Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892-4435
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Sommer, Marc A. and Robert H. Wurtz. Composition and Topographic Organization of Signals Sent From the Frontal Eye Field to the Superior Colliculus. J. Neurophysiol. 83: 1979-2001, 2000. The frontal eye field (FEF) and superior colliculus (SC) contribute to saccadic eye movement generation, and much of the FEF's oculomotor influence may be mediated through the SC. The present study examined the composition and topographic organization of signals flowing from FEF to SC by recording from FEF neurons that were antidromically activated from rostral or caudal SC. The first and most general result was that, in a sample of 88 corticotectal neurons, the types of signals relayed from FEF to SC were highly diverse, reflecting the general population of signals within FEF rather than any specific subset of signals. Second, many neurons projecting from FEF to SC carried signals thought to reflect cognitive operations, namely tonic discharges during the delay period of a delayed-saccade task (delay signals), elevated discharges during the gap period of a gap task (gap increase signals), or both. Third, FEF neurons discharging during fixation were found to project to the SC, although they did not project preferentially to rostral SC, where similar fixation neurons are found. Neurons that did project preferentially to the rostral SC were those with foveal visual responses and those pausing during the gap period of the gap task. Many of the latter neurons also had foveal visual responses, presaccadic pauses in activity, and postsaccadic increases in activity. These two types of rostral-projecting neurons therefore may contribute to the activity of rostral SC fixation neurons. Fourth, conduction velocity was used as an indicator of cell size to correct for sampling bias. The outcome of this correction procedure suggested that among the most prevalent neurons in the FEF corticotectal population are those carrying putative cognitive-related signals, i.e., delay and gap increase signals, and among the least prevalent are those carrying presaccadic burst discharges but lacking peripheral visual responses. Fifth, corticotectal neurons carrying various signals were biased topographically across the FEF. Neurons with peripheral visual responses but lacking presaccadic burst discharges were biased laterally, neurons with presaccadic burst discharges but lacking peripheral visual responses were biased medially, and neurons carrying delay or gap increase signals were biased dorsally. Finally, corticotectal neurons were distributed within the FEF as a function of their visual or movement field eccentricity and projected to the SC such that eccentricity maps in both structures were closely aligned. We conclude that the FEF most likely influences the activity of SC neurons continuously from the start of fixation, through visual analysis and cognitive manipulations, until a saccade is generated and fixation begins anew. Furthermore, the projection from FEF to SC is highly topographically organized in terms of function at both its source and its termination.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The importance of the frontal eye field (FEF) and the superior
colliculus (SC) to oculomotor behavior is well established. Electrical
stimulation using low currents in either structure elicits saccadic eye
movements (Bruce et al. 1985; Robinson
1972
; Robinson and Fuchs 1969
; Schiller
and Stryker 1972
) or inhibits them such that the eyes stay
fixed (Burman and Bruce 1997
; Munoz and Wurtz
1993b
). Neurons in both FEF and SC discharge immediately before
saccade initiation (Bruce and Goldberg 1985
;
Schiller and Koerner 1971
; Wurtz and Goldberg
1971
) or during fixation (Bizzi 1968
;
Munoz and Wurtz 1993a
; Suzuki et al.
1979
). Reversible inactivation of either structure severely
disrupts saccades and fixations (Dias and Segraves 1999
;
Hikosaka and Wurtz 1985
, 1986
;
Schiller et al. 1987
; Sommer and Tehovnik
1997
). Ablation of either structure impairs saccades and
fixations for a few days or weeks, but animals then recover and exhibit
only a few types of long-term deficits (e.g., Deng et al.
1986
; Schiller et al. 1987
). If both the FEF and
the SC are bilaterally ablated, however, the ability to make saccades and fixations is permanently devastated (Schiller et al. 1980
).
The FEF projects to the SC (reviewed by Leichnetz and Goldberg
1988), and there is evidence that much of the FEF's influence over oculomotor behavior is mediated by this projection. The FEF relays
oculomotor signals to the SC (monkey: Segraves and Goldberg 1987
; cat: Weyand and Gafka 1998b
), electrical
stimulation of FEF modulates neuronal activity in the SC (monkey:
Schlag-Rey et al. 1992
; cat: Guitton and Mandl
1974
), and if the SC is reversibly inactivated, the ability to
evoke saccades electrically from the FEF is impaired (Hanes and
Wurtz 1999
).
To understand the role of the FEF in the oculomotor system, therefore,
it is important to elucidate the nature of the signals relayed from FEF
to SC. One way to accomplish this is to record from neurons in the FEF
that are identified as projecting to the SC by virtue of their
antidromic activation after stimulation of the SC. In a landmark
application of this method, Segraves and Goldberg (1987)
concluded that the output of FEF to the SC primarily consists of
signals related to saccade generation or suppression. Because the FEF
is known to contain a wide variety of signals, from purely visual to
purely motor in nature (Bruce and Goldberg 1985
;
Schall 1991
), the FEF's output to SC appeared to be
"selectively enriched" in motor-related signals (Goldberg and Segraves 1990
; Segraves and Goldberg 1987
).
When we began the present study, no one had examined the projection
from FEF to SC in the monkey since Segraves and Goldberg (1987). Of necessity, therefore our first goal was to determine the composition of signals in this projection so as to replicate the
previous findings. To characterize the signals flowing from FEF to SC
as carefully as possible, we took advantage of techniques that have
become common in the past decade: 1) use of a grid system for aiming electrodes that facilitates the systematic exploration of a
cortical region and 2) statistical analysis of spike trains that facilitates the objective classification of signals carried by
neurons. Also, we tried to correct for sampling bias caused by cell
size variation using a method adapted from primary motor cortex research.
The present study was primarily motivated by three recent findings
regarding SC neurons. First, there are tonic neuronal discharges in the
SC that intervene after the phasic response to a visual target for a
saccade and before the phasic discharge that is synchronized to saccade
initiation. These tonic delay signals can predict hundreds of milliseconds in advance where, or whether, a saccade will be made,
suggesting that they help to mediate attention, memory, or planning
(Basso and Wurtz 1998; Glimcher and Sparks
1992
; Kojima et al. 1996
; Munoz and Wurtz
1995
; Sommer et al. 1997
). Second, neuronal
discharges in the SC can increase during a temporal gap that elapses
after a foveated spot disappears and before a visual target for a
saccade appears in the periphery (Dorris and Munoz 1998
;
Munoz and Wurtz 1995
); such gap signals are
correlated with relatively fast reaction times (Saslow
1967
) and therefore may help mediate fixation disengagement or
movement planning (e.g., Paré and Munoz 1996
;
Reuter-Lorenz et al. 1995
). Third, neurons concentrated
in the rostral pole of the monkey SC exhibit tonic discharges during
steady fixation (Munoz and Wurtz 1993a
). Often, neurons
with these fixation signals also pause during saccades and
show an increase in activity after saccades, all of which suggests that
the neurons are important for keeping the eyes still. All three of
these recently studied types of signals in the SC also have been found
in the FEF (Bizzi 1968
; Bruce and Goldberg 1985
; Dias and Bruce 1994
; Funahashi et
al. 1989
; Hanes et al. 1998
; Joseph and
Barone 1987
).
The second goal of this study, therefore, was to examine the properties
of delay, gap, and fixation signals that may be relayed from FEF to SC.
The report of Segraves and Goldberg (1987) did not
discuss delay and gap signals. Both types of signals are thought to
help mediate cognitive operations, as noted above, and if neurons projecting from FEF to SC were found to carry these signals, this would
reveal a distinct subcortical route through which frontal lobe
cognitive operations might influence oculomotor behavior. Segraves and Goldberg (1987)
previously demonstrated
that fixation-related signals are relayed from FEF to SC, and they
briefly commented that FEF neurons with such signals could be activated
from "a wide range of points" on the SC map (their p. 1399). We
followed up on this note by systematically testing whether
fixation-related signals might project preferentially to the rostral as
opposed to the caudal SC. If a rostral bias were present, this would
provide strong evidence that the FEF is a source of the
fixation-related signals carried by rostral SC neurons.
