas (e.g., see von Helmholtz 2000). More generally, the diverse roles of the FEF not only in vision but also in motor planning, learning, and memory (reviewed by Schall 1997; Tehovnik et al. 2000) imply that it could use corollary discharge for other purposes as well, for example in coordinating saccadic sequences. In our view, therefore, an important role of the SC-MD-FEF pathway is to convey presaccadic activity that may represent corollary discharge. To test this hypothesis, we would have to interrupt signal flow in the pathway and see if this causes deficits in tasks that require corollary discharge. We have indeed done this (Sommer and Wurtz 2002), and the accompanying paper documents our findings in detail (Sommer and Wurtz 2004b).
SIGNALS THAT ASCEND FROM THE SC. We next discuss the data at a more reductionist level by stepping one at a time through each stage of the pathway. Our basic result pertaining to the first leg of the pathway was that a broad array of signals travels from SC to MD (Figs. 11 and 12). Most SC source neurons carried combinations of visual, delay, and presaccadic activity, and many had gap activity as well. All of these signals are quite common in the SC intermediate layers (Munoz et al. 2000; Sparks and Hartwich-Young 1989; Wurtz et al. 2000). Moreover, the visual and saccadic bursts of our SC source neurons were very similar to those generally found in the SC (Fig. 14). In short, the signals sent from SC to MD represent all of the signals in the SC intermediate layers, not just a subset. This is consistent with our previous hypothesis (Sommer and Wurtz 2000b) that, in the saccadic system at least, output signals of a structure closely resemble the general population of signals within that structure; selectivity is rare or absent. Lack of output selectivity also has been found for FEF (Everling and Munoz 2000; Sommer and Wurtz 2000b; see also cat results, Weyand and Gafka 1998a,b) and the lateral intraparietal area (Paré and Wurtz 1997, 2001). However, subtle differences could exist at a quantitative level between a structure's output signals and its general population of signals; for example, peak times of presaccadic bursts were slightly earlier in SC source neurons than in neurons of the general SC population (Fig. 14; Table 2, 6th row). The functional significance of such small differences is unclear.
MD RELAY NODE. Our basic finding pertaining to the relay node in the pathway was that MD neurons faithfully conveyed phasic activity (visual and presaccadic bursts) from SC to FEF but suppressed tonic activity (delay, tonic visual, and gap activity). This is suggestive of high-pass filtering, although thresholding may have contributed as well because the bursts had stronger peak firing rates than did the tonic activity. The exact mechanism is not important to the current discussion. The main point is the end result: the pathway primarily informs the FEF about when and where a visual stimulus appeared and when and where an upcoming saccade will go, information carried in the visual and saccadic bursts. In contrast, the pathway removes tonic activity and the cognitive-related signals it may convey (Fuster 1997; Goldman-Rakic 1995; Munoz et al. 2000; Wurtz et al. 2000, 2001). Leichnetz et al. (1981) hypothesized that the pathway plays a role in attention, but our data cast doubt on this considering that a prime mediator of attentional signals is tonic activity (e.g., Luck et al. 1997; Treue 2001). To the extent that attentional signals are carried in visual bursts, however, the hypothesis remains plausible.
Preferential transmission of bursts over tonic activity has been found in at least one other thalamic region, the lateral geniculate nucleus (LGN). An action potential arriving at an LGN neuron from the retina that rapidly follows another retinal input spike (within 20 ms) is particularly effective in evoking an action potential from the neuron (Levine and Cleland 2001; Mastronarde 1987; Rowe and Fischer 2001; Usrey et al. 1998). Also, all thalamic relay neurons alternate between "tonic mode," in which they reproduce their input fairly linearly with gain 1, and "burst mode," in which a single input spike can elicit a burst of spikes. In behaving monkeys, LGN neurons are usually in tonic mode but can slip into burst mode (Ramcharan et al. 2000a,b). MD relay neurons may be normally in low-gain tonic mode but occasionally shift into burst mode as the monkey anticipates target onset or saccade initiation. A sudden volley of spikes from the SC could then trigger an unusually vigorous burst from the MD neurons.
