Foxe et al (in press)

Foxe, McCourt & Javitt “Parietal Control of Spatial Attention” 1

Right hemisphere control of visuospatial attention: 'Line-bisection' judgments evaluated with

high-density electrical mapping and source analysis.

John J. Foxe a,b,c,* , Mark E. McCourt d, Daniel C. Javitt a,e

a The Cognitive Neurophysiology Laboratory,Nathan S. Kline Institute for Psychiatric Research,

Program in Cognitive Neuroscience and Schizophrenia,140 Old Orangeburg Road,

Orangeburg, New York 10962, USA

b Department of Neurosciencec Department of Psychiatry and Behavioural Science,

Albert Einstein College of Medicine,1300 Morris Park Avenue,

Bronx, New York 10461, USA

d Department of Psychology,North Dakota State University

Fargo, North Dakota 58105, USA

e Department of Psychiatry,New York University School of Medicine,

550 1st Avenue,New York, New York 10016, USA

NeuroImage (in press). Please do not cite without prior permission.

*Correspondence can be addressed to:

Dr. John J. FoxeThe Cognitive Neurophysiology Laboratory,Nathan S. Kline Institute for Psychiatric Research, Program in Cognitive Neuroscience and Schizophrenia, 140 Old Orangeburg Road, Orangeburg, NY 10962, USAVox: (845) 398-6547; Fax: (845) 398-6545e-mail: [email protected]

mailto:[email protected]


ABSTRACT

The ‘line-bisection’ task has proven an especially useful clinical tool for assessment of spatial

neglect syndrome in neurological patients. Here, we investigated the neural processes involved

in performing this task by recording high-density event-related potentials (ERP) from 128 scalp-

electrodes in normal observers. We characterize a robust net negative potential from 170-400 ms

post stimulus presentation that correlates with line-bisection judgments. Topographic mapping

shows three distinct phases to this negativity. The first phase (~170-190 ms) has a scalp

distribution exclusively over the right parieto-occipital and lateral-occipital scalp, consistent with

generators in the region of the right temporo-parietal junction and right lateral occipital cortices.

The second phase (~190-240 ms) sees the emergence of a second negative focus over the right

central-parietal scalp, consistent with subsequent involvement of right superior parietal cortices.

In the third phase (~240-400 ms), the topography becomes dominated by this right central-

parietal negativity. Inverse source-modeling confirmed that right hemisphere lateral occipital,

inferior parietal and superior parietal regions were the likeliest generators of the bulk of the

activity associated with this effect. The line stimuli were also presented at three contrast levels

(3%, 25% and 100%) in order to manipulate both the latency of stimulus processing and the

relative contributions from magnocellular and parvocellular inputs. Through this manipulation,

we show that the line-bisection effect systematically tracks/follows the latency of the N1

component, which is considered a temporal marker for object processing in the ventral visual

stream. This pattern of effects suggests that this task invokes an allocentric (object-based) form

of visuo-spatial attention. Further, at 3% contrast, the line-bisection effect was equivalent to the

effects seen at higher contrast levels, suggesting that parvocellular inputs are not necessary for

successful performance of this task.


INTRODUCTION

Line-bisection tasks are a commonly used metric for the clinical assessment of visuo-spatial

neglect syndrome, a condition that predominantly results from vascular lesions to the right

inferior parietal or temporo-parietal cortex (e.g. Vallar and Perani, 1987; Cappa et al., 1991;

Mesulam, 2000; Na et al., 2000; Kerkhoff, 2001; see Karnath, 2001 for a comprehensive

treatment). Patients with visuospatial neglect syndrome generally bisect lines significantly to the

right of veridical center (Robertson and Halligan, 1999), due either to a decrement in the ability

to allocate attention to left visual space, or to hyper-attention to rightward space. Clinical

findings from neglect patients allied to the scores of neuroimaging studies showing a

predomination of right parietal activity during tasks requiring visuo-spatial attention (e.g.

Corbetta et al., 2000; Coull et al., 2001) have led to the formulation that while both left and right

parietal areas are involved in attention to the right visual field, right parietal areas alone may

control attention to the left visual hemifield (e.g. Heilman and van den Abell, 1980; Weintraub

and Mesulam, 1987). A measure of support for this conjecture is derived from the finding that

neurologically normal subjects demonstrate a phenomenon known as ‘pseudoneglect’ (Bowers &

Heilman, 1980), in which a significant and systematic misbisection of lines (or space) occurs that

is leftward of veridical center. This leftward tendency in normal observers has been theorized to

result from a profound parietal asymmetry in attentional control, which gives rise to some degree

of hyper-attentiveness to the left visual field (in space-based attention), or to the left-hand side of

individual objects (in object-based attention) (see Jewell and McCourt, 2000; McCourt, 2001a;

McCourt & Jewell, 1999; McCourt et al., 2000).

Functional imaging (fMRI) studies have confirmed a central role for right parietal cortices in

performance of both line-bisection tasks (Weiss et al., 2000; Fink et al., 2000a, 2000b, 2001,


2002; Galati et al., 2000) as well as judgments of object location relative to the midsagittal plane

(Vallar et al., 1999; Galati et al., 2000). There have, to date, been no electrophysiological

investigations of line-bisection; consequently the timing of right parietal involvement relative to

the timing of ongoing stimulus processing is as yet unknown. In the current study, we performed

high-density electrical mapping (from 128 scalp electrodes) of the visual event-related potential

(ERP) while subjects engaged in either a tachistoscopic forced-choice line-bisection task

(McCourt & Olafson, 1997) or in a control task in which they simply judged whether lines were

transected or not. Our main objectives were to both confirm the involvement of and define the

timecourse of right parietal activity in performance of the line-bisection task. In particular, we

wished to assess the relationship of parietal attentional processes in the dorsal visual processing

stream to the processing of the line stimuli by object recognition areas of the ventral visual

stream. An open question is whether line midpoint judgments can only be made upon

completion of object recognition processes for the object that is to be bisected. In the present

study, we systematically varied the timing of object-recognition processes by varying the

contrast level at which lines were displayed. We used the well-characterized N1 component of

the VEP as an index of the timing of object recognition processes, since this component has

repeatedly been shown to be correlated with the processes involved in object recognition (e.g.

Allison et al., 1999; Bentin et al., 1999; Doniger et al., 2000, 2001). Systematically varying the

latency of this component allowed us to assess whether bisection processes tracked this latency

manipulation.


MATERIALS AND METHODS

Subjects

Nine (4 male) neurologically normal, paid volunteers (ages 19-45 years, mean = 29.2 years)

participated. All subjects provided written informed consent, and the Institutional Review Boards

of the Nathan Kline Research Institute and North Dakota State University approved all

procedures. All subjects possessed normal or corrected-to-normal vision and were right-handed,

as measured using the Oldfield (1971) laterality inventory (mean score = 58.3, sd=22.7).

Instrumentation and Stimuli

Subject responses were sensed and collected, and stimuli were presented as 640x480 pixel

images on a 21" flat-screen monitor; frame refresh rate was 60 Hz and mean display luminance

was 22 cd/m2. The generation and sequencing of stimuli and the collection of subject responses

were accomplished using the ERTS software package (Beringer, 1995). Luminance and contrast

calibrations were made using a photometer.