Our third goal was to analyze the topography of visual and movement
fields in the FEF and determine how this topography projects onto the
map of space within the SC. It has long been known that visual and
movement space is represented topographically across the SC; in
particular, the eccentricities of visual receptive fields and movement
fields decrease gradually from caudal to rostral (Apter
1945; Cynader and Berman 1972
; Sparks et
al. 1976
). In the FEF, the eccentricities of visual and
movement fields appear to decrease from mediodorsal to ventrolateral
(Bruce et al. 1985
). Three important aspects of the FEF
eccentricity gradient, however, are still unknown. First, it is not
known which laminae in the FEF contain this eccentricity map. We
examined whether an eccentricity map exists specifically in the
corticotectal population of FEF neurons concentrated in
layer V (Fries 1984
; Leichnetz et al. 1981
). Second, the exact angle of the eccentricity gradient
across the two-dimensional area of the FEF is unknown. To explicitly determine this angle, we plotted eccentricity as a function of two-dimensional location in the FEF. Third, it is unknown whether the
FEF's eccentricity gradient projects directly onto the known gradient
of eccentricity in the SC. We analyzed this by comparing the
eccentricities represented by FEF neurons to the collicular termination
zones of these neurons. Prior, less direct evidence for a superposition
of FEF and SC eccentricity maps has come from a variety of anatomic
(Komatsu and Suzuki 1985
; Stanton et al. 1988
) and electrophysiological studies (Schlag-Rey et
al. 1992
; Segraves and Goldberg 1987
).
In the present study, we first physiologically identified the FEF and SC (Fig. 1A) and implanted stimulating electrodes in the rostral and caudal SC (Fig. 1B). We then characterized the task-related signals of FEF neurons that were antidromically activated from the SC (Fig. 1C), estimated the locations of these neurons within the FEF, and estimated their termination locations along the rostrocaudal axis of the SC. We found that essentially all the neuronal types previously identified in the FEF can be antidromically activated from the SC, suggesting that the output of the FEF to the SC is not selective but reflects the general population of FEF signals. A large proportion of FEF corticotectal neurons exhibited delay signals, gap signals, or both. Surprisingly, FEF neurons with activity strongly related to the act of fixating did not project preferentially to rostral SC, although other types of corticotectal neurons did. We found a two-dimensional map of eccentricity in the FEF corticotectal neuron population and showed that it projects in an orderly manner onto the map within the SC.
|
Brief reports pertaining to some of these data have appeared previously
(Sommer and Wurtz 1998a,b
, 1999
;
Wurtz and Sommer 1998
).
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Surgery
Two monkeys (Macaca mulatta) were surgically prepared
in aseptic conditions using isofluorothane anesthesia. We inserted eye coils subconjunctivally (Judge et al. 1980), drilled and
tapped holes in the skull for the placement of screws, and trephined holes for accessing the FEF (this hole was centered at A25, L20 for
monkey H and at A23, L18 for monkey C) and the SC
(this hole was centered on the midline and angled 42° back from
vertical so that electrode penetrations would approach the SC
approximately orthogonally to its surface, for both monkeys). Recording
chambers were placed over the trephinations, plugs were attached for
accessing eye coil leads, and dental acrylic was applied so that the
cylinders, eye coil plugs, and a post for head restraint all were held
securely, and so that the entire implant was connected firmly to the
skull via the screws. To permit magnetic resonance images (MRIs) of the
monkeys, screws were titanium and the chambers and head holder were
plastic. Monkeys received analgesics and antibiotics postoperatively. All procedures were approved by the Institute Animal Care and Use
Committee and complied with Public Health Service Policy on the humane
care and use of laboratory animals.
Antidromic stimulation
The FEF and the SC (Fig. 1A) were located
physiologically. To find the FEF, we explored the cortex rostral to the
arcuate sulcus (the sulcus was visible through the dura mater during
surgery). We defined the mediolateral range of FEF in our monkeys as
those sites just rostral to the arcuate sulcus where penetrations
yielded saccade-related corticotectal neurons (Visuomovement or
Movement Neurons as defined in RESULTS; see Fig. 7,
A and D). We verified that these sites were
within the FEF of Bruce et al. (1985) by electrically
evoking saccades from these sites, or immediately adjacent sites, at
low current threshold (<50 µA using 70-ms trains of biphasic pulses,
0.25 ms/phase, at 350 Hz). Threshold was defined as current that evoked
saccades on 50% of trials. Stimulation began 200 ms after
disappearance of a foveated light while the monkey's task was to
maintain fixation on the blank screen (during the fixation task
described in Behavioral procedures). The SC was identified
physiologically by its characteristic lamination, with visually
responsive neurons located dorsal to neurons discharging before and
during saccade generation (e.g., Sparks and Hartwich-Young 1989
), and by its topographic map of stimulation-evoked
saccades (Robinson 1972
).
Stimulating electrodes were implanted in rostral and caudal SC (Fig.
1B). They were used for 1-3 mo and then replaced at
slightly different locations once they began to fail (i.e., when their ability to conduct current degraded). Electrodes in rostral
SC all were within the 3° amplitude representation on the SC map (Robinson 1972), and those in caudal SC all
were between the 7 and 20° amplitude representation. Electrodes were
placed near the representation of the horizontal meridian. We chose the
depth of stimulation according to the following criteria. Rostral SC electrode tips were placed at depths in the SC where visual receptive fields were foveal, where activity continued while the monkey fixated a
spot that blinked off for several hundred milliseconds, and where we
could delay ipsiversive visually guided saccades, evoke small
contraversive saccades, or both, using <20 µA. In practice, these
criteria led to placement of rostral electrode tips 2.4 ± 0.6 (SD) mm below the SC surface (range 1.6-3.3 mm), where saccades were
inhibited or <3° amplitude saccades were evoked at thresholds of
9.5 ± 5.1 µA (range 3-14 µA). When placing caudal SC
electrode tips, we chose sites where large contraversive saccades were
evoked using <10 µA and where the dominant neuronal discharge was
presaccadic burst activity. These criteria led to placement of caudal
electrode tips 1.8 ± 0.5 mm below the SC surface (range 1.5-2.7
mm) where saccades of amplitude 12 ± 6° (range 7
20°) were
evoked using current thresholds of 4.3 ± 1.9 µA (range 2-7 µA). Distances between the rostral and caudal electrode tips in the
SC, as estimated from inter-electrode distances in the grid, were
1.8 ± 0.4 mm (range 1.4-2.2 mm). The characteristics of the rostral SC stimulation sites indicated that they were in the
intermediate gray layer zone where "fixation" neurons are found
(Munoz and Wurtz 1993a
), and the characteristics of
caudal sites indicated that they were in the intermediate gray layer
region where saccade-related "burst" and "buildup" neurons are
found (Munoz and Wurtz 1995
).
Once the SC stimulating electrodes were cemented into place (by
applying epoxy to bind together the electrode shafts, guide tubes,
grid, and implanted cylinder), near daily recording sessions commenced.
During a penetration through the FEF, we first isolated a neuron and
then attempted to activate it from the rostral or the caudal SC using a
single biphasic pulse of current (cathodal-anodal, 0.15 ms and 600 µA
per phase). Once an activated neuron was found we lowered the current
to find the threshold for activating it from each electrode (threshold
defined as current for which activation occurred 50% of the time).
Antidromic activation was confirmed for all neurons in this study using
the collision test (Fig. 1C) (see Lemon 1984
for review of the collision test). Activation latency was measured from
the start of the stimulation artifact until the start of the evoked
action potential. Conduction velocity was calculated using the formula
D/(L
u), where D is
the axon distance from FEF to SC (estimated to be 40.5 mm)
(Segraves and Goldberg 1987
), L is the
antidromic activation latency, and u is the utilization
time, i.e., the time it takes for electrical stimulation to elicit an
action potential, estimated to be 0.2 ms (reviewed by Lemon
1984
).
We used tungsten microelectrodes (Frederick Haer) for recording and
stimulating (impedances were 300-1,200 k and 90-110 k
at 1,000 Hz, respectively). Electrodes were inserted through a guide tube held
by a grid (Crist et al. 1988
) that was attached within
the implanted chamber. Use of the grid was especially important for
recordings, because it permitted systematic exploration of the cortex
within and surrounding the FEF. For the FEF, guide tubes were made as
short as possible, so that they barely passed through the dura (to
avoid damaging the cortex). For the SC, guide tubes were inserted so
their ends were ~4 mm above the SC surface.
Behavioral procedures
During experimental sessions, a monkey sat in a primate chair
centered within magnetic fields used for detecting eye position (Robinson 1963). Visual stimuli (0.3 × 0.3° blue
or red spots on a dark background) were back-projected onto a tangent
screen 57 cm in front of the monkey using an LCD projector (Sharp model 850). Ambient room light was dim. Coverage of the visual field was
80° horizontally and 60° vertically, centered on a point straight ahead from the midpoint of the monkey's eyes. A personal computer controlled the presentation of visual stimuli, and this computer in
turn was controlled by a personal computer running a QNX-based real
time experimentation data acquisition system (REX) (Hays et al.