Guillery and Sherman (2002) suggested on the basis of our brief report (Sommer and Wurtz 2002) that our MD relay neurons might receive a modulatory input, rather than a driving input, from the SC. This seems unlikely in light of the present results. We showed here that single pulse stimulation in the SC activated MD neurons very quickly (median: 1.4 ms, including a presumed synaptic delay of only 0.57 ms) and required normal current thresholds for this type of study (mean: 264 µA). The SC-MD synapse therefore was fast and strong, more like a driver than a modulator. Furthermore the firing characteristics of SC source neurons and MD relay neurons were quite similar, consistent with the former driving the latter (Figs. 11A and 13B). Guillery and Sherman (2002) proposed that more likely candidates as drivers of the MD relay neurons might be descending inputs from cortex. However, the rat anatomy paper they cited as evidence for a modulatory SC input onto MD neurons stated that "collicular boutons tend to be larger and distribute to more proximal parts of the dendrites than those from the prefrontal cortex." (Kuroda and Price 1991; p. 550). Thus SC inputs should have more of an influence on MD thalamus than cortical inputs. Also, the SC inputs made asymmetric, excitatory synapses onto the thalamic neurons, and we see no reason to assume they cannot drive them. We think the evidence clearly favors a driving, not a modulatory, role for SC inputs onto MD neurons in this particular circuit.
FEF RECIPIENT NEURONS. Our basic findings regarding the FEF recipient neurons concerned the prevalence and timing of their visual responses. First, visual activity was nearly ubiquitous in the neurons. This had implications for a corollary discharge function of the SC-MD-FEF pathway, as discussed in the preceding text, and also suggested that the FEF recipient neurons get additional visual signals from elsewhere, since their input from MD was significantly less visual (Fig. 11A). Second, visual responses of the FEF recipient neurons started before those of MD relay neurons (Fig. 13B left). This further supported the argument that FEF recipient neurons receive extra visual input, and a reasonable guess is that this comes from extrastriate cortex.
Although the visual signals sent from MD to FEF were relatively slow, they were nevertheless abundant and strong. A possible function for these visual inputs might be to modulate visual signals arriving from extrastriate cortex. For example, the ascending inputs might contribute to changes in the initial visual response related to saccadic target selection ("saccadic enhancement" effects: Goldberg and Bushnell 1981; Wurtz and Mohler 1976; "target discrimination" effects: Schall and Thompson 1999). This possibility is supported by our finding that most of the visually responsive SC source neurons and MD relay neurons also had presaccadic activity (visuomovement neurons). The visual activity could be a sort of preparatory corollary discharge signal, telling the FEF which stimulus will be targeted by the upcoming saccade, prior to the presaccadic activity that represents the actual corollary discharge of the saccade. The visual activity thus should be modulated in Go/Nogo tasks, being larger in Go trials when a stimulus will be targeted by a saccade than in Nogo trials when the stimulus will be irrelevant. Further experiments are needed to test this prediction.
Alternatively, of course, visual signals sent upstream by SC and MD neurons might simply be pure visual responses and not modulated by behavioral context. Two papers previously hypothesized that much of the visual activity in the prefrontal cortex, including in the FEF, might come from SC (Mohler et al. 1973; Suzuki and Azuma 1983). This was because FEF visual receptive fields are relatively large and unselective for visual attributes like line orientation, making them more reminiscent of SC visual receptive fields than extrastriate cortical visual receptive fields. With regard to the early phase of the FEF visual response, this hypothesis is not supported by our data because short-latency FEF visual responses cannot come from the SC. It is possible that the later phase of the FEF visual response, however, is driven partly by SC input. If so, a testable prediction is that the initial visual response in FEF may exhibit marked visual tuning (e.g., for orientation) and relatively small receptive fields, reflecting input solely from extrastriate cortex, but later in the response the visual tuning might broaden and the receptive fields expand, reflecting additional input arriving from the SC.
