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Review Article
Production, Control, and Visual Guidance of
Saccadic Eye Movements
Jeffrey D. Schall
Department of Psychology, Center for Integrative & Cognitive Neuroscience, Vanderbilt Vision Research Center, Vanderbilt University,
Nashville, TN 37240, USA
Received July ; Accepted August
Academic Editors: Y. Ohyagi, A. K. Petridis, D. Schier, L. Srivastava, and E. M. Wassermann
Copyright © Jerey D. Schall. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Primate vision is served by rapid shis of gaze called saccades. is review will survey current knowledge and particular problems
concerning the neural control and guidance of gaze shis.
1. Introduction
Being primates endowed with a fovea providing acute vision
over a very small range of the visual eld, we must shi gaze
to explore the world. Rapid eye movements called saccades
direct the line of sight onto objects of interest in the visual
eld, oen conspicuous objects like a berry among leaves and
sometimes important objects like the family member among
a social group. More is understood about visually guided
saccade production than any other sensory motor system
for several reasons. First, movements of the eyes are simpler
than movements of the limbs or vocal apparatus because
they have fewer degrees of freedom and can ignore gravity.
Second, every neuron from the sensory through the motor
is accessible to inquiry within the cranium. ird, advances
in technology have provided accurate measurements and
manipulations of the ne details of eye movements.
Eye movement research with macaque monkeys has pro-
foundly inuenced clinical neurology and ophthalmology,
and this translational interface runs both directions. On the
one hand, insights from monkey studies have been essential
for clinicians to interpret neurological examinations. On the
other hand, properties of human eye movements have stimu-
lated neurophysiological studies that have, in turn, informed
clinical practice. While the neural control of movements is
certainly instantiated through molecular mechanisms, it has
become clear that knowledge at the level of neural systems is
most useful for this clinical translation. For example, monkey
models of strabismus and amblyopia (e.g., [–]), fourth
nerve palsy (e.g., []), nystagmus (e.g., [, ]), and Parkinson’s
disease (e.g., [, ]) have provided precise information that
would otherwise have been le to clinical guesswork. ese
monkey models have furthermore provided renements of
new treatments such as deep brain stimulation for Parkinson’s
disease, optical treatments for developmental strabismus,
and drugs for nystagmus. Similarly, many neuropsychiatric
disorders are associated with problems of gaze control (e.g.,
[]), so obtaining neurophysiological data from monkeys
performing tasks in which these problems are expressed by
patients (and their relatives) will provide information that
can improve the diagnosis and possibly treatment of these
disorders.
e literature on the production, guidance, and eects
ofsaccadesisverybroad.APubMedsearchinJuly
with the keyword “saccade” resulted in > publications.
Publications about saccades appeared at a relatively low
rate (</year) until the s whereupon the publication
rate increased dramatically to a level of ∼/year. Such a
vast literature cannot be surveyed here, but comprehensive
reviews have appeared recently (e.g., [–]). is review
will focus on new developments in our understanding of how
the brain controls the initiation and guides the endpoint of
saccadic eye movements.
Spacedoesnotpermitreviewingfascinatingnewresearch
ontherelationshipsbetweenvisionandsaccades,sotheinter-
ested reader is pointed to the body of research demonstrating
thatgazetendstofocusonconspicuousandinformative
features of an image during scrutiny of simple geometric
ISRN Neurology
stimuli (e.g., Liversedge and Findlay ), natural images
(e.g., []) or text (e.g., []), and during complex natural
behaviors (e.g., [–]) leading to the hypothesis that gaze
canbedirectedinastatisticallyoptimalmanner(e.g.,
Najemnik and Geisler, ). e reader should also be
alerted to the renewed interest and continuing disagreements
about the eects, utility, and production of microsaccades
(</
∘
) in relation to vision (e.g., []; Martinez-Conde &
Macknik ) and attention (e.g., [–]).Wealsowillnot
review the literature investigating how saccades inuence
vision beyond noting that as you can learn by watching
yourselfshigazeinamirrorbetweenleandrighteyes,
and we experience phenomenal blindness during saccades
in part because of visual masking and in part because the
responsiveness of neurons in the visual pathway is attenuated
during saccades (e.g., [, ]). In laboratory testing, visual
perception of location and spatial relations is systemati-
cally distorted immediately before, during, and immediately
aer saccades (e.g., []) presumably due to shis of the
visual eld representation coinciding with saccade generation
(e.g., [, ]). e stability of visual perception that we
experience even though we are shiing gaze two or three
times each second has been explained as the consequence
of an eerence copy signal []thatrecentphysiological
research has mapped through the visuomotor pathway [].
We should note the more recent research has found that these
eects are attenuated when multiple objects are presented
(e.g., []), so the generality of the laboratory ndings with
single spots of light presented at predictable locations for
vision in crowded natural environments requires further
investigation.
2. Saccade Production
e biomechanical and neural processes in the brainstem
producing saccades have been described in detail (reviewed
by [, ]). Recent years have witnessed important insights
into the complexity of the oculomotor periphery. ese
include the organization of the extraocular muscles into
functionally distinct ber groups and the presence of con-
nective tissue pulleys that change the pulling directions of
rectus muscles, so that the eye’s rotational axis varies with
eye position to accomplish Listing’s law. It is now possible to
characterize the motor neurons innervating dierent muscle
bers types (e.g., []) and measure innervation and forces
simultaneously (e.g., []).
Saccadic eye movements are initiated when a pulse of
force is produced through the high-frequency discharge
of oculomotor neurons innervating the extraocular mus-
cles. e pulse of force overcomes the viscoelastic forces
acting against ocular rotation. Eye position is maintained
at eccentric angles by a step of force produced through
sustained discharge of oculomotor neurons. Saccadic eye
movements are characterized by a very precise relationship
between amplitude, velocity, and duration. is relationship
is achieved through a circuit in the brainstem consisting of
burst neurons that provide the burst of action potentials to
the oculomotor neurons to produce ipsiversive saccades; the
magnitude of the burst scales with eye velocity for saccades
is less than ∼
∘
. e circuit also includes tonic neurons that
innervate the oculomotor neurons and are innervated by the
burst neurons and are understood to perform velocity to
position integration that provides the step of force needed
to maintain eccentric gaze. e details of this integration
process have occupied considerable attention in recent years
(e.g., [, ]).
Burst neuron activation is gated by omnipause neurons
(OPNs) and inhibitory burst neurons (IBNs), so that initia-
tion of a saccade requires inhibition of the omnipause neu-
rons (e.g., []). is inhibition has been described through
intracellular recordings [] and more recently through LFPs
[]. It begins as an abrupt hyperpolarization, controlled
more by glycinergic than GABAergic inputs []thatis
sustained until the saccade is completed. e inhibition on
omnipause neurons has multiple sources including long-
lead burst neurons in the brainstem, the superior colliculus,
the frontal eye eld, and the supplementary eye eld. IBNs
receive monosynaptic excitation from contralateral SC sites
producing saccades of all vectors and disynaptic inhibition
from the ipsilateral SC via contralateral IBNs. OPNs receive
excitation from the rostral end of contralateral and ipsilateral
SC and disynaptic inhibition from the caudal SC mainly via
IBNs [].
While the neural processes responsible for initiating
and producing saccades are reasonably well understood,
the mechanism responsible for terminating saccades is less
certain. Research on this problem has been guided by the
engineering principles of feedback control systems []. e
received view is that the burst neurons are driven by a
dynamic motor error signal that is the dierence between
current and desired eye position (or displacement). Evidence
for a feedback control mechanism seems beyond dispute.
Experimental activation of OPN while saccades are in ight
canresultinarrestedvelocity,butwhenthestimulationis
removed, the saccade continues to completion, fullling the
motor error.
How this comparison is accomplished in the feedback
loop remains uncertain. Key questions center on whether
the error signal is eye position, eye displacement in the
current saccade or even gaze (eye + head), and also the
anatomical substrate of the comparator. It seems unlikely
that natural reactivation of OPN terminate saccades because
the duration of the OPN pause does not correlate well with
saccade duration; normal saccades can be produced aer
OPN lesions and patients with diseases that cause abnormal
saccade durations exhibit high-frequency conjugate oscil-
lations following saccades indicative of OPN inactivation
(e.g., []). One hypothesis proposed that the SC is in
the dynamic motor error feedback loop through a pattern
of spatiotemporal dynamics of activation moving from the
location representing the vector of the saccade to the rostral
endoftheSCthatwassupposedtoengageactivexation(e.g.,
[]). Evidence against this hypothesis (e.g., []) has shied
attention to the cerebellum that is necessary for adapting the
amplitude and duration of saccades across conditions (e.g.,
[]).
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3. Control of Saccade Initiation
We must shi gaze to see things in our environment, but
vision is impaired during saccades, so the brain must balance
these competing constraints. In this section, we will survey
how the brain prepares and initiates saccades and how
those processes may be adjusted by other brain systems that
monitor the consequences of actions.
3.1. Direct Control. Direct control will refer to the processes
that specify the response time (RT). ese processes can vary
with task demands and context. For example, when given a
warning (“ready”) before an imperative trigger signal (“go”),
subjectsrespondearlierandmorereliablythanwhenno
warning is given (Niemi & N
¨
a
¨
at
¨
anen ). Also, saccade
RT is inuenced by repetition of stimuli or responses and
by the history of reinforcement (e.g., Dorris et al. ;
[, ]). is variation can be explained in terms of a
process that transpires aer the warning signal that leads
to faster responses and is inuenced by events in preceding
trials to inuence the readiness to initiate a movement. We
will refer to this process as response preparation.Further
evidence for response preparation is the observation that
partially prepared responses are more dicult to withhold if
an imperative “stop” signal occurs later in time (e.g., Logan &
Cowan ; Hanes & Schall ).
e connections between these preparatory processes
and the events that trigger a saccade are not understood. We
know that the OPNs are not modulated at all during periods
of saccade preparation (Everling et al. ). Most models
of the brainstem mechanisms of saccade generation do not
address the question of what turns o the omnipause neurons
to release inhibition on the burst neurons that will generate
the pulse through the oculomotor neurons (reviewed by
[]). In some models, it just happens (e.g., [, ]), and
in others it is related to the specication of a motor error
signal (e.g., [–]).eoriginalmodelswerenotconcerned
with explaining the variation of saccade initiation time, but
in subsequent models, the events that ultimately inhibit the
omnipause neurons are related to processes occurring in
the superior colliculus, basal ganglia, thalamus, and cerebral
cortex (e.g., [–]). e latest models were inspired by
the observation that the dynamics of the activity of specic
neurons in the FEF, and SC accounts for the variation
of saccade initiation time. Saccades are initiated when the
discharge rate of presaccadic movement neurons in FEF
and SC reaches a particular threshold (e.g., []; Hanes &
Schall ). e variation of saccade latency in a range of
tasks calling for speeded responses is accounted for by the
time taken to reach that threshold; the variation in time
to threshold arises from randomness in the rate of growth
(Hanes&Schall;Ratclietal.,)[, ]
although other studies in other task conditions nd variability
of the baseline activity as well (Dorris et al. ) []and
also systematic changes in the onset of the accumulation
when it takes longer to locate the target []oradjusttotask
conditions []. is variable accumulation to a threshold
inspired the identication of this activity with the process
described by stochastic accumulator models developed by
cognitive psychologists (e.g., []).
e neural control of movement initiation has been inves-
tigated fruitfully using the stop signal (or countermanding)
task. Developed to investigate human performance, the coun-
termanding paradigm probes a subject’s ability to control
the initiation of movements by infrequently presenting an
imperative stop signal in a response time task (reviewed by
[]). is task is diagnostic of disorders of impulse control
and response monitoring (e.g., [–]). e subjects’ task
is to produce a saccade as quickly as possible aer a target
appears to cancel that partially prepared saccade if a stop
signal is presented; the stop signal was the reappearance
of the xation spot (Hanes & Schall, ). Performance
of this task can be understood as the outcome of a race
between a process with random nish times that generates the
movement (GO process) and another random process that
cancels the movement (STOP process) (Logan and Cowan
). Under reasonable assumptions, the duration of the
covert STOP process can be derived from the proportion of
successful stop trials and the RT on trials with no stop signal
(nish time of overt GO process). e duration of the STOP
process is referred to as stop signal reaction time;itmeasures
the time needed to cancel the planned movement.
e validity of SSRT as a measure of the time to interrupt
movement preparation and execution has been tested using
various approaches. For example, saccades can be elicited
prematurely by delivering an air pu to the eye that causes an
eyelid blink that inhibits omnipause neurons. When monkeys
performed the stop signal task, air pus presented more
than ∼ ms aer the stop signal rarely evoked saccades,
and the saccades triggered close to SSRT tended to be
hypometric []. Also, during a combined eye-head gaze
countermanding task, a burst of antagonist neck muscle
activity was observed on stop signal trials when subjects
initiated small head movements even though gaze remained
stable due to the vestibular ocular reex (Goonetilleke et al.