1982
). A third personal computer ran in-house software that
served as a digital oscilloscope (50 kHz), allowing us to separate
action potential waveforms using time and amplitude windows. The REX
system recorded at 1 kHz the eye position, the occurrence of action
potentials, and the timing of task events. Visual stimuli actually
appeared on the screen an average of 12 ms after the times noted in
data files, as reported previously (Basso and Wurtz 1998
; Eifuku and Wurtz 1998
), and we accounted
for this by shifting these times in the data files later by 12 ms.
Monkeys performed three tasks that allowed us to characterize the signals carried by neurons: the delayed-saccade task, the gap task, and the fixation task.
DELAYED-SACCADE TASK. At the beginning of the delayed-saccade task (Fig. 2A), a monkey was required to fixate a central spot of light for a random duration (500-800 ms), and then a target appeared in the periphery. In visual trials (Vis. in Fig. 2A), the target remained lit for the rest of the trial; in memory trials (Mem. in Fig. 2A), the target disappeared after 100 ms. We randomly interleaved these two versions of the delayed-saccade task to help us identify tonic visual responses, as described in RESULTS. After a random delay period of 500-1,000 ms, the fixation light disappeared, providing the cue to make a saccade to the target's location. When analyzing results, the mean firing rates during five periods (Analysis Epochs in Fig. 2A) were quantified and compared (statistical analysis is described in STATISTICAL ANALYSIS OF NEURONAL SIGNALS). The Baseline epoch was 500-200 ms before target onset, the Visual epoch was 50-150 ms after target onset, the Delay Period epoch was 300-0 ms before the cue to move, the Presaccadic epoch was 50-0 ms before saccade initiation, and the Postsaccadic epoch was 50-150 ms after saccade termination.
|
GAP TASK. In the gap task (Fig. 3A), the monkey first fixated a spot for a random duration of 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; the monkey could then look at the target with no further imposed delay. Firing rate during a Gap Period epoch, from 50 ms before target onset to 50 ms after, was compared with firing rate during a Baseline epoch 500-200 ms before start of the gap. We inspected all the data to ensure that the Gap Period epoch did not overlap with periods of phasic peripheral visual activity occurring after target onset.
|
FIXATION TASK. In the fixation task (Fig. 4A), the monkey foveated a spot for a random duration of 500-1,000 ms, and then the spot disappeared for a random duration of 400-600 ms while the monkey had to maintain fixation. Then the spot reappeared at the same place for an additional random duration of 500-1,000 ms. Five analysis epochs were defined. The Baseline epoch was during the intertrial period, 300-0 ms before fixation spot onset, the First Fixation epoch was 100-300 ms after start of fixation, the Foveal Visual Offset epoch was 100-300 ms after disappearance of the fixation spot, the Second Fixation Epoch was 300-0 ms before fixation spot reappearance, and the Foveal Visual Onset epoch was 100-300 ms after fixation spot reappearance. Firing rates during all five epochs were quantified and compared with each other statistically, as described below, but only a few of the resulting comparisons were found to be useful for characterizing the neurons, as described in RESULTS.
|
GENERAL TESTING PROCEDURE.
The basic protocol for characterizing the signals carried by each
antidromically activated neuron was as follows. First, we determined
the extent of the neuron's visual receptive field or movement field by
having the monkey perform the delayed-saccade or gap task while the
position of the target was varied throughout the testing space until a
location was found that evoked maximal visual- or movement-related
firing (as judged by on-line inspection of action potential rasters and
histograms). This location was termed the best location for
the neuron. Then, during formal testing using the delayed-saccade and
gap task, the visual target was presented at this best location (for a
minority of neurons, visual- and movement-related activity did not vary
throughout the testing space, i.e., there was no best location, so
during formal testing of these neurons we arbitrarily chose to present
the target contralaterally, 10° eccentric on the horizontal
meridian). Often a separate block of gap task trials also was run in
which the target location was randomized twofold (described in
RESULTS), to see whether gap-related signals depended on
knowledge of eventual target location and to help facilitate comparison
of our results with those of Dias and Bruce (1994). If a
neuron appeared to change its firing rate at the start of fixation
during the delayed-saccade or gap tasks, the monkey was then run on the
fixation task to better characterize the foveal-related signals. Eye
position tolerance windows around fixation spots were 2 × 2°,
and those around target stimuli typically were 5 × 5°
(sometimes larger for targets in the far periphery). Correct responses
were rewarded with drops of water during experiments (water intake was
controlled in the monkey's home cage).
STATISTICAL ANALYSIS OF NEURONAL SIGNALS. For each neuron and each type of task, the data set consisted of mean firing rates during the series of epochs associated with the task events. First, to see whether the neuron's activity varied at all during the task, we ran an ANOVA on the data. If this was significant (P < 0.01), we then performed an all-pairwise multiple comparison test (Student-Newman Keuls or Dunn's) so that we could determine whether firing rates in any two epochs differed from each other (P < 0.05). Specific types of signals (e.g., delay signals) were defined according to comparisons between epochs, as presented in RESULTS.
Estimating cell body and axon termination locations
To estimate the location of a neuron's soma in the FEF, we
moved the recording electrode carefully up and down until the action potential voltage was peak-to-peak maximal and then recorded the depth
of the electrode tip with respect to the end of the guide tube. Over
the course of the study, after numerous penetrations, it became evident
that the ends of the guide tubes for monkey C rested on top
of the cortex (because 1st neurons typically were encountered 0-500
µm below the end of the guide tube even though the guide tube was
barely through the dura), whereas the ends of the guide tubes for
monkey H were 1 mm above the cortex. During data analysis,
the noted depths of all the FEF neurons were adjusted using this
corrective information to estimate how deep the neuron was located with
respect to the top of the cortex. To analyze topographies within the
FEF, cell body locations in FEF were plotted on a standard
two-dimensional map [similar to the practice of plotting SC neurons on
a standard map (e.g., Anderson et al. 1998)]. Derivation of the FEF standard map is described in RESULTS.
The rostrocaudal location of axon termination in the SC was estimated
by comparing the current threshold, I, for activating each
FEF neuron from the rostral versus the caudal SC electrodes. We
preferred to use a quantity that increased with increasing ease of
activating a neuron; therefore we defined an ability to activate,
A, as I1. As examples,
A = 0 meant the neuron could not be activated
antidromically from an electrode, A = 2,500 meant that
a neuron could be activated, but at relatively high current threshold
(400 µA), and A = 100,000 meant that it could be
activated very easily (using only 10 µA). To compare the ability to
activate a neuron at the rostral and caudal electrodes, we defined an
Electrode Preference Index, EPI, using a standard contrast
ratio: EPI = (Acaudal
Arostral)/(Acaudal + Arostral). Therefore EPI = 1 meant that the neuron was activated only from the caudal electrode,
EPI =
1 meant that it was activated only from the rostral
electrode, and EPI = 0 meant that it was activated with equal ease
from both electrodes. These techniques appeared to provide a good
estimate of where a neuron's axon terminated along the rostrocaudal
axis of the SC, as reviewed in the DISCUSSION. [Note, if
one prefers to think in terms of current threshold, I,
rather than its reciprocal, A, then the above equation can be rearranged to yield EPI = (Irostral
Icaudal)/(Irostral + Icaudal).]
Correction for sampling bias
Estimates of signal composition in a population of neurons can
suffer from sampling bias due to the preferential recording of larger
neurons (Towe and Harding 1970). In terms of quantities that are measurable during in vivo extracellular recordings, neurons with higher conduction velocities are oversampled (conduction velocity
is directly related to cell size) (Cullheim 1978
;
Gasser 1941
; Kernell and Zwaagstra 1981
).