Because of the relatively late arrival of visual information from the ascending pathway into FEF, one might expect the FEF visual response to be bimodal, with an early "extrastriate input" burst followed 21 ms later (see Table 1, 2nd row) by a secondary "ascending pathway input" burst. Whether this occurred is difficult to say. On the one hand, the average shape of all the visual bursts in this study was bimodal (Figs. 13B and 14, left insets), but visual bursts in FEF were not any more bimodal than those in SC and MD, and the time lag between the peaks, 50 ms, was longer than the expected 21 ms. However, that all the visual responses were bimodal is not easy to explain in itself. It may be that bimodality starts in the FEF recipient neurons because of the two out-of-phase visual inputs and then propagates down to SC through corticotectal projections, inducing bimodality everywhere including in the ascending pathway back to FEF. Modeling this circuit might shed light onto why in the steady state condition the separation between peaks becomes, on average, 50 ms apart everywhere.
Issues of methodology
IMPORTANCE OF PHYSIOLOGICAL IDENTIFICATION. One might argue that our antidromic and orthodromic identification methods were unnecessary—perhaps the SC-MD-FEF pathway could have been adequately described by just comparing the general populations of SC, MD, and FEF neurons with each other. Neurons in each of these structures, however, are inter-connected with wide-ranging parts of the brain and may be part of numerous possible networks. Only through physiological identification could we be confident that a neuron belonged to the SC-MD-FEF pathway. The activity of our identified neurons was sometimes quite different from that reported previously for general populations of neurons. For example, as noted in the preceding text, our FEF recipient neurons seemed more visual in nature than neurons in the general FEF population. Also, our MD relay neurons rarely had delay activity, which seemed surprising considering the many prior reports of delay activity in neurons of MD and nearby thalamic regions (Fuster and Alexander 1971; Tanibuchi and Goldman-Rakic 2003; Watanabe et al. 2000; Wyder et al. 2003). Results such as these had important implications as to the function of the pathway and were critically dependent on physiologically identifying the neurons.
POSSIBLE ORTHODROMIC ACTIVATION THROUGH COLLATERALS. There is always an element of ambiguity about orthodromic activation because it can occur through routes other than the assumed one. We think that when we stimulated the SC and orthodromically drove MD and FEF neurons, this activation occurred via the ascending pathway. It could be, however, that it occurred via collaterals of corticotectal neurons ("collateral hypothesis"). Many cortical neurons project to the SC, and SC stimulation can antidromically activate them. An antidromically evoked action potential traveling in the axon of such a cortical neuron could invade a collateral terminating on an MD or FEF neuron. If input from this collateral causes the postsynaptic neuron to fire, one might mistakenly think that the neuron was being orthodromically driven through the ascending pathway.
We emphasize first that even if one completely ignores our orthodromic activation results because of this caveat, the basic conclusion of this paper remains the same. From antidromic activation results alone we know that intermediate layer SC neurons send presaccadic activity and other signals to the lateral edge of MD and that neurons there send similar signals, except with tonic activity diminished, into the FEF. These results still indicate that the pathway is highly active during visuosaccadic behavior and that presaccadic activity is one of the main signals carried through it.