). is “braking” pulse only occurred when the head
movement was interrupted in midight and was concomitant
with SSRT.
e most direct evidence for a neural instantiation of
stoppinghasbeenobtainedinsingle-unitrecordingsfromthe
FEF and SC of macaque monkeys (Hanes et al. ; Par
´
e&
Hanes, ) []. e logic of the countermanding paradigm
establishes two criteria; a neuron must meet to play a direct
andsucientroleincontrollingtheinitiationofamovement.
First, the neuron must discharge dierently when a saccade
is initiated versus when a saccade is withheld because of a
stop signal. Second, this dierence must occur before the stop
signal reaction time, because that is when the act of control is
accomplished. Recent researches investigating human brain
function during manual stop signal tasks have focused on a
circuit involving the right inferior frontal gyrus, preSMA, and
the subthalamic nucleus (e.g., [,
]). However, numerous
other brain regions contribute to inhibiting partially planned
movements (e.g., []). Firm conclusions in this area of
the literature are premature, though, because the functional
measures do not have sucient time resolution. In contrast,
single-unit recordings can resolve the timing of modulation
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at a level necessary to attribute function with more certainty.
In FEF, neurons with visual responses but no saccade-
related modulation did not satisfy these criteria; they simply
responded to the presentation of the stimulus. However, neu-
rons with saccade-related and xation-related modulation
in FEF and SC did satisfy the criteria (Figure ). Aer the
target appeared, movement-related activity in both structures
began to grow toward the trigger threshold. If the stop
signal occurred but the activity happened to reach threshold,
a noncanceled error was produced. However, successfully
canceled trials occurred when the movement-related activity
wasinhibited,sothatitdidnotreachthethresholdactivation
level. e source of this inhibition appears to be a signal such
as that conveyed by xation neurons in FEF and SC. e
pronounced modulation of xation-related and movement-
relatedactivitywhensaccadeswerecanceledoccurredjust
before SSRT elapsed. e quality of modulation of the
movement and xation neurons is entirely consistent with
the fact that movement and xation neurons in FEF and SC
provide direct input to the brainstem structures that produce
eye movements (Segraves, ) [].
ese results obtained with stop signal task have been
replicated in a double-step saccade task with visual search
[] for which performance is the outcome of a race with two
GO processes and a STOP process (Camalier et al. ). A
subsequent analysis demonstrated a quantitative dierence
between movement and visuomovement neurons (Ray et al.
). Movement neurons exhibited a progressive accumula-
tion of discharge rate following target presentation that trig-
geredasaccadewhenitreachedathreshold;ifsaccadeswere
canceled, this accumulating activity was interrupted at levels
progressively closer to the threshold at progressively longer
stop signal delays. In contrast, visuomovement neurons
exhibited a maintained elevated discharge rate until a brief
enhancement announced saccade initiation; if saccades were
canceled, the enhancement did not occur. e functional
distinction between movement and visuomovement neurons
is consistent with recent evidence for biophysical dierences
as evidenced by spike width ([]; see also [, ]).
e pattern of results obtained in SC and FEF with
the countermanding task is consistent with our best under-
standing of the functional properties and connectivity of the
dierent neuron types. us, the countermanding paradigm
is diagnostic of neurons producing signals sucient to
control saccade initiation and thus be said to contribute
directly to saccade preparation. Now, neurons in other
cortical areas such as SEF and LIP have been described as
saccade related (e.g., Schlag & Schlag-Rey ; Schall ;
[]). is hypothesis has been tested in both areas with the
countermanding paradigm, and the results are unambiguous.
Vanishingly few neurons modulate before SSRT in SEF
(Stuphorn et al. ) or LIP []. is result indicates terms
like “preparation” or even “intention” may not apply usefully
to neural activity in SEF or LIP.
3.2.InteractiveRaceModelofCountermanding. e control
of saccade initiation is accomplished by interactions between
gaze-holding and gaze-shiing neurons. e current data
demonstrate this for movement and xation neurons in the
FEF and SC, but it is likely that corresponding neurons in
the basal ganglia, thalamus, cerebellum, and brainstem will
be modulated in a manner sucient to be said to control
saccade initiation. Does this mean that gaze-shiing and
gaze-holding neurons instantiate the GO and STOP processes
of the race model explaining countermanding performance?
e specication of this linking proposition is not trivial [].
One facet of this complexity concerns the central assumption
of the race model, namely, that the nish times of the GO and
STOP processes are independent (Logan & Cowan, ).
If the neural circuit that instantiates the GO and STOP
processes consists of interacting neurons, how can the circuit
produce behavior that appears to be the result of independent
processes? is paradox has been resolved through a simple
network model consisting of one GO unit and one STOP unit
(Boucher,etal.;seealso[]). Each unit was a noisy
accumulator with RT specied by the time when the GO
unit reached a threshold. e network t the performance
data and replicated the form of the activation of movement
and xation neurons if and only if the STOP unit inhibited
theGOunitinadelayedandpotentfashion(Figure ).
is interactive race has been instantiated in a network of
biophysically realistic spiking neurons [].
is fruitful coordination of a task producing a particular
pattern of performance, a formal mathematical model, and
neurophysiological observations establishes the plausibility
of identifying the abstract, formal GO, and STOP processes
with the activity of specic neurons. is result validates
the utility of SSRT as a measure of impulse control in
developmental and clinical studies. However, the mechanistic
basis of the potency of the STOP unit inhibition that aords
the appearance of an independent race between the GO and
STOP processes is not entirely clear. e current evidence
emphasizes the contribution of xation neurons in FEF and
SC, but other recent work has demonstrated that neurons in
rostral SC contribute to production of microsaccades [].
Hence, perhaps “stopping” a saccade to a peripheral target is
accomplished by producing more microsaccades around the
xation spot. is plausible hypothesis is contradicted by a
recent nding of less, not more extraocular muscle activation
when saccades are canceled []. Furthermore, it seems
beyond dispute that some active gaze-holding mechanism
exists. Another plausible source for a general gaze-holding
signal is the SNpr (e.g., []); however, this pathway seems
more complex than a simple inhibitory gate (e.g., []). Yet
another source of inhibition of the neurons instantiating the
GO process is local inhibition within FEF, SC, thalamus,
and basal ganglia, but how could such intrinsic inhibition be
coordinated?
3.3. Executive Control. Executive control will refer to the
processes that adapt RT according to the consequences of
actions. Recent research on the executive control of saccades
hasbeenreviewed[]. Aer mastering the countermanding
task, adjustments of performance continue ([]; Nelson et
al. ). For example, RT varies adaptively with incidental
or deliberate variation of the proportion of stop signal trials;
RT is delayed as more stop signal trials are encountered (see
also []).
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Conflict
Error
Reward
S
T
0 100 200
Time from array (ms)
0 100 200
Time from array (ms)
MN
BN
OPN
TN
Color
Shape
Salience evidence
Target template
working memory
S
D
S
T
GO
D
GO
T
STOP
OPN and BN
GO
D
GO
T
STOP
OPN and BN
SSRT
S
D
0 100 200
Time from array (ms)
Motion, depth,
etc.
GO
T
GO
D
STOP
“T ”
F : Neural networks for the guidance and control of visually guided saccades. Consider visual search for a red “𝑇” among randomly
oriented red and green “L”s. e color and shape of the objects are specied in feature maps that could also represent motion, depth, and
other visual features. ese feature maps converge on a map that represents the evidence for salience at each location. is salience map is
also informed by a target template in working memory. e timecourse of the salience evidence representation at the target location (𝑆
𝑇
,
solid line) and a distractor location (𝑆
𝐷
, dotted line) is plotted. According to the gated accumulator model, this evidence is integrated by a
network of mutually inhibitory units that will produce a saccade to the target (GO
𝑇
, solid line) or to a distractor (GO
𝐷
,dottedline).Agate
(orange box) prevents integration of noise by requiring the salience evidence to be of sucient magnitude. A saccade is produced when the
activation of a GO unit reaches a threshold (gray horizontal line) at which point inhibition is imposed on omnipause (OPN) neurons (red
line) that releases inhibition of burst neurons (BNs) that innervate motor neurons (MNs) to produce a pulse of force to rotate the eye rapidly.
e eye velocity signal from the BNs is integrated by a network of tonic neurons (TNs) that also innervate the MN to establish a step of force
necessary to maintain eccentric xation of the target. e activation of the GO units is also inuenced by gaze-holding STOP units that release
inhibition on the GO units while saccade preparation transpires. If a stop signal of some kind occurs, then the STOP units potently interrupt
the GO unit activation from reaching the threshold; this interruption occurs within the theoretical interval known as stop signal reaction
time (SSRT) (rightmost columns). An executive control network (yellow) comprised of neurons sensitive to errors, reward, and the conict
arising from coactivation of mutually incompatible response processes signals the consequences and conditions of an action. is executive
control network may inuence the level of the gate that systematically changes the beginning of the accumulation process to emphasize either
speed or accuracy in task performance.
An extensive body of research with humans has identied
areas in medial frontal cortex with executive control (e.g.,
[]). Consistent with this framework, in monkeys perform-
ing the saccade countermanding task, a variety of patterns of
neural activity are observed in SEF and dorsal ACC (Ito et al.,
; Stuphorn et al. ). In both SEF and ACC we found
distinct populations of neurons that were active aer errors or
in association with reinforcement, and in SEF but not in ACC,
we also found a population of neuron that was active aer
successful withholding of a partially prepared movement.
ese three forms of activation could not be explained
by sensory or motor factors. While interpreting signals in
ACC in terms of monitoring performance is not novel, this
interpretationaboutSEFwasanewperspective.However,
this framework has been supported by new evidence from
functional brain imaging studies (Curtis, et al. ; Nachev,
et al. ) and eects of lesions restricted to SEF (e.g., Parton
et al., ; Sumner et al. ).
e neurons in SEF and ACC discharging aer errors
may contribute to the intracranial source of an event-related
potential recorded over medial frontal cortex known as the
error-related negativity (ERN) (reviewed by []) that was
the rst physiological signature of a supervisory control
system. A bridge between the monkey single-unit result and
the human ERN has been constructed through a series of
studies showing rst that local eld potentials in ACC and
SEF exhibit polarization corresponding precisely to the ERN
[, ], second that macaque monkeys exhibit an ERN
recorded from the cranial surface that is consistent with
current sources in medial frontal cortex [, ], and third
that humans performing the saccade countermanding task
exhibit the same form of ERN with a comparable distribution
of current sources in medial frontal areas (Reinhart et al.