To correct for this sampling bias we used the method described in
detail by Humphrey et al. (1978)
and applied to primary
motor cortex data by Humphrey and Corrie (1978)
. Their
premise is that, "with equivalent transmembrane action potentials,
the discharge of a large neuron will generate a greater flow of
membrane current, a larger extracellular spike, and a potential field
that is above recording noise levels over a greater distance than will
a small cell. Thus the larger a neuron, the greater is the distance
that it may lie from an exploring electrode before its spike becomes
undetectable or too small to observe reliably. Because of this
relationship, the effective volume of neural tissue that is `sampled'
or `observed' during a given microelectrode penetration is not a
constant, but is instead larger when recording extracellularly from
large cells than when recording from small cells. In order to estimate
the true relative densities of cells of different sizes, it is
necessary, therefore to divide observed measures of their relative
densities or frequencies within a given sample of units by estimates of
their relative, effective recording volumes
(Veff). For example, if
No(
) is an experimentally observed
distribution of cellular conduction velocities (
), then the true or
unbiased distribution, Nt(
), would be given by Nt(
) = No(
)/Veff(
) where
Veff(
) is now considered to be an explicit
function of axonal conduction velocity, rather than that of the closely
related quantity, cell size." (Humphrey and Corrie
1978
, p. 234). Therefore the key to correcting for sampling bias due to cell size variation is to find
Veff(
). Humphrey et al. (1978)
derived an equation for pyramidal neurons that described the
extracellular spike amplitude as a function of various neuronal characteristics (e.g., dendritic geometry), extracellular conductivity, and distance from the cell body's center to the recording site. Empirical measurements verified that the equation was accurate (Humphrey et al. 1978
), and therefore it was used to
evaluate Veff. Further models and
physiological experiments revealed a relation between extracellular
spike amplitude and conduction velocity, and by combining this result
with the equation noted above, Humphrey et al. (1978)
concluded that Veff(
) = k
3/2, where k is a constant.
We used the above expression for Veff() to
correct for sampling bias. First, the experimentally observed
distribution of conduction velocities for our sample of antidromically
activated neurons was expressed as a histogram
No(
i), representing the number of
neurons, No, that had conduction velocities
within each bin
i (18 bins of 5 m/s width were used,
spanning 0 to 90 m/s; see Fig. 5). The
estimated true distribution, therefore was
Nt(
i) = No(
i)/k
i3/2.
The value of k is unknown, but it can be canceled out by
converting the numerical histogram,
Nt, into a histogram of proportions, P, of neurons that are in each conduction velocity bin
![]() |
|
In summary, this corrected distribution estimates the actual
proportion of neurons in the underlying population that have various
conduction velocities. The major assumption of the method is that the
neurons are pyramidal such that their effective recording volumes
(Veff) are cylindrical, aligned with
the apical dendrite. Although FEF corticotectal neuron morphology is
not known in detail, most neurons in FEF layer V appear to be pyramidal
(e.g., Stanton et al. 1989; Walker 1940
),
and studies of partially filled FEF corticotectal neurons suggest that
most of them are pyramidal (Fries 1984
; Leichnetz
et al. 1981
).
Using the corrected distribution of conduction velocities, the
corrected proportion of each functionally defined class of neuron can
then be calculated. To illustrate this procedure, consider the simple
case in which there are two conduction velocity bins, 1 and
2,
and three neurons in the recorded sample. Assume that one neuron fell
in bin
1 and two neurons fell in bin
2. After correction, assume that the
corrected distribution indicates that 80% of neurons in the underlying
population actually fall into bin
1 and
20% fall into bin
2. Now, assume that
only one of the recorded neurons is of cell type X (e.g.,
the class of neurons carrying delay signals) and that this neuron fell
into bin
2. In the experimentally
observed data, therefore cell type X made up 50% of the
cells in bin
2, or 33.3% of the entire
sample. After correction, cell type X still accounts for
50% of the data that fall into bin
2,
but now it has been calculated that cells with conduction velocity in
bin
2 actually make up only 20% of the
underlying population. Therefore the corrected proportion of
cell type X in the population is 50% of 20%, or 10%. This
procedure is easily extended to cases where there are arbitrary numbers of cell classes or conduction velocity bins. The only assumption is
that neurons in the same velocity bin (i.e., neurons of similar sizes)
are sampled with equal likelihood; this assumption seems valid because
sampling bias appears to be caused primarily by cell size variation
(Towe and Harding 1970
).
Anatomic verification of FEF and SC sites
MRIs (1.5 Tesla) were taken of the brain in both monkeys, and
frontal and parasagittal planes were inspected at 1-mm intervals. A few
days before taking the MRI we implanted electrodes with their tips at
locations in the FEF that had yielded many corticotectal neurons so
that we could visualize these locations. For monkey H, over
a series of days near the end of the experiment, we made marking
lesions at the sites of antidromically activated neurons in the FEF and
through the tips of the stimulating electrodes in the SC, using DC of
10 µA for 20 s (for FEF) and 20 µA for 60 s (for SC).
About 1 wk later we overdosed the monkey with pentobarbital sodium,
inserted several guide pins into the brain through reference holes in
the FEF chamber grid, and perfused the animal transcardially with 10%
neutral buffered Formalin. The guide pins, fixed in place, were then
used to direct blocking cuts of the FEF. We sectioned the FEF block in
a plane normal to the cortical surface and parallel to the principal
sulcus in 30-µm sections. The SC was sectioned coronally every 30 µm. For both FEF and SC, in every three consecutive sections, two
were stained for cell bodies (thionin) and one for myelin (modified
protocol of Gallyas 1979) to aid in recovery of marking
lesions. The other monkey is being used for further experiments.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
We isolated 138 neurons in the FEF that were activated antidromically from the SC (monkey H, n = 82; monkey C, n = 56). Of these, 88 were analyzed using our behavioral tasks. Of the remaining 50 neurons, 4 were not modulated by any of our tasks, and 46 were lost before they could be fully tested on the tasks.
Composition of signals sent from FEF to SC
We analyzed neuronal discharges that occurred in relation to
visual stimulation, saccade generation, fixation, delay periods, and
gap periods. These discharges were the "signals" carried by neurons. Neurons that carried specific combinations of signals were
grouped into "neuron types." For example, neurons discharging just
after visual stimulation and also just before saccade generation were
termed Visuomovement Neurons (after the nomenclature of Bruce and Goldberg 1985). Summary data for each signal type and each neuron type are listed in Tables 1 and
2, respectively.
|
|
SIGNALS RELATED TO DELAY PERIODS, PERIPHERAL VISUAL STIMULATION, OR
MOVEMENT.
We used the delayed-saccade task to detect signals related to delay
periods, peripheral visual stimulation, and saccade generation. A
neuron had a delay signal if, in memory trials, its firing
rate during the delay period (Del epoch, Fig. 2A) differed
from its baseline firing rate (Base epoch). Only memory trials were
considered because, in the delay period and baseline epochs of these
trials, visual stimulation (fixation spot on, target off) and motor
behavior (steady fixation) were identical. Firing rate differences
between the epochs therefore may primarily reflect cognitive processes (e.g., see Basso 1998; Fuster 1973
). Of
the 88 neurons tested, 33 had a delay signal (Fig. 2B). For
21 of the neurons the delay period firing rate was higher than
baseline, and for the remaining 12 neurons it was lower than baseline
[both elevated and suppressed delay signals are thought to play a role
in cognitive operations (e.g., Funahashi et al. 1989
;
Fuster et al. 1982
; Niki 1974
)]. It has
been proposed that delay signals related to a restricted range of
target locations or saccade vectors may reflect spatially restricted
attention, memory, or planning (e.g., Niki 1974
;
Niki and Watanabe 1976
). Thus we tested most of the
neurons that had delay signals with multiple target locations and found
that 90% (26/29) did exhibit spatially restricted delay signals
(spatial regions associated with the delay signals were contralateral
for 80% of neurons, ipsilateral for 8%, and on the vertical meridian for 12%).
GAP-RELATED SIGNALS.
We used the gap task to identify signals during gap periods that may be
associated with cognitive processes such as fixation disengagement
(e.g., Dias and Bruce 1994). A neuron had a gap increase signal if it increased its firing rate during the gap period (Gap epoch, Fig. 3A) compared with baseline (Base
epoch). Of the 88 neurons tested, 34 exhibited this type of signal
(Fig. 3B). We note three important characteristics of these
neurons. First, many neurons with gap increase signals also exhibited
peripheral visual signals (62%, 21/34), presaccadic burst signals
(65%, 22/34), or delay signals (44%, 15/34) when tested with the
delayed-saccade task. In terms of neuron types, gap increase signals
were carried by 41% (7/17) of Visual Neurons, by 61% (14/23) of
Visuomovement Neurons, and by 44% (8/18) of Movement Neurons. Second,
gap increase signals usually occurred even if target location was
randomized. We tested 25 of the neurons with gap increase signals in a
separate block of gap task trials in which the target appeared either
within the visual or movement field of the neuron or, randomly on 50% of the trials, at the same eccentricity but 180° opposite in
direction. Most neurons (88%, 22/25) still exhibited a gap increase
signal in this block of trials. Third, when the target appeared outside the visual or movement field, elevated gap discharges quickly ceased
after the target appeared (Fig. 3B). With respect to all of
these discharge characteristics, our neurons with gap increase signals
appear to be very similar to the FEF neurons described by Dias
and Bruce (1994)
.
