The Role of Human Motion Processing Complex, MT+, During Sustained Perception and Attention

The role of human motion processing complex, MT+, during sustained perception and attention

Author: Preston P. Thakral

Persistent link: http://hdl.handle.net/2345/2745

This work is posted on eScholarship@BC, Boston College University Libraries.

Boston College Electronic Thesis or Dissertation, 2012

Boston College

The Graduate School of Arts and Sciences

Department of Psychology

THE ROLE OF HUMAN MOTION PROCESSING COMPLEX, MT+, DURING

SUSTAINED PERCEPTION AND ATTENTION

a dissertation

PRESTON P. THAKRAL

submitted in partial fulfillment of the requirements

for the degree of

Doctor of Philosophy

August 2012

The role of human motion processing complex, MT+,

during sustained perception and attention

Preston P. Thakral

Advisor: Scott D. Slotnick

Abstract

The overarching aim of this dissertation is to examine the role of human motion processing complex, MT+ during sustained perception and attention. MT+ is comprised of sub-region MT, which processes motion in the contralateral visual field (i.e., left hemisphere MT processes motion in the right visual field and vice versa), and sub- region MST, which processes motion in both the contralateral and ipsilateral visual fields. Whereas previous transcranial magnetic stimulation (TMS) research has provided compelling evidence that region MT+ is necessary for low-level motion processing, Chapter 1 describes an experiment testing whether the sub-region MT is necessary for contralateral low-level motion processing. Chapter 2 describes an experiment that dissociates low-level sensory attentional modulation in MT+ from high- level attentional control processing in the parietal cortex (i.e., during sustained attention). Chapter 3 describes an experiment investigating the role of MT+ during aesthetic processing when viewing visual art. Importantly, this experiment tests whether the aesthetic is tied to not only low-level motion processing in MT+ but also high-level processing in frontal regions. Taken together, the results across the three experiments provide novel evidence for the role of MT+ during low-level motion processing during sustained perception and attention. Moreover, these low-level motion processing effects

together with the observed high-level processes in frontal-parietal regions provide neural mechanisms for the cognitive processes of sustained perception and attention.

TABLE OF CONTENTS

Introduction ...... 1

References ...... 5

Chapter 1: Disruption of MT impairs motion processing ...... 11

Experiment 1

Methods ...... 14

Participants ...... 14

Localization of MT ...... 14

TMS Neuronavigation ...... 17

Stimuli and Tasks ...... 18

Results ...... 19

Experiment 2

Methods ...... 20

Participants ...... 21

Stimuli and Tasks ...... 21

Results ...... 23

Discussion ...... 24

References ...... 27

Chapter 2: The role of the parietal cortex during sustained visual spatial attention ...... 35

Methods ...... 39

Participants ...... 39

Stimuli and Tasks ...... 39 ii

fMRI Acquisition and Data Analysis ...... 40

Results ...... 44

Sustained attention MT+ effects ...... 44

Sustained attention control regions ...... 47

Discussion ...... 51

References ...... 57

Chapter 3: A neural mechanism for aesthetic experience ...... 68

Methods ...... 71

Participants ...... 71

Stimuli and Tasks ...... 71

fMRI Acquisition and Data Analysis ...... 72

Results ...... 74

Motion Experience ...... 74

Pleasantness Experience ...... 75

Degree of Motion Experience ...... 76

Discussion ...... 77

References ...... 81

Discussion ...... 86

References ...... 89

iii

Acknowledgements

I would like to thank the members of my committee, Hiram Brownell, Sean

MacEvoy, Marilee Ogren, and Gorica Petrovich. Of utmost importance, I am eternally grateful to one of the most amazing people in my life, Scott Slotnick, who will always be my friend, personal mentor, and scientific leader. I would also like to thank my ma, Harjit

Thakral, my sisters, Harjot and Manu Thakral, Lauren and Sonya Moo, and Jenny Wong who are the greatest people in the world and who keep me alive every day. Lastly, I am forever indebted to Howard Stern and Metallica.

Introduction

When decomposing cognitive processes (e.g., attention, memory, or imagery) into their component neural processes, it is commonly assumed that such processes are either of the low-level or high-level nature. Across attention, memory, and imagery, frontal-parietal regions have been shown to be involved in high-level control processes and occipital-temporal regions have been shown to reflect the sensory low-level effects of these high-level processes. For example, during attention, frontal-parietal higher-level regions provide top-down signals that selectively modulate activity in low-level sensory occipital-temporal regions that reflect the enhanced processing of the attended stimulus

(for review see, Desimone and Duncan, 1995; Corbetta & Shulman, 2002; Yantis &

Serences, 2003). Frontal-parietal control activity is observed both transiently when attention is shifted from location to location or from feature to feature (Slotnick & Yantis,

2005; Kelley, Serences, Giesbrecht & Yantis, 2008) or sustained when attention is maintained at a single location or feature for an extended period of time (Thakral &

Slotnick, 2009). The low-level sensory effects of attention are observed in stimulus- specific, feature, and object-based sensory regions. For example, when attending to an item in the left versus right field, an increase in activity is observed in right visual cortex

(and vice-versa, Martinez et al., 1999; Hopfinger, Buonocore, & Mangun, 2000; Slotnick,

Schwarzbach, & Yantis, 2003; Slotnick & Yantis, 2005), when attending to something in color, attentional amplification is observed in color processing region V4/V8 (Chawla,

Rees, & Friston, 1999; Liu, Slotnick, Serences, & Yantis, 2003), and when attending to a face versus a place, attentional modulation is observed in the fusiform versus parahippocampal gyrus, regions selective for face versus place processing, respectively 2

(O’Craven, Downing, & Kanwisher, 1999; Serences, Schwarzbach, Courtney, Golay, &

Yantis, 2004). Critically, the low-level sensory effects, together with the respective high-

level control processes, provide a mechanism by which attention related amplification of

sensory processing enhances behavioral performance for attended stimuli (see,

Desimone & Duncan, 1995).

The same process dissociation holds for the cognitive processes of memory and imagery. During memory and imagery, frontal-parietal regions are involved in high-level control processes such as attending to, selecting, and monitoring successfully retrieved

or imagined information (Buckner, Koutsaal, Schacter, Wagner, & Rosen, 1998;

Slotnick, Moo, Segal, & Hart, 2003; Wheeler & Buckner, 2003; Hayama & Rugg, 2009;

Slotnick, 2009a; Slotnick, Thompson, & Kosslyn, 2005, 2012; for review see, Buckner &

Wheeler, 2001; Buckner, 2003; Hutchinson, Uncapher, & Wagner, 2009). These high-

level control processes stand in contrast to the low-level sensory effects observed in

occipital-temporal cortex. For example, during memory for visual stimuli, reactivation is

observed in visual processing regions (Vaidya, Zhao, Desmond, & Gabrlieli, 2002;

Wheeler & Buckner, 2003, 2004; Slotnick & Schacter, 2004; Slotnick, 2009a), during

memory for sounds, reactivation is observed in auditory processing regions (Nyberg,

Habib, McIntosh, & Tulving, 2000; Wheeler, Petersen, & Buckner, 2000), and memory

for color and motion reactivates color processing region V8 and motion processing

complex MT+, respectively (Slotnick, 2009b; Slotnick & Thakral, 2011). During imagery,

low-level sensory effects are analogous to those observed during memory and

attention, where imagery of visual stimuli can reactivate the corresponding visual location of the perceived stimulus (i.e., imagery of left visual stimuli activates right visual 3

cortex and vice versa, Slotnick et al., 2005; see also, Kosslyn, et al., 1999; for review

see, Kosslyn & Thompson, 2003) and imagining color or motion information reactivates

color and motion processing regions, respectively (Kaas, Weigelt, Roebroeck, Kohler, &

Muckli, 2010; Kosslyn, Thompson, Constanini-Ferrando, Alpert, & Spiegel, 2000).

Again, across both imagery and memory, the low-level sensory processes in occipital-

temporal regions and high-level control processes in frontal-parietal regions work

together as a neural mechanism to construct the imagined and/or remembered sensory stimulus (see, Slotnick, 2004; Slotnick, et al., 2012).

As observed across the three cognitive processes of attention, memory, and imagery, the dichotomization between low-level and high-level component processes provides neural mechanisms for how these cognitive processes work. In this thesis, I present three experiments that extend this low-level versus high-level processing dichotomy to motion processing and provide novel evidence for the role of human motion processing complex, MT+ during sustained perception and attention. MT+ is comprised of sub-region MT, which processes motion in the contralateral visual field

(i.e., left hemisphere MT processes motion in the right visual field and vice versa), and sub-region MST, which processes motion in both the contralateral and ipsilateral visual fields. In Chapter 1, I present an experiment demonstrating the necessity of this region, specifically the sub-region MT, in low-level sensory motion processing using transcranial magnetic stimulation (TMS). In Chapter 2, I capitalize on the known low- level sensory effects of attention that occur in MT+ in order to elucidate the role of the parietal cortex in high-level attentional control processing (i.e., sustaining versus shifting attention). Lastly, in Chapter 3, I provide a novel neural mechanism for aesthetic 4 processing (i.e., an experience of beauty and pleasantness during the perception of visual art) that dissociates low-level sensory processing in MT+ from high-level processing in the prefrontal cortex. Across the three experiments, I hope to provide a clear demonstration of how both low-level motion processing in MT+ and high-level attentional control or aesthetic processing in frontal-parietal regions, despite being distinct, work together to form a neural mechanism during both sustained perception and attention. 5

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Chapter 1

Disruption of MT impairs motion processing

Human motion processing region MT+, which has been localized to the ascending limb of the inferior temporal sulcus (Watson et al., 1993), is comprised of sub-region MT, which processes motion in the contralateral visual field (i.e., left hemisphere MT processes motion in the right visual field and vice versa), and sub- region MST, which processes motion in both the contralateral and ipsilateral visual fields (Dukelow, DeSouza, Culham, van den Berg, Menon, & Vilis, 2001; Huk,

Dougherty, & Heeger, 2002; Goosens, Dukelow, Menon, Vilis, & van den Berg, 2006;

Smith, Wall, Williams, & Singh, 2006; Becker, Erb, & Haarmeier, 2008; Ohlendorf,

Sprenger, Speck, Haller, & Kimmig, 2008; Amano, Wandell, & Dumoulin, 2009). There is also functional magnetic resonance imaging (fMRI) evidence that attention to motion can increase the magnitude of activity in MT+ (Liu, Slotnick, Serences, & Yantis, 2003), and contralateral motion attention effects, presumably reflecting modulation of sub- region MT, have also been reported (Slotnick & Yantis, 2005). It should be noted that sub-region MT can process motion in the ipsilateral visual field to some degree

(Raiguel, Van Hulle, Xiao, Marcar, & Orban, 1995; Tootell, Mendola, Hadjikhani, Liu, &

Dale, 1998); however, this sub-region predominantly processes motion in the contralateral visual field (Dukelow et al., 2001; Huk et al., 2002; Smith et al., 2006;

Goosens et al., 2006; Becker et al., 2008; Ohlendorf et al., 2008; Amano et al., 2009).