).
e neurons in SEF and ACC that responded to reinforce-
ment events were more diverse (see also Amiez et al., ;
Shidara & Richmond ). Some responded to a secondary
tone reinforcer as well as to the primary juice reinforcer.
Others responded only to the primary juice reward both
when it was earned and when it was delivered unexpectedly.
Still other ACC neurons responded only to noncontingent,
unexpected juice reward; some of these also showed an
apparent visual response. is pattern of activity resembles
the signals produced by brainstem dopamine neurons (e.g.,
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Schultz, ). Furthermore, some of the error-related neu-
rons as well as the LFP signaled when earned reward was
withheld. e existence of these signals in medial frontal
cortex is consistent with models of executive function based
on dopaminergic learning signals transmitted to ACC (e.g.,
[]).
A third population of neurons in SEF was distinguished
from the error and reinforcement neurons (see also []).
ese neurons exhibited elevated discharge rate specically
during stop signal trials in which the saccade was cor-
rectly canceled, but the modulation occurred aer SSRT,
so it cannot be responsible for inhibiting the movement.
A comparable signal was also observed in LFP recorded
in SEF []. An interpretation of the signal produced by
these neurons is inspired by the hypothesis that the medial
frontal cortex monitors response conict that arises when
mutually incompatible processes are activated simultane-
ously but cannot both run to completion (e.g., [, ]). is
hypothesishasbeenoeredasanexclusivealternativetothe
hypothesis that the medial frontal lobe only detects errors.
e existence of distinct populations of neurons signaling
error, reinforcement, and putative response conict indicates
that each hypothesis has merit. Of interest, no neurons or LFP
havebeenfoundinACCthatcouldsignalconict(Itoetal.,
) [, ]. Based on these results, some have proposed
thatmacaquemonkeysdonothavetheneuralsubstrates
necessary to generate performance monitoring ERPs similar
tothoseobservedinhumans([, ]; but see []). However,
the presence of all the relevant signals in both single units and
LFP as well as a homologue of the ERN calls into question the
merits of proposal.
As soon as performance monitoring signals were dis-
covered, their relationship to performance adjustments was
explored []. is has been tested through intracortical
microstimulation of SEF of monkeys performing the saccade
countermanding task (Stuphorn & Schall, ). Electrical
stimulation was delivered simultaneously with the presen-
tationofthestopsignal,atacurrentlevelwellbelow
the threshold for eliciting a saccade. e inuence of this
stimulation on performance was measured by comparing the
fraction of non-canceled trials with and without stimulation.
e evidence was quite clear that microstimulation of nearly
all sites in SEF improved performance by reducing the
fraction of non-canceled saccades resulting in a delayed
inhibition function. is was a general eect, occurring for
both contraversive and ipsiversive saccades. To determine
how the electrical stimulation enhanced monkeys’ ability to
inhibit saccades, stimulation was delivered on some trials
with no stop signal. Stimulation in this context caused an
increase in saccade latency; this delaying of the GO process
allowedmoretimefortheSTOPprocesstonishrstthereby
improving performance.
ArecentanalysisoftheoriginaldatafromFEFand
SC showed how this slowing is accomplished []. Stochas-
tic accumulator models account for adaptation of RT to
minimize errors and maximize rewards most commonly
through changes in the threshold of accumulation that
triggers a response (Nakahara et al., ; Simen et al., ;
Forstmann et al., ) []. However, the systematic delay
in response time aer stop-signal trials was accomplished not
through a change of threshold, baseline, or accumulation rate,
but instead through a change in the time when presaccadic
movement activity rst began to accumulate. is result
highlights the subtlety entailed in mapping computational
models onto neural processes.
4. Guidance of Saccades by
Vision and Knowledge
Research on the neural mechanisms of saccade target selec-
tion in the context of visual search paradigms used in human
studies (e.g., Wolfe and Horowitz ; []) began
years ago (Schall & Hanes ) and is now a focus for
many research groups. is topic has been reviewed before
([]; Schiller and Tehovnik ; []; Fecteau and Munoz
; [–]),sowewillonlyframethemajorissuesand
highlight more recent ndings.
Research on visual search and saccade target selection
can be organized through the concept that search is guided
through a salience map (also known as priority map), a
spatially organized representation in which bottom-up and
top-down inuences converge (e.g., [, ]) (Figure ).
Salience refers to how distinct one element of the image
is from surrounding elements. is distinctness can occur
because the element has visual features that are very dierent
from the surrounding (a ripe, red berry in green leaves).
e distinctness can also occur because the element is more
important than others (the face of a friend among strangers).
e distinctness derived from visual features and importance
confersuponthatpartoftheimagegreaterlikelihoodof
receiving enhanced visual processing and a gaze shi. In the
models of visual search referred to above, one major input
tothesaliencemapisthemapsofthefeatures(color,shape,
motion,depth)ofelementsoftheimage.Anothermajorinput
is top-down modulation based on goals and expectations.
e representation of likely targets that is implicit in and
dependent on the feature maps becomes explicit in the
salience map. Peaks of activation in the salience map that
develop as a result of competitive interactions represent
locations that have been selected for further processing and
thus covert orienting of attention.
Saccade target selection coincides with the allocation
of visual attention that has been the focus of consider-
able research (e.g., [, ]). Attentional allocation and
saccade production interact variously. Some investigators
have explained the connection between saccade production
and attention allocation by proposing that the allocation of
attention amounts to a subthreshold command to shi gaze.
isviewisknownastheoculomotorreadinesshypothesis
(Klein and Pontefract ) or the premotor theory of
attention(Rizzolatti).Althoughthisisaninuential
hypothesis, many observations are inconsistent with a strict
interpretation of it (e.g., []), and we will highlight more
below. Alternatively, numerous lines of evidence demonstrate
that the neural process of selecting a target for orienting is
functionally distinct from the neural process of preparing a
saccade.
ISRN Neurology
4.1. Neural Processing for Target Selection. Anetworkof
structures in the visual pathway contributes to selecting
targets for saccades. Neurons in primary visual cortex and
extrastriate areas in parietal and temporal lobes represent
a variety of more or less elaborated features, surfaces, and
objects. But visual processing is not concluded in the parietal
and temporal lobes, for extensive convergence of signals from
numerous areas occurs in FEF (e.g., [, ]) and SC [].
AlthoughFEFhasbeenidentiedwithanadvancedlevel
in the hierarchy of visual areas [], the latency of visual
responses in FEF is comparable to that in, for example, area
MT and even proceed the latencies of some neurons in V
[]. Moreover, the density of neurons in the supragranular
layers that project to area V identies a feedforward con-
nection [] with terminals on dendritic spines, mainly in
supragranular layers of V []. e inuence conveyed by
this connection from FEF to visual cortex is a central feature
of some network models of visual attention (e.g., []).
Extensive research has demonstrated how neurons in
cortical areas that represent stimulus features are modulated
by target and surrounding nontarget features under various
task demands (e.g., [–]). Another major input is top-
down modulation based on goals and expectations enabled
by neural circuits in the frontal lobe (e.g., [–]).
We will suppose that the functional salience map corre-
sponds to a population of neurons that are not intrinsically
feature-selective but receive input from feature-selective neu-
rons, so that they signal the location of objects that are the
targetoraretargetlikeinamannerthatcanbeusedtoguide
an action like an eye movement. According to this deni-
tion, compelling evidence obtained in multiple laboratories
supports the conclusion that the neural representation of the
salience map is distributed among multiple cortical areas and
subcortical structures including FEF, parietal areas LIP and a
as well as the superior colliculus, basal ganglia, and associated
thalamic nuclei. e heterogeneity of neural function within
and diversity of connectivity between these areas makes clear
that this salience representation is instantiated by an inter-
connectedcircuitbuiltfromsomebutnotalloftheneuronsin
these structures. Evidence that the selection process observed
in these sensorimotor structures can be identied with a
salience representation includes the following observations.
When a search array appears (either by ashing on during
xation or aer a previous scanning saccade), activation
increases at all locations in the map corresponding to the
potential saccade targets. is happens because these neurons
are not naturally selective for visual features (but see []).
Following the initial volley, activation becomes relatively
lower at locations that would produce saccades to nontarget
objects and is sustained or grows at locations correspond-
ing to more conspicuous or important potential targets
(Figure ). is process has been observed in FEF (e.g., Schall
and Hanes, ; [, –]), posterior parietal cortex
(e.g., [–]), superior colliculus (SC) [–], substantia
nigra pars reticulata [], and ocular motor thalamic nuclei
[]. In these studies, monkeys are responding to one among
multiple alternatives for the purpose of earning reinforce-
ment,usuallywithasinglesaccade.etargetselection
process has also been observed during natural scanning eye
movements (e.g., [, , ]; Zhou & Desimone ).
Microstimulation and inactivation have demonstrated causal
roles in target selection of FEF (e.g., [–]); superior
colliculus (e.g., [, ]), and LIP (Wardak et al. ; [–
]).
Manipulations that inuence attention allocation in
humans inuence parallel monkey performance and con-
comitant modulation of neural activity. For example, when
search is less as compared to more ecient because target
and distractor stimuli are more dicult to discriminate, then
the selection process occupies more time and accounts for a
greaterproportionofthevariabilityofRT(e.g.,[, ,
,
–]). e well-known eects of target-distractor simi-
larity on search performance that are expressed in response
times and choices by macaque monkeys are paralleled in
the magnitude and timing of the visual selection process
measured in FEF neurons (e.g., []). When the target is
more similar to distractors through either feature similarity
or recent stimulus history, the level of neural activity in FEF
representing the alternative stimuli is less distinct, leading
to a higher likelihood of treating a distractor as if it were
the target [, ]. is parallel suggests that the statement
“less ecient allocation of attention” describes a the state
of the network in which the activity representing a target
and distractors is less capable of being distinguished by
either a neurophysiologist or a read-out circuit. Another
inuence believed to be mediated through the salience map
is inhibition of return, the decreased likelihood of directing
gaze to a location previously xated. Neural correlates of this
have been described in FEF [], LIP []andSC(Fecteau
&Munoz).
e representation of salience is regarded to guide covert
as well as overt orienting independent of eector. e neural
selection of the target as a visual location to which to orient
attention does not inevitably and immediately lead to re-
orienting of the eyes. It occurs if no overt response at all
is made [, ] or if the saccade is directed away from a
color singleton [, ]. e selection process occurs as well
if target location or property is signaled by through a manual
response [, –].
Having identied key nodes in the network representing
visual salience, further investigation of the mechanism has
been accomplished. All of the results described above were
based entirely on modulation of discharge rates of individual
neurons. It is clear, though, that saccade target selection is
accomplished by pools of neurons [, , ]andprobably
entails more than just modulation of spike rate because
cooperation and competition between pairs of neurons is
modulated during target selection []. Indeed, correlation
in discharge rates of FEF neurons over longer time scales has
been reported even before stimulus presentation []. Other
researchershavemeasuredlocaleldpotentials(LFP)inV,
LIP, and FEF during visual search and attention tasks and
described increased coherence in the gamma band between
spikes and LFP within and across areas such as V, LIP,
and FEF [, , ]. Although believed to enhance the
representation of attended objects, the functional utility of
such signals is not undisputed (e.g., []).
ISRN Neurology
An alternative analysis of LFPs is simply to measure the
timecourse of dierences in polarization when the target is
in or out of the RF. is approach corresponds to the mea-
surement of an ERP on the scalp known as the Npc, that is,
a signature of the locus and time of attention allocation (e.g.,
[]). e Npc has been found in macaque monkeys [].