Stimuli were line segments (29 cm wide by 0.5 cm high) presented for 150 ms. At the

viewing distance of 108 cm, lines subtended 15.3o (width) by 0.27o (height) of visual angle. All

lines were horizontally and vertically centered within the display. Seventy-five percent of the

lines were transected at one of 25 different locations ranging from ±0.6o of visual angle relative

to veridical line midpoint. This range of transector locations is sufficient to determine perceived

line midpoint in most observers (McCourt, 2001a). The remaining 25% of lines were non-

transected. Lines were presented at three levels of Michelson contrast: 3%, 25%, and 100%. This

range of stimulus contrast was employed for both methodological and theoretical reasons.

Methodologically, the presence of low contrast lines ensured that the visual discriminations in

the feature detection task (transected versus non transected) would not be trivially easy, and that


subjects would remain alert and vigilant throughout the blocks of trials. Theoretically, it was of

interest to determine whether there would be any unique behavioral or electrophysiological

signature regarding the lowest contrast stimulus that, at 3% contrast, is well below the operating

range of the parvocellular division of the geniculostriate projection, and thus preferentially

engages the magnocellular stream (Shapley and Perry, 1986).

Figure 1 illustrates examples of the line stimuli. Both members of the upper pair of lines (A,

B) possess 100% contrast, and are transected to the left of center, by −0.33o (−2.17%) and −0.60o

(−3.91%), respectively. Both members of the lower pair of lines (E, F) possess 3% contrast and

are transected to the right of center, by +0.47o (3.04%) and +0.17o (1.09%), respectively. Lines C

and D possess 25% contrast; C is veridically transected and line D lacks a transector. Pairs (A,

B) and (E, F) differ in contrast polarity. Lines of varying contrast and contrast polarity appeared

with equal frequency. The order of appearance of all line types was quasi-randomized within

blocks of trials.

Insert Figure 1 Here

Procedures and Tasks

Subjects were seated in a comfortable chair with their midsagittal plane aligned with the

display monitor. Stimuli were viewed binocularly through natural pupils.

Each block of trials consisted of 200 line presentations. On alternate blocks subjects

performed either one of two tasks. In the Control Task subjects performed an oddball (feature

discrimination) task in which they judged whether lines were transected (75% of trials) or not

(25% of trials). The non-bisected lines thus served as "target" stimuli. Use of the oddball task as

the control condition ensured that subjects were actively engaged in an attentionally demanding


task in both conditions and that equivalent button push responses were made during both tasks. If

a simple passive viewing task were to be used, changes in general arousal level might have

accounted for any effects seen.

In the Line-bisection task subjects made judgments regarding transector location (left versus

right) relative to perceived line midpoint by depressing the appropriate mouse button "left" or

"right", respectively. Subjects were instructed to respond to non-transected lines by depressing

either mouse button.

Subjects used their dominant (right) hand to depress mouse buttons. Subjects were instructed

to delay their responses for at least 1 second following stimulus presentation to obviate motor

artifacts in the EEG signal. Inter-trial intervals were approximately 2 sec., since subsequent trials

were initiated 750 ms following the previous response. Each subject completed 3 or 4 blocks of

both Line-bisection and Control Task trials. At each level of line contrast subjects made either

six or eight "left-right" judgments at each transector location, such that estimates of perceived

line midpoint in each line contrast condition were determined based on 150-200 bisection trials.

Each block of trials was completed in approximately 9 minutes.

Measurements and Analyses

Behavioral Measures

For behavioral analysis the dependent measure was the proportion of trials on which subjects

indicated that transectors appeared to the "left" of perceived line midpoint. The method of

constant stimuli was used to derive psychometric functions, and nonlinear least-squares

regression was used to fit a cumulative Gaussian distribution to the psychometric functions (see

McCourt & Jewell, 1999). Based on these fits, transector locations corresponding to a 50% "left"


response rate were determined. The transector location for which "left" and "right" responses

occur with equal frequency is called the "point of subjective equality" (pse) and is an objective

measure of perceived line midpoint. Inferential statistical analyses were performed on the pse

values.

Electrophysiological Measures

Continuous EEG was acquired from 128 scalp electrodes (impedances < 5kΩ), referenced to

nose, band-pass filtered from 0.05 to 100Hz, and digitized at 500Hz. Data were epoched off-line

from −100 pre-stimulus to 500 ms post-stimulus and baseline-corrected from −100 to 0 ms.

Thereafter, trials with blinks and eye movements were rejected on the basis of horizontal and

vertical electro-oculogram. An artifact rejection criterion of ±60µV was used at all other scalp

sites to reject trials with excessive EMG or other noise transients. The average number of

accepted trials per condition across subjects was 476 (S.D. = 84.2). Responses to the non-

transected lines, which served as "target" stimuli in the control task, were not included in the

averages nor analyzed further. This latter point is important, as during the control task the N2/P3

component complex associated with infrequent target stimuli was generated for these stimuli (see

e.g. Ritter and Vaughan, 1969; He et al., 2001). Thus, use of these responses as constituents of

the "control" averaged response would have been problematic. Also, false alarms (which were

very few) were also excluded from this analysis.

The latencies and scalp topographies of the standard ERP componentry over posterior scalp

were identified from group-averaged waveforms collapsed across the Control and Line-bisection

conditions. Repeated measures analyses of variance (ANOVA) was used to test for significant

differences between conditions for four pre-selected time-windows, centered at the peak


amplitude of the P1 (92-100 ms), the N1 (174-182 ms), the P2 (230-240 ms) and the following

negative deflection over occipito-temporal regions, N280ot, (270-280 ms). For these time-

windows, a measure of integrated amplitude was derived between the response and the 0 µV

baseline. ANOVAs possessed a repeated-measures 2 X 2 X 4 design with the following factors:

condition (control, line-bisection), hemisphere (left, right) and electrode (4 electrode pairs over

lateral occipito-parietal scalp).

Topographic Mapping

Scalp topographic maps in the present study represent interpolated potential distributions,

derived from the 128-scalp measurements and based on the computation of a common average

reference. These interpolated potential maps are displayed on the 3-D reconstruction of an

average rendered scalp surface (derived from anatomical MRIs), using the boundary element

method (BEM; e.g. Fuchs et al., 1998) and as implemented in the CURRY multimodal

neuroimaging analysis software package (Version 4.0 − Philips Research, Hamburg, Germany).

Exact electrode locations were assessed for each subject on the day of testing by 3D-

digitization of the locations of the scalp electrodes with respect to fiduciary landmarks (i.e. the

nasion and pre-auricular notches) using a magnetic digitization device (Polhemus Fastrak and

3DspaceDX software, Neuroscan, Inc.). Electrode placement was highly consistent across

subjects due to the use of a custom-designed electrode cap that constrained inter-electrode

spacing and placement. An averaged version of these electrode locations was projected onto the

averaged rendered head for computation of the group topographic data.

Lastly, one obvious constraint of the printed page is that only a limited number of

discrete maps can be shown to represent a given topographic distribution, and such static maps


fail to depict the full spatio-temporal dimensionality of the data. This can make it particularly

difficult for the reader to assess the extent of contribution to the maps of background noise. In

determining the display-gain to be used for the maps in the current study, we followed the

topography over its entire timecourse (through observing animated time-series). Observation of

these maps in the baseline period (from -100 ms up to the onset of significant activity at about 50

ms) allowed us to determine the relative contribution of noise to the topographic maps. The gain

was then set so that background noise during this baseline period accounted for less than 1-2

topographic lines of potential in the maps.