The preceding fMRI evidence (Dukelow et al., 2001; Huk et al., 2002; Liu et al.,

2003; Slotnick & Yantis, 2005; Goosens et al., 2006; Smith et al., 2006; Becker et al.,

2008; Ohlendorf et al., 2008; Amano et al., 2009) suggests region MT+, which includes 12 sub-regions MT and MST, is associated with motion processing. However, fMRI is correlational in nature; thus, fMRI activity associated with a given cognitive process may be epiphenomenal (Kosslyn, et al., 1999; Moo, Emerton. & Slotnick, 2008). If a region is necessary for a given cognitive process, its disruption should impair the corresponding behavioral performance. This type of evidence has been reported in previous studies that have used transcranial magnetic stimulation (TMS) to temporarily disrupt MT+ which impaired motion processing. However, the MT+ target locations in these studies have typically been based on fixed distances from non-brain landmarks such as the inion (Beckers & Hömberg, 1992; Beckers & Zeki, 1995; Walsh, Ellison, Batelli, &

Cowey, 1998, Hotson & Anand, 1999) or subjective measures such as the site of TMS induced motion phosphenes (Anand, Olson, & Hotson, 1998; Stewart, Battelli, Walsh, &

Cowey, 1999; Antal, Nitsche, & Paulus, 2003; Silvanto, Lavie, & Walsh, 2005; Ellison,

Lane, & Schenk, 2007; Laycock, Crewther, Fitzgerald, & Crewther, 2007; Harvey,

Braddick, & Cowey, 2010; but see, Thompson, Aaen-Stockdale, Koski, & Hess, 2009).

While such techniques may have localized MT+, they might have also stimulated other adjacent neural regions such as motion sensitive extrastriate region V3A. In four recent fMRI guided TMS studies, motion related fMRI activity within the ascending limb of the inferior temporal sulcus (Watson et al., 1993) was used to specifically target MT+ which impaired motion processing (Sack, Kohler, Linden, Goebel, & Muckli, 2006; McKeefry,

Burton, Vakrou, Barrett, & Morland, 2008; Burton, McKeefry, Barrett, Vakrou, &

Morland, 2009; Stevens, McGraw, Ledgeway, & Schluppeck, 2009; see also, Battelli,

Alvarez, Carlson, & Pascual-Leone, 2008). The latter results provide compelling evidence that region MT+ is necessary for motion processing. 13

The aim of the present study was to use fMRI guided TMS to selectively target sub-region MT, located on the posterior bank of the ascending limb of the inferior temporal sulcus (Dukelow et al., 2001; Huk et al., 2002; Beauchamp, Yasar, Kishan, &

Ro, 2007), to determine whether temporary disruption of this sub-region would be sufficient to produce an impairment in motion processing. As MT is known to predominantly process motion in the contralateral visual field (Dukelow et al., 2001; Huk et al., 2002; Goosens et al., 2006; Smith et al., 2006; Becker et al., 2008; Ohlendorf et al., 2008; Amano et al., 2009), selective disruption of this region should be evidenced by preferentially impaired motion detection in the visual field contralateral to the hemisphere of TMS application. Of relevance, Hotson and Anand (1999) reported impaired motion processing in the contralateral visual field following TMS to putative

MT+; however, color processing was similarly impaired suggesting a more posterior extrastriate region may have been targeted (Hotson & Anand, 1999; see also, Beckers

& Hömberg, 1992). In addition, McKeefry et al. (2008) used fMRI guided TMS to target

MT+ which impaired motion processing in the contralateral visual field, but ipsilateral targets were not presented such that contralateral versus ipsilateral performance could not be evaluated (McKeefry et al., 2008; see also, Beckers & Zeki, 1995; Sack et al.,

2006). Considering these findings, the present study was conducted to test whether

TMS to MT would produce a contralateral motion processing impairment

Experiment 1

Methods

Participants

Ten participants (8 females, age range 19-28 years) from the Boston College community with normal or corrected-to-normal vision took part in the TMS study (only left MT TMS data were acquired for one participant). The TMS and fMRI protocols were approved by the Boston College and Massachusetts General Hospital Institutional

Review Boards, respectively. Informed consent was obtained before each session commenced.

Localization of MT

MRI was conducted using a Siemens 3 Tesla Trio Scanner. Functional images were acquired using an echo-planar imaging sequence (TR = 2 s, TE = 30 ms, 64 x 64 acquisition matrix, 30 axial slices, 4 mm isotropic resolution) and anatomic images were acquired using a magnetization prepared rapid acquisition gradient echo sequence (TR

= 30 ms, TE = 3.3 ms, 128 sagittal slices, 1.33 x 1 x 1 mm resolution). fMRI analysis was conducted using BrainVoyager QX (Brain Innovation B.V., Maastricht, The

Netherlands). Functional image pre-processing included slice-time correction, motion correction, spatial filtering via convolution with a 4 mm full-width-half-maximum

Gaussian smoothing kernel, and high-pass temporal filtering by removal of linear trends and temporal components below 3 cycles per run.

During fMRI participants viewed a full-field (14.5o x 19.3o) stimulus that alternated

between periods of moving dots and stationary dots (Figure 1.1A). Each of 8 moving- 15 stationary cycles lasted 28 s. The stimulus was comprised of 400 dots (0.05o in diameter) that appeared at random locations along the outer edge and then moved toward the central fixation point with 100% coherence and a velocity of 5o per s.

Participants were instructed to maintain central fixation and, during motion periods,

press a button when they detected a brief whole-field slowdown (which occurred twice

per motion period).

An individual participant general linear model analysis was conducted, where

significant motion related activity (p < 0.01) was identified by contrasting periods of

moving dots versus stationary dots (Slotnick & Yantis, 2005) and then projected onto

each participant’s cortical surface representation. For each hemisphere of a given

participant, the precise location of motion processing sub-region MT was identified

using functional, anatomic, and meta-analytic constraints: 1) MT was constrained to be

within the significant motion related activity on the cortical surface, 2) MT was

constrained to be within the posterior bank of the ascending limb of the inferior temporal

sulcus (Dukelow et al., 2001; Huk et al., 2002; Beauchamp et al., 2007), and 3) MT was

constrained to be within the range of motion processing region coordinates produced by

a meta-analysis of the literature (Moo et al., 2008). In each hemisphere, these conjoint

constraints yielded the specific locus of MT that was subsequently targeted during TMS

(Figure 1.1B).

Figure 1.1 (A) The motion localizer stimulus alternated between periods of moving and stationary dots (arrows illustrate movement and were not present during the experiment). (B) fMRI guided neuronavigation. To the left, a representative participant’s head surface and left hemisphere cortical surface with motion related activity (gyri and sulci are shown in light and dark gray, respectively; more significant activity is shown in green). The TMS coil is delineated by two wireframe wheels. TMS was applied to motion processing region MT, marked by the red sphere on the posterior bank of the ascending limb of the inferior temporal sulcus (ITS; magnified MT region is shown to the right with a dotted line tracing the fundus). (C) During the spatial attention protocol, participants shifted attention between moving dots in the left or right hemifield when dots in the attended hemifield briefly increased speed (wide arrow) or pressed a key when dots in the attended hemifield briefly decreased speed, a detect target (narrow arrows; dotted circles illustrate the locus of attention and were not present during the 17

experiment). (D) Percent detection of targets in the ipsilateral (ipsi.) visual field following TMS, contralateral (contra.) visual field following TMS, and no TMS (control) performance separated by hemisphere of TMS stimulation (*p < 0.05, **p < 0.01, ***p < 0.001, ns = not significant) (figure from, Thakral & Slotnick, 2011).

TMS Neuronavigation

The BrainVoyager TMS Neuronavigation System was used for TMS positioning relative to the target location (for details, see Sack et al., 2006; McKeefry et al., 2008;

Stevens et al., 2009). In brief, landmarks on the head and TMS coil were identified in both external space (using a digitizer pen) and BrainVoyager space, and co-registered.

Ultrasound transmitters affixed to the head and TMS coil emitted signals that were picked up by a receiving sensor device in external space to precisely track the location of the TMS coil in relation to the head (and underlying cortical surface) in BrainVoyager space. For a given hemisphere, before TMS commenced, the MT target location was placed on the cortical surface (Figure 1.1B, red sphere within the white square). To temporarily disrupt MT in each hemisphere, a Magstim Rapid2 system with a Double 70

mm Coil (The Magstim Company Ltd., Carmarthenshire, Wales) was used to apply 1-Hz

repetitive TMS at 70% of maximum output for 10 minutes. Of importance, these TMS

parameters (i.e., 1-Hz stimulation for 10 minutes) constitute a standard TMS protocol

that has been shown to impair processing in the targeted cortical region for at least 10

minutes following the offset of stimulation (Kosslyn et al., 1999). The coil was positioned

to be approximately perpendicular to the head surface with minor adjustment to ensure

the TMS beam was focused at the target point (MT) on the posterior bank of the inferior

temporal sulcus. Stimulation of the anterior bank of the inferior temporal sulcus, the

known location of motion processing sub-region MST (Dukelow et al., 2001; Huk et al., 18

2002) was specifically avoided. The TMS cable was oriented posteriorly and downward

45° from horizontal. During TMS, participants made odd/even digit judgments to black digits (ranging from 0-9) presented at fixation on a gray background (each digit was presented for 1 s followed by a 1-10 s fixation period). For each participant, there was a

30 minute break between TMS of each hemisphere. The initial hemisphere of TMS was randomly assigned for each participant and behavioral testing was completed within 7 minutes of TMS offset.