Source localization procedures indicate that the Npc arises
from parietal and occipitotemporal sources in humans (e.g.,
[]) and macaques []. In both ecient and inecient
search conditions, the target is selected signicantly earlier
inneuralspikeratemodulationthaninLFPpolarization[,
],andthedelayvarieswithsearcheciency.Itappearsthat
local processing within FEF mediated by spike rates results in
delayed changes of synaptic potentials manifest in the LFP.
4.2. Interactions between the Frontal Lobe and Visual Cortex
during Target Selection. We have described a target selection
process that occurs more or less concurrently in multiple
cortical areas and subcortical structures. Recent studies in
macaque monkeys have investigated directly interactions
between FEF and LIP [], V (Gregoriou et al. ; Zhou
& Desimone ), and inferior temporal (IT) cortex [,
] as well as an ERP component recorded over visual
cortex that indexes attention []. While rm conclusions
are premature because results were obtained with dierent
tasks, neural signals, measurement procedures, and areas,
some results seem consistent across laboratories. First, when
search is inecient, neural signals of attention allocation in
FEF precede those in extrastriate visual areas. For example, a
recent study demonstrated that spatial selection of a location
in FEF precedes object recognition by IT neurons at that
location [] and the selection in FEF is necessary for
detection and identication of the target []. Similarly,
the target selection observed in spike rate and LFP in FEF
precedes the Npc [], and the delay between selection in
FEF and visual cortex increased with the number of distractor
stimuli demonstrating that the delay is not due simply to
conduction lags. ese results expose a puzzling question—
if dierent times of target selection are measured in dierent
nodes of the network and scales of signal; then, when would
we say that attention has been allocated? Given the variation
in selection time across neurons even within an area, can we
say that the target is selected when the earliest, the latest,
or some intermediate population of neurons resolve target
location? Such a basic question highlights our profound
uncertainty about how signals arise in and are conveyed
between the areas representing features, objects, and salience.
is inuence of FEF on visual cortex can inuence
the quality of attentive visual processing [, ]. Weak
electrical stimulation of FEF inuences extrastriate visual
cortex activity in a manner similar to what is observed when
attention is allocated [–].
4.3. From Salience to Saccade. Explaining how sensory rep-
resentations lead to accurate movements is a classic problem.
Oneapproachtothisproblemisbasedonthepremisethat
noisy evidence guiding a response is accumulated over time
until a threshold is achieved at which time the response
is initiated (e.g., [, ]). A recent model inspired by
this approach provides an explanation for how signals from
neurons that represent target salience can be transformed
into a saccade command [, ](Figure ). e model uses
the activity of visually responsive neurons in the frontal eye
eld representing object salience as evidence for stimulus
salience that is accumulated in a network of deterministic
accumulators producing saccades to each possible target
location to generate accurate and timely saccades during
visual search. Response times are specied by the time at
which the integrated signal reaches a threshold. e model
included leak in the integration process and lateral inhibition
between the ensemble of accumulators as well as a form of
inhibition that gates the ow of perceptual evidence to the
accumulators. Alternative model architectures were excluded
because they did not t the actual distributions of response
times nor produce activation proles corresponding to the
form of actual movement neuron activity. At present, this
is the only model of visual search that accounts for the
range and from of response time distributions []. is
union of cognitive modeling and neurophysiology indicates
how the visual motor transformation can occur and provides
a concrete mapping between neuron function and specic
cognitive processes.
e picture that emerges is that the process of visual
selection occupies a certain amount of time that can be
shorter and less variable if the target is conspicuous, or it can
be longer and more variable if the target is less conspicuous.
If subjects wish to prevent a saccade to a nontarget stimulus,
then the preparation of the saccade can be delayed until
the visual selection process has proceeded to a high degree
of resolution. Neural activity mediating saccade preparation
begins to grow as the selection process is completed and the
rate of growth of activity leading to the movement varies
apparently randomly such that sometimes gaze shis sooner
and sometimes gaze shis later.
4.4. Stimulus-Response Mapping. e gated feedforward cas-
cade model assumes that saccade production is guided
entirely by the visual salience representation. us, errant
saccades would be explained by failure to represent evidence
correctly. While this has been observed in some testing
conditions [, ], several other lines of research demon-
strate that the salience representation can be correct even if
responses are incorrect. For example, in monkeys performing
a saccade double step task with visual search, visual neurons
in the FEF locate the new location of the oddball in the search
array correctly even when monkeys incorrectly shi gaze to
the old location []. Similarly, when manual response errors
occur, the selection process in FEF locates the singleton in the
search array correctly [].Butifthebrainlocatedthenew
location of the oddball correctly, why was an error made? A
plausible answer appeals to the hypothesis that the response
production stage, even though guided by the perceptual stage,
can operate independently of the perceptual stage. Further
evidence for this is the fact that these errors can be corrected
very rapidly, even before the brain can register that the gaze
shi was an error ([
]; see also []).
Saccade target selection has also been investigated under
conditions that explicitly dissociate visual target location
ISRN Neurology
from saccade endpoint. For example, one study trained
monkeys to make a prosaccade to a color singleton or an
antisaccade to the distractor located opposite the singleton;
the shape of the singleton cued the direction of the saccade
[]. As observed in previous studies, the response time
for antisaccades was greater than that for prosaccades. A
goal of this experiment was to account for this dierence in
terms of the neural processes that locate the singleton, encode
itsshape,mapthestimulusontotheresponse,selectthe
endpoint of the saccade, and nally initiate the saccade. Two
types of visually responsive neurons could be distinguished
in FEF. e rst, called Type I, exhibited the typical pattern
of initially indiscriminant activity followed by selection of the
singleton in the response eld through elevated discharge rate
regardless of whether the singleton’s features cue a prosaccade
or an antisaccade. Some of these Type I neurons maintained
the representation of singleton location in antisaccade trials
untilthesaccadewasproduced.However,themajorityof
the Type I neurons exhibited a remarkable and dramatic
modulation of discharge rate before the antisaccade was
initiated (Figure (a)). Aer showing higher discharge rates
for the singleton as compared to a distractor in the receptive
eld, the ring rates changed such that higher discharge
rates were observed for the endpoint of the antisaccade
relative to the singleton location. is modulation could
be described as the focus of attention shiing from one
location to the other before the saccade. e second type of
neuron, called Type II, resembled qualitatively the form of
modulation of Type I neurons in prosaccade trials, but in
antisaccade trials, these neurons did not select the location
of the singleton and instead only selected the endpoint of the
saccade (Figure (b)). is endpoint selection was distinct
from movement neuron activation. e selection times of
Type II, but not Type I, neurons accounted from some of
thevariabilityofsaccaderesponsetimeonprosaccadeand
antisaccade trials.
is experiment revealed a sequence of processes that
can be distinguished in the modulation of dierent popula-
tions of neurons in FEF. e timecourse of these processes
can be measured and compared across stimulus-response
mapping rules (Figure (c)).Tosummarize,TypeIneurons
selected the singleton earlier than did Type II neurons. In
the population of Type I neurons, the time of selection of
the singleton in prosaccade and antisaccade trials did not
vary with stimulus response mapping or account for the
dierence in RT. However, the singleton selection time of
TypeIIneuronsinprosaccadetrialswaslesssynchronized
with array presentation and more related to the time of
saccade initiation. In antisaccade trials, the time of endpoint
selection by Type I neurons was signicantly later than that
of Type II neurons. is result is as if the endpoint of a
saccade must be identied before, attention can shi to the
location. e endpoint selection time of Type I neurons in
antisaccadetrialswastoolatetoexplaintheincreasein
RT relative to prosaccade trials. In contrast, the endpoint
selection time of Type II neurons in antisaccade trials, like
the singleton selection time in prosaccade trials, accounted
for some but not all of the delay and variability of RT. e
results of this experiment demonstrate that the process of
saccadetargetselectionrequiresanumberofrepresentations
and transformations beyond simply representing stimulus
salience and producing a saccade.
4.5. Testing the Premotor eory of Attention. If shiing
visual spatial attention corresponds to preparing a saccade,
then it should be impossible to dissociate saccade prepa-
ration from the focus of attention even if the endpoint of
a saccade is directed opposite the attended stimulus. is
was tested by probing the evolution of saccade preparation
using electrical stimulation of the FEF []. e focus of
attention was dissociated momentarily from the endpoint
of a saccade by training monkeys to perform visual search
for an attention-capturing color singleton and then shi
gaze either toward (prosaccade) or opposite (antisaccade)
this color singleton according to its orientation []. Sac-
cade preparation was probed by measuring the direction
of saccades evoked by intracortical microstimulation of the
frontal eye eld at dierent times following the search
array. Eye movements evoked on prosaccade trials deviated
progressivelytowardthesingletonthatwastheendpoint
of the saccade, as expected []. Eye movements evoked
on antisaccade trials deviated not toward the singleton but
only toward the saccade endpoint opposite the singleton. e
interpretation of these results is framed by earlier research
showing that on antisaccade trials, most visually responsive
neurons in frontal eye eld initially select the singleton
whileattentionisallocatedtodistinguishitsshape[]. In
contrast, preliminary data indicates that movement neurons
are activated but do not produce a directional signal aer
the saccade endpoint is selected. Evidence consistent with
these observations has been obtained in human participants
using transcranial magnetic stimulation []andinastudy
probing explicitly the locus of attention []. us, the brain
can covertly orient attention without preparing a saccade
to the locus of attention. In other words, target selection
and saccade preparation are distinct processes because they
can be modied separately (Sternberg ). is separate
modiability occurs because dierent populations of neurons
carry out dierent functions as reviewed above.
Testing the premotor theory requires specifying the
anatomical level at which the mechanism maps onto the
brain. If shiing attention is accomplished by the same neu-
rons that are preparing a saccade and if saccade commands
are issued by layer pyramidal neurons in FEF and if FEF
inuences attention by projections to areas V and TEO, then
numerous layer neurons must be double-labeled by tracer
injections in SC and V/TEO. A recent study found, though,
that whereas only pyramidal neurons in layer projected to
the superior colliculus, the large majority of neurons in FEF
projecting to extrastriate visual cortex are located in the layers
and , and no neurons projecting to both SC and visual
cortex were found []. us, we can reject the premise
that shiing attention is accomplished by the population of
neurons that prepare saccades. is conclusion is based on
a strict mapping between populations of specic types of
neurons and the cognitive processes of attention allocation
and saccade preparation. However, a theory formulated too
generally to map onto specic neural types loses the relevance
ISRN Neurology
Time from search array (ms)
0 200
(a)
0
200
0 200
Time from search array (ms)
(b)
0
100
50
0
100
50
Prosaccade trials
Antisaccade trials
200100 300
Time from array (ms)
0
200100 300
Time from array (ms)
0
(%)
(%)
(c)
F : Pattern and timing of neural activity in FEF when mapping between location of visual target and endpoint of saccade is various.