This is more readily seen in the animation appendix to this paper, which can be viewed or

downloaded at (http//academicpress.com/ni/linebisection.avi ???)

Dipole source analyses

Information about the intracranial generators contributing to effects seen in the data was

also obtained through dipole source analysis using electro-magnetic source estimation (EMSE)

as implemented in CURRY version 4.0 software. This method assumes that there are a limited

and distinct number of active brain regions over the evoked potential epoch, each of which can

be approximated by an equivalent dipole. Dipole generators are placed within a three-shell

spherical volume conductor model and overlaid on and adjusted to a BEM-segmented structural

MRI (in this case, an averaged brain). The forward solution to this dipole configuration is tested

against the observed experimental data. When not fixed, the positions and orientations of the

dipoles are iteratively adjusted to minimize the residual variance between the forward solution

and the observed data. The upper bound of the number of modeled dipole sources is determined

using a test dipole (Scherg & Picton, 1991). If the number of modeled sources, m, is adequate,


then addition of another source (test dipole) and solving for m+1 sources would not be expected

to further reduce the residual variance, above that attributable to noise. The reader is referred to

the following papers for comprehensive treatments of source localization procedures (Simpson,

1995a,b; Scherg and Berg, 1997; Michel et al., 2001).

RESULTS

Behavioural Results

Figure 2 presents group-averaged psychometric functions obtained in the Line-bisection

condition at each level of line contrast. Open symbols plot mean percent “left” responses (±1

s.e.m.) against transector location (in degrees relative to veridical line midpoint). The data are


well behaved, and the range of transector locations sampled is observed to encompass perceived

line midpoint in this sample of subjects. Solid lines depict cumulative Gaussian distributions

fitted to the data by nonlinear least-squares regression. The cumulative Gaussian function is

described by the equation:

f(x,α,β,σ)=α(50+50(erf((x−β)/20.5 σ)))

where x is transector location (in degrees relative to veridical line midpoint), α is an overall gain

parameter, β is the x-axis location corresponding to the mean of the underlying Gaussian density

function (i.e., pse − the transector location at which left-right responses occur with equal frequency),

and σ is its standard deviation. The error function (erf) is an approximation to the cumulative

Gaussian distribution, for which there is no closed-form analytical expression. The horizontal

dashed line in each panel indicates the 50% “left” response rate; the transector location for which


the cumulative Gaussian intersects the dashed line is one measure of perceived line midpoint

(pse).

The solid symbols (and vertical dotted lines) in each panel plot mean pse (±1 s.e.m.) based

on the analysis of psychometric functions from individual observers. The agreement with pse

estimates from the group-averaged fits is excellent, and reveals the systematic leftward error

(pseudoneglect) in perceived line midpoint that typifies the performance of neurologically normal

right-handed observers (Jewell & McCourt, 2000; McCourt, 2001a). A one-way repeated-measures

ANOVA conducted on the pse values in each line contrast condition revealed no significant effect

of line contrast, F(2, 16) = 0.74, p = 0.49. While single-sample t-tests comparing mean pse values in

each line contrast condition against veridical fail to achieve significance: 100%, t(8) = −1.63, p =

0.14; 25%, t(8) = −1.73, p = 0.12; 3%, t(8) = −1.68, p = 0.13, increasing statistical power by

collapsing across levels of line contrast revealed, however, that grand mean pse is shifted

significantly leftward of veridical by approximately 0.2o, or 1.4%, t(26) = −2.98, p = 0.006.

Electrophysiological Results

The analysis of behavioural results revealed that line contrast had no significant effect on

bisection performance, and we therefore collapsed across the three levels of line contrast in the

initial statistical analysis of the electrophysiological data. Inspection of group-averaged visual

evoked potentials for both the Line-bisection and Control Task conditions revealed the

traditional series of ERP components, including P1, N1 and P2 (Figure 3.). These components

were maximal over visual cortices.



The earliest robust component, the P1, showed no amplitude or latency difference between

conditions. However, over right hemisphere occipito-parietal sites, responses in the line-

bisection condition showed a markedly increased negativity relative to those in the control task;

this difference began during the peak of the N1 component and then continued for some 300 ms.

At left hemisphere electrode sites, this negative shift was seen to onset later during the N1/P2

transition. This negativity can be seen in Figure 3, where the right hemisphere electrode site of

maximal difference is plotted along with the equivalently positioned left hemisphere site.

As expected, the ANOVA for the P1 latency bin (92-100 ms) yielded no significant main

effect of condition (p = 0.62). The ANOVA for the N1 latency range yielded a significant

interaction of Condition X Hemisphere (F (1,8) = 5.19, p = 0.05). Follow-up planned-

comparisons showed that this was due to a robust main effect of condition over the right

hemisphere electrode sites (F (1,8) = 8.8, p < 0.02), whereas no main effect of condition was

seen over the equivalent left hemisphere sites in this latency range (p = 0.44). The ANOVA for

the P2 latency range revealed a significant main effect of condition (F(1,8) = 31.33, p < 0.001)

but no interaction of Condition X Hemisphere (p = 0.68). Similarly, the ANOVA for the N280ot

latency range revealed only a significant main effect of condition (F(1,8) = 29.27, p < 0.001).

As the ANOVA for N1 showed that the effect of Condition onset earlier over the right

hemisphere, we performed a post-hoc analysis to determine rough onset times for the effect in

both hemispheres. We used a series of paired two-tailed t-tests between the Control and Line-

bisection conditions at the four representative pairs of electrode sites used in the above analyses.

Tests were conducted at latencies preceding the P2 peak to mark the earliest timepoint that

conformed to a 0.05 criterion. Onset latencies across the four left and across the four right

hemisphere electrode sites were averaged to provide a best estimate of onset in a given


hemisphere. A point was only accepted as the earliest divergence if at least 11 subsequent

consecutive time-points (>20ms at 500 Hz digitization rate) met the 0.05 criterion (see also

Guthrie and Buchwald, 1991; Foxe and Simpson, 2002). The criterion was met at 172 ms for the

right hemisphere and 208 ms for the left, indicating that bisection-related attentional processes

onset in the right hemisphere some 30-40 ms earlier than they do in the left hemisphere.

Topographic Analysis

Figure 4 illustrates that the net negative activity associated with line-bisection judgments

(hereafter referred to as the “line-bisection effect”) consists of three distinct phases that can be

discerned through topographic mapping.

- Dominating the earliest phase of the response (~170-190 ms) is a negative focus

concentrated over the right lateral parieto-occipital scalp. There is little or no

concurrent effect over the equivalent left scalp.

- In the second phase (190-240 ms) an additional robust negative focus is evident over

right central parietal scalp, during which the right parieto-occipital focus persists.

Negativity is also evident over left lateral-occipital cortex during this phase.

- In the final phase, as the point of maximal effect is approached (~310 ms), the

topographic pattern becomes dominated by the right central-parietal negativity.

While Figure 4 shows these three distinct phases, the reader is referred to the accompanying

web appendix (http//academicpress.com/ni/linebisection.avi ???). Readers can download an

animation of the scalp topography of the line-bisection effect that better illustrates the spatio-

temporal dynamics of this negative potential.



Analysis by Contrast Level

We next investigated the timing of the line-bisection effect at the three different contrast

levels that were employed (100%, 25% and 3%). We wished to assess the relationship of the

timing of the effect to ongoing stimulus processing as indexed by the N1 component. First we

established the peak latency of N1 for each of the 3 contrast conditions by the following method.