Stimuli and Tasks

The spatial attention stimulus was composed of moving dots within two squares, one in each hemifield, rotated 30° from horizontal (Figure 1.1C). Each square had a 5o edge length with the nearest corner 2o from the central fixation point, and contained 320

dots (0.06 o in diameter) which moved with 70% coherence at a velocity of 6o per s. To

avoid perceptual grouping, dots in the left square moved downward and dots in the right

square moved upward. A brief increase in dot speed within the attended hemifield (i.e.,

a shift target) cued participants to shift attention to the square in the opposite visual field

(and press the corresponding ‘shift’ key) and sustain attention at this new location. A

brief decrease in dot speed within the attended hemifield (i.e., a detect target) cued participants to press the ‘detect’ key. Each participant completed two runs during the

TMS session (i.e., one run following each stimulation period) lasting 145-150 s where dot speed changes occurred at random times every 2-10 s within each hemifield (dot

speed increases or decreases occurred with equal probability; the total number of

possible detect targets was 10.98 ± 0.89 and 12.02 ± 0.81 in the left and right visual 19 field, respectively). Eight of the ten participants also completed two runs with no TMS, which served as a control level of behavioral performance. Percent detection was calculated based on the possible number of detect targets occurring within the attended hemifield. One-tailed t-tests were employed because temporary disruption of MT was expected to preferentially impair detection of targets in the contralateral visual field (only p-values < 0.05 were considered significant).

Results

TMS to left MT produced a significant impairment in detection of targets in the contralateral versus ipsilateral visual field (Figure 1.1D, bars 1, 2; t(9) = 1.86, p < 0.05).

Performance following TMS was compared to no TMS (control) performance to assess whether disruption of left MT impaired contralateral target detection, facilitated ipsilateral target detection, or produced both of these effects. Contralateral target detection following TMS to left MT was significantly lower than no TMS performance (Figure 1.1D, bars 2, 3; t(7) = 2.59, p < 0.05), and ipsilateral target detection following TMS to left MT was also significantly lower than no TMS performance (Figure 1.1D, bars 1, 3; t(7) =

3.36, p < 0.01). Together, these results demonstrate that TMS to left MT impaired contralateral target detection and did not facilitate ipsilateral target detection (which would have been manifested by higher ipsilateral performance following TMS as compared to no TMS performance; the opposite was observed).

TMS to right MT did not produce a significant difference between contralateral versus ipsilateral target detection (Figure 1.1D, bars 4, 5; t(8) < 1), and appeared to produce an impairment in both visual fields as contralateral and ipsilateral performance 20 did not significantly differ from contralateral (impaired) performance following TMS to left

MT (Figure 1.1D, bars 2, 4, 5; F(2,16) < 1). Moreover, no TMS target detection was significantly greater than ipsilateral and contralateral target detection following TMS to right MT (Figure 1.1D, bars 4, 5, 6; t(6) = 2.22, p < 0.05). These results suggest that temporary disruption of right MT produced both a contralateral and ipsilateral impairment in target detection, in contrast to temporary disruption of left MT which produced a preferential impairment in contralateral target detection.

Experiment 2

Methods

The previous experiment used an attention task, where participants shifted attention between hemifields and detected targets in the attended hemifield. Because such tasks involve both focused attention to and perceptual processing of a particular spatial location (Thakral & Slotnick, 2009), it is uncertain whether the preceding contralateral motion effects were due to impaired visual attentional processing or impaired visual perceptual processing. To address this, a motion detection task was employed to determine whether TMS to MT would impair perceptual processing without an explicit attentional component. Moreover, single-pulse TMS was used to test whether a motion processing impairment would be observed using a different TMS protocol, and a color detection task was used to ensure that the effects were specific to motion (as it could be argued that TMS of a more posterior extrastriate region associated with contralateral, but not motion specific, visual processing might have produced the effects in Experiment 1). 21

Participants

Unless otherwise stated, the experimental procedure was identical to Experiment

1. Four participants from the Boston College community with normal or corrected-to- normal vision took part in the study (two had participated in Experiment 1). One participant was excluded due to chance performance, such that three participants were included in the final analysis (1 female, age range 21-39 years). The TMS and fMRI protocols were approved by the Boston College and Massachusetts General Hospital

Institutional Review Boards, respectively. Informed consent was obtained before the experiment commenced.

Stimuli and Tasks

The identical stimulus protocol was used for both a motion detection task and a color detection task (Figure 1.2A). On each trial, an abstract shape with a white outline and either blue or green internal lines was presented to the left or right of fixation and moved briefly up or down, followed by a 1.4 s period of fixation (for a detailed description of shape construction, see Slotnick & Schacter, 2004). Internal line color, spatial location, and movement direction were randomly determined, with the constraint that all conditions occurred equally often in each run. Shapes were never repeated.

Each shape moved vertically across the horizontal meridian, traversing 0.21o with a velocity of 3.4-6.9o per s (velocity was adjusted for each participant such that

performance was approximately 75% correct). After practicing the tasks, each

participant completed one motion detection run and one color detection run during TMS.

In motion detection runs, participants were instructed to maintain central fixation and 22 press one of two buttons to classify each shape as moving up or down (and were instructed to ignore color information). In color detection runs, participants were instructed to maintain central fixation and press one of two buttons to classify each shape as blue or green (and were instructed to ignore motion information).

Figure 1.2 (A) Stimulus for the motion detection and color detection tasks. (B) TMS effect (minimum minus maximum percent correct) for the motion detection task and color detection task (*p < 0.05, **p < 0.01, ***p < 0.001, ns = not significant) (figure from, Thakral & Slotnick, 2011).

For each participant, the MT target location was identified using the same procedure as described in Experiment 1 (although in this experiment, a single hemisphere of stimulation was randomly selected; 1 right hemisphere). TMS was applied at 70% of maximum output using a single-pulse TMS protocol, where on each trial the stimulus computer triggered the TMS system to deliver a pulse at a specific time following stimulus onset (with the aim of disrupting processing in MT at that time). TMS pulses occurred in 17 ms increments within 68-218 or 98-248 ms after stimulus onset, and were time-locked to the vertical refresh rate (60 Hz). Each run consisted of 200 23 trials (20 trials at each of 10 pulse times). Analysis was restricted to 98-201 ms after stimulus offset, the expected time period of impaired motion processing following single- pulse TMS (Laycock et al., 2007), to minimize the contribution of noise in the analysis.

The TMS effect for both tasks was computed as the minimum minus the maximum percent correct (see Figure 1.3). One-tailed t-tests were employed as temporary disruption of MT was expected to preferentially impair detection of motion targets (only p-values < 0.05 were considered significant).

Figure 1.3 Individual participant motion detection performance as a function of time following TMS to MT (figure from, Thakral & Slotnick, 2011).

Results

TMS to MT produced a significantly greater impairment in motion detection than color detection (Figure 1.2B, task, motion and color, by TMS effect interaction p < 0.001;

Levene’s test for homogeneity of variance, both task p-values > 0.20). This result was not due to differences in task difficulty as performance did not differ between tasks at the first timepoint (t(2) < 1), a measure of baseline performance. 24

Consistent with the Experiment 1 right hemisphere TMS findings, TMS to MT impaired motion detection in both the contralateral visual field (t(2) = 11.00, p < 0.01) and the ipsilateral visual field (t(2) = 7.00, p < 0.01). There was no significant spatial location (contralateral and ipsilateral) by TMS effect interaction (p = 0.09).

Discussion

In Experiment 1, 1 Hz TMS to left MT preferentially impaired motion processing in the contralateral visual field during an attention task. In Experiment 2, single-pulse

TMS to MT impaired motion processing to a greater degree than color processing during a perception task. Taken together, these results suggest that TMS to MT can produce contralateral and feature-specific motion processing impairments, arguing against the possibilities that MST, which processes both contralateral and ipsilateral motion, was targeted or that a motion and color processing region was targeted.

Moreover, the results of Experiment 2 illustrated that TMS to MT could disrupt perceptual processing (attention and perception effects were confounded in Experiment

1).

In a recent case study (Moo et al., 2008), we reported a patient with a putative left MT+ lesion who was preferentially impaired at motion processing tasks in the contralateral visual field, as in the present experiment, with minimal fMRI motion perception or motion attention effects in this region. These impairments occurred primarily in the contralesional visual field suggesting the lesion included sub-region MT.

However, the extent of the lesion was uncertain and may have included adjacent motion sensitive region V3A. As such, the results are the first, to our knowledge, where 25 definitive disruption of MT impaired motion processing in the contralateral greater than ipsilateral visual field.

Of relevance, in nonhuman primates, MT and MST have been both functionally and anatomically segregated (Van Essen, Maunsell, & Bixby, 1981; Saito, Yukie,

Tanaka, Hikosaka, Fukada, & Iwai, 1986; Ungerleider & Desimone, 1986; Komatsu &

Wurtz, 1988a, 1988b; Newsome, Wurtz, & Komatsu, 1988; Duffy & Wurtz, 1991;

Boussaoud, Desimone, & Ungerleider, 1992; Lewis & Van Essen, 2000). For example, neurons in the primate MST contain denser connections from extraretinal motion signals than does MT (Newsome et al., 1988). Also, MT has much sparser connections from the ventral intraparietal area than does MST (Lewis & Van Essen, 2000). Of particular importance, functionally, neurons in MT have a much smaller receptive field size than those of MST (Duffy & Wurtz, 1991) with the response of these neurons extending only

10-15o into the ipsilateral visual field (Ungerleider & Desimone, 1986). In contrast, the

response of MST neurons extends 30-40o into the ipsilateral visual field (Raiguel, Van

Hulle, Xiao, Marcar, Lagae, & Orban, 1997). The present results bolster these primate

dissociations between MT and MST by providing further functional evidence for the

specificity of MT in contralateral motion processing. It will be important for future

research conducted in humans to determine whether the anatomic dissociations observed in primates is consistent across species (e.g., by using appropriate techniques such as diffusion tensor imaging).

It is important to highlight that TMS to MT impaired contralateral and ipsilateral motion processing in both experiments, which suggests disruption of MT may have transferred to more anterior sub-region MST. This is an inherent weakness of the 26 current study that may have methodological implications for future fMRI-guided TMS research. The present results suggest that using fMRI localization to guide stimulation may be limited to selectively target MT and identify its role in contralateral motion processing. Silvanto and Muggleton (2008) differentially targeted MT+ by employing a visual adaptation paradigm with motion properties that were selectively processed by this region. If such a technique is used in conjunction with localization procedures, as in the present study, it could enhance TMS accuracy and better guide stimulation of distinct neural populations within a single cortical area (e.g., sub-region MT or MST within motion processing region MT+).