(a) Activity of FEF neuron with activity that can be identied with the allocation of attention (Type I). Average spike density function when
the singleton fell in the neuron’s receptive eld (thick line) and when the singleton was located opposite the receptive eld (thin line) in
prosaccade (top) and antisaccade (bottom) trials. ick bar on abscissa marks range of RT. Scale bar represents spikes/sec. (b) Activity of
FEF neuron with activity that can be identied with selection of the saccade endpoint (Type II). (c) Cumulative distributions of modulation
times in prosaccade (le) and antisaccade (right) trials for Type I (thin) and Type II (thicker) neurons with corresponding RT (thickest).
e inset arrays indicate hypothesized functional correlates. Aer presentation of the array, selection of the singleton location occurs rst
in Type I neurons (indicated by the spotlight on the singleton); this occurs at the same time in prosaccade and antisaccade trials and does
not relate to whether or when gaze shis. In prosaccade but not antisaccade trials, Type II neurons select the singleton at a later time which
accounts for some of the variability of RT. A comparison of activation in prosaccade and antisaccade trials reveals the time at which the shape
of the singleton is encoded to specify the correct saccade direction; this follows singleton selection and coincides for Type I (thin blue) and
Type II (thicker blue) neurons in antisaccade trials. At this moment in antisaccade trials, the representation of the singleton decreases, and
the representation of the location opposite the singleton, the endpoint of the antisaccade increases (indicated by the weaker spotlight on the
singleton and growing spotlight on the saccade endpoint). At this same time in prosaccade trials, the representation of the saccade endpoint
is enhanced by the selection that occurs in the Type II neurons (indicated by the highlighted spotlight on the singleton). Subsequently, in
antisaccade trials, the endpoint of the saccade becomes selected more than the location of the singleton by Type I (thin, red, dashed) and Type
II (thicker red, dashed) neurons (indicated by the highlighted spotlight on the antisaccade endpoint). e time taken to select the endpoint
of the saccade predicts some of the delay and variability of RT. Modied from Sato and Schall [].
ISRN Neurology
of mechanism and force of falsiability. is result entails
that FEF delivers dierent signals to the visual and ocular
motor systems. What, then, is the nature of the inuence
ofFEFonvisualprocessing?Ifitisnotaneerentcopyof
the saccade command, what else could it be? Anatomical
reconstruction of recording sites shows that neurons located
in the supragranular layers of FEF are active during the
process of attentional target selection []. erefore, the
kind of signal that extrastriate cortex receives from FEF
corresponds to the target selection process described above.
Ofcourse,thisisjustwhatisneededtoguidetheallocation
of attention.
5. Outlook
is review should demonstrate why researchers in this area
feel that steady progress is being made. Looking forward,
key questions remain unanswered, though, such as what is
the detailed relationship between motor neuron properties,
extraocular muscle ber types, and the forces acting on
the eyes? How is the dynamic motor error comparison
accomplished? How does preparation of a saccade turn o
the OPNs? How can the accumulating activation of multiple,
redundant movement neurons be coordinated to produce a
saccade at one RT? How are targets for saccades selected?
How do multiple, redundant neurons across structures arrive
at a single salience representation? Or do multiple salience
representations exist in dierent brain structures, and if so,
how are they coordinated? What changes in the representa-
tion of salience and preparation of saccades to trade between
speed and accuracy? How can the tremendous heterogeneity
of neurons be reconciled with the rather limited number of
stages and computational processes currently employed to
account for performance?
e author is condent that answers can be achieved with
eort coordinated across laboratories through complemen-
tary tasks and common measurement methods designed to
systematically eliminate alternative hypotheses [] and not
contribute to publication bias []. e author also believes
that answering these and related questions about saccades
should not diminish our sense of marvel at the nimble and
exible movements of these shiny globes of gristle.
Acknowledgments
e auther is grateful and indebted to the many collaborators
and colleagues whose research and insights created the
content of this review. Research in the author’s laboratory has
been supported by the National Eye Institute, the National
Institute of Mental Health, the National Science Founda-
tion, the McKnight Endowment Fund for Neuroscience, the
Air Force Oce of Scientic Research, and by Robin and
Richard Patton through the E. Bronson Ingram Chair in
Neuroscience.
References
[]L.Fu,R.J.Tusa,M.J.Mustari,andV.E.Das,“Horizontal
saccade disconjugacy in strabismic monkeys,” Investigative
Ophthalmology and Visual Science, vol. , no. , pp. –,
.
[] A.C.JoshiandV.E.Das,“Responsesofmedialrectusmotoneu-
rons in monkeys with strabismus,” Investigative Ophthalmology
&VisualScience,vol.,no.,pp.–,.
[] L. Kiorpes, “Visual processing in amblyopia: animal studies,”
Strabismus,vol.,no.,pp.–,.
[] J. R. Economides, D. L. Adams, C. M. Jocson, and J. C. Horton,
“Ocular motor behavior in macaques with surgical exotropia,”
Journal of Neurophysiology, vol. , no. , pp. –, .
[] G. Lennerstrand, “Strabismus and eye muscle function,” Acta
Ophthalmologica Scandinavica,vol.,no.,pp.–,.
[]W.P.MadiganandW.M.Zein,“Recentdevelopmentsinthe
eld of superior oblique palsies,” Current Opinion in Ophthal-
mology,vol.,no.,pp.–,.
[] V.E.Das,R.J.Leigh,M.Swann,andM.J.urtell,“Muscimol
inactivation caudal to the interstitial nucleus of Cajal induces
hemi-seesaw nystagmus,” ExperimentalBrain Research,vol.,
no.,pp.–,.
[]N.Shichinohe,G.Barnes,T.Akaoetal.,“Oscillatoryeye
movements resembling pendular nystagmus in normal juvenile
macaques,” Investigative Ophthalmology & Visual Science,vol.
, no. , pp. –, .
[] B. A. Brooks, A. F. Fuchs, and D. Finocchio, “Saccadic eye
movement decits in the MPTP monkey model of Parkinson’s
disease,” Brain Research, vol. , no. -, pp. –, .
[] H. Slovin, M. Abeles, E. Vaadia, I. Haalman, Y. Prut, and H.
Bergman, “Frontal cognitive impairments and saccadic decits
in low-dose MPTP-treated monkeys,” Journal of Neurophysiol-
ogy,vol.,no.,pp.–,.
[] D. L. Levy, A. B. Sereno, D. C. Gooding, and G. A. O’Driscoll,
“Eye tracking dysfunction in schizophrenia: characterization
and pathophysiology,” Current Topics in Behavioral Neuro-
sciences,vol.,pp.–,.
[] R. J. Leigh and D. S. Zee, e Neurology of Eye Movements,
Oxford University Press, New York, NY, USA, th edition, .
[] S. Liversedge, I. Gilchrist, and S. Everling, Oxford Handbook of
Eye Movements, Oxford University Press, .
[] D. P. Munoz and B. C. Coe, “Saccade, search and orient—the
neural control of saccadic eye movements,” European Journal of
Neuroscience, vol. , no. , pp. –, .
[] J. M. Henderson, “Eye movements and scene perception,” in
Oxford Handbook of Eye Movements, S. Liversedge, I. Gilchrist,
and S. Everling, Eds., pp. –, Oxford University Press,
.
[] K. Rayner and S. P. Liversedge, “Linguistic and cognitive inu-
ences on eye movements during reading,” in Oxford Handbook
of Eye Movements, S. Liversedge, I. Gilchrist, and S. Everling,
Eds., pp. –, Oxford University Press, .
[] M. Land and B. Tatler, Looking and Acting: Vision and Eye
Movements in Natural Behaviour, Oxford University Press,
.
[] H.-K. Ko, M. Poletti, and M. Rucci, “Microsaccades precisely
relocate gaze in a high visual acuity task,” Nature Neuroscience,
vol. , no. , pp. –, .
[] M. M. Hayhoe and D. H. Ballard, “Mechanisms of gaze control
in natural vision,” in Oxford Handbook on Eye Movements,S.
P.Liversedge,I.P.Gilchrist,andS.Everling,Eds.,pp.–,
Oxford University Press, .
[] H. Collewijn and E. Kowler, “e signicance of microsaccades
for vision and oculomotor control,” Journal of Vision,vol.,no.
, article , .
ISRN Neurology
[] Z. M. Hafed and J. J. Clark, “Microsaccades as an overt measure
of covert attention shis,” Vision Research,vol.,no.,pp.
–, .
[] T. S. Horowitz, E. M. Fine, D. E. Fencsik, S. Yurgenson, and J.
M. Wolfe, “Fixational eye movements are not an index of covert
attention,” Psychological Science,vol.,no.,pp.–,.
[]J.Laubrock,R.Kliegl,M.Rolfs,andR.Engbert,“Whendo
microsaccades follow spatial attention?” Attention, Perception,
and Psychophysics,vol.,no.,pp.–,.
[] D. W. Royal, G. S
´
ary, J. D. Schall, and V. A. Casagrande,
“Correlates of motor planning and postsaccadic xation in
the macaque monkey lateral geniculate nucleus,” Experimental
Brain Research,vol.,no.-,pp.–,.
[] Z. M. Hafed and R. J. Krauzlis, “Microsaccadic suppression
of visual bursts in the primate superior colliculus,” Journal of
Neuroscience, vol. , no. , pp. –, .
[] D. C. Burr and M. C. Morrone, “Spatiotopic coding and
remapping in humans,” Philosophical Transactions of the Royal
Society B,vol.,no.,pp.–,.
[]N.J.HallandC.L.Colby,“Remappingforvisualstability,”
Philosophical Transactions of the Royal Society B,vol.,pp.
–, .
[] M. Ibbotson and B. Krekelberg, “Visual perception and saccadic
eye movements,” Current Opinion in Neurobiology,vol.,no.,
pp. –, .
[] B. Bridgeman, “Visual stability,” in Oxford Handbook on Eye
Movements, S. P. Liversedge, I. P. Gilchrist, and S. Everling, Eds.,
pp. –, Oxford University Press, .
[] W. M. Joiner, J. Cavanaugh, and R. H. Wurtz, “Modulation
of shiing receptive eld activity in frontal eye eld by visual
salience,” Journal of Neurophysiology,vol.,no.,pp.–
, .
[] D. E. Angelaki, “e oculomotor plant and its role in three-
dimensional eye orientation,” in Oxford Handbook on Eye
Movements, S. P. Liversedge, I. P. Gilchrist, and S. Everling, Eds.,
pp.–,OxfordUniversityPress,.
[] K. E. Cullen and M. R. Van Horn, “e neural control of
fast vs. slow vergence eye movements,” European Journal of
Neuroscience,vol.,no.,pp.–,.
[] G. Ugolini, F. Klam, M. D. Dans et al., “Horizontal eye move-
ment networks in primates as revealed by retrograde transneu-
ronal transfer of rabies virus: dierences in monosynaptic
input to “slow” and “fast” abducens motoneurons,” Journal of
Comparative Neurology,vol.,no.,pp.–,.
[] J. M. Miller, R. C. Davison, and P. D. Gamlin, “Motor nucleus
activity fails to predict extraocular muscle forces in ocular
convergence,” Journal of Neurophysiology,vol.,no.,pp.
–, .
[] E.Aksay,I.Olasagasti,B.D.Mensh,R.Baker,M.S.Goldman,
and D. W. Tank, “Functional dissection of circuitry in a neural
integrator,” Nature Neuroscience, vol. , no. , pp. –,
.
[] A. Miri, K. Daie, A. B. Arrenberg, H. Baier, E. Aksay, and D.
W. Tank, “Spatial gradients and multidimensional dynamics in
a neural integrator circuit,” Nature Neuroscience,vol.,no.,
pp. –, .
[] Y. Shinoda, Y. Sugiuchi, M. Takahashi, and Y. Izawa, “Neural
substrate for suppression of omnipause neurons at the onset of
saccades,” Annals of the New York Academy of Sciences,vol.,
no. , pp. –, .
[] K. Yoshida, Y. Iwamoto, S. Chimoto, and H. Shimazu, “Saccade-
related inhibitory input to pontine omnipause neurons: an
intracellular study in alert cats,” Journal of Neurophysiology,vol.
,no.,pp.–,.
[] M.R.VanHorn,D.E.Mitchell,C.Massot,andK.E.Cullen,
“Local neural processing and the generation of dynamic motor
commands within the saccadic premotor network,” Journal of
Neuroscience, vol. , no. , pp. –, .