We identified the scalp-site of maximum N1 amplitude by inspecting the group-averaged voltage

waveforms over the right temporo-occipital scalp for the control condition. We then measured

the latency of N1 for each individual subject at this scalp site, where N1 latency was defined as

the point of maximum negative deflection in the latency window between 120 and 240 ms (i.e.

following the P1 component up until P2). Clearly identifiable N1’s were obtained for 8 of the 9

subjects in this study. We excluded from this phase of the analysis the one subject for whom a

clear N1 could not be identified. By this method we obtained the following N1 latency measures:

100%: 156.5 ms (± 17.3); 25%: 163.1 ms (± 21.5); 3%: 192.1 ms (± 19.2). Paired t-tests showed

that the latency difference between the 100% and 25% conditions reached significance (p<0.05),

and in turn, that the difference between 25% and 3% was also significant (p<0.002). Thus, the

contrast manipulation was successful in its aim of systematically manipulating N1 latency.

We now used the running t-test method described above to register the approximate onset of

the line-bisection effect at each of the three contrast conditions. Recall that a given time-point is

only accepted as the earliest divergence if at least 11 subsequent consecutive time-points (>20ms

at 500 Hz digitization rate) meet the 0.05 criterion. The 11-point criterion was met at the

following latencies for the respective contrast levels: 100%: 164 ms; 25%: 172 ms; 3%: 210 ms.

Thus, in all three cases, the onset of significant difference in the line-bisection effect lags the

peak latency of N1 and appears to systematically track the latency of N1. This pattern can be


clearly seen in Figure 5, which illustrates the responses obtained at the three different line

contrasts.


Dipole Source-Analysis

A strong set of a-priori hypotheses regarding the likely intracranial generators of the line-

bisection effect was possible due to the series of detailed functional imaging studies of this task

that have been previously conducted, as discussed above (see also Fig 6). We used the following

strategy to guide the present source analysis. We performed a meta-analysis of three previous

fMRI reports on the line-bisection task (Fink et al, 2000a; Fink et al., 2001; Fink et al., 2002).

We made a list of regions that were consistently activated in the task, that is, regions that were

activated in at least two of the three studies. For example, the right lateral inferior posterior

parietal region was activated in all three of these studies with some minor variation in the exact

locus of the center of activation. As would be expected, slight variations in the exact coordinates

of a given activation were found across these studies, so we tabulated and averaged the Talairach

co-ordinates of common activations in order to derive a single average set of coordinates for a

given area.

This strategy led to the following list of five areas: Right Lateral Occipital Cortex

(RLOC- X=34, Y=-89, Z=03), Right Lateral Inferior Posterior Parietal Cortex (RIPP- 41, -40,

50), Right Lateral Superior Posterior Parietal Cortex (RSPP- 23, -58, 61), Medial

Striate/Extrastriate Cortex (mXST- 00, -80, 14) and Left Cerebellum (LCer- -30, -60, -30).

We used these five sets of co-ordinates as a guide in our spatio-temporal source-analysis,

seeding dipoles in these regions when fitting data over time epochs during which we had


hypothesized that activity was being generated in these areas. The stability of a given dipole

location was tested by also allowing each dipole in turn to freely fit the data. Where one of these

“seeded” dipoles did not sufficiently explain the data, we employed additional dipoles that were

freely fit to the data. By this combination of approaches (both solving the forward and inverse

problem), we arrived at a solution that employed seven dipoles, including the five from the list

and 2 additional dipoles.

The source solution is shown in Figure 6 and the dipole locations and orientations are listed

in Table 1. The following section details the exact strategy, step by step, that was taken to arrive

at this solution:

1) A dipole was fixed in the coordinates of RLOC and allowed to fit the data in the initial 10

msec period of the effect (172-182 msec). This dipole accounted for 57.9% of the

variance in the data for this epoch. Note that allowing the dipole to freely fit the data in

this period resulted in a dipole that went more medially and superiorly into the medial

occipital cortex (-7, -87, 24). This freely fit dipole resulted in no real improvement in fit

with essentially the identical percentage of the variance explained (58.1%). The dipole

was therefore fixed in the RLOC and its orientation was also fixed (see Table 1).

2) A second dipole was fixed in the RIPP location. The fitting period was extended for

another 10 msec (172-192) and the dipole orientation was allowed to freely fit the data.

This resulted in an explained variance of 63.1% over the 20 msec epoch. Again, we

allowed this dipole to freely fit as a test. This caused the dipole to move to a more

inferior and medial location in the region of the right superior occipital gyrus (32, -84,

29) with an improvement in explained variance to 69.1%. This was a clear improvement

in the proportion of explained variance, suggesting that there was significant activity in


the region of the right superior occipital / occipito-temporal region that needed to be

explained in this early period. We therefore fixed this second dipole in the freely fit

location in the right superior occipital gyrus (RSOG).

3) We added a third dipole, again fixing its location in the RIPP, and allowed it to fit for

orientation over the 172-192 msec epoch. Explained variance improved to 73.8%.

Allowing this dipole to freely fit for location and orientation resulted in only a very slight

change in location (<1 cm) and no improvement in explained variance. We therefore

fixed the dipole in the RIPP cords defined above. We tested the stability of the fit so far

by allowing dipole #2 to freely fit this epoch again. This resulted in no change in the

dipole’s position or orientation, indicative of a relatively stable fit.

4) We added a fourth freely fitting dipole and extended the analysis window out to 202

msec (a 30 msec epoch). This resulted in a second dipole in the region of the superior

occipital gyrus / middle temporal gyrus (49, -82, 22) that was more lateral than dipole #2

above. Explained variance for the 30 msec epoch was 71.0%.

5) The proximity of this dipole to dipole #2 suggested that these two dipoles might be trying

to explain the same data. We tested this by turning off dipole #2 and allowing #4 to freely

fit over this 30 msec epoch. This resulted in a dipole that moved slightly more medially

between the two previous dipole locations (45, -85, 25). The explained variance was

71.5%. Clearly, only a single dipole in the RSOG was required. Therefore, we fixed the

location and orientation of this latter dipole.

6) We then added a dipole in the RSPP and again extended the epoch by 10 msec to 212

msec. The reader will note that during this latter 10 msec period, the focus over superior

parietal scalp has begun to emerge strongly, as detailed in the topographic analysis above.


Addition of this dipole resulted in an explained variance of 76.8% over the 40 msec

epoch (172-212). It is noteworthy that at the end of the epoch, explained variance was

83.5% (212 msec). Allowing this dipole to freely fit resulted in only a very slight change

of location, indicating that its location in RSPP was a relatively stable fit, so the dipole

was fixed in the coordinates defined above.

7) We next added both a medial striate and left cerebellar dipole and extended the fitting

window to 50 msec (172-222 msec), allowing the orientations of these two dipoles to fit

the data. These six dipoles resulted in an explained variance of 81.7% over the epoch

with a best fit at the last point (222 msec) of 93.0%. We fixed these latter two dipoles

orientations.

8) We then opened up the epoch across the duration of the entire effect (172 – 400 msec)

and allowed these six dipoles to fit the data. This resulted in an average explained

variance of 92.0% over this 228 msec epoch (see Fig 7B). It is of note that during the

period when the effect was of largest amplitude 220-320 msec (i.e. highest signal-to-

noise in our data), the averaged explained variance was ~97.5%.