FOVEAL-RELATED SIGNALS. While testing neurons using the delayed-saccade and gap tasks, we noticed that 39% (34/88) changed their firing rate at the start of fixation. This foveal-related activity was quantified using the fixation task (Fig. 4A), and two kinds of signals were defined. A neuron had a fixation-related signal (Fig. 4B) if its activity during the late blink period (Fix2 epoch, Fig. 4A) was different (greater or less than) baseline (Base epoch). This activity was not a foveal visual response for two reasons: first, it was not a foveal off-response because the change in activity persisted for hundreds of milliseconds after fixation spot disappearance; second, it was not a response to the diffuse light on the screen because activity during the Fix2 epoch was different from baseline activity even though the fovea was illuminated with the same diffuse light during both periods. The only difference between the Base epoch and the Fix2 epoch was the requirement to maintain fixation at the center of the screen during the latter, and therefore we interpreted the type of activity shown in Fig. 4B as related to the motor act of fixating. On the other hand, some neurons did carry signals clearly related to foveal visual stimulation. We considered a neuron to have a foveal visual signal (Fig. 4D) if it increased its activity just after fixation spot reappearance (VisOn epoch) compared both to baseline and to the late blink period. Twenty-four neurons had fixation-related or foveal visual signals (20 had fixation-related signals, 7 had foveal visual signals, and 3 had both). The remaining 10 neurons exhibited discharges during the fixation task that resisted simple classification.
We defined two mutually exclusive neuron types to separate our foveal-related neurons into visual and motor extremes. Two neurons were termed Pure Fixation Neurons (Fig. 4C) and were considered to fall at the motor end of the spectrum of signals, because their discharges were elevated relatively steadily above baseline throughout the entire trial period (i.e., during all 4 epochs Fix1, VisOff, Fix2, and VisOn of Fig. 4A). At the other extreme, four neurons appeared to be entirely visual, having a foveal visual signal but no fixation-related signal at all; these were called Pure Foveal Visual Neurons (Fig. 4D). Pure Foveal Visual Neurons simply discharged when the fovea was illuminated with a discrete spot of light and fell silent otherwise. Note that the lack of activity during the Fix2 epoch (Fig. 4D) was not related to the act of steadily fixating because an identical lack of activity occurred during the Base epoch, when fixations and saccades were interspersed.CONDUCTION VELOCITY, CELL SIZE, AND SAMPLING BIAS.
Conduction velocity distributions for the 88 neurons tested on
behavioral tasks and for all 138 neurons are shown in Fig. 5A (medians 30 and 26 m/s, respectively; not significantly
different). We compared the conduction velocities of neurons carrying
each type of signal or belonging to each defined neuron type to the conduction velocities of all the other neurons analyzed with behavioral tasks. The only significant results were that Movement Neurons had
higher conduction velocities than other neurons (Fig. 5B; medians 43 vs. 25 m/s, P = 0.007) and that the general
class of all neurons carrying a presaccadic burst signal had higher
conduction velocities than other neurons (Fig. 5C; medians
37 vs. 21 m/s, P = 0.002). These two categories of
neurons, therefore probably had larger axons and cell bodies than the
other neurons (Cullheim 1978; Gasser
1941
; Kernell and Zwaagstra 1981
).
|
Topographic organization of signals sent from FEF to SC
DISTRIBUTIONS OF CELL BODIES IN FEF AND AXON TERMINALS IN SC.
To analyze the distribution of corticotectal cell bodies, we first
constructed a standard map of the FEF. Successful penetration entrance
sites in the FEF (i.e., those yielding saccade-related corticotectal
neurons) are shown for monkey C in Fig.
7A and for monkey H in Fig. 7D. MRIs verified that
penetration trajectories went through the rostral bank of the arcuate
sulcus (MRI of monkey C is shown in Fig. 7B). For
monkey H this was further confirmed by inspection of marking
lesions and electrode tracks in histological sections (not shown).
Low-threshold electrical stimulation (<50 µA) within these recording
sites or adjacent sites (×, Fig. 7, A and D)
evoked saccades at short latency (Fig. 7C). The amplitude of
evoked saccades decreased from medial to lateral (Fig. 7C) and also from dorsal to ventral within a penetration (not shown). Our
recording sites therefore were in the FEF as classically defined (e.g.,
Bruce et al. 1985; Robinson and Fuchs
1969
). The recording sites tended to form a curve that
paralleled the arcuate sulcus (Fig. 7, A and D),
undoubtedly because to yield corticotectal neurons the penetration
trajectories had to intersect with or follow the contour of layer V
(Fries 1984
; Leichnetz et al. 1981
), which runs parallel to the sulcus. For each monkey, we drew a curve
representing the top edge of layer V onto the map of penetrations (Fig.
7, A and D). This curve defined a
mediolateral axis (Fig. 7E, top), with zero at
the medial edge of the FEF (*, Figs. 7, A and D)
and with values increasing toward the more lateral FEF. The location of
each recording site was described in relation to the mediolateral axis
using orthogonal projection as shown schematically in Fig.
7D. Recording depth below the cortical surface defined a
second, dorsoventral axis (Fig. 7E, top), with
zero at the cortical surface and with values increasing down through the bank, parallel to the sulcus. Note that the mediolateral and dorsoventral axes used in this report are rotated from the conventional stereotaxic axes (Fig. 7E, bottom).
|
|
|
DISTRIBUTIONS OF TASK-RELATED SIGNALS IN CORTEX. Using the FEF standard map, we compared the FEF locations of neurons carrying each type of signal or belonging to each defined neuron type to the FEF locations of all the other neurons analyzed with behavioral tasks. Comparisons were made in the mediolateral and the dorsoventral directions (Student's t-test or Mann-Whitney rank sum tests were used as appropriate, and because we tested the data twice, along orthogonal axes, the significance criterion was adjusted to P < 0.05/2 = 0.025). Signals putatively related to cognitive operations (delay and gap increase signals) were carried by neurons located more dorsally in the FEF than other neurons (Fig. 10A; medians 2.7 vs. 3.6 mm along the dorsoventral axis, P < 0.001). This dorsal bias was significant for each of the component signal types, too (i.e., for the neurons carrying a delay signal as well as for those carrying a gap increase signal). Neurons carrying a peripheral visual signal but not a presaccadic burst signal (Visual Neurons) were biased laterally in the FEF compared with other neurons (Fig. 10B; medians 3.5 vs. 2.5 mm along the mediolateral axis, P = 0.018). In contrast, neurons carrying a presaccadic burst signal but not a peripheral visual signal (Movement Neurons) were biased medially in the FEF compared with other neurons (Fig. 10C; medians 2.1 vs. 3.2 mm along the mediolateral axis, P = 0.010). No other cortical topographies of signals or defined neuron types were found.
|
DISTRIBUTIONS OF TASK-RELATED SIGNALS PROJECTING TO SC.
Using the EPI measure, we compared the axon termination locations of
neurons carrying each type of signal or belonging to each defined
neuron type to the axon termination locations of all the other neurons
analyzed with behavioral tasks (Student's t-test or
Mann-Whitney rank sum tests were used as appropriate; P < 0.05 criterion). Three cases of projection bias were found. First,
Movement Neurons projected more caudally in the SC than did other
neurons (Fig. 10D; median EPIs 0.44 vs. 0.09 respectively, P = 0.043). Second, neurons carrying a gap decrease
signal projected more rostrally than did other neurons (Fig.
10E; median EPIs
1.0 vs. 0.114, P = 0.017). Third, Pure Foveal Visual Neurons projected more rostrally than
did other neurons (median EPIs
1.0 vs. 0.084, P = 0.034). This bias of Pure Foveal Visual Neurons should be interpreted
cautiously, however, due to small sample size. In light of a prediction
by Dias and Bruce (1994)
that FEF neurons with elevated
gap activity may project uniformly over the SC, we note that our data
are consistent with this prediction in that the EPI distribution of
neurons with gap increase signals was broad and not biased rostrally or
caudally (not shown).