Of direct relevance to our aim, the present results showed that selective disruption of MT, the sub-region of MT+ that preferentially processes contralateral motion, can impair contralateral motion processing. These findings complement previous neuroimaging studies that have associated motion perception and motion attention with region MT+ (Watson et al., 1993; Liu et al., 2003) and sub-region MT

(Dukelow et al., 2001; Huk et al., 2002; Slotnick & Yantis, 2005; Goosens et al., 2006;

Smith et al., 2006; Becker et al., 2008; Ohlendorf et al., 2008; Amano et al., 2009;). Of primary importance, building on previous MT+ TMS studies (Sack et al., 2006; Battelli et al., 2008; McKeefry et al., 2008; Burton et al., 2009; Stevens et al., 2009), the present findings indicate sub-region MT is necessary for motion processing. 27

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Chapter 2

The role of the parietal cortex during sustained visual spatial attention

Selective attention can enhance processing within a specific region of the visual field and produce increased activity within contralateral striate and extrastriate cortex

(Mangun & Hillyard, 1988; Heinze et al., 1994; Clark & Hillyard, 1996; Tootell et al.,

1998; Martinez et al., 1999; Hopfinger, Buonocore, & Mangun, 2000; Yantis et al., 2002;

Slotnick, Schwarzbach, & Yantis, 2003a). These effects of attention within occipital cortex are thought to reflect attention related amplification of visual sensory processing.

Attentional control, by comparison, can refer to either a shift of attention from one spatial location to another or sustained attention to a single location. A large body of neuroimaging evidence has shown that attentional control involves the parietal cortex

(including the intraparietal sulcus and superior parietal lobule) and the dorsolateral prefrontal cortex (Pardo, Fox, & Raichle, 1991; Corbetta, Miezin, Shulman, & Petersen,

1993; Corbetta, Kincade, Ollinger, McAvoy, & Shulman, 2000; Corbetta, Kincade, &

Shulman, 2002; Nobre et al., 1997; Coull & Nobre, 1998; Gitelman et al., 1999; Rosen et al., 1999; Wojciulik & Kanwisher, 1999; Hopfinger et al., 2000; Beauchamp, Petit,

Ellmore, Ingeholm, & Haxby, 2001; Ikkai & Curtis, 2007; for a review, see Corbetta and

Shulman, 2002). Previous studies, however, have not dissociated neural activity associated with shifts in attention versus sustained attention, due to methodological limitations (such as the poor temporal resolution of positron emission tomography) or the use of experimental protocols in which these cognitive operations occurred in close temporal proximity (as in standard attentional orienting paradigms). 36

Using event-related functional magnetic resonance imaging (fMRI), there has been some work on isolating the neural regions associated with different aspects of attentional control. In two studies (Vandenberghe, Gitelman, Parrish, & Mesulam, 2001;

Yantis et al., 2002), during central fixation, participants were cued to either shift attention from one peripheral location to another or to maintain attention to the same spatial location. Shifting attention, to a greater degree than sustained attention, was associated with activity in the superior parietal lobule (see also, Le, Pardo, & Hu, 1998;

Liu et al., 2003; Yantis & Serences, 2003).

Given that the superior parietal lobule and intraparietal sulcus have been associated with attentional control and the superior parietal lobule has been associated with shifting attention, subtractive logic would suggest that the intraparietal sulcus may be associated with sustained attention. There is some evidence in support of this, as sustained attention has been associated with activity in more lateral parietal regions

(Vandenberghe et al., 2001; Serences and Yantis, 2007; Kelly, Serences, Giesbrecht, &

Yantis, 2007). In Vandenberghe et al. (2001), during central fixation, participants either sustained attention to a white square presented in the left or right visual field (pressing a button when it dimmed) or passively fixated while no peripheral stimuli were presented.

Regions associated with sustained attention were identified by contrasting sustained attention > passive fixation. This contrast, however, was confounded by perceptual processing (see also, Le et al., 1998). Serences and Yantis (2007) and Kelley et al.,

(2007) used paradigms involving rapid serial visual presentation of letters where, depending on target letter identity, participants either shifted attention to a new location

(following a ‘shift’ target) or maintained attention at the current location (following a 37

‘hold’ target). Regions associated with hold targets were assumed to reflect sustained attention. One critical aspect of these paradigms is that distractor letters were presented adjacent to target letters (to motivate focused attention). As such, it is not possible to disentangle activity associated with sustained attention from voluntary suppression of distractors (Serences, Yantis, Culberson, & Awh, 2004). Furthermore, the cognitive operations involved in these studies are not well defined. While it could be the case that a hold target corresponds to sustained attention to a particular spatial location, a hold target may also trigger participants to disengage or shift attention from that location and then reallocate attention to the same location (see Sperling and Weichselgartner, 1995).

The current study was designed to avoid such perceptual or cognitive confounds.

In the present fMRI study, we aimed to identify the generalized control regions associated with sustained attention. Following previous studies that found generalized frontal-parietal regions engaged during both spatial and nonspatial attention

(Giesbrecht, Woldorff, Song, & Mangun, 2003; Slagter et al., 2007), we employed a moving dot protocol and a flickering checkerboard protocol (Figure 2.1). These protocols consisted of alternating 14 second periods of sustained attention to motion or flicker, sustained perception of motion or flicker, and sustained perception of stationary dots or a stationary checkerboard. As generalized control processing is necessarily coupled with feature-specific attentional modulation in sensory regions (Giesbrecht et al., 2003; Liu et al., 2003; Slagter et al., 2007), a region-of-interest (ROI) analysis was conducted to confirm that attention to moving dots > perception of moving dots modulated activity in motion processing region MT+ (and attention to flickering checkerboards > perception of flickering checkerboards did not). Pertaining to the aim of 38 the study, we then identified regions commonly associated with sustained attention via a conjunction of attention to moving dots > perception of stationary dots and attention to flickering checkerboards > perception of stationary checkerboards.

Figure 2.1 (A) The motion protocol was comprised of dots moving from the outer edge of the display toward the fixation point during alternating periods of sustained attention (followed by a stationary period with no motion) and sustained perception (also followed by a stationary period). During attention periods, cued auditorily with the word “attend”, participants were instructed to press a button each time the moving dots briefly slowed. During perceive periods, cued auditorily by the word “perceive”, participants were instructed to continually perceive the entire stimulus. (B) The flicker protocol was a circular checkerboard that reversed in contrast during attention and perception periods, with no flicker during stationary periods. During attention periods, participants were instructed to press a button each time a red square briefly appeared (figure from, Thakral & Slotnick, 2009).

Methods

Participants

Eight participants (4 females) with normal or corrected-to-normal visual acuity participated in the experiment. The experimental protocol was approved by the Johns

Hopkins University Institutional Review Board. Informed consent was obtained before the experiment commenced.

Stimuli and Tasks

Figure 2.1 illustrates the motion and flicker protocols. The motion protocol included periods of motion where dots appeared at a random location on the outer edge of the display (which measured 13.6º x 18.1º of visual angle), moved toward the central fixation point at a speed of 5º of visual angle per second, and then disappeared 0.74º of visual angle away the fixation point (there were 400 dots in total, each 0.05º of visual angle in diameter; Figure 2.1A). Participants were instructed to maintain fixation at all times. Motion periods lasted 14 s and alternated with stationary periods (‘motion- stationary’) where the dots remained in place for 14 s. Motion periods further alternated between periods of attention and perception. During attention periods (‘motion-attend’), which were cued auditorily by the word “attend” presented at the period onset, the speed of the dots briefly slowed twice for 250-400 ms, once at a random time during the period and the other near the end of the period (to encourage sustained attention during the entire period). Participants were instructed to press a button with their left hand as quickly as possible after they detected a speed decrease (a relatively easy task). During perception periods (‘motion-perceive’), which were cued auditorily by the word 40

“perceive” presented at the period onset, participants were instructed to relax and simply perceive the moving dots (which never changed speed). The flicker protocol was identical to the motion protocol except that the stimulus was a circular checkerboard

(diameter of 13.6º of visual angle) that was stationary (‘flicker-stationary’) or flickering, reversing in contrast every 120.5 ms (Figure 2.1B). During attention periods (‘flicker- attend’) participants detected a briefly presented red square presented at a random location within the stimulus, and during the perceive periods (‘flicker-perceive’) participants were instructed to relax and simply perceive the flickering checkerboard (no targets were presented).

fMRI Acquisition and Data Analysis

Images were acquired on a Phillips ACS−NT 1.5 T scanner. An echo-planar imaging sequence (TR = 2 s, TE = 40 ms, flip angle = 90º, 26 slices, no gap, orientation

= axial, 4.5 mm isotropic resolution) was used to acquire functional data and a magnetization prepared rapid gradient echo sequence (TR = 8.1 ms, TE = 3.7 ms, flip angle = 8º, 1 mm isotropic resolution) was used to acquire anatomic data. Participants completed 6-8 cycles of the motion protocol and 8 cycles of the flicker protocol.

Unless otherwise noted, data analysis was conducted using SPM5 (Wellcome

Department of Cognitive Neurology, London, UK). Functional image pre-processing included slice time correction, motion correction, spatial smoothing with a 5 mm FWHM gaussian kernel, temporal smoothing (using the default high-pass filter of 128 s), and normalization to Montreal Neurological Institute (MNI) space (resampled at 2 mm).

Anatomic images were also normalized to MNI space (resampled at 1 mm). A whole 41 brain general linear model analysis was conducted where all event types (motion- attend, motion-perceive, motion-stationary, flicker-attend, flicker-perceive, flicker- stationary) were modeled based on their respective onsets and 14 s durations (via convolution with a canonical hemodynamic response function; mean activity across each run was also modeled). On an individual participant basis, these models were fit to each voxel’s activation timecourse to yield beta-weights that specified the degree to which that activity correlated with each event type.

To assess the degree to which the motion and flicker protocols produced different patterns of sensory neural activity, a region-of-interest (ROI) analysis was conducted. For each participant, the contrast of motion-attend > motion-stationary was conducted to isolate motion processing related activity, as is typically done (e.g.

O’Craven, Rosen, Kwong, Treisman, & Savoy, 1997; Slotnick and Yantis, 2005). On a voxel-by-voxel basis, this differential activity was treated as a random effect to isolate activity that was consistently positive across all participants (using a one-tailed t-test).