9) Finally, it is clear from the topographic data that there is activity over the left hemisphere

that is unlikely to be simply a result of volume conduction from right hemisphere

activations. Left hemisphere activations are also seen in the fMRI data although the exact

loci across studies are not consistent (except for the left cerebellum). We added a left

hemisphere inferior posterior parietal dipole (-38, -42, 40) and fit it to a window from

200 to 260 msec. These coordinates were taken from Fink et al. (2001). It was during this

epoch that the strongest activity over left scalp was observed electrophysiologically. We

then fixed its orientation and opened the epoch up to the entire window (172-400 msec)


and refit the data with these seven dipoles. Explained variance across the entire epoch

was only marginally improved to 92.4%.

Insert Figure 6 Here and Table 1 about here

It is noteworthy that Fink and colleagues also find consistent activation of right frontal

regions including orbito-frontal cortex and the right dorsolateral prefrontal cortex. In our study,

we also see foci of electrical activity over frontal regions but these activations occur relatively

late in time, mostly after the posterior parieto-occipital line-bisection effect is over. These frontal

effects are not treated further in the present data analysis.

It is important to emphasize that the fMRI activations seen in previous studies, and which

we have used to guide this source analysis, cannot be though of as discrete activations of

individual brain regions. Rather, as can be seen in Figure 7, many of these activation clusters are

much larger than a single cortical area and are likely to represent the activity of a cluster of

functional areas. The same is certainly the case for the electrophysiological results reported in

the present manuscript, where a given scalp topography almost certainly represents coordinated

activity within a cluster of functionally related areas. For instance the lateral occipital cortex

contains a cluster of subregions and it would be incorrect to think of the initial phase of the line-

bisection effect as representing activity in just a single one of these. As such, fitting each cluster

or time-epoch with a single equivalent current dipole clearly represents a highly over simplified

model of activity within a given cluster of areas. As such, it is important that the reader should

consider these dipoles to represent a “center-of gravity” rather than a discrete neural locus or a

single neural event.


DISCUSSION

The current findings explicate the brain mechanisms underlying performance of the visual

line-bisection task, a perceptual version of the perceptual-motor task that is frequently employed

in the clinic to disclose the presence and severity of visuospatial neglect syndrome. We define an

electrophysiological correlate of line-bisection judgments, which manifests as a right parieto-

occipital negative potential that is significantly earlier in latency and larger in magnitude than

that over left scalp. This net negative potential change is seen to persist over a latency window

from approximately 170-400 ms post stimulus, and consists of three distinct phases that can be

discerned through topographic mapping. Dominating the earliest phase of the response

(~165-190 ms) is a negative focus concentrated over the right lateral parieto-occipital scalp. In

this early phase, the effect appears to be largely if not entirely unilateral with no differences seen

over the left hemisphere. In the second phase (190-240 ms), a distinct additional negative focus

develops over more superior right central-parietal scalp, during which the right parieto-occipital

focus persists. In the final phase, as the point of maximal amplitude effect is approached (~310

ms), the topographic pattern becomes dominated by this second focus over right central-parietal

scalp. We refer to this net negative difference as the line-bisection effect.

The Intracranial Generators of the Line-Bisection Effect:

Recent fMRI investigations using very similar experimental paradigms to ours have detailed

a network of brain areas that are activated during line-bisection judgments (see e.g. Fink et al.,

2000a, 2000b, 2001). Figure 7, which is adapted from work by Fink and colleagues (Fink et al.,

2001), illustrates the regional distribution of the activated regions during a line-bisection task,

and clearly shows the involvement of right inferior and superior parietal cortices, in addition to

earlier visual areas, frontal regions and regions in the cerebellum. Our topographic results


(Figure 3) appear to be in good agreement with these findings and provide the critical temporal

activation pattern across these regions. Although topographic mapping of the ERP alone permits

only relatively crude spatial localization in terms of the intracranial generators responsible for a

given scalp topography, observation of the correspondence between the fMRI results of Fink et

al. (2001) and the present data allows for a degree of added confidence in such interpretations.

Clearly, the scalp topography of the earliest phase of the line-bisection effect suggests that

regions in the right lateral occipital cortex and the right temporo-parietal-occipital junction (TPJ)

are the likeliest generators, rather than parietal areas. Indeed, previous fMRI results show an

extended region of robust activation in these more inferior right occipital regions (e.g. Fink et al.,

2001). In turn, the second phase of the line-bisection effect, during which a strong focus develops

over the right central-parietal scalp, is likely generated in regions of the right superior parietal

cortex, where again, fMRI shows a very strong regional activation.

To further assess the putative intracranial sources of the effect, we conducted a source

analysis to augment our topographic mapping data. A stable fit that accounted for more than 90%

of the variance contained in the data was found, which included generators in right lateral

occipital cortex, right superior occipital gyrus, right lateral inferior posterior parietal cortex and

right lateral superior posterior parietal cortex. Additional generators were modeled in medial

occipital cortex, the left cerebellum and left lateral inferior parietal cortex. The latter dipole in

left inferior parietal cortex contributed very little to the source solution. To arrive at this

solution, we took advantage of the previous fMRI studies of line-bisection to guide our source

investigation (e.g. Fink et al., 2001). The model shows that dipoles seeded in the major activation

centers previously defined, provide a very stable fit of our data.



It is noteworthy that the earliest phase of the line-bisection effect we describe here has a

somewhat more inferior distribution than might be predicted for a generator in the inferior

parietal lobule and may be more consistent with a primary generator in superior occipito-

temporal or lateral occipital regions of cortex. Source analysis suggested that two dipoles were

needed to account for his early phase, one in right lateral occipital cortex and a second in right

lateral superior occipital gyrus, directly adjacent to the middle temporal gyrus. Karnath (2001)

has recently suggested that the rostral portion of the superior temporal cortex, just inferior to the

temporo-parietal junction, is the principal region involved in spatial awareness and the primary

site of injury in cases of neglect (see also Karnath et al., 2001). Karnath argues that this region

represents the interface between the ventral (object: what) and dorsal (spatial: where) visual

processing streams. Our data appear to accord well with this interpretation, particularly when the

temporal sequence of activations is taken into account. First, we find that there is extensive

visual processing prior to the occurrence of any spatial attention effects, as indexed by the N1

component of the VEP which has been repeatedly implicated as a marker for ventral stream

object processing (e.g., Allison et al., 1999; Doniger et al., 2000, 2001; Murray et al., 2002).

The onset of the initial phase of the line-bisection effect is seen to follow the peak of the N1 and

appears to be generated in and around the right lateral occipital region and the right superior

occipital gyrus, which is relatively close to the TPJ. As Karnath notes, the TPJ is ideally situated

at the junction between the two visual processing streams. Subsequently, the effect appears to be

transmitted into inferior parietal and then more superior parietal areas of the dorsal stream,

potentially for further spatial processing. A strong prediction based on the present results is that

object recognition processes, as indexed by the N1 component, should be relatively intact in

neglect patients but that the essential link or relay between initial object-based processing


(accomplished within the ventral stream) and subsequent visuo-spatial processing (subserved by

the dorsal stream) is selectively impaired.