In our opinion, however, the orthodromic activation results are valid; we are confident for several reasons that in our experiments the collateral hypothesis is wrong. The first reason is based on our stimulation-related data. If the collateral hypothesis were correct, stimulation in the SC should always directly activate the same neuronal elements (axons at or near their termination) regardless of whether the later event at the recorded neuron were antidromic invasion of the soma or orthodromic activation via synapses. Our EPI data, however, indicate that the same neuronal elements in the SC are not directly activated in the two situations. Recall that the EPI is an index summarizing how easy it is to drive a neuron from rostral versus caudal SC. We previously described the EPI distribution for antidromically activating FEF neurons from the SC (Sommer and Wurtz 2000b), and this distribution was strikingly bimodal (Fig. 9A, ); more than half of the FEF corticotectal neurons could be activated only from the rostral electrode (EPI = -1) or only from the caudal electrode (EPI = 1). When orthodromically activating FEF neurons from the SC in the present study, however, the EPI distribution was broadly unimodal; nearly every neuron could be driven from both the rostral and caudal SC electrode (Fig. 9A, ). The vastly different EPI distributions strongly suggest that different neuronal elements in the SC are recruited in antidromic versus orthodromic activation—probably axon terminals during antidromic activation but axon hillocks and initial segments during orthodromic activation—and this seems to rule out the collateral hypothesis.
A second reason to doubt the collateral hypothesis pertains to activation latencies. The latencies of activating FEF recipient neurons from the SC were quite precisely predicted by the latencies of signals passing through MD relay neurons (Fig. 6B). The simplest explanation for this is that all activations passed through the ascending pathway from SC to MD to FEF.
A third reason to doubt the collateral hypothesis is based on studies of other pathways. Investigators stimulating the LGN to orthodromically activate striate cortex (V1) neurons, for example, have been concerned about inadvertently activating the neurons via collaterals of corticothalamic neurons. They were in the fortunate position, however, of being able to directly test this by stimulating the optic tract and seeing if the V1 neurons still fired; this could occur only if LGN efferents drove the V1 neurons. When this test has been performed, nearly every V1 neuron activated orthodromically at short latency from LGN also has been activated from the optic tract (e.g., Bullier and Henry 1979; Ferster and Lindström 1983; Singer et al. 1975; Stone and Dreher 1973; Toyama et al. 1974). One can drive V1 neurons via collaterals, but only by increasing the stimulation intensity 5- to 10-fold (Ferster and Lindström 1983, 1985). Similarly, in neurons of primary motor cortex (M1), excitatory postsynaptic potentials arising from thalamic input are more potent than those arising from collaterals of pyramidal tract neurons; membrane potentials from thalamic input are shorter-latency, faster-rising, and much more likely to evoke action potentials (Deschênes et al. 1979). In sum, collaterals in V1 and M1 are relatively weak and we see no reason why they would be stronger elsewhere.
There are also further reasons to doubt the collateral hypothesis as we discussed previously (Sommer and Wurtz 1998). These multiple lines of evidence deem it unlikely that spurious orthodromic activation via collaterals substantially affected our data.
POSSIBLE TERMINATION OF SC SOURCE NEURONS ONTO NONRELAY NEURONS. Our SC source neurons projected to lateral MD, as shown by antidromic activation, but some may have terminated on thalamic neurons that do not project to the FEF (Fig. 2B). We doubt that this confound was a major factor because we were careful to activate SC neurons only from sites of MD relay neurons and because the highly similar activity patterns of SC source neurons and MD relay neurons were consistent with their being connected.
COMPARING SIGNAL CONTENT BETWEEN AREAS. An analytical limitation pertains to our comparison of signal types at each stage of the ascending pathway. We felt we could infer how signals change from area to area because we studied only neurons known to be in the pathway. This seems better than the usual practice of comparing populations of neurons recorded with no regard to their connections (e.g., Alexander and Crutcher 1990a,b; Crutcher and Alexander 1990). However, even improved inferences are still inferences. Some might be incorrect. For example, the presaccadic bursts of FEF recipient neurons were similar in every way to the presaccadic bursts of MD relay neurons, so a logical inference is that the FEF bursts were derived from MD input. It is possible, however, that much or all of the FEF presaccadic activity came from elsewhere. Presaccadic input from MD might only create postsynaptic potentials in FEF neurons that do not cause action potentials but modify other inputs. Our corollary discharge hypothesis makes no strong prediction about this. Although SC neurons must drive MD neurons so that presaccadic activity is relayed accurately, the influence of MD input on FEF neurons could be multifold: MD input could modulate FEF neurons to immediately influence saccadic planning or visual analysis, it could drive them so as to relay corollary discharge onward to other neurons or networks that use the information, or it could have both influences, modulating some FEF neurons and driving others.