[] T. Kanda, Y. Iwamoto, K. Yoshida, and H. Shimazu, “Glycinergic
inputs cause the pause of pontine omnipause neurons during
saccades,” Neuroscience Letters, vol. , no. , pp. –, .
[] D. A. Robinson, “Oculomotor control signals,” in Basic Mecha-
nisms of Ocular Motility and eir Clinical Implications,pp.–
, Pergamon Press, Oxford, UK, .
[]J.C.Rucker,S.H.Ying,W.Mooreetal.,“Dobrainstem
omnipause neurons terminate saccades?” Annals of the New
York Academy of Sciences,vol.,no.,pp.–,.
[] L. M. Optican, “Field theory of saccade generation: temporal-
to-spatial transform in the superior colliculus,” Vision Research,
vol. , no. -, pp. –, .
[] R.Soetedjo,C.R.S.Kaneko,andA.F.Fuchs,“Evidenceagainst
a moving hill in the superior colliculus during saccadic eye
movements in the monkey,” Journal of Neurophysiology,vol.,
no. , pp. –, .
[] P. eir, “e oculomotor cerebellum,” in Oxford Handbook of
Eye Movements, S. Liversedge, I. Gilchrist, and S. Everling, Eds.,
pp.–,OxfordUniversityPress,.
[] N. P. Bichot and J. D. Schall, “Priming in macaque frontal cortex
during popout visual search: feature-based facilitation and
location-based inhibition of return,” Journal of Neuroscience,
vol.,no.,pp.–,.
[]E.E.Emeric,J.W.Brown,L.Boucheretal.,“Inuenceof
history on saccade countermanding performance in humans
and macaque monkeys,” Vision Research,vol.,no.,pp.–
, .
[]B.GirardandA.Berthoz,“Frombrainstemtocortex:com-
putational models of saccade generation circuitry,” Progress in
Neurobiology,vol.,no.,pp.–,.
[] R. J
¨
urgens, W. Becker, and H. H. Kornhuber, “Natural and drug-
induced variations of velocity and duration of human saccadic
eye movements: evidence for a control of the neural pulse
generator by local feedback,” Biological Cybernetics,vol.,no.
,pp.–,.
[] C. A. Scudder, “A new local feedback model of the saccadic burst
generator,” JournalofNeurophysiology,vol.,no.,pp.–
, .
[] G. Gancarz and S. Grossberg, “A neural model of the saccade
generator in the reticular formation,” Neural Networks, vol. ,
no. -, pp. –, .
[] C. Quaia, P. Lef
`
evre, and L. M. Optican, “Model of the control
of saccades by superior colliculus and cerebellum,” Journal of
Neurophysiology, vol. , no. , pp. –, .
[] T. P. Trappenberg, M. C. Dorris, D. P. Munoz, and R. M. Klein,
“A model of saccade initiation based on the competitive inte-
gration of exogenous and endogenous signals in the superior
colliculus,” Journal of Cognitive Neuroscience,vol.,no.,pp.
–, .
[] C.-C. Lo and X.-J. Wang, “Cortico-basal ganglia circuit mech-
anism for a decision threshold in reaction time tasks,” Nature
Neuroscience,vol.,no.,pp.–,.
ISRN Neurology
[] B. A. Purcell, R. P. Heitz, J. Y. Cohen, J. D. Schall, G. D. Logan,
and T. J. Palmeri, “Neurally constrained modeling of perceptual
decision making,” Psychological Review, vol. , no. , pp. –
, .
[] B.A.Purcell,J.D.Schall,G.D.Logan,andT.J.Palmeri,“From
salience to saccades: multiple-alternative gated stochastic accu-
mulator model of visual search,” Journal of Neuroscience,vol.,
no. , pp. –, .
[] D. L. Sparks, “Functional properties of neurons in the monkey
superior colliculus: coupling of neuronal activity and saccade
onset,” Brain Research,vol.,no.,pp.–,.
[] J. H. Fecteau and D. P. Munoz, “Warning signals inuence
motor processing,” JournalofNeurophysiology,vol.,no.,pp.
–, .
[] J. W. Brown, D. P. Hanes, J. D. Schall, and V. Stuphorn,
“Relation of frontal eye eld activity to saccade initiation during
a countermanding task,” Experimental Brain Research,vol.,
no. , pp. –, .
[] G. F. Woodman, M.-S. Kang, K. ompson, and J. D. Schall,
“e eect of visual search eciency on response preparation:
neurophysiological evidence for discrete ow: research article,”
Psychological Science,vol.,no.,pp.–,.
[] P.Pouget,G.D.Logan,T.J.Palmeri,L.Boucher,M.Par
´
e, and
J. D. Schall, “Neural basis of adaptive response time adjustment
during saccade countermanding,” JournalofNeuroscience,vol.
,no.,pp.–,.
[] P. L. Smith and R. Ratcli, “Psychology and neurobiology of
simple decisions,” Trends in Neurosciences,vol.,no.,pp.–
, .
[] F. Verbruggen and G. D. Logan, “Response inhibition in the
stop-signal paradigm,” Trends in Cognitive Sciences,vol.,no.
, pp. –, .
[] D.M.Barch,T.S.Braver,C.S.Carter,R.A.Poldrack,andT.
W. Robbins, “CNTRICS nal task selection: executive control,”
Schizophrenia Bulletin,vol.,no.,pp.–,.
[] J. Lipszyc and R. Schachar, “Inhibitory control and psy-
chopathology: a meta-analysis of studies using the stop signal
task,” Journal of the International Neuropsychological Society,
vol. , no. , pp. –, .
[] K. N. akkar, J. D. Schall, L. Boucher, G. D. Logan, and S. Park,
“Response inhibition and response monitoring in a saccadic
countermanding task in schizophrenia,” Biological Psychiatry,
vol.,no.,pp.–,.
[] M. M. G. Walton and N. J. Gandhi, “Behavioral evaluation of
movement cancellation,” Journal of Neurophysiology,vol.,no.
, pp. –, .
[] A. R. Aron and R. A. Poldrack, “Cortical and subcortical
contributions to stop signal response inhibition: role of the
subthalamic nucleus,” Journal of Neuroscience,vol.,no.,pp.
–, .
[]A.R.Aron,T.E.Behrens,S.Smith,M.J.Frank,andR.A.
Poldrack, “Triangulating a cognitive control network using
diusion-weighted Magnetic Resonance Imaging (MRI) and
functional MRI,” Journal of Neuroscience,vol.,no.,pp.
–, .
[] B. B. Zandbelt and M. Vink, “On the role of the striatum in
response inhibition,” PLoS ONE, vol. , no. , Article ID e,
.
[]A.Murthy,S.Ray,S.M.Shorter,J.D.Schall,andK.G.
ompson, “Neural control of visual search by frontal eye eld:
eects of unexpected target displacement on visual selection
and saccade preparation,” Journal of Neurophysiology,vol.,
no.,pp.–,.
[] J. Y. Cohen, P. Pouget, R. P. Heitz, G. F. Woodman, and J. D.
Schall, “Biophysical support for functionally distinct cell types
inthefrontaleyeeld,”Journal of Neurophysiology,vol.,no.
, pp. –, .
[]K.Johnston,J.F.X.DeSouza,andS.Everling,“Monkey
prefrontal cortical pyramidal and putative interneurons exhibit
dierential patterns of activity between prosaccade and antisac-
cade tasks,” Journal of Neuroscience,vol.,no.,pp.–
, .
[] G. Vigneswaran, A. Kraskov, and R. N. Lemon, “Large identied
pyramidal cells in macaque motor and premotor cortex exhibit
“in Spikes”: implications for cell type classication,” Journal
of Neuroscience,vol.,no.,pp.–,.
[] L. H. Snyder, A. P. Batista, and R. A. Andersen, “Intention-
related activity in the posterior parietal cortex: a review,” Vision
Research,vol.,no.-,pp.–,.
[]E.Brunamonti,N.W.D.omas,andM.Par
´
e, “e activity
patterns of lateral intraparietal area neurons is not sucient
to control visually guided saccadic eye movements,” Program
No. .., Neuroscience Meeting Planner Society for Neuro-
science, Washington, DC, USA, .
[] J. D. Schall, “On the role of frontal eye eld in guiding attention
and saccades,” Vision Research,vol.,no.,pp.–,
.
[]K.Wong-Lin,P.Eckho,P.Holmes,andJ.D.Cohen,“Opti-
mal performance in a countermanding saccade task,” Brain
Research,vol.,pp.–,.
[] C.-C. Lo, L. Boucher, M. Par
´
e, J. D. Schall, and X.-J. Wang,
“Proactive inhibitory control and attractor dynamics in coun-
termanding action: a spiking neural circuit model,” Journal of
Neuroscience, vol. , no. , pp. –, .
[] Z. M. Hafed, L. Goart, and R. J. Krauzlis, “A neural mechanism
for microsaccade generation in the primate superior colliculus,”
Science,vol.,no.,pp.–,.
[]D.C.Godlove,A.K.Garr,G.F.Woodman,andJ.D.Schall,
“Measurement of the extraocular spike potential during saccade
countermanding,” Journal of Neurophysiology,vol.,no.,pp.
–, .
[] O.Hikosaka,Y.Takikawa,andR.Kawagoe,“Roleofthebasal
ganglia in the control of purposive saccadic eye movements,”
Physiological Reviews, vol. , no. , pp. –, .
[] J. Shires, S. Joshi, and M. A. Basso, “Shedding new light on
the role of the basal ganglia-superior colliculus pathway in eye
movements,” Current Opinion in Neurobiology,vol.,no.,pp.
–, .
[] J. D. Schall and L. Boucher, “Executive control of gaze by the
frontal lobes,” Cognitive, Aective and Behavioral Neuroscience,
vol. , no. , pp. –, .
[] P. G. Bissett and G. D. Logan, “Post-stop-signal slowing:
strategies dominate reexes and implicit learning,” Journal of
Experimental Psychology: Human Perception and Performance,
.
[] K. R. Ridderinkhof, M. Ullsperger, E. A. Crone, and S. Nieuwen-
huis, “e role of the medial frontal cortex in cognitive control,”
Science,vol.,no.,pp.–,.
[] W. J. Gehring, Y. Liu, J. M. Orr, and J. Carp, “e error-related
negativity (ERN/Ne),” in Oxford Handbook of Event-Related
Potential Components, S.J. Luck and E. Kappenman, Eds., pp.
–, Oxford University Press, New York, NY, USA, .
ISRN Neurology
[] E.E.Emeric,J.W.Brown,M.Leslie,P.Pouget,V.Stuphorn,and
J. D. Schall, “Performance monitoring local eld potentials in
the medial frontal cortex of primates: anterior cingulate cortex,”
Journal of Neurophysiology,vol.,no.,pp.–,.
[] E. E. Emeric, M. Leslie, P. Pouget, and J. D. Schall, “Performance
monitoring local eld potentials in the medial frontal cortex of
primates: supplementary eye eld,” Journal of Neurophysiology,
vol. , no. , pp. –, .
[] D.C.Godlove,E.E.Emeric,C.M.Segovis,M.S.Young,J.D.
Schall, and G. F. Woodman, “Event-related potentials elicited
by errors during the stop-signal task—I. macaque monkeys,”
Journal of Neuroscience,vol.,no.,pp.–,.
[] C. B. Holroyd, N. Yeung, M. G. H. Coles, and J. D. Cohen, “A
mechanism for error detection in speeded response time tasks,”
Journal of Experimental Psychology,vol.,no.,pp.–,
.