The observation that lesions to the superior temporal cortices appear to be the primary

culprits in spatial neglect syndrome (Karnath, 2001), raises questions regarding the functional

role played by superior parietal regions during performance of the line-bisection task. Clearly

superior parietal areas are involved in the processing demanded for line-bisection judgments as

represented by the late phase of the line-bisection effect over superior parietal scalp seen here,

and based on results from the many hemodynamic imaging studies of line-bisection (e.g. Fink et

al., 2000a; 2001). One possible explanation might be that the initial phase of the line-bisection

effect over TPJ represents a necessary but insufficient component of the task whereas the

subsequent processing in more superior parietal regions represents more refined processes

critical to the accuracy of judgments but not necessary for the performance of the task per se.

Such a sequence might help to explain the sometimes confusing and contradictory findings

regarding the multiple areas of right parietal and/or temporal cortex which appear to result in

neglect when lesioned (e.g. Vallar and Perani, 1986; Vallar, 2001).

Attempts to dissociate the relative contributions of inferior and superior parietal regions to

the processes of visuo-spatial attention have been made (Corbetta et al., 2000). Using fMRI,

Corbetta and colleagues conducted a typical visuo-spatial ‘cueing’ experiment, whereby

centrally presented arrows cued subjects to the likeliest location for a subsequent target stimulus,

which was then presented to either the left or right of fixation. They found that the right

temporo-parietal junction (TPJ) was primarily activated when visual attention was reoriented to

the occurrence of a target stimulus and that this activation was greater to targets that occurred in

the uncued region of space. Thus, they interpreted this finding as evidence that TPJ was


involved in the re-orienting of spatial attention when attention was captured − commonly known

as exogenous attention in the literature. Importantly, the TPJ was not found to be active in

response to the cue stimulus that oriented subjects’ attention to the subsequent targets, arguing

that TPJ was not involved in the voluntary orienting of attention (so-called endogenous

attention). On the other hand, they found that the intraparietal sulcus (IPS) and superior parietal

regions were involved in the voluntary directing and maintenance of attention, showing sustained

activation to the endogenous cues used to direct attention. This latter finding accords well with

recent electrophysiological studies of endogenous attention mechanisms, which showed

involvement of right parietal regions in the anticipatory biasing of visuo-spatial attention in

somewhat similar cue-target designs (Foxe et al., 1998; Worden et al., 2000; Fu et al., 2001).

However, on initial consideration, the present findings do not appear to accord well with the

findings of Corbetta and colleagues. Here we find that the first and putatively most critical

modulation of the ERP, due to the spatial attention required for the line-bisection task, appears to

occur in the region of the right lateral occipital cortex and the right TPJ. Clearly, in this task,

attention is not being captured by the stimulus. Rather, this task involves the

voluntary/endogenous orienting of spatial attention to an object (the line). However, the

apparent discrepancy between these results may have to do with the large differences in

experimental paradigm. One clear difference between the current task and the kinds of tasks that

are typically used to investigate visuo-spatial attention is that here, spatial attention is being

directed to an object, whereas in the Corbetta study, spatial attention was being directed to a

portion of space. Thus, regions of TPJ may become involved when spatial attention is

voluntarily oriented to an object. In support, Karnath (2001) argues that the rostral superior

temporal gyrus, by virtue of inputs from both the dorsal and ventral stream, may be involved in


both spatial orienting and in the analysis of objects in space. By this reasoning, both the findings

of Corbetta et al. (2000) and the present findings are consonant with activity in the TPJ. Of

course, given the spatial uncertainty regarding the exact generator locus of the early line-

bisection effect from ERP topographic mapping alone, an alternate explanation may be that sub-

regions in and around the temporo-parietal junction serve different roles and that the region in

TPJ that is active during exogenous attention in the Corbetta et al. (2000) study is not the same

region that is activated in the present study.

Magnocellular and parvocellular involvement in spatial attention

Arising in the retina, and projecting centrally into temporal and parietal cortical regions, the

primate visual system is comprised of two principal neural pathways, the parvocellular (P) and

magnocellular (M) processing streams (Shapley & Perry, 1986). The M stream has a predominant

dorsal projection to areas V2, V3, V4, MT, MST and area 7a in posterior parietal cortex. The P

stream courses ventrally to areas V2, VP, V4 and to regions of inferotemporal cortex (DeYoe &

Van Essen, 1988; Webster & Ungerleider, 1998). Cells in the M pathway possess high contrast

sensitivity, and demonstrate early response saturation; cells of the P pathway are far less sensitive,

and respond in a graded fashion even to high contrast stimuli (Kaplan & Shapley, 1982; 1986).

Neuronal contrast response functions are well described by the Michaelis-Menten equation, where

C50 represents the stimulus contrast producing half-maximal response (the semi-saturation constant).

Primate P and M LGN neurons possess median values of C50 of 0.50 and 0.11, respectively; for cells

in primary visual cortex (V1), which receive both M and P input, this value is 0.33, and for area MT

it is 0.07 (Sclar et al., 1990).

It is presently unknown to what extent visuospatial attentional mechanisms depend

differentially upon M and P pathway input. Relevant is evidence that VEP's to luminance


contrast in the neglected hemifield of neglect patients are delayed compared to the non-neglected

hemifield. The delay is exacerbated at lower luminance contrasts, and no latency differences are

observed for isoluminant chromatic stimuli (Spinelli et al., 1994; 1996). These findings have

been interpreted to suggest that neglect may, at least in part, result from a selective impairment

of M stream input to parietal cortical regions. Anatomical evidence also indicates that the

parietal cortex receives rich input from the M stream, supported by recent functional

neuroimaging evidence in humans (Tootell et al., 1995a;b) that neurons in dorsal V3 are

activated at low stimulus contrasts. Area V3, in turn, receives M stream input from layer 4B of

V1 and from the "thick stripes" of V2, and has reciprocal connections with other regions

innervated by the M stream, such as parietal cortex and V5 (Shipp et al., 1994; Zeki & Shipp,

1988; Webster & Ungerleider, 1998).

The present behavioral results, as well as those of a more extensive study involving 59

observers (McCourt, unpublished results), reveal that leftward error (pseudoneglect) on the line-

bisection task is remarkably stable as a function of stimulus contrast over the range of 1.5-100%,

which readily encompasses the transition from M to P stream function. It is clear from these data

that parvocellular inputs do not appear to be a necessary component for successful performance

of the line-bisection task, as at contrast levels below about 8% there is little or no parvocellular

input (Tootell et al., 1988). The current electrophysiological data provide similar evidence

against a major role for parvocellular inputs as at the 3% contrast level, a robust line-bisection

effect is observed and this effect has highly similar morphology to the effects seen for the 25%

and 100% contrast conditions. The line-bisection effect at 3% contrast persists despite large

effects upon P1 amplitude and N1 latency due to the contrast manipulation. Rather, the primary


effect of the contrast manipulation upon the line-bisection effect was simply to delay its onset,

which will be discussed in the next section.

Confluence of object-based and space-based attentional processing

While the most prominent omnibus symptom of neglect syndrome is simply left inattention,

the existence of numerous subtypes of neglect has become increasingly clear, dissociated along

the dimensions of near (peripersonal) versus far (extrapersonal) space (Halligan and Marshall,

1991; Vuilleumier et al., 1998; Cowey et al., 1994; Tegner & Levander, 1991b), perceptual

versus motor origin (Bisiach et al., 1990; Tegner & Levander, 1991a), and referenced to

egocentric (self-centered) versus allocentric (object-based) spatial coordinate systems

(Behrmann, 1999; Driver & Pouget, 2000; Walker, 1995). Similar distinctions have been made

with respect to pseudoneglect, where the degree of leftward error on line-bisection tasks is

influenced by motor activity (McCourt et al., 2001a), viewing distance (McCourt et al., 2001b)

and object geometry (McCourt & Jewell, 1999; McCourt et al., 2001c). Our results are

particularly interesting with respect to the distinction between egocentric and allocentric

attention. Note that spatial judgments of line midpoint in a bisection task necessarily involve

computing the spatial location of a specific feature (the transector) with respect to features of an

object (the line itself), and thus explicitly invokes object-based attention. Our

electrophysiological results speak to this issue.