For all contrasts in the present study, an individual voxel threshold of p < 0.01 was used, corrected for multiple comparisons to p < 0.001 by enforcing a cluster extent threshold (Poline & Mazoyer, 1993; Roland, Levin, Kawashima, & Åkerman, 1993;

Forman et al., 1995; Ledberg, Åkerman, & Roland, 1998; Slotnick, Moo, Segal, & Hart,

2003b). This corrected p-value translated into a minimum cluster extent threshold of 114 contiguous resampled voxels, computed via a Monte Carlo simulation conducted using custom software written in MATLAB (The MathWorks, Natick, MA). For each of 10,000 iterations, activity within each voxel of the acquisition matrix was modeled as a normally distributed random number (with a mean of 0 and a standard deviation of 1). Spatial 42 correlation was simulated through convolution with a 4 mm full-width-half-maximum

Gaussian. Across all iterations, the probability of a given cluster size was computed, where the probability of systematically larger clusters progressively decreased. The specific cluster threshold was selected such that the probability of observing that cluster size or larger was smaller than the desired corrected p-value (p < 0.001). Within each hemisphere, the locus of MT+ was identified as the most significant anterior sensory activity, as is commonly done (e.g., Watson et al., 1993; Beauchamp, Cox, & DeYoe,

1997; Huk et al., 2002). In the present study, the corresponding motion related activity in both hemispheres was within the ascending limb of the inferior temporal sulcus, reproducing the known anatomic locus of this region (Watson et al., 1993; Slotnick &

Yantis, 2005; Dukelow et al., 2001; Huk et al., 2002; Beauchamp et al., 2007). Similarly, the locus of V1 was identified within each hemisphere as the most significant activity within the calcarine sulcus, the known anatomic location of primary visual cortex.

After MT+ and V1 were localized within each hemisphere, event-related activity, the mean beta-weight activity within a 5 mm cube, was extracted from each ROI using custom software written in MATLAB. It is notable that we also conducted the analysis by extracting event-related activation timecourses from each ROI; however, as observed previously (Slotnick & Schacter, 2006), the timecourse results were markedly less sensitive than the beta-weight results (so only beta-weight results were reported).

Attention effects were investigated by comparing the conditions motion-attend > motion- perceive and flicker-attend > flicker-perceive. It is important to mention that differential effects using these comparisons can be assumed to only reflect attentional processing, as the same stimuli were used in both conditions within each contrast (such that 43 perceptual processing, which was constant across both conditions, was subtracted out).

Perception effects were investigated by comparing the conditions motion-perceive > motion-stationary and flicker-perceive > flicker-stationary (where differential effects can be assumed to reflect perceptual/sensory processing, given that the task was constant across conditions). Effects were assessed using a one-tailed t-test.

Relating to the aim of the present study, a conjunction analysis was also conducted to isolate activity associated with generalized (protocol independent) sustained attention (Caplan and Moo, 2004; Nichols, Brett, Andersson, Wager, &

Poline, 2005). Specifically, the conjunction of (motion-attend > motion-perceive) ∩

(flicker-attend > flicker-perceive) was used to identify the neural regions associated with sustained attention during both motion and flicker protocols. Following Nichols et al.

(2005), for all conjunctions in the present study, the individual voxel threshold for each contrast was set to p < 0.05 (corresponding to a joint p-value of p < 0.0175, computed using the Fisher technique; Fisher, 1973). The activity was corrected for multiple comparisons to p < 0.05 by enforcing a cluster extent threshold of 57 resampled voxels

(computed using the Monte Carlo procedure described above).

Functional results were projected onto a cortical surface representation from one representative participant (for precise anatomic locations, see Table 1). Cortical segmentation and reconstruction was conducted using BrainVoyager (Brain Innovation,

Maastricht, The Netherlands; for detailed procedures, see Slotnick, 2005).

Event-related activation timecourses were extracted from −4 to 28 s following event onset within a 5 mm cube centered at a given coordinate. Linear trends were removed and each timecourse was baseline corrected by subtracting the mean level of 44 activity from −4 to 0 s following event onset. Activity was evaluated from 6 to 18 s after event onset, determined a priori by modeling a 14-s duration hemodynamic response

(see Slotnick, 2005) and selecting the time range that spanned the full-width-half- maximum (i.e., the expected period of sustained activity).

Results

Sustained Attention MT+ Effects

Figure 2.2 and Table 2.1 illustrate the location of left and right hemisphere MT+ and the event-related activity extracted from these ROIs used to assess attention and perception effects. In right MT+ (Figure 2.2, left), there was a significant attention effect

(attend > perceive) for the motion protocol (t(7) = 4.62, p < 0.01) but not for the flicker protocol (t(7) < 1). Of importance, the corresponding interaction between protocol

(motion and flicker) and condition (attend and perceive) was significant (F(1,7) = 20.40, p < 0.01), which confirmed the expected motion specific attention effects in MT+. In left

MT+ (Figure 2.2, right), although the same pattern of attention effects were observed, they were not as robust and neither attention effect was significant (motion t(7) = 1.73, p

= 0.064; flicker, t(7) < 1) and the corresponding protocol by condition interaction was also not significant (F(1,7) = 3.66, p = 0.097). In both right and left MT+, there were significant perception effects (perceive > stationary) for both protocols, with marginally reliable protocol by condition interactions (right MT+, motion, t(7) = 24.62, p < 0.01, flicker, t(7) = 4.46, p < 0.01, interaction, F(1,7) = 5.43, p = 0.053; left MT+, motion t(7) =

11.13, p < 0.01, flicker, t(7) = 3.16, p < 0.01, interaction, F(1,7) = 5.00, p = 0.060). To assess whether attention effects were specific to MT+, we also evaluated event-related 45 activity extracted from ROIs in left and right hemisphere V1 (at the coordinates in Table

1) and found no significant attention effects (right V1, motion, t(7) < 1, flicker, t(7) < 1; left V1, motion t(7) = 1.48, p = 0.092, flicker, t(7) < 1). It is notable that the preceding analysis was based on standard methods for localizing MT+, while no such procedure exists for localizing flicker processing activity (which could have been used to further evaluate protocol specific attention effects). In an effort to identify flicker specific attention effects we conducted a whole brain analysis contrasting flicker-attend > flicker- perceive, but no significant activity was observed.

Figure 2.2 Motion processing activity, identified by the contrast motion-attend > motion- stationary, shown in purple/orange on a cortical surface representation of one participant (orange reflects greater significance; lateral and slightly oblique view, with occipital poles toward the lateral edges of the figure; gyri and sulci are shown in light and dark gray, respectively). In both hemispheres, motion processing region MT+ was identified (shown by white dots) and activity associated with motion and flicker attention (Att.), perception (Perc.), and stationary (Stat.) conditions was extracted for analysis. Right MT+ activity corresponding to motion-attend, motion-perceive, and motion- 46

stationary conditions are shown to the outer left while activity corresponding to flicker- attend, flicker-perceive, and flicker-stationary conditions are shown to the inner left. Left MT+ activity for the same motion and flicker conditions are shown to the inner and outer right, respectively. For each plot, differential attention > perception activity (first bar > middle bar) corresponds to an attention effect while differential perception > stationary activity (middle bar > third bar) corresponds to a perception effect. Within participant standard errors are shown (red reflects attention effect standard error, yellow reflects perception effect standard error; bicolor standard errors allow for attention effect, red to red, or perception effect, yellow to yellow, standard error comparisons) (figure from, Thakral & Slotnick, 2009)

Table 2.1 – Sensory regions used in ROI analysis and control regions associated with generalized sustained attention effects identified by whole brain analysis using the conjunction (motion- attend > motion-perceive) ∩ (flicker-attend > flicker-perceive) (table from, Thakral & Slotnick, 2009). Region BA x y z

Sensory regions

Right MT+ 19 38 –73 3

Left MT+ 19 –41 –81 6

Right V1 17 10 –85 –1

Left V1 17 –14 –93 0

Control regions

Right intraparietal sulcus 7/40 36 –43 41

Right middle frontal gyrus 9/46 42 40 27

Right superior temporal gyrus 22 58 –38 15

Right insula 13 30 22 –3

Left cerebellum - –35 –59 –24

BA refers to Brodmann area and coordinates (x, y, z) are in Talairach space.

Sustained Attention Control Regions

Figure 2.3 and Table 2.1 illustrate generalized control regions associated with sustained attention, identified using the conjunction (motion-attend > motion-perceive) ∩

(flicker-attend > flicker-perceive). All of the significant cortical activations were in the right hemisphere and included the intraparietal sulcus (BA 7/40), the right middle frontal gyrus (BA 9/46), the right superior temporal gyrus (BA 22), and the right insula (BA 13).

Figure 2.3 Generalized (protocol independent) sustained attention related activity identified via the conjunction (motion-attend > motion-perceive) ∩ (flicker-attend > flicker-perceive), shown in purple/orange on a cortical surface representation of one participant (orange reflects greater significance; posterior-lateral view, with occipital pole toward the left of the figure). Motion and flicker attention (Att.), perception (Perc.), and stationary (Stat.) related activity was extracted from the right intraparietal sulcus (IPS) and the right middle frontal gyrus (MFG). For each plot, differential attention > perception activity (first bar > middle bar) corresponds to an attention effect while differential perception > stationary activity (middle bar > third bar) corresponds to a perception effect. Within participant standard errors are shown (red reflects attention effect standard error, yellow reflects perception effect standard error; bicolor standard 48

errors allow for attention effect, red to red, or perception effect, yellow to yellow, standard error comparisons) (figure from, Thakral & Slotnick, 2009).

Event-related activity was extracted from the intraparietal sulcus and middle frontal gyrus (at the coordinates in Table 2.1), given that these regions have been classically associated with attentional control. In the intraparietal sulcus, there were significant attention effects (attend > perceive) for both protocols (motion, t(7) = 5.20, p

< 0.001; flicker, t(7) = 2.22, p < 0.05), and the protocol by condition interaction was not significant (F(1,7) < 1) suggesting the attention effects corresponding to both motion and flicker protocols were of similar magnitude. Also within this region, there were no significant perceptual effects (perceive > stationary) for either protocol (motion, t(7) =

1.65, p = 0.071; flicker, t(7) = 1.25, p = 0.13) and the protocol by condition interaction was not significant (F(1,7) = 1.57, p > 0.20). The middle frontal gyrus showed the same pattern of activity, with significant attention effects for both protocols (motion, t(7) = 3.18, p < 0.01; flicker, t(7) = 3.53, p < 0.01) and no significant protocol by condition interaction

(F (1,7) < 1). This region also showed no significant perception effects for either protocol

(motion, t(7) < 1; flicker, t(7) < 1), although the protocol by condition interaction was significant (F(1,7) = 7.87, p < 0.05). It is important to highlight that in both of these regions there were significant attention effects but no significant perception effects, as would be expected in regions involved in attentional control. The present sustained attention effects in intraparietal sulcus are particularly compelling when considered in relation to the previously reported attentional shift effects in the superior parietal lobule

(Vandenberghe et al., 2001; Yantis et al., 2002).