VISUAL AND MOVEMENT FIELD ECCENTRICITY. Most of the neurons evaluated using behavioral tasks (90%, 79/88) had spatially restricted visual receptive fields, movement fields, or both. The best location of each field (see METHODS) was described in polar coordinates, yielding a best eccentricity and best direction. There were too few data to analyze topographies of visual and movement fields separately, so we combined the data (this appeared reasonable, because for neurons with both a peripheral visual signal and a presaccadic burst signal, their visual and movement fields overlapped considerably such that there was nearly always a single best location for both types of activity). Occasionally we could determine only a best eccentricity or a best direction, but not both.
Seventy-two neurons exhibited a distinct best eccentricity of their visual or movement field. To search for topographic organization, we examined whether a neuron's best eccentricity varied as a function of its mediolateral and dorsoventral location in FEF using multiple linear regression, and this was highly significant (R = 0.64, P < 0.001). We also tried using the logarithm (base 10) of eccentricity as the dependent variable, and this worked equally well (R = 0.64, P < 0.001). Therefore the choice of dependent variable, eccentricity or log10(eccentricity), was arbitrary. We decided to use the latter because eccentricity seems to be represented in the brain most often logarithmically [for example in SC (Ottes et al. 1986
|
|
VISUAL AND MOVEMENT FIELD DIRECTION.
Sixty-seven neurons exhibited a distinct best direction of their visual
or movement fields. To summarize the general distribution of best
directions, they were oriented contralaterally for 69% of neurons
(46/67), ipsilaterally for 9% (6/67), and vertically for 22% (15/67).
Too few corticotectal neurons were encountered in each penetration to
discern whether there was a significant rotation of best direction with
depth of penetration, as was described for stimulation-evoked saccades
by Bruce et al. (1985). In some penetration sites we
could reliably obtain nearly the same best direction from day to day
within a narrow range of depths, which suggests that an underlying map
of direction might exist. However, we could not detect any systematic
topographic layout of best direction in our data.
OMNISPATIAL VISUAL AND MOVEMENT FIELDS. Ten percent of the neurons (9/88) had unrestricted visual and movement fields; i.e., they exhibited approximately equal visual- or movement-related activity over all of the testing space. We found no topographies of cell distribution in the FEF or of projection across the SC for these neurons. The most interesting property of these neurons was that nearly all (8/9) exhibited postsaccadic signals and three also carried fixation-related signals. Less common signal types in these neurons included peripheral visual signals (1 neuron) and presaccadic burst signals (1 neuron). A speculative role for these omnispatial neurons therefore would be to help terminate all saccades by projecting onto inhibitory interneurons in the SC that act to suppress the firing of movement-related neurons.
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Signal flow from FEF to SC
The first goal of this study was to evaluate the composition of
signals coursing from FEF to the SC. We found that the FEF engages in
an exuberant narration during oculomotor behavior, telling the SC about
nearly everything that occurs. Signals relating to fixation, to visual
stimulation, to possible cognitive operations, and to saccade
initiation and termination are all relayed from FEF to SC.
Notably, all these types of signals are carried by the general
population of FEF neurons, as well (e.g., Bruce and Goldberg
1985; Funahashi et al. 1989
; Hanes et al.
1998
; Schall 1991
). We see no compelling
evidence that any signal type is over- or underrepresented at the
output of FEF relative to the general population of signals in FEF.
In contrast, Segraves and Goldberg (1987) concluded that
purely saccade-related signals are overrepresented and purely
visual-related signals are underrepresented in the output of FEF
relative to the general population of signals within FEF. There are
several possible reasons why our results differ from those of
Segraves and Goldberg (1987)
in this respect. The most
important reasons may be related to topography: we found that purely
saccade-related output neurons (Movement Neurons) tend to be
concentrated in medial FEF (Fig. 10C) and tend to project
preferentially to caudal SC (Figure 10D). If Segraves
and Goldberg (1987)
focused their recordings in medial FEF or
their stimulations in caudal SC, this would have led to a larger
proportion of purely saccade-related neurons in their sample than in
ours. Although we suspect that this occurred, Segraves and
Goldberg (1987)
did not publish plots of their recording or
stimulation sites. Assuming they did record primarily in medial FEF, we
would agree with them that output is largely saccade-related for this
particular part of FEF. Even within medial FEF, however, it does not
necessarily follow that there is an enrichment of saccade-related
signals at the output compared with the general population. It could be
that in medial FEF a large percentage of neurons in all laminae have
saccade-related discharges. Regarding the lack of purely visual-related
neurons in the sample of Segraves and Goldberg (1987)
,
this too might be explained if they focused their recordings in medial
FEF rather than in the visually rich lateral region (cf. Fig.
10B).
We found that saccade-related neurons are the largest corticotectal
neurons of the FEF (Fig. 5, B and C) and thus are
likely to be oversampled relative to other corticotectal neurons. This probably did not cause the differences between our study and that of
Segraves and Goldberg (1987), however. Oversampling of
larger neurons should have affected both studies equally, and yet even in our uncorrected data there were fewer neurons primarily related to
saccades (20%, 18/88) than in their data (53%, 27/51). Therefore we
suspect that topographic factors, as described above, were the main
reasons for differences between the studies.
It should be noted that there were subtle differences in the way that
we and Segraves and Goldberg (1987) classified neurons. The two studies used different methods of detecting signals (we used
statistical analyses and they used visual inspection) and some
different tasks (e.g., we used randomly interleaved visual and memory
forms of the delayed-saccade task and they did not, and they used a
task in which a peripheral visual stimulus was presented that was not
the target of a saccade and we did not). Nevertheless, in general it
seemed to us that our Visual, Visuomovement, and Movement Neuron
categories were similar to their categories of the same names. Also,
our definitions of neurons with postsaccadic signals and foveal-related
signals were about the same as theirs. They did not classify neurons in
terms of their delay signals, and they did not test their neurons for
gap signals, so comparisons between the studies with respect to these
categorizations were not possible.
The only other study of FEF corticotectal signals was performed in cat
by Weyand and Gafka (1998a,b
), who directly compared these FEF output signals to the general population of FEF signals recorded in the same animals. We agree with their general finding, that
FEF corticotectal signals are very similar to signals in the general
FEF population.
Neuronal recordings in which projections are identified are crucial for
testing models of how brain structures interact. In particular they
help to evaluate cognitive models (Fuster
1997), which posit that signals are processed in stages (e.g.,
Miller 1988
; Taylor 1976
). What do our
data suggest about modeling the relationship between FEF and SC? A
major type of processing in FEF seems to be the transformation of
visual signals into movement commands (Bruce and Goldberg
1985
). There are two ways to represent this in terms of
cognitive models. In a discrete multistage representation, only the
output of the transformation, a movement command, is passed on to the
next stage (Fig. 13A). In a
continuous multistage representation, signals at any point in the
transformation can go to the next stage (Fig. 13B). We found
that purely visual-related and purely saccade-related signals, as well
as signals representing possible intermediates from vision to movement,
are all found in the output of FEF. Therefore we think that
the FEF and SC are best modeled as forming a continuous multistage
system (Fig. 13B): visual signals may be transformed into
movement commands within the FEF, but they also are relayed straight to
the SC, where they again become susceptible to visuomotor
transformation.
|
Comparison to other cortical output systems
Is broad diversity of output signals, and similarity between the
output signals and the general population of signals within a brain
region, unique to the FEF? No, and in fact it may be a common principle
in brain organization. Signals carried by neurons in primary motor
cortex that are known to project into the spinal cord (pyramidal tract
neurons) are only mildly different from signals carried by the general
population of motor cortex neurons (reviewed by Porter and Lemon
1993); for example, 40-50% of general motor cortex neurons
are modulated by static force as compared with 62% of pyramidal tract
neurons. Both populations are extremely diverse in signal content
(Porter and Lemon 1993
). Also, a great diversity of
signals is sent from the lateral intraparietal area to the SC
(Paré and Wurtz 1997
), including peripheral visual signals, delay signals, and presaccadic burst signals, and these signals are similar to those found generally in the lateral
intraparietal area (cf. the review of Andersen and Gnadt
1989
).
Some exceptions to this principle have been reported, as well. However,
any conclusion that output signals represent only a subset of signals
in the source area depends on a negative result (namely, that certain
signals present in the general population are not part of
the cortical output). This may be interpretable if a large sample of
antidromically activated neurons is quantitatively analyzed, but that
has not been the case for recent claims of signal specificity in
cortical outputs [e.g., visual and polysensory cortex to SC,
n = 8-22 neurons analyzed per area in Wallace
et al. (1993); MT to pretectum, n = 41 neurons
in Ilg and Hoffman (1993)
; V1 to MT, n = 9 neurons in Movshon and Newsome (1996)
]. Furthermore,
it would be important to provide evidence that the entire cortical
region of interest was sampled because high specificity in output
signals might be only a local property, caused by topographic organization of a region's output signals as was found in the present study.