Perhaps the best-known effect of selective visuo-spatial attention upon the ERP is the oft-

reported modulation of the P1 component, which is observed when attention is directed to a

specific portion of the visual field while other parts of visual space are ignored (e.g. Van Hoorhis

and Hillyard, 1977; Martinez et al., 1999; 2001). This spatial attention effect occurs relatively

early in visual processing (typically in the 70-130 ms latency range) and is an example of the


case where attention is being apportioned in an egocentric spatial coordinate system. Clearly, the

present findings are wholly different in that the latency of the line-bisection effect is late (post N1

at 170 ms). Moreover, its latency tracks with that of N1 (not P1), as a function of decreasing line

contrast. The timecourse of N1 has been shown to be a marker for ventral stream processing (e.g.

Allison et al., 1999; Doniger et al., 2001), and as such, the relationship of N1 peak latency and

the onset of the line-bisection effect suggests that the effect is linked to the timing of object

processing in the visual system. Object-based attention must have a substrate upon which to act,

that is, an object, and the synthesis of coherent objects from visual primitives such as blobs,

lines and edges is associated with processing in the ventral pathway (e.g. Gross et al., 1992; Sary

et al., 1993; Janssen et al., 2001). Attention that is referenced to particular objects must therefore

receive input from the ventral stream and this is what is meant by allocentric spatial attention.

Thus, in the present study, the line itself (especially its endpoints) must first be encoded; spatial

attention is only subsequently engaged upon the object to determine the location of the transector

in relation to the object’s midpoint. Compellingly, several recent studies have revealed that, in

the absence of an "object" upon which to operate, the severity of both neglect (Vuilleumier &

Landis, 1998) and pseudoneglect are reduced (Post et al, 2001). Thus, it would appear that

neglect might be more severe during allocentric spatial attention. These findings are consistent

with the notion of the superior temporal gyrus as an interface between object processing and

spatial processing streams, as posited by Karnath (2001).

While our contrast manipulation succeeded in its goal of systematically lengthening peak N1

latency, especially at the lowest contrast level used (3%), it is worth emphasizing that the

amplitude of N1 appears to behave quite differently from that of P1 in response to this

manipulation. The P1 gets consistently smaller as the contrast is dropped, especially between the


25% and 3% levels, whereas the N1 maintains its amplitude across the three contrast levels. It is

perhaps surprising that the N1 shows such preserved amplitude at the 3% contrast level given

that N1 has been often taken to predominantly represent processing within ventral visual stream

structures (e.g. Doniger et al., 2000, 2001; Murray et al., in press). Clearly, these results show

that while the timing of N1 is affected, the amplitude of N1 is largely unaffected when

stimulation is biased towards magnocellular input. The relative independence of P1 and N1

amplitudes suggests that N1 generation does not depend causally on inputs from the generators

of the earlier P1 component and that the processes represented by the N1 component can be

successfully initiated through magnocellular inputs. Further investigation is clearly necessary to

delineate the relative contributions of magnocellular and parvocellular inputs to the componentry

of the VEP (see also Foxe et al., 2001; Butler et al., 2001).

Relation of ERP timecourse to TMS derived estimates

While fMRI studies have provided strong evidence that activation of right parietal

regions accompanies tasks requiring spatial attention (e.g., line-bisection tasks), and whereas the

present study using high-density topographical ERP methods has verified the involvement of

right parietal and temporo-parietal-occipital regions, including the temporal dynamics of their

activation, neither fMRI nor ERP techniques actually establish a causal relationship between

neural activity and behavioral performance. In this regard a useful adjunct technique is

transcranial magnetic stimulation (TMS), in which briefly generated magnetic fields transiently

disrupt neural activity in target cortical regions. The deficits in behavior produced by TMS can

be causally related to the disruption of normal activity within the networks of stimulated brain

regions. Strong evidence that right parietal regions are essential for spatial attention comes from

the finding that rapid-rate TMS over these regions attenuates the allocation of attention into left


hemispace, producing visual extinction similar to that in neglect patients (Pascual-Leone et al.,

1994; Fierro et al., 2000). More recently a study using single-pulse TMS over right posterior

parietal cortex (electrode site P6) reported significant rightward deviation of line midpoint

judgments in a line-bisection task (i.e., neglect-like behavior) when pulses were delivered 150

ms post stimulus (Fierro et al., 2001). This value agrees very well with the observed timecourse

of initial right parietal activation as revealed in the present ERP study, and the optimal

stimulation location over site P6 is highly similar to the observed center of the initial negative

focus of the line-bisection effect.

One potentially informative direction for a future TMS study would be to selectively

interrupt the early (parieto-occipital) and later (superior-parietal) phases of the line-bisection

effect to attempt to dissociate and identify the separate contributions of these two distinct regions

to line-bisection judgments. Mapping both the exact timing and topography of these information

processing phases on a subject-by-subject basis could further enhance the specificity of this

method, as some degree of temporal and topographic variation was observed between subjects in

the current sample.

Clinical utility of ERP measures of the ‘Line-Bisection Effect’

One problematic issue surrounding the use of standard line-bisection tasks to define spatial

neglect syndrome is that motor responses are often required from the patient, such as asking

them to draw bisectors with a pencil through lines on a page, or to point to the longer/shorter end

of a displayed line. Critically, there are often significant motor deficits in patients with lesions

that involve frontal cortex and also visual cortices, and this can be a confounding factor in results

of the line-bisection task that involve such overt responses (see e.g. Darling et al., 2001). That

is, systematic bisection errors by a motor-compromised patient could reflect an inability or


reluctance to move the drawing or pointing hand in the necessary direction for correct

judgments. The presence of a highly robust ERP effect over right occipito-parietal areas may

provide a simple means for assessing integrity of function in patients without the necessity for

overt motor or even verbal responses.

Summary

In conclusion, the current study reveals a robust negative potential over the right lateral

occipito-parietal and right central-parietal scalp that indexes the neural processing involved in

performance of the ‘line-bisection’ task. Through high-density topographic mapping, we detail

the spatio-temporal dynamics of this processing on the scalp surface. The observed topographies

are consistent with recent hemodynamic imaging studies that have suggested a prominent role

for regions in and around the right temporo-parietal junction and regions of the right superior

parietal cortices in this task. Source analysis confirmed the involvement of these areas as well as

early involvement of right lateral occipital cortices. The present data provide the critical temporal

activation pattern across these regions and underscore the importance of defining the temporal

patterns of attentional modulation, which will be critical to our understanding of the mechanisms

of attentional control in the human brain (e.g. Schroeder et al., 2001).


ACKNOWLEDGEMENTS

We express our sincere appreciation to Deirdre Foxe, Beth Higgins and Dr. Micah Murray

for their technical help with this study. We are most grateful to Dr. Gereon Fink and his

colleagues for generously allowing us to reproduce their fMRI data in the current report. Dr.