Event-related activation timecourses were also extracted from the intraparietal sulcus (at the coordinates in Table 2.1) to better characterize the patterns of activity 49 over time. Figure 2.4 illustrates the activation timecourses associated with sustained attention and sustained perception (collapsing over protocol based on the non- significant protocol by condition interactions above). The attention effect, computed by comparing the mean magnitude of attention versus perception activity from 6 to 18 seconds after stimulus onset, was significant (t(7) = 1.94, p < 0.05).

Figure 2.4 Event-related activation timecourses associated with sustained attention and perception extracted from the right intraparietal sulcus (IPS; color key to upper right). Within participant error bars are shown (figure from, Thakral & Slotnick, 2009)

It is important to consider that targets were only presented during sustained

attention periods of both protocols, in an effort to motivate participants to maintain

attention during these epochs. Because of this, it is possible that motor responses to

targets could account for differences attributed to attention. However, targets occurred

infrequently such that motor responses could be assumed transient, which does not

correspond to the extended periods of sustained attention modeled to identify sustained

activity or observed in the intraparietal sulcus activation timecourse. Even if there was

differential motor activity between conditions, the neural regions associated with motor

processing (Picard and Strick, 2001) and motor preparation/attention (Rushworth ,

Johansen-Berg, Gobel, & Devlin, 1997; Rushworth, Nixon, Renowden, Wade, &

Passingham, 2003; Coull & Nobre, 1998; but see, Snyder, Batista, & Andersen, 1998) 50 are distinct from the intraparietal sulcus region observed in the present study (a parallel argument can be made against eye movement related activity, which has also been associated with distinct neural substrates that were not observed; Corbetta et al., 1998).

Still, to directly address this point, sustained attention and motor response activation timecourses, associated with the motion protocol of five participants, were extracted from the intraparietal sulcus (at the coordinates in Table 2.1; behavioral responses were only measured in this subset of participants; accuracy was 79.38%). Of importance, both event-related timecourses were extracted from the sustained attention period, with sustained attention onsets time-locked to the beginning of the epoch (as above; Figure

2.4) and the motor onsets time-locked to the second motor response (to disentangle attention and motor events, as the first motor response and sustained attention onsets were temporally proximal). Figure 2.5 depicts the sustained attention and motor activation timecourses in the intraparietal sulcus. In line with the previous activation timecourse results (Figure 2.4), the magnitude of attention effects were sustained over time, as suggested by a non-significant interaction (F(6, 24) = 1.47, p > 0.20). Of particular relevance, motor activity was not significantly greater than zero in this region

(t(4) < 1), while sustained attention activity was significantly greater than zero (t(4) =

3.76, p < 0.05) and significantly greater than motor activity (t(4) = 2.67, p < 0.05). These findings indicate the present sustained attention effects within the intraparietal sulcus were not due to a motor confound (which would have been evidence by significant motor activity in this region).

Figure 2.5 Event-related activation timecourses associated with sustained attention and motor response extracted from the right intraparietal sulcus (IPS; color key to upper right). Within participant error bars are shown (figure from, Thakral & Slotnick, 2009).

Discussion

In the present study, generalized sustained attention effects were observed in the right intraparietal sulcus (BA 7/40), the right middle frontal gyrus (BA 9/46), the right superior temporal gyrus (BA 22), the right insula (BA 13), and the left cerebellum. The involvement of prefrontal and parietal cortex replicates a large body of evidence implicating these regions in attentional control (Pardo et al., 1991; Corbetta et al., 1993,

2000, 2002; Nobre et al., 1997; Coull & Nobre, 1998; Gitelman et al., 1999; Rosen et al., 1999; Wojciulik and Kanwisher, 1999; Hopfinger et al., 2000; Beauchamp et al.,

2001; Ikkai and Curtis, 2007; for a review, see Corbetta & Shulman, 2002). It is notable that all of our cortical activations were lateralized to the right hemisphere, which is consistent with a model of the right hemisphere being preferentially involved in spatial attention (Corbetta & Shulman, 2002). We also found differential effects in right MT+, with significant motion but not flicker attention effects in this region. These protocol dependent attention effects were notably distinct from the protocol independent attention effects observed in attentional control regions. 52

It could be argued that the effects we have attributed to sustained attention, allocation of attention to a particular stimulus and spatial location over time (Yantis &

Serences, 2003), actually reflected vigilance, a general state of active processing

(Coull, 1998). A vigilance account, however, would predict the same pattern of activity for both protocols. Since differential MT+ activity was observed across protocols (i.e., attention effects were significantly greater for the motion but not flicker protocol in right

MT+), the current results cannot be attributed to general differences in vigilance.

Moreover, if our effects were due to vigilance it is arguable that there should have been a relatively greater extent of activity associated with the attention condition as compared to the perception condition (Lawrence et al., 2003). Figure 2.6 illustrates that exactly the opposite occurred, as there was a smaller extent of activity associated with sustained attention, identified using the conjunction (motion-attend > motion-perceive) ∩ (flicker- attend > flicker-perceive), compared to sustained perception, identified using the conjunction (motion-perceive > motion-attend) ∩ (flicker-perceive > flicker-attend) (see also, Buckner et al., 2008). It is also feasible that participants may have been attending, to some degree, to the stimuli during the perception periods which would have reduced the significance of our attention effects or, rather, participants may not have been engaged during the perception periods (e.g., if they had closed their eyes) which would have reduced the significance of our perception effects. However, robust attention and perception effects were observed, so these were not significant concerns. 53

Figure 2.6 Sustained attention > perception activity shown in purple/orange and sustained perception > attention activity shown in yellow/black on a cortical surface representation of one participant (orange and yellow reflect greater significance; superior view with both hemispheres rotated laterally, occipital pole toward the bottom of the figure) (figure from, Thakral & Slotnick, 2009).

It is also possible that participants made multiple shifts in spatial attention during the attend period (rather than sustaining attention to the entire stimulus display). If this were the case, we should have observed sustained attention related activity in the superior parietal lobule, as this region has been associated with shifts of spatial attention (Vandenberghe et al., 2001; Yantis et al., 2002). However, there was no evidence of sustained attention activity in the superior parietal lobule, identified using the conjunction (motion-attend > motion-perceive) ∩ (flicker-attend > flicker-perceive), even at a reduced threshold of p < 0.20. This indicates that our effects were not due to transient shifts in attention, but rather reflected sustained attention.

Much of the previous literature concerning attentional control have focused mainly on cortical structures such as the parietal cortex and the dorsolateral prefrontal cortex (Pardo, Fox, & Raichle, 1991; Corbetta, Miezin, Shulman, & Petersen, 1993;

Corbetta, Kincade, Ollinger, McAvoy, & Shulman, 2000; Corbetta, Kincade, & Shulman,

2002; Nobre et al., 1997; Coull & Nobre, 1998; Gitelman et al., 1999; Rosen et al., 54

1999; Wojciulik & Kanwisher, 1999; Hopfinger et al., 2000; Beauchamp, Petit, Ellmore,

Ingeholm, & Haxby, 2001; Ikkai & Curtis, 2007; for a review, see Corbetta and Shulman,

2002). However, numerous subcortical structures have also been strongly associated with attentional processing. These structures include the superior colliculus as well as the pulvinar nucleus of the thalamus (for a review, see Shipp, 2004). The pulvinar, for example, has been shown to be involved with the control of spatial attention, filtering of distracting information, and attentional orienting (Smith, Cotton, Bruno, & Moutsiana,

2009; Petersen, Robinson, & Morris, 1987; LaBerge, 1990; for a review, see Robinson

& Petersen, 1992). In the current study the only subcortical structure activated during sustained attention was the cerebellum, thus future research will need to elucidate whether other subcortical structures are also involved during this process.

In the current study, generalized control processing was observed in the intraparietal sulcus and was coupled with feature-specific attentional modulation in MT+.

Such coupling would suggest that these regions are connected anatomically to mediate sustained attention to motion. In support of this, numerous anatomic studies conducted in nonhuman primates have observed strong connections between these specific regions (Maunsell & Van Essen, 1983; Ungerledier & Desimone, 1986; Fellemen & Van

Essen, 1991; Ninomiya, Sawamura, Inoue, & Takada, 2012). Of importance, these findings bolster the correlational/functional evidence provided here and support the suggestion that the parietal cortex sends generalized top-down sustained attention signals to selectively modulate motion processing in MT+.

Posner and Petersen (1990) proposed an influential model of visual spatial attention with neural subsystems dedicated to disengaging attention from a given 55 location, shifting attention to a target location, and then engaging (i.e., sustaining) attention at the new location. It should be highlighted that the engage operation in standard attentional orienting paradigms has much shorter duration than that of the present study. As such, it is uncertain whether the neural regions associated with sustained attention observed in the present study also mediate sustained attention for shorter durations. There is some evidence that this might be the case, as attentional control related activity has been reported in the intraparietal sulcus and superior parietal lobule (along with the dorsolateral prefrontal cortex; Pardo et al., 1991; Corbetta et al.,

1993, 2000, 2002; Nobre et al., 1997; Coull & Nobre, 1998; Gitelman et al., 1999;

Rosen et al., 1999; Wojciulik and Kanwisher, 1999; Hopfinger et al., 2000; Beauchamp et al., 2001; Ikkai & Curtis, 2007; for a review, see Corbetta & Shulman, 2002). Given that the superior parietal lobule has been associated with shifting attention

(Vandenberghe et al., 2001; Yantis et al., 2002), subtractive logic suggests the intraparietal sulcus is associated with sustained attention, even in paradigms with relatively brief periods of sustained attention. Still, future research will be necessary to determine the degree to which the neural regions associated with sustained attention for relatively long periods, identified in the present study, also mediate sustained attention for shorter periods.