Correction for sampling bias
To estimate the composition of signals flowing from FEF to SC as
carefully as possible, we tried to account for sampling bias caused by
cell size variation. Did this procedure, originally developed for motor
cortex data (Humphrey and Corrie 1978), succeed when
adapted to our data? We tested this by seeing whether we could better
predict the actual distribution of corticotectal neuron sizes in the
FEF using the corrected, rather than the experimentally observed,
conduction velocity data. We transformed the corrected and observed
distributions of conduction velocities into estimated cell diameter
distributions and then compared each to the known distribution of FEF
corticotectal cell diameters (Fries 1984
). Using the
relationship Diameter = a(Conduction
Velocity)b, we set b to a
physiologically relevant value (from 0.4 to 0.9 in increments of 0.1)
(Kernell and Zwaagstra 1981
) and then varied the
coefficient a until optimal fit was found between the
estimated and actual cell diameter distributions (judged by least sum
of squared errors). The overall best fits are shown in Fig.
14A, and the least sum of
squared errors for each value of b is shown in Fig.
14B. The cell diameter distributions derived from the
corrected data always provided the better fit to the actual
distribution. We conclude therefore that application of the correction
procedure did counter some of the sampling bias and thus led to a more
realistic estimate of the proportions of each signal type that leave
the FEF.
|
Delay, gap, and fixation signals
We found that delay and gap increase signals are among the more prevalent types of signals relayed from FEF to SC. Furthermore, we found that fixation-related signals in FEF do not go preferentially to the rostral SC. Rostral biases, however, were found in the projections of neurons carrying other types of foveal-related signals, i.e., gap decrease signals and foveal visual signals. We will discuss each of these findings in turn.
It has long been hypothesized that processes occur in the brain (which
we call cognitive operations) that are not directly observable to
psychophysicists but exert considerable influence over the motor
behavior of primates. The discovery of delay signals in prefrontal
cortex (Fuster and Alexander 1971; Kubota and
Niki 1971
) provided a clear candidate for a neuronal correlate
to cognitive operations. Some of these delay signals are spatially
selective (Kubota et al. 1974
; Niki 1974
)
and therefore might play a role in spatially restricted attention,
memory, or movement planning (Niki and Watanabe 1976
).
These early experiments studied hand or arm movements. Cognitive
operations also influence the generation of eye movements (a brief list
of relevant studies and reviews includes Andrews and Coppola
1999
; Ballard et al. 1992
; Buswell 1935
; Hoffman and Subramaniam 1995
;
Kowler 1990
; Land and Furneaux 1997
;
Miyashita et al. 1996
; Paré and Munoz
1996
; Sommer 1997
; Yarbus 1967
),
and studies also have found spatially selective delay signals in
prefrontal cortex, including within the FEF, that are related to eye
movements (Bruce and Goldberg 1985
; Funahashi et
al. 1989
; Joseph and Barone 1987
).
Although there have been reports that delay signals exist in the FEF
and that these signals may be related to cognitive operations such as
spatial memory (Funahashi et al. 1989) or deciding which saccade to make (Kim and Shadlen 1999
), where these FEF
delay signals go has been entirely unknown. We demonstrated
here for the first time that at least some of them go to the SC. Delay signals from FEF therefore may be a major source of the delay signals
expressed by SC neurons. The relay of delay signals from FEF to SC may
help to strengthen an animal's cognitive influence over its oculomotor
behavior, because compared with the FEF, the SC has more direct access
to the reticular formation premotor neurons that synapse directly onto
muscle-innervating neurons (reviewed by Büttner-Ennever
and Büttner 1988
). Therefore delay signals in the SC,
compared with those in FEF, are in better position to increase the
excitability of select groups of premotor neurons through tonic
depolarization (see Kojima et al. 1996
).
We do not mean to imply that FEF delay signals go only to SC, or that
the SC receives delay signals only from the FEF. Further work is needed
to identify other recipients of FEF delay signals. The SC receives
delay signals also from the substantia nigra (Hikosaka and Wurtz
1983) and the lateral intraparietal area (Paré and Wurtz 1997
).
Gap increase signals in the FEF are similar to delay signals in that
both classes of signals may reflect cognitive operations and both are
often carried by the same neurons. However, they are different in that
gap increase signals seem to be less spatially selective. FEF gap
increase signals therefore may primarily reflect nonspatial cognitive
operations such as fixation disengagement (Dias and Bruce
1994). It was suggested by Dias and Bruce (1994)
that the nonspatial effects of FEF neurons carrying gap increase signals may be mediated in part by their uniform pattern of projection onto the SC. In the present study we confirmed part of this hypothesis, in that we found that many FEF neurons that carry gap increase signals
do in fact project to the SC. Furthermore, our EPI results were consistent with the idea that these neurons project uniformly across the SC.
Twenty of our neurons had fixation-related signals, and these projected
about equally to rostral and caudal SC, exhibiting no bias in their
EPIs (regarding the 2 that were Pure Fixation Neurons, one had an EPI
of 1.0 and the other of 1.0). This suggests that the primary purpose
of FEF fixation-related corticotectal neurons is not to drive rostral
SC fixation neurons (Munoz and Wurtz 1993a
). Rather,
they might work in parallel to rostral SC fixation neurons, causing
inhibition of saccade-related neurons throughout the SC (Munoz
and Istvan 1998
). The eight neurons that we found with
omnispatial movement fields and carrying postsaccadic signals also may
contribute to this function.
The above result concerning fixation-related signals is consistent with
the comment by Segraves and Goldberg (1987, their p.
1399) that FEF "foveal neurons were antidromically excited from a
wide range of points within the topographic representation in the
superior colliculus." However, we also found two types of FEF neurons
with foveal-related signals that did appear to project in a
biased manner to the SC, being antidromically activated more easily
from the rostral than the caudal SC. The first type, neurons carrying
gap decrease signals, had four characteristics in common with rostral
SC neurons: decreased activity during the gap (Dorris and Munoz
1995
) and often foveal visual responses, presaccadic drops in
activity, and postsaccadic increases in activity (Munoz and
Wurtz 1993a
). The second type, the relatively rare Pure Foveal
Visual Neurons, had foveal visual responses in common with rostral SC
neurons. We conclude that in these two types of rostral-projecting FEF
neurons we might be seeing signals that converge on rostral SC neurons,
contributing at least partially to their activity profiles.
The paucity of Pure Fixation Neurons in our sample was surprising to
us, and it leads to the question of whether the FEF was sufficiently
explored. We did investigate a large portion of the FEF. The overall
cortical area sampled (Fig. 8) was in accord with prior estimates of
the range and shape of the FEF and its layer V. The shape
(approximately an inverted triangle) is consistent with that described
for layer V by Stanton et al. (1989), who noted that FEF
layer V was about twice as wide mediolaterally at the lip compared with
at the fundus. The mediolateral range of our corticotectal neurons,
~6.2 mm (Fig. 8), covered much of the 10-mm range estimated for FEF
in general (Bruce et al. 1985
) and for layer V
specifically (Stanton et al. 1989
). We explored medially
and laterally beyond this range, but none of the corticotectal neurons
we encountered were saccade-related (and hence these penetrations were
considered outside the FEF), and none were Pure Fixation Neurons. The
dorsoventral range of our corticotectal neurons, ~10 mm (Fig. 8),
fully covered the dorsoventral extent as illustrated in prior studies
of the FEF or its layer V (Bruce et al. 1985
, their Fig.
9, ~8 mm; Segraves and Goldberg 1987
, their Figs. 5 and 7, ~7 mm; Stanton et al. 1989
, their Fig. 1, ~6
mm). The estimated depths of our cell body locations probably were
somewhat exaggerated as an artifact of the electrode dimpling the
cortex during penetrations.
Gradient of visual and movement field eccentricity in the FEF that projects onto the SC
We found a significant gradient of visual and movement field
eccentricity in the FEF that was oriented ~19° up relative to the
arcuate lip (Fig. 11, A-C). This demonstrates explicitly
for the first time that an eccentricity map exists in a specific
population of neurons in the FEF, in this case the corticotectal
population concentrated in layer V. In the future it will be necessary
to determine whether eccentricity maps exist in other populations of
FEF neurons as well, which may include neurons of other laminae. It is
notable that the oblique orientation of the eccentricity gradient of
FEF corticotectal neurons may explain why saccades evoked electrically
from FEF decrease in amplitude not only from medial to lateral but also
from dorsal to ventral (Bruce et al. 1985).