Antigona Martinez provided valuable comments on an earlier version of the manuscript for

which we are indebted to her. Our thanks also go to two anonymous reviewers for their careful

and constructive comments. This work was supported in part by grants from the National

Institute of Mental Health (MH63434 – JJF; MH49334 – DCJ), the National Eye Institute

(EY12267 – MEM), North Dakota EPSCoR (MEM), the Neuropsychiatric Research Institute,

Fargo, ND (MEM), the North Dakota State University Development Foundation (MEM), and by

generous support from the Burroughs Wellcome Fund.


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FIGURE CAPTIONS

Figure 1. Line Stimuli Used in the Experiment. Both members of the upper pair of lines (A,

B) possess 100% contrast, and are transected to the left of center, by −0.33o (−2.17%) and −0.60o

(−3.91%), respectively. Both members of the lower pair of lines (E, F) possess 3% contrast and

are transected to the right of center, by +0.47o (3.04%) and +0.17o (1.09%), respectively. Lines C

and D possess 25% contrast; C is veridically transected and line D lacks a transector. Pairs (A,

B) and (E, F) differ in contrast polarity. Lines of varying contrast and contrast polarity appeared

with equal frequency. The order of appearance of all line types was quasi-randomized within

blocks of trials.

Figure 2. Behavioral Data. Group-averaged psychometric functions obtained in the Line

Bisection condition at each level of line contrast. Open symbols plot mean percent “left”

responses (±1 s.e.m.) against transector location (in degrees relative to veridical line midpoint).

Solid lines depict cumulative Gaussian distributions fitted to the data by nonlinear least-squares

regression. The horizontal dashed line in each panel indicates the 50% “left” response rate; the

transector location for which the cumulative Gaussian intersects the dashed line is one measure

of perceived line midpoint (pse).

The solid symbols (and vertical dotted lines) in each panel plot mean pse (±1 s.e.m.) based

on the analysis of psychometric functions from individual observers. The agreement with pse

estimates from the group-averaged fits is excellent, and reveals the systematic leftward error

(pseudoneglect) in perceived line midpoint that typifies the performance of neurologically normal

right-handed observers.

Figure 3. Sustained Negative Modulation during Line-Bisection Task. The 128-channel

electrode montage is shown here projected onto a three-dimensional scalp-reconstruction (from


structural MRI data) of one of the subjects (BH). Group-averaged (n=9) ERP voltage waveforms

are plotted for two electrode sites (darkened in Montage display), showing the marked negative

deflection when subjects performed the line-bisection task (solid trace) relative to the control

task (dashed trace). The bottom two panels show the p-values (pointwise 2-tailed t-test

comparisons between conditions), illustrating the timecourse of significant differences at these

electrode sites.

Figure 4. Topographic Mapping of the Line-Bisection Effect. Group-averaged (n=9)

potential maps are shown for three timepoints during the three phases of the 'line-bisection'

effect. These topographies are derived from the difference waves, obtained by subtracting the

control-condition from the line-bisection condition. Surface negativity is depicted in blue/cyan

and positivity in red/yellow. The first phase of the effect (top maps ~176 ms) shows a highly

lateralized negative focus over right temporo-parietal scalp. During the second phase (middle

maps ~220 ms), at least two distinct negative foci are evident with the emergence of a strong

central parietal negative focus. During the third phase, the time-period of the largest effect

(bottom maps ~310 ms), the topography is dominated by a right central parietal negativity.

Figure 5. Three levels of contrast. Group-averaged (n=9) voltage waveforms are shown for the

three levels of display contrast used (same parieto-occipital scalp site as shown in figure 3). The

line-bisection effect can be seen at each level. As N1 latency increases with decreasing contrast,

the line-bisection effect moves systematically with this N1 latency shift.

Figure 6. Source analysis of the Line-Bisection Effect. A). The locations of the seven dipoles

used to model the line-bisection effect are shown projected into a 3D rendering of an averaged

human brain. Each dipole location is color-coded. B). The amount of variance explained in the

data by these seven dipoles across the 172-400 msec epoch of the effect. C). Waveforms


depicting the source strength of each dipole are plotted for the 172-400 msec epoch (same color

convention as used in A).

Figure 7. fMRI Activation During the Line-Bisection Task. Comparison of the fMRI

activations seen here with the scalp-topography of the line-bisection effect shown in figure 4

shows strong correspondence between the electrophysiological and hemodynamic data sets.

(adapted with permission from Fink et al. 2001. The neural basis of vertical and horizontal line

bisection judgments: An fMRI study of normal volunteers. Neuroimage 14: S59-67.) Areas of

significant activation are shown projected into standard stereotactic space in a sagittal, coronal

and axial view (from left to right).

TABLE CAPTION

Table 1. Talairach coordinates and orientations are given for each dipole.


Appendix:

Readers are encouraged to visit the NeuroImage website at the following URL to

download the animation file which accompanies the present report

http//academicpress.com/ni/linebisection.avi ???

This animation shows the evolution of the "line-bisection effect" at a rate approximately 100

times slower than real time. It begins with a display of the 128-channel montage as the 3D rendered head

rotates before settling with a view of the scalp from directly behind the head. The electrodes then

disappear before the topographic maps begin. The counter at the bottom right corner of the panel shows

time in milliseconds and the animation of topography begins at 0 ms which is when the stimulus

appeared. The group-averaged data have been projected onto a 3D-rendered scalp surface. Recall that the

line-bisection effect is derived by subtracting the control condition from the experimental condition and

therefore, all activity associated with the common sensory processing of these stimuli has been eliminated

from the data. Therefore, it can be seen that for the first 150 ms, there is no activity that exceeds noise.

The following is a description of the evolution of the effect, which may help to orient the reader

as they observe the animation.

- At about 160 ms, a negative focus over right parieto-occipital scalp is seen to emerge and build

rapidly in amplitude. By 172 ms (the point at which the effect reaches statistical significance)

the negativity is clearly discernable. This right parieto-occipital negativity continues to build

in amplitude up until ~200-210 ms.

- At approximately 188 ms, the initial right parieto-occipital negativity appears to extend

dorsally and centrally over mid-parietal scalp and this extension of the negativity quickly

develops into a second distinct focus by approximately 206-212 ms.

- By 210 ms, a third negative limb begins to be apparent over the left parieto-occipital

scalp although this left scalp negativity never becomes fully distinct from the two right

foci.


- At 224 ms, the right parieto-occipital focus begins to decrease in amplitude and the

topography becomes dominated by the central parietal negativity. This continues until

approximately 260 ms when the right parieto-occipital focus begins to increase its

amplitude for a second time.

- Between 260 and ~340 ms, this pattern is essentially maintained. However, the reader

will notice that both the right parieto-occipital and central parietal foci appear to wax

and wane somewhat independently during this period. While it is impossible to

determine at this stage what these dynamics represent functionally, we would speculate

that these modulations are likely to represent successive rounds of activation within

functionally distinct modules of the spatial attention network, and perhaps

communication between two distinct centers of the network.

- By 340 ms, the negativity becomes concentrated over central parietal scalp and the

bilateral parieto-occipital foci are diminishing in amplitude. By 400 ms, the effect is

essentially over.

Note that the reader may find it useful to use the manual advance option on their media player to

control the progression of the animation in order to get a better look at the topographic transition

points detailed above.

Foxe et al (in press)

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