As mentioned immediately above, there is compelling evidence that shifting attention is mediated by the superior parietal lobule (Vandenberghe et al., 2001; Yantis et al., 2002; see also, Le et al., 1998; Yantis & Serences, 2003; Liu et al., 2003), while there is some evidence suggesting more lateral parietal regions are involved in sustained attention (Vandenberghe et al., 2001; Serences & Yantis, 2007; Kelley et al., 56

2007; see also, Husain & Nachev, 2007; Malhotra, Coulthard, & Husain, 2009). Of direct relevance to the aim of the present study, generalized sustained attention related activity was observed in the intraparietal sulcus, which complements the known attentional shift related activity in the superior parietal lobule. The present results, in conjunction with previous findings, suggest there may be a functional-anatomic architecture with regard to attentional control in the parietal cortex, where more superior activity mediates attentional shifts and more lateral activity mediates sustained attention. 57

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Chapter 3

A neural mechanism for aesthetic experience

When viewing a piece of art, such as a painting or a sculpture, one can have the experience that it is beautiful. This aesthetic experience has been hypothesized to intimately depend on visual sensory details in the art (Bell, 1924), such as the wavy lines and colors that constitute the modern painting Stairway at Auvers by van Gogh

(Figure 3.1S). It has also been hypothesized that aesthetic experience depends on concepts or thoughts associated with viewing art to a greater degree than visual sensory details (Danto, 1998), such as a contemporary sculpture Brillo Soap Pads Box by Andy Warhol (Warhol, 1964) that is nearly identical – perceptually – to those that were once found on supermarket shelves.

Figure 3.1 van Gogh paintings employed. Paintings are ordered from the least to the most motion experience (from the top left to the bottom right) based on the average motion ranking across participants. Paintings M, Q, and T were excluded from the analyses due to implied motion, although the same pattern of results was obtained if these paintings were included in the analysis (figure from, Thakral & Slotnick, 2012). A. van Gogh V. (1888). Portrait of Armand Roulin. Museum Folkwang, Essen. B. van Gogh V. (1889). Self-portrait with a Bandaged Ear. The Courtald Gallery, London. C. van Gogh V. (1889). Self-portrait. Private Collection. D. van Gogh V. (1887). Self-portrait. The Art Institute of Chicago, Chicgao. E. van Gogh V. (1888). The Yellow House. Van Gogh Museum, Amsterdam. F. van Gogh V .(1889). Irises. The Getty Center, Los Angeles. G. van Gogh V. (1889). Self-portrait. Musée d’Orsay, Paris. H. van Gogh V. (1888). The Langlois Drawbridge. Wallraf-Richartz-Museum, Cologne. I. van Gogh V. (1890). The Church in Auvers-sur-Oise, View from the Chevet. Musée d’Orsay, Paris. 70

J. van Gogh V. (1888). Self-portrait with Felt Hat. Van Gogh Museum, Amsterdam. K. van Gogh V. (1888). Field with Flowers near Arles. Van Gogh Museum, Amsterdam. L. van Gogh V. (1888). Fishing Boats on the Beach at Saintes-Maries-de-la-Mer. Van Gogh Museum, Amsterdam. M. van Gogh V. (1890). White House at Night. The State Hermitage Museum, St. Petersburg. N. van Gogh V. (1889). Landscape with Wheat Sheaves and Rising Moon. Kröller- Müller Museum, Otterlo. O. van Gogh V. (1889). Cypresses. The Metropolitan Museum of Art, New York. P. van Gogh, V. (1889). A Wheat Field, with Cypresses. The National Gallery, London. Q. van Gogh V. (1888). The Sower. Kröller-Müller Museum, Otterlo. R. van Gogh V. (1889). The Starry Night. The Museum of Modern Art, New York. S. van Gogh V. (1890). Stairway at Auvers. Saint Louis Art Museum, St. Louis. T. van Gogh V. (1890). Wheat Field with Crows. Van Gogh Museum, Amsterdam.

Brain-based evidence has provided some support for both the sensory hypothesis of aesthetic experience (Zeki, 1999) and the conceptual hypothesis of aesthetic experience (Cela-Conde, Agnati, Hutson, Moa, & Nadal, 2011). That is, increasing preference for paintings has been correlated with systematically greater activity in occipital brain regions (Vartanian & Goel, 2004) that mediate visual sensory processing, and pictures of art or true-life photographs (e.g., landscapes or objects) that were classified as beautiful were associated with activity in prefrontal brain regions

(Cela-Conde, Marty, Maestú, Ortiz, Munar, Fernandez, et al., 2004) that mediate conceptual processing. However, previous studies that have investigated the neural basis of aesthetic experience have not disentangled low-level visual sensory processing and high-level conceptual processing.

In the present study, to provide a more complete neural mechanism of aesthetic experience, participants viewed modern paintings and we separately evaluated sensory effects and conceptual effects in the brain. The sensory analysis capitalized on the fact that each visual feature, such as color or motion, is preferentially processed in a particular cortical region (Slotnick. 2004). Specifically, we used functional magnetic 71 resonance imaging (fMRI) to measure the magnitude of activity in visual sensory motion processing region MT+ and in the prefrontal cortex while participants viewed van Gogh paintings that evoked a range of motion experience (Figure 3.1; Aragón, Naumis, Bai,

Torres, & Maini, 2008).

Methods

Participants

The experimental protocol was approved by the Massachusetts General Hospital

Institutional Review Board. Sixteen participants with normal or corrected-to-normal vision took part in the study.

Stimuli and Tasks

During functional magnetic resonance imaging (fMRI), participants viewed 20 van

Gogh paintings and classified each painting as either pleasant or unpleasant, a measure of the aesthetic (Figure 3.1, shows all the paintings). Paintings ranged in size from 5.7-13.8º by 2.1º of visual angle. All of the paintings were presented at fixation for

4-8 s and then were repeated (there was a 4 s fixation period at the end of the run).

Participants were instructed to maintain central fixation and make a pleasant or an

unpleasant judgment using their left index and middle finger, respectively, such that

there was an approximately equal number of each response type.

72 fMRI Acquisition and Data Analysis

All images were acquired with a Siemens Trio 3 T scanner. Functional images were acquired using an echo-planar imaging sequence (TR = 2 s, TE = 30 ms, 64 x 64 acquisition matrix, 33 slices, no gap, 4 mm isotropic resolution). Anatomic images were acquired using a magnetization prepared rapid gradient echo sequence (1.33 x 1 x 1 mm resolution). Analysis was conducted using BrainVoyager QX (Brain Innovation,

Maastricht, The Netherlands). Participants also completed a functional run to localize sensory motion processing region MT+ (Thakral & Slotnick, 2009) in which dots alternated every 14 s between moving from the outer edge of the screen toward the fixation point and remaining stationary.

fMRI data pre-processing included slice-time correction, motion correction, and temporal high-pass filtering by removal of low frequency components below 2 cycles per run length using a Fourier basis set. A random-effect general linear model analysis was conducted. For each participant, MT+ was identified by contrasting moving dots versus stationary dots. To restrict motion-related activity to the ascending limb of the inferior temporal sulcus, the known anatomic location of MT+ (Thakral & Slotnick, 2009), an individual voxel threshold of p < 5 x 10-38 was enforced (Bonferroni corrected for

multiple corrections to p < 0.001). Event-related activation timecourses associated with

each painting were extracted from a 7 mm cube centered at MT+ (identified by the

localizer results of each participant), and were then collapsed across both hemispheres.

Activation timecourses were extracted from 0 to 10 s following event onset (baseline

corrected from 0 to 2 s). The timecourse analysis was restricted to 6 s following event

onset (to ensure statistical independence), the expected maximum of the fMRI 73 response. The motion-unpleasant versus stationary-pleasant analysis was restricted to the 10 participants who had at least 4 trials of each event type.

Following fMRI, each participant rank ordered the previously presented paintings from the lowest degree of motion experience to the highest degree of motion experience

(Figure 3.2), and then identified a boundary that separated paintings that were relatively stationary from paintings that were relatively in motion. For any given participant, each paintings rank order was within 2 standard deviations of the mean rank order for that painting. Analysis was restricted to the 17 paintings (Figure 3.1) in which implied object motion could not be inferred (Kourtzi & Kanwisher, 2000; Kim & Blake, 2007; Osaka,

Matsuyoshi, & Ikeda, & Osaka, 2010). Activity in MT+ (Figure 3.2, top) was evaluated as a function of motion experience and pleasantness using a one-tailed t-test.

Figure 3.2 Top, cortical surface with motion processing activity in MT+ (demarcated by white circles). Bottom left, MT+ activity (percent signal change) as a function of motion experience associated with each painting, with the best-fit line shown in red. Bottom right, MT+ activity (percent signal change) associated with motion-unpleasant paintings and stationary-pleasant paintings (figure from, Thakral & Slotnick, 2012).

Results

Motion Experience

A parametric analysis revealed a significant positive correlation between the degree of motion experience associated with viewing each painting (based on each participant’s motion experience rankings) and the magnitude of activity in MT+ (t(15) =

2.07, p < 0.05, r = 0.25; Figure 3.2, bottom left). Furthermore, paintings classified as pleasant were associated with a greater magnitude of activity in MT+ as compared to paintings classified as unpleasant (t(15) = 1.83, p < 0.05, r = 0.20). These findings suggest that activity in MT+ is associated with the experience of both motion and pleasantness. To assess which of these factors was driving the activation of MT+, we compared activity associated with motion-unpleasant paintings with stationary-pleasant paintings (based on each participant’s stationary-motion boundary). MT+ activity was significantly greater for motion-unpleasant paintings as compared to stationary-pleasant paintings (t(9) = 1.98, p < 0.05; Figure 3.2, bottom right). In addition, consistent with previous results (Kawabata & Zeki, 2004), the magnitude of activity associated with viewing stationary-pleasant paintings did not differ from 0 (t(9) < 1).

In an effort to determine whether the experience of motion was specific to MT+, we conducted a second parallel analysis probing another sensory region, color processing region, V8. If the experience of motion is specific to MT+, then no significant correlation should be observed between the degree of motion experience and the magnitude of activity in V8 and this effect should be greater in MT+ than V8. V8 was identified as significant activity during the perception of the paintings within the collateral sulcus (i.e., the known location of V8; Talairach coordinates x = -32, y = -52, z = -17 and 75 x = 32 y = -52, z = -17, Slotnick, 2009). Significant activity was proximal to the known anatomic location of V8 (Talairach coordinates x = -32, y = -52, z = -7 and x = 32, y = -

52, z = -9, left and right hemisphere, respectively). The degree of motion experience associated with viewing each painting (based on each participant’s motion experience rankings) and the magnitude of activity in V8 was not significantly correlated (t(15) =

1.34, p > 0.10). V8 activity was also not significantly greater for motion-unpleasant paintings as compared to stationary-pleasant paintings (t(9) = 1.67, p > 0.05). The correlation, however, between the degree of motion experience and the magnitude of activity was not significantly greater in MT+ than V8 (t(15) < 1). Directly comparing the correlation values yielded the same pattern of results (t(15) < 1).