We also found that within the FEF the gradients of eccentricity and of
projection to the SC were closely aligned (Fig. 11C). When
the eccentricity map of FEF afferents was superimposed onto the
eccentricity map of the SC (Fig. 12), we found good agreement between
the two maps. The eccentricity map of FEF afferents appeared to be
logarithmic, like the SC map, and both maps were similarly scaled.
However, the FEF afferent map was shifted ~1 mm rostral compared with
the SC map. Future histological studies using punctate injection of
anterograde tracer within precisely defined regions of the FEF
corticotectal map would be helpful in determining whether neurons in
the FEF truly do project to regions in SC that represent slightly less
eccentric space. Regardless, our critical point is that FEF neurons
representing a certain eccentricity project closely to the location in
SC that contains neurons representing similar eccentricities. This
confirms prior suggestions from anatomic (Komatsu and Suzuki
1985; Stanton et al. 1988
) and
electrophysiological studies (Schlag-Rey et al. 1992
;
Segraves and Goldberg 1987
) that much of the FEF seems
to be hardwired as a function of eccentricity onto the SC.
Our results concerning patterns of projection onto the SC rely on our
method for estimating axonal terminations. It is important to consider
whether this method was sound. Although our intent was to electrically
stimulate axon terminals, axons of passage also might have been
stimulated. We have two reasons to believe that we stimulated terminals
much more often than axons of passage. First, most FEF afferents enter
at the rostral pole of the SC (Stanton et al. 1988) and
proceed caudally, with some terminating along the way. If our
electrodes preferentially activated axons of passage, it should have
been much easier to activate FEF neurons from the rostral stimulating
electrode than from the caudal one. This would have caused our EPI
distributions to be strongly skewed toward
1.0 with few, if any,
values at 1.0. In fact, however, the EPI distributions tended to be
symmetric (Fig. 9C), which is more consistent with the
preferential activation of relatively homogeneously distributed
elements such as axon terminals. Second, we found a systematic
topography of the FEF projection onto the SC that was consistent with
prior anatomic studies (Fig. 11C), i.e., in general the
medial FEF projected to caudal SC and the lateral FEF projected to
rostral SC (Komatsu and Suzuki 1985
; Stanton et
al. 1988
). This projection topography in our data are easy to
explain if axon terminals were preferentially activated but hard to
explain if axons of passage were preferentially activated. We conclude
therefore that axon terminals were preferentially activated and that we
were generally successful at distinguishing rostral from caudal
projections in the SC.
We speculate that the preferential activation of axon terminals was due
to a higher density of axon terminals than axon main fibers near our
stimulating electrode tips, which we always tried to position within
the SC's intermediate gray layer. Corticotectal afferents that enter
the rostral SC (Stanton et al. 1988) probably course
through the intermediate white layer (i.e., stratum album intermediale)
before turning sharply and ascending into the intermediate gray to
terminate. A similar scheme of innervation was described by Cajal for
the SC superficial layers in many mammalian species (Swanson and
Swanson 1995
). It should be noted that other afferents from the
FEF might follow a dorsal trajectory from the midbrain tegmentum before
terminating in the SC (Leichnetz et al. 1981
). For this
class of afferents, it would be particularly easy to understand how
terminals (proximal to the electrode tips) would be activated
preferentially over main fibers (more distal and ventral to the
electrode tips).
Although we believe that axon terminals were preferentially activated in our experiments, it is possible that axon main fibers were occasionally activated instead. In fact, the slight rostral shift of the FEF afferent map relative to the intrinsic SC map (Fig. 12) is most likely an artifact of occasionally activating axon main fibers. As noted above, most FEF corticotectal afferents probably enter the rostral pole and proceed caudally, terminating along the way. Assume for the moment that the afferent map of eccentricity and the intrinsic SC map truly are in perfect register. Then, if stimulation at an SC site occasionally activates fibers that terminate more caudally in the SC, the average eccentricity of FEF neurons activated from the site will exceed the average eccentricity of FEF neurons that actually terminate near the site. If this occurs at both SC stimulating electrodes, the end result will be to slightly overestimate the eccentricity represented by FEF afferents at both the rostral and caudal sites. The measured afferent map of eccentricity therefore would seem to be shifted rostrally relative to the intrinsic SC map, as was seen.
Topographies of corticotectal signals within the FEF
It is important to emphasize that the cortical region we examined
appeared to be a single functional entity (because it contained a
single, orderly map of eccentricity) that was involved primarily in
saccade generation (because throughout its extent we found saccade-related neurons and evoked saccades at low current threshold). However, within this single, general region known as the FEF we detected three local topographies of corticotectal signals. First, Movement Neurons were biased medially, and second, Visual Neurons were
biased laterally. These first two topographic biases in signal content
correspond in interesting ways to mediolateral variations in FEF
anatomy. Stanton et al. (1988) found that the FEF
projection to the SC varies across two collicular dimensions: medial
FEF (where the Movement Neurons are) projects caudally and also
deeply in the SC, whereas lateral FEF (where the Visual
Neurons are) projects more rostrally and more shallowly.
This is consistent with the fact that neurons in deeper SC exhibit more
saccade-related activity than do neurons in shallower SC, which, in
contrast, exhibit more visual-related activity (reviewed by
Sparks and Hartwich-Young 1989
). Also, medial and
lateral FEF differ with respect to their cortical afferents, in that
the lateral FEF (where the Visual Neurons are) receives a denser input
from the highly visual inferotemporal cortex (Bullier et al.
1996
; Schall et al. 1995
). Finally, FEF efferents to posterior cortical areas also tend to follow this lateral-visual and medial-motor pattern: only lateral FEF projects to
highly visual areas such as inferotemporal cortex, area MT, and areas
V3 and V4, whereas the entire FEF (including medial FEF) projects to
the saccade-related area LIP (Stanton et al. 1995
). In
summary, although the FEF is a single functional entity involved in
saccade generation, lateral FEF seems to be more visual in nature and
medial FEF more purely motor in nature. The FEF also has been separated
mediolaterally in terms of cytoarchitecture: medial FEF was designated
area 8A and lateral FEF area 45 by Walker (1940)
, and
this basic dichotomy has been confirmed repeatedly (e.g., Bonin
and Bailey 1947
) and is now generally accepted (reviewed by
Schall 1997
). Hence a structure-function relationship is
implied in which area 8A may correspond to the more motor subfield of FEF and area 45 to the more visual subfield.
An interesting implication of this organization is that, due to the
underlying eccentricity map of the FEF (Fig. 11B), lateral FEF is not only more visual than medial FEF, but it also tends to
represent less peripheral space. This suggests that lateral FEF plays a
special role in generating small saccades in tight coordination with
visual analysis, for example during the examination of natural visual
scenes (a behavior in which most saccades are <15° in amplitude)
(e.g., Andrews and Coppola 1999; Bahill et al.
1975
; Henn and Cohen 1973
).
Finally, the third type of signal topography within the FEF was that
neurons carrying signals thought to reflect cognitive operations (delay
and gap increase signals) were biased dorsally. This bias is correlated
with a prominent gradation in FEF cytoarchitecture: layer IV is thick
and densely packed in the dorsal half of the FEF but tapers off
ventrally toward the fundus of the arcuate sulcus (e.g., Stanton
et al. 1989). Therefore assuming a radial organization of
signal flow between layers, the activity of layer IV neurons in FEF
might contribute to the delay and gap increase signals of corticotectal
neurons in layer V. Moreover, thalamocortical afferents terminate in
layer IV and thus might play a role in generating delay and gap
increase signals via reentrant circuits (Fuster 1997
)
perhaps involving the FEF-SC-thalamus-FEF loop (Lynch et al.
1994
; Sommer and Wurtz 1998a
).
![]() |
ACKNOWLEDGMENTS |
---|
We thank M. E. Goldberg, M. Paré, M. A. Basso, D. P. Hanes, N. L. Port, E. J. Tehovnik, and two anonymous referees for helpful suggestions and M. K. Smith for histological expertise. We are grateful to the Laboratory of Diagnostic Radiology Research at the National Institutes of Health for magnetic resonance images.
![]() |
FOOTNOTES |
---|
Address for reprint requests: M. A. Sommer, Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bldg. 49, Rm. 2A50, 9000 Rockville Pike, Bethesda, MD 20892-4435.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 11 August 1999; accepted in final form 28 December 1999.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|