Despite the limitations involved in comparing signal types across areas, we still think this type of analysis has great merit in describing signal flow in a pathway as long as all neurons under consideration are identified as belonging to the pathway. At the very least it provides a first-order description that may be refined by later experiments, such as cross-correlation studies to see if neurons dually recorded in two connected areas have the predicted relationship, or reversible inactivation studies to see if inhibiting input from one area (e.g., MD) predictably changes the activity of neurons in another area (e.g., FEF).
Other ascending pathways
Many other ascending pathways remain to be explored in the awake, behaving monkey. For example, the FEF is the target of disynaptic pathways originating not only from the SC but also from the substantia nigra pars reticulata, relayed via ventroanterior thalamus, and from the dentate nucleus of the cerebellum, relayed via ventrolateral thalamus (Lynch et al. 1994; Middleton and Strick 2000). Another pathway, from superficial SC to pulvinar to extrastriate cortex, has been examined by looking at the general populations of neurons at all three levels (reviewed by Sommer and Wurtz in 2004a), but so far only one study has investigated an identified class of neurons in the pathway (superficial SC source neurons: Marrocco et al. 1981). Other ascending pathways are implied by signals found in cortex that must originate subcortically (e.g., vestibular-related activity) (Andersen 1997; Brandt and Dieterich 1999), by anatomical demonstrations of myriad brain stem inputs to thalamus (Steriade et al. 1997), and by results of psychophysical studies (e.g., Tanaka 2003). In the skeletomotor system, prominent pathways course from the deep cerebellar nuclei and pallidum through thalamus to motor cortex (for reviews see Middleton and Strick 2000; Sommer 2003). They have been studied with identified neuron methods extensively in anesthetized, paralyzed cats (e.g., Cohen et al. 1962; Deschênes and Hammond 1980; Futami et al. 1986; Henneman et al. 1950; Shinoda et al. 1985a,b) but only rarely in behaving monkeys (e.g., Anderson and Turner 1991; Holdefer et al. 2000; Nambu et al. 1991).
We suggest that the overall approach taken in studying the SC-MD-FEF pathway might serve as a good model for studying these other pathways. This approach was as follows: the anatomy of the pathway was thoroughly established (e.g., Lynch et al. 1994), neurons at all levels of the pathway were identified using ortho- and antidromic stimulation methods, and the signals encoded by the neurons were deciphered by having monkeys perform a variety of tasks. These methods, and complementary ones such as simultaneous recordings in multiple areas, hold great promise for eventually describing ascending pathways at a level of detail that may someday approach our understanding of the more traditionally studied routes coursing across cerebral cortex and down to spinal cord and brain stem.
Conclusion
Schlag-Rey and Schlag (1989) ended a comprehensive review of oculomotor thalamus by writing, "at the present time we know some of the signals and some of the lines [in thalamus], but not the signal flow through the lines. The story of the central thalamus is still very incomplete." In this study, we took initial steps toward completing the story. We discovered that a variety of signals are sent from SC to MD to FEF, with presaccadic signals appearing to be the most important. We now have a good idea about what the SC tells the FEF, but a major question remains: what is the purpose of this ascending presaccadic activity? A strong possibility discussed in the preceding text is that it plays a corollary discharge function, informing the cerebral cortex about upcoming saccades, and this hypothesis is tested in the accompanying paper (Sommer and Wurtz 2004b).
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: M. A. Sommer, Bldg 49, Room 2A50, MSC 4435, NEI, NIH, 9000 Rockville Pike, Bethesda, MD 20892-4435 (E-mail: mas{at}lsr.nei.nih.gov).
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ABSTRACT
INTRODUCTION
) on the standard SC map of Robinson (1972
) 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.