That viewing certain paintings activated MT+, which presumably produced the experience of motion, provides support for the sensory hypothesis of the aesthetic.

However, although MT+ activity did track motion experience, this region did not reflect the experience of pleasantness. Thus, these results constrain the role of MT+ during aesthetic processing by indicating that the computation mediating the experience of pleasantness must be conducted in a different neural region.

Pleasantness Experience

We next evaluated activity in the dorsolateral and anterior prefrontal cortex given that these regions have been associated with aesthetic processing (Cela-Conde et al.,

2004, 2011; Jacobsen, Schubotz, Höfel, & Cramon, 2006). Paintings classified as pleasant were contrasted with paintings classified as unpleasant, and activations within the anterior or dorsolateral prefrontal cortex were identified (p < 0.001, uncorrected). 76

This contrast produced 2 activations in the anterior prefrontal cortex (Figure 3.3, left; both activations were in Brodmann area 10, Talairach coordinates x = -13, y = 54, z = 4, and x = 9, y = 55, z = 6). Within the left anterior prefrontal cortex, the magnitude of activity associated with stationary-pleasant paintings was not significantly greater than that associated with motion-unpleasant paintings (t(9) < 1). Critically, within the right anterior prefrontal cortex, the magnitude of activity associated with stationary-pleasant paintings was significantly greater than motion-unpleasant paintings (t(9) = 2.00, p <

0.05), and the magnitude of activity associated with motion-unpleasant paintings did not differ from 0 (t(9) < 1; Figure 3.3, right). Considered together, the preceding results suggest that when viewing certain van Gogh paintings, MT+ is involved in processing motion experience and the anterior prefrontal cortex is involved in processing pleasantness experience.

Figure 3.3 Left, cortical surface with anterior prefrontal cortex activity in green associated with pleasantness (the right hemisphere activation is demarcated by a white circle). Right, right anterior prefrontal cortex activity (percent signal change) associated with motion-unpleasant paintings and stationary-pleasant paintings (figure from, Thakral & Slotnick, 2012).

Degree of Motion Experience

We next used MT+ activity to quantify the degree of motion experience associated with viewing paintings as compared to viewing real motion. The painting with the highest degree of motion experience produced MT+ activity that was 56.6 percent of 77 the magnitude of activity produced by viewing coherently moving dots. As it can be assumed that the MT+ response is linearly correlated with motion experience (Rees,

Friston, & Koch, 2000), this result suggests that viewing paintings can produce a very realistic sensory experience in which approximately half of the elements in the paintings appear to be in motion.

Discussion

The current findings provide a neural mechanism for the aesthetic. Specifically, aesthetic experience associated with viewing van Gogh paintings was driven by sensory activity in MT+ and also involved processing in the anterior prefrontal cortex. It should be highlighted that this is only one mechanism for aesthetic processing. Aesthetic experience associated with viewing other kinds of art, particularly contemporary art, may depend largely or even completely on conceptual processing (Danto, 1998). Future research will be needed to empirically address this issue.

Whereas previous evidence has shown that MT+ does activate in response to implied motion in paintings (i.e., where motion can be inferred based on objects that appear to be in motion; Kim & Blake, 2007; Osaka et al., 2010), the current analysis was done to avoid such effects. Thus the current motion experience may parallel the experience when viewing visual illusions where motion is not inferred based simply on objects but is elicited cortically through an interaction of contrast, luminance, and position. Figure 3.4 depicts two such examples, the Enigma illusion (Leviant, 1996;

Ruzzoli, Gori, Pavan, Pirulli, Marzi, & Miniussi, 2011, Figure 3.4, left) and the Rotating

Snakes illusion (Conway, Kitaoka, Yazdanbakhsh, Pack, & Livingstone, 2005, Figure 78

3.4, right). The Enigma illusion, for example, elicits motion through its high luminance contrast gratings and appears to be ‘shimmery’ (Kumar & Glaser, 2006). This illusion activates MT+ (Zeki, Watson, & Frackowiak, 1993; Ruzzoli et al., 2011). Similar to this illusion, paintings by van Gogh such as Starry Night (Figure 3.1R) have been shown to contain distinct patterns of luminance changes (so called, ‘turbulent luminance’; Aragón, et al., 2006). Thus, the mechanisms known to elicit motion in visual illusions may, in part, map onto those that are present in van Gogh’s paintings to elicit a similar motion experience through activation of MT+.

Figure 3.4 Left, the Enigma illusion (figure from, Ruzzoli et al., 2011). Right, the Rotating Snakes illusion (figure from, Conway et al., 2005).

In Chapter 1, the finding that region MT is linked to contralateral motion

processing was supported by similar findings in nonhuman primates. Following this, it is

fair to question the extent to which the aesthetic is also preserved across species

through visual sensory details, as shown in the present experiment. It has been argued

that in humans, one of the critical visual sensory details that the aesthetic is dependant

on is symmetry, as humans show a preference for symmetrical visual displays but not

random ones (for review see, Winner, 1985). Similarly, primates will naturally select symmetrical patterns over random patterns (for review see, Bleakney, 1970). This 79 selective behavior has been hypothesized to be experienced as pleasurable based on the fact that the earliest visual experiences, such as viewing faces, are inherently symmetric and linked with pleasurable experiences such as warmth and food

(Bleakney, 1970). Experimental evidence is necessary to support this hypothesis.

Nevertheless, it would not be surprising that some type of experience of pleasure is linked to visual sensory details (e.g., symmetry or motion) which are shared across species. Moreover, connectivity analyses done in primates have shown connections between the frontal cortex and MT (Ungerleider & Desomone, 1986; Palmer & Rosa,

2006; Ninomiya, Sawamura, Inoue, & Takada, 2012). These findings, together with the present results, suggest that these connections may mediate the aesthetic across species and more importantly, bolster the correlational/functional evidence observed in the present study.

Of relevance, event-related potential (ERP) research has shown that implied motion effects in MT+ occur 260-400 ms after stimulus onset (Lorteije, Kenemans,

Jellema, van der Lubbe, de Heer, & van Wezel, 2006), while aesthetic processing effects in the prefrontal cortex occur 300-400 ms after stimulus onset (Jacobsen &

Höfel, 2003). The overlapping windows of activation suggest that these processes may interact to give rise to aesthetic experience. Additional studies that employ techniques with high temporal resolution, such as ERPs, will be needed to evaluate whether these regions are synchronously active or whether they interact in a top-down or bottom-up manner during aesthetic processing (Cela-Conde et al., 2011, cf., Slotnick, 2010). The techniques employed in the current study will serve as a framework for future studies to 80 investigate the neural basis of aesthetic experience associated with other visual and non-visual art forms such as sculpture, architecture, or music.

In the present study, while participants viewed van Gogh paintings, motion experience (but not pleasantness experience) was associated with activity in motion processing region MT+ and the experience of pleasantness (but not motion experience) was associated with activity in the anterior prefrontal cortex. To date, this evidence constitutes the most complete neural mechanism of aesthetic experience. 81

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Discussion

The three experiments presented in this thesis provide novel evidence for the role of human motion processing complex, MT+ during sustained perception and attention. Experiment 1 extended prior research demonstrating the necessity of MT+ during low-level motion processing during perception and revealed the necessity of sub- region, MT, for low-level contralateral motion processing (Chapter 1). Experiment 2 provided evidence for the role of MT+ during sustained attention to motion but not flicker

(i.e., feature-specific sensory attentional modulation). In contrast to these low-level feature-specific sensory effects of attention in MT+, the parietal cortex, specifically the intraparietal sulcus, was active in a generalized and feature independent manner with greater activity associated with attention versus perception during both attention to motion and attention to flicker. Thus across both regions, the low-level sensory feature- specific effects of attention in MT+ and the high-level feature-independent attentional control activity in the parietal cortex provide a neural mechanism for sustained attention

(Chapter 2). That is, the parietal cortex exhibits greater activation when sustaining attention versus perceiving for an extended period of time regardless of the stimulus type. Of importance, this high-level control signal is coupled with feature-specific low- level sensory attentional modulation in occipital cortex which enhances the processing of that specific stimulus (i.e., sensory modulation in MT+ when attending to motion).

Experiment 3 provided novel evidence for the role of MT+ during aesthetic processing when viewing visual art (Chapter 3). During sustained perception of visual art, activity in

MT+ tracked the low-level sensory experience of motion. This stands in direct contrast to activity in the frontal cortex, specifically the anterior prefrontal cortex, which tracked 87 the high-level experience of pleasantness associated with viewing visual art. Similar to

Experiment 2, both the low-level processing in MT+ together with the high-level processing in the frontal cortex provides a neural mechanism for the aesthetic, with MT+ mediating the sensory experience and the frontal cortex mediating the pleasantness experience.

As stated in the Introduction, across other cognitive processes such as attention, memory, and imagery, frontal-parietal regions have been shown to be involved in high- level control processes and occipital-temporal regions have been shown to reflect the sensory low-level effects of these high-level processes. This dichotomy has been used to successfully provide a mechanistic understanding of these cognitive processes. For example, during memory, activity in frontal-parietal regions reflects high-level control processes such as attending to, selecting, and monitoring successfully retrieved information (Buckner, Koutstaal, Schacter, Wagner, & Rosen, 1998; Slotnick, Moo,

Segal, & Hart,, 2003; Wheeler & Buckner, 2003; Hayama & Rugg, 2009; Slotnick,

2009a; for review see, Buckner & Wheeler, 2001; Buckner, 2003; Hutchinson,

Uncapher, & Wagner, 2009). In contrast, activity in occipital-temporal sensory regions reflects the actual low-level sensory components of the retrieved information (e.g., when retrieving motion or color information, sensory reactivation is observed in color processing region V8 and motion processing region, MT+, respectively, Slotnick, 2009a;

Slotnick & Thakral, 2011). Mechanistically speaking, these low-level and high-level processes in frontal-parietal and occipital-temporal regions, respectively, work to construct an accurate representation of a remembered stimulus (see, Slotnick, 2004;

Slotnick, 2009b). The current experiments extend this commonly used dichotomization 88 between low-level and high-level processing to provide novel neural mechanisms for the cognitive processes of sustained perception and attention. This decomposition into low- level versus high-level processes may be a very fruitful approach for future research when examining the component neural processes and underlying mechanisms of any cognitive process of interest.

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