[] K.Nakamura,M.R.Roesch,andC.R.Olson,“Neuronalactivity
in Macaque SEF and ACC during performance of tasks involv-
ing conict,” Journal of Neurophysiology,vol.,no.,pp.–
, .
[] M. M. Botvinick, C. S. Carter, T. S. Braver, D. M. Barch,
and J. D. Cohen, “Conict monitoring and cognitive control,”
Psychological Review,vol.,no.,pp.–,.
[] N. Yeung, M. M. Botvinick, and J. D. Cohen, “e neural basis
of error detection: conict monitoring and the error-related
negativity,” Psychological Review, vol. , no. , pp. –,
.
[] M. W. Cole, N. Yeung, W. A. Freiwald, and M. Botvinick,
“Cingulate cortex: diverging data from humans and monkeys,”
Trends in Neurosciences,vol.,no.,pp.–,.
[] M. W. Cole, N. Yeung, W. A. Freiwald, and M. Botvinick,
“Conict over cingulate cortex: between-species dierences in
cingulate may support enhanced cognitive exibility in hu-
mans,” Brain, Behavior and Evolution,vol.,no.,pp.–,
.
[] J. D. Schall and E. E. Emeric, “Conict in cingulate cortex func-
tion between humans and macaque monkeys: more apparent
than real. Comment on “Cingulate cortex: diverging data from
humans and monkeys”,” Brain, Behavior and Evolution,vol.,
no. , pp. –, .
[] R. Ratcli and G. McKoon, “e diusion decision model:
theory and data for two-choice decision tasks,” Neural Compu-
tation,vol.,no.,pp.–,.
[] W. S. Geisler and L. K. Cormack, “Models of overt attention,”
in Oxford Handbook on Eye Movements,S.P.Liversedge,I.P.
Gilchrist, and S. Everling, Eds., pp. –, Oxford University
Press, .
[] N. P. Bichot and R. Desimone, “Finding a face in the crowd:
parallel and serial neural mechanisms of visual selection,”
Progress in Brain Research,vol.,pp.–,.
[] J. D. Schall and J. Y. Cohen, “e neural basis of saccade
target selection,” in Oxford Handbook on Eye Movements,S.
P. Liversedge, I. P. Gilchrist, and S. Everling, Eds., Oxford
University Press, .
[] J. W. Bisley and M. E. Goldberg, “Attention, intention, and
priority in the parietal lobe,” Annual Review of Neuroscience,vol.
, pp. –, .
[] C. Constantinidis, “Posterior parietal mechanisms of visual
attention,” Reviews in the Neurosciences,vol.,no.,pp.–
, .
[] J. Gottlieb and P. Balan, “Attention as a decision in information
space,” Trends in Cognitive Sciences,vol.,no.,pp.–,
.
[] C. Wardak, E. Olivier, and J.-R. Duhamel, “e relationship
between spatial attention and saccades in the frontoparietal
network of the monkey,” European Journal of Neuroscience,vol.
, no. , pp. –, .
[] M. Par
´
e and M. C. Dorris, “e role of posterior parietal
cortex in the regulation of saccadic eye movements,” in Oxford
Handbook on Eye Movements,S.P.Liversedge,I.P.Gilchrist,and
S. Everling, Eds., pp. –, Oxford University Press, .
[] L. Itti and C. Koch, “Computational modelling of visual atten-
tion,” Nature Reviews Neuroscience,vol.,no.,pp.–,
.
[] J. K. Tsotsos, A Computational Perspective on Visual Attention,
MIT Press, .
[]E.Awh,K.M.Armstrong,andT.Moore,“Visualandocu-
lomotor selection: links, causes and implications for spatial
attention,” Trends in Cognitive Sciences,vol.,no.,pp.–
, .
[] A. Kristjansson, “e intriguing interactive relationship
between visual attention and saccadic eye movements,” in
Oxford Handbook on Eye Movements,S.P.Liversedge,I.P.
Gilchrist, and S. Everling, Eds., pp. –, Oxford University
Press, .
[] J. D. Schall and K. G. ompson, “Neural mechanisms of
saccade target selection: evidence for a stage theory of attention
and action,” in Cognitive Neuroscience of Attention,M.I.Posner,
Ed., pp. –, Guileford Press, .
[]J.D.Schall,A.Morel,D.J.King,andJ.Bullier,“Topography
of visual cortex connections with frontal eye eld in macaque:
convergence and segregation of processing streams,” Journal of
Neuroscience,vol.,no.,pp.–,.
[] N. T. Markov, P. Misery, A. Falchier et al., “Weight consistency
species regularities of macaque cortical networks,” Cerebral
Cortex, vol. , no. , pp. –, .
[] P. J. May, “e mammalian superior colliculus: laminar struc-
ture and connections,” Progress in Brain Research,vol.,pp.
–, .
[] D. J. Felleman and D. C. Van Essen, “Distributed hierarchical
processing in the primate cerebral cortex,” Cerebral Cortex,vol.
,no.,pp.–,.
[] M. T. Schmolesky, Y. Wang, D. P. Hanes et al., “Signal timing
access the macaque visual system,” Journal of Neurophysiology,
vol. , no. , pp. –, .
[] P.Barone,A.Batardiere,K.Knoblauch,andH.Kennedy,“Lam-
inar distribution of neurons in extrastriate areas projecting to
visual areas V and V correlates with the hiearchical rank
and intimates the operation of a distance rule,” Journal of
Neuroscience,vol.,no.,pp.–,.
[] J. C. Anderson, H. Kennedy, and K. A. C. Martin, “Pathways of
attention: synaptic relationships of frontal eye eld to V, lateral
intraparietal cortex, and area in macaque monkey,” Journal
of Neuroscience,vol.,no.,pp.–,.
[] F. H. Hamker and M. Zirnsak, “V receptive eld dynamics
as predicted by a systems-level model of visual attention using
feedback from the frontal eye eld,” Neural Networks,vol.,no.
,pp.–,.
[] T.OgawaandH.Komatsu,“TargetselectioninareaVduring
a multidimensional visual search task,” Journal of Neuroscience,
vol.,no.,pp.–,.
ISRN Neurology
[] T. Ogawa and H. Komatsu, “Neuronal dynamics of bottom-
up and top-down processes in area V of macaque monkeys
performing a visual search,” Experimental Brain Research,vol.
,no.,pp.–,.
[] G. Mirabella, G. Bertini, I. Samengo et al., “Neurons in area V
of the macaque translate attended visual features into behav-
iorally relevant categories,” Neuron,vol.,no.,pp.–,
.
[] R. E. B. Mruczek and D. L. Sheinberg, “Activity of inferior tem-
poral cortical neurons predicts recognition choice behavior and
recognition time during visual search,” JournalofNeuroscience,
vol.,no.,pp.–,.
[] J. A. Mazer and J. L. Gallant, “Goal-related activity in V during
free viewing visual search: evidence for a ventral stream visual
salience map,” Neuron, vol. , no. , pp. –, .
[] N.P.Bichot,A.F.Rossi,andR.Desimone,“Parallelandserial
neural mechanisms for visual search in macaque area V,”
Science,vol.,no.,pp.–,.
[] S. V. David, B. Y. Hayden, J. A. Mazer, and J. L. Gallant, “Atten-
tion to stimulus features shis spectral tuning of V neurons
during natural vision,” Neuron,vol.,no.,pp.–,.
[] M. Saruwatari, M. Inoue, and A. Mikami, “Modulation of V
shis from dependent to independent on feature during target
selection,” Neuroscience Research,vol.,no.,pp.–,
.
[]G.T.BuracasandT.D.Albright,“Modulationofneuronal
responses during covert search for visual feature conjunctions,”
Proceedings of the National Academy of Sciences of the United
States of America,vol.,no.,pp.–,.
[] I. Opris, A. Barborica, and V. P. Ferrera, “Microstimulation
of the dorsolateral prefrontal cortex biases saccade target
selection,” Journal of Cognitive Neuroscience,vol.,no.,pp.
–, .
[] A. F. Rossi, N. P. Bichot, R. Desimone, and L. G. Ungerleider,
“Top-down attentional decits in Macaques with lesions of
lateral prefrontal cortex,” Journal of Neuroscience,vol.,no.,
pp. –, .
[] R.P.Hasegawa,M.Matsumoto,andA.Mikami,“Searchtarget
selection in monkey prefrontal cortex,” Journal of Neurophysiol-
ogy,vol.,no.,pp.–,.
[] C. Constantinidis, M. N. Franowicz, and P. S. Goldman-Rakic,
“e sensory nature of mnemonic representation in the primate
prefrontal cortex,” Nature Neuroscience,vol.,no.,pp.–,
.
[] S.Everling,C.J.Tinsley,D.Gaan,andJ.Duncan,“Selective
representation of task-relevant objects and locations in the
monkey prefrontal cortex,” European Journal of Neuroscience,
vol. , no. , pp. –, .
[] H.-H. Zhou and K. G. ompson, “Cognitively directed spatial
selection in the frontal eye eld in anticipation of visual stimuli
to be discriminated,” Vision Research,vol.,no.,pp.–
, .
[] N.P.Bichot,J.D.Schall,andK.G.ompson,“Visualfeature
selectivity in frontal eye elds induced by experience in mature
macaques,” Nature,vol.,no.,pp.–,.
[] K. G. ompson, D. P. Hanes, N. P. Bichot, and J. D. Schall,
“Perceptual and motor processing stages identied in the
activity of macaque frontal eye eld neurons during visual
search,” Journal of Neurophysiology,vol.,no.,pp.–
, .
[] T.Sato,A.Murthy,K.G.ompson,andJ.D.Schall,“Search
eciency but not response interference aects visual selection
in frontal eye eld,” Neuron,vol.,no.,pp.–,.
[] J. Y. Cohen, R. P. Heitz, G. F. Woodman, and J. D. Schall, “Neural
basis of the set-size eect in frontal eye eld: timing of attention
during visual search,” Journal of Neurophysiology,vol.,no.,
pp.–,.
[] K.-M. Lee and E. L. Keller, “Neural activity in the frontal eye
elds modulated by the number of alternatives in target choice,”
Journal of Neuroscience,vol.,no.,pp.–,.
[] R. M. McPeek, “Incomplete suppression of distractor-related
activity in the frontal eye eld results in curved saccades,”
Journal of Neurophysiology,vol.,no.,pp.–,.
[] J. P. Gottlieb, M. Kusunoki, and M. E. Goldberg, “e represen-
tation of visual salience in monkey parietal cortex,” Nature,vol.
, no. , pp. –, .
[] P. F. Balan, J. Oristaglio, D. M. Schneider, and J. Gottlieb,
“Neuronal correlates of the set-size eect in monkey lateral
intraparietal area,” PLoS Biology,vol.,no.,articlee,.
[]T.J.BuschmanandE.K.Miller,“Top-downversusbottom-
up control of attention in the prefrontal and posterior parietal
cortices,” Science, vol. , no. , pp. –, .
[] C. Constantinidis and M. A. Steinmetz, “Posterior parietal
cortex automatically encodes the location of salient stimuli,”
Journal of Neuroscience,vol.,no.,pp.–,.
[] A.E.Ipata,A.L.Gee,M.E.Goldberg,andJ.W.Bisley,“Activity
in the lateral intraparietal area predicts the goal and latency
of saccades in a free-viewing visual search task,” Journal of
Neuroscience, vol. , no. , pp. –, .
[] T. Ogawa and H. Komatsu, “Condition-dependent and con-
dition-independent target selection in the macaque posterior
parietal cortex,” Journal of Neurophysiology,vol.,no.,pp.
–, .
[] N.W.D.omasandM.Par
´
e, “Temporal processing of saccade
targets in parietal cortex area LIP during visual search,” Journal
of Neurophysiology,vol.,no.,pp.–,.
[]B.KimandM.A.Basso,“Saccadetargetselectioninthe
superior colliculus: a signal detection theory approach,” Journal
of Neuroscience, vol. , no. , pp. –, .
[] R. M. McPeek and E. L. Keller, “Saccade target selection in
the superior colliculus during a visual search task,” Journal of
Neurophysiology, vol. , no. , pp. –, .
[] K. Shen and M. Par
´
e, “Neuronal activity in superior colliculus
signals both stimulus identity and saccade goals during visual
conjunction search,” Journal of Vision,vol.,no.,article,
.
[] B. J. White and D. P. Munoz, “Separate visual signals for sac-
cade initiation during target selection in the primate superior
colliculus,” Journal of Neuroscience,vol.,no.,pp.–,
.
[] M. A. Basso and R. H. Wurtz, “Neuronal activity in substantia
nigra pars reticulata during target selection,” Journal of Neuro-
science,vol.,no.,pp.–,.
[] M. T. Wyder, D. P. Massoglia, and T. R. Stanford, “Contextual
modulation of central thalamic delay-period activity: represen-
tation of visual and saccadic goals,” Journal of Neurophysiology,
vol. , no. , pp. –, .
[] A. N. Phillips and M. A. Segraves, “Predictive activity in
Macaque frontal eye eld neurons during natural scene search-
ing,” Journal of Neurophysiology,vol.,no.,pp.–,
.
ISRN Neurology
[] J. O’Shea, N. G. Muggleton, A. Cowey, and V. Walsh, “Timing
of target discrimination in human frontal eye elds,” Journal of
Cognitive Neuroscience,vol.,no.,pp.–,.
[] C. Wardak, G. Ibos, J.-R. Duhamel, and E. Olivier, “Contribu-
tion of the monkey frontal eye eld to covert visual attention,”
Journal of Neuroscience, vol. , no. , pp. –, .
[] I. E. Monosov and K. G. ompson, “Frontal eye eld activity
enhances object identication during covert visual search,”
Journal of Neurophysiology,vol.,no.,pp.–,.
[] R. M. McPeek, “Reversal of a distractor eect on saccade
target selection aer superior colliculus inactivation,” Journal of
Neurophysiology,vol.,no.,pp.–,.
[] L. P. Lovejoy and R. J. Krauzlis, “Inactivation of primate superior
colliculus impairs covert selection of signals for perceptual
judgments,” Nature Neuroscience, vol. , no. , pp. –,
.
[] C. Wardak, E. Olivier, and J.-R. Duhamel, “A decit in covert
attention aer parietal cortex inactivation in the monkey,”
Neuron,vol.,no.,pp.–,.
[] P. F. Balan and J. Gottlieb, “Functional signicance of nonspatial
information in monkey lateral intraparietal area,” Journal of
Neuroscience,vol.,no.,pp.–,.
[] K.Mirpour,W.S.Ong,andJ.W.Bisley,“Microstimulationof
posterior parietal cortex biases the selection of eye movement
goals during search,” Journal of Neurophysiology,vol.,no.,
pp. –, .
[]T.R.SatoandJ.D.Schall,“Eectsofstimulus-response
compatibility on neural selection in frontal eye eld,” Neuron,
vol. , no. , pp. –, .
[] G. F. Woodman, M.-S. Kang, A. F. Rossi, and J. D. Schall,
“Nonhuman primate event-related potentials indexing covert
shis of attention,” Proceedings of the National Academy of
Sciences of the United States of America,vol.,no.,pp.
–, .
[] B. Y. Hayden and J. L. Gallant, “Time course of attention reveals
dierent mechanisms for spatial and feature-based attention in
area V,” Neuron,vol.,no.,pp.–,.
[] K.G.ompson,N.P.Bichot,andT.R.Sato,“Frontaleyeeld
activity before visual search errors reveals the integration of
bottom-up and top-down salience,” Journal of Neurophysiology,
vol.,no.,pp.–,.
[]R.P.Heitz,J.Y.Cohen,G.F.Woodman,andJ.D.Schall,
“Neural correlates of correct and errant attentional selection
revealed through Npc and frontal eye eld activity,” Journal of
Neurophysiology,vol.,no.,pp.–,.
[] K.Mirpour,F.Arcizet,W.S.Ong,andJ.W.Bisley,“Beenthere,
seen that: a neural mechanism for performing ecient visual
search,” Journal of Neurophysiology,vol.,no.,pp.–
, .
[] K.G.ompson,N.P.Bichot,andJ.D.Schall,“Dissociationof
visual discrimination from saccade programming in macaque
frontal eye eld,” Journal of Neurophysiology,vol.,no.,pp.
–, .
[] F.Arcizet,K.Mirpour,andJ.W.Bisley,“Apuresalienceresponse
in posterior parietal cortex,” Cerebral Cortex, vol. , no. , pp.
–, .
[] K.G.ompson,K.L.Biscoe,andT.R.Sato,“Neuronalbasis
of covert spatial attention in the frontal eye eld,” Journal of
Neuroscience,vol.,no.,pp.–,.
[] J. Oristaglio, D. M. Schneider, P. F. Balan, and J. Gottlieb,
“Integration of visuospatial and eector information during
symbolically cued limb movements in monkey lateral intrapari-
etal area,” Journal of Neuroscience,vol.,no.,pp.–,
.
[] A.E.Ipata,A.L.Gee,J.W.Bisley,andM.E.Goldberg,“Neurons
in the lateral intraparietal area create a priority map by the
combination of disparate signals,” Experimental Brain Research,
vol. , no. , pp. –, .
[] N.P.Bichot,K.G.ompson,S.C.Rao,andJ.D.Schall,“Reli-
ability of macaque frontal eye eld neurons signaling saccade
targets during visual search,” Journal of Neuroscience,vol.,no.
,pp.–,.
[]B.KimandM.A.Basso,“Aprobabilisticstrategyforunder-
standing action selection,” Journal of Neuroscience,vol.,no.
, pp. –, .
[]J.Y.Cohen,E.A.Crowder,R.P.Heitzetal.,“Cooperation
and competition among frontal eye eld neurons during visual
target selection,” Journal of Neuroscience,vol.,no.,pp.–
, .
[]T.OgawaandH.Komatsu,“Dierentialtemporalstorage
capacity in the baseline activity of neurons in macaque frontal
eye eld and area V,” Journal of Neurophysiology,vol.,no.
, pp. –, .
[] G.G.Gregoriou,S.J.Gotts,H.Zhou,andR.Desimone,“High-
Frequency, long-range coupling between prefrontal and visual
cortex during attention,” Science, vol. , no. , pp. –
, .
[] S. Ray and J. H. R. Maunsell, “Dierences in gamma frequencies
across visual cortex restrict their possible use in computation,”
Neuron,vol.,no.,pp.–,.
[] G.F.WoodmanandS.J.Luck,“Electrophysiologicalmeasure-
ment of rapid shis of attention during visual search,” Nature,
vol. , no. , pp. –, .
[] C.N.Boehler,J.K.Tsotsos,M.A.Schoenfeld,H.-J.Heinze,and
J.-M. Hopf, “Neural mechanisms of surround attenuation and
distractor competition in visual search,” Journal of Neuroscience,
vol. , no. , pp. –, .
[] M.S.HowellYoung,R.P.Heitz,J.D.Schall,andG.F.Wood-
man, “Modeling the neural generators of monkey event-related
potentials indexing covert shi of attention,” Program No. .
Neuroscience Meeting Planner. Society for Neuroscience San
Diego, Calif, USA, .
[] I.E.Monosov,J.C.Trageser,andK.G.ompson,“Measure-
ments of simultaneously recorded spiking activity and local
eld potentials suggest that spatial selection emerges in the
frontal eye eld,” Neuron,vol.,no.,pp.–,.
[] J.Y.Cohen,R.P.Heitz,J.D.Schall,andG.F.Woodman,“On
the origin of event-related potentials indexing covert attentional
selection during visual search,” Journal of Neurophysiology,vol.
, no. , pp. –, .
[] I.E.Monosov,D.L.Sheinberg,andK.G.ompson,“Paired
neuron recordings in the prefrontal and inferotemporal cor-
tices reveal that spatial selection precedes object identication
during visual search,” Proceedings of the National Academy of
Sciences of the United States of America,vol.,no.,pp.
–, .
[] T. Moore and M. Fallah, “Microstimulation of the frontal eye
eld and its eects on covert spatial attention,” Journal of
Neurophysiology,vol.,no.,pp.–,.
[] K.M.Armstrong,J.K.Fitzgerald,andT.Moore,“Changesin
visual receptive elds with microstimulation of frontal cortex,”
Neuron,vol.,no.,pp.–,.
ISRN Neurology
[] L. B. Ekstrom, P. R. Roelfsema, J. T. Arsenault, H. Kolster, and
W. Vanduel, “Modulation of the contrast response function
by electrical microstimulation of the macaque frontal eye eld,”
Journal of Neuroscience,vol.,no.,pp.–,.
[] P.C.J.Taylor,A.C.Nobre,andM.F.S.Rushworth,“FEFTMS
aects visual cortical activity,” Cerebral Cortex,vol.,no.,pp.
–, .
[] R. Walker, P. Techawachirakul, and P. Haggard, “Frontal eye
eld stimulation modulates the balance of salience between
target and distractors,” Brain Research,vol.,pp.–,
.
[] M. Usher and J. L. McClelland, “e time course of perceptual
choice: the leaky, competing accumulator model,” Psychological
Review,vol.,no.,pp.–,.
[]J.M.Wolfe,E.M.Palmer,andT.S.Horowitz,“Reaction
time distributions constrain models of visual search,” Vision
Research, vol. , no. , pp. –, .
[] J. C. Trageser, I. E. Monosov, Y. Zhou, and K. G. ompson, “A
perceptual representation in the frontal eye eld during covert
visual search that is more reliable than the behavioral report,”
European Journal of Neuroscience,vol.,no.,pp.–,
.
[] A. Murthy, S. Ray, S. M. Shorter, E. G. Priddy, J. D. Schall,
and K. G. ompson, “Frontal eye eld contributions to rapid
corrective saccades,” Journal of Neurophysiology,vol.,no.,
pp.–,.
[] C.-H.Juan,S.M.Shorter-Jacobi,andJ.D.Schall,“Dissociation
of spatial attention and saccade preparation,” Proceedings of the
National Academy of Sciences of the United States of America,
vol. , no. , pp. –, .
[] D. L. Sparks and L. E. Mays, “Spatial localization of saccade
targets—I. Compensation for stimulation-induced perturba-
tions in eye position,” Journal of Neurophysiology,vol.,no.
,pp.–,.
[]C.-H.Juan,N.G.Muggleton,O.J.L.Tzeng,D.L.Hung,
A.Cowey,andV.Walsh,“Segregationofvisualselectionand
saccades in human frontal eye elds,” Cerebral Cortex,vol.,
no. , pp. –, .
[] D. T. Smith and T. Schenk, “Enhanced probe discrimination at
the location of a colour singleton,” Experimental Brain Research,
vol. , no. , pp. –, .
[] P. Pouget, I. Stepniewska, and E. A. Crowder, “Visual and motor
connectivity and the distribution of calcium-binding proteins
in macaque frontal eye eld: implications for saccade target
selection,” Frontiers in Neuroanatomy,vol.,.
[] J. R. Platt, “Strong Inference: certain systematic methods of
scientic thinking may produce much more rapid progress than
others,” Science,vol.,pp.–,.
[] J. P. A. Ioannidis, “Why most published research ndings are
false,” PLoS Medicine, vol. , no. , article e, .
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