Modulation of Endogenous and Exogenous Mechanisms of Attention

Transcription

1 Modulation of Endogenous and Exogenous Mechanisms of Attention A Master s Thesis Presented to The Faculty of the Graduate School of Arts and Sciences Brandeis University Department of Psychology Dr. Robert Sekuler, Advisor In Partial Fulfillment of the Requirements for the Degree Master of Arts by Sylvia Guillory August, 2012

2 This thesis, directed and approved by Sylvia Guillory s committee, has been accepted and approved by the Graduate Faculty of Brandeis University in partial fulfillment of the requirements for the degree of: MASTER OF ARTS Thesis Committee: Dr. Robert Sekuler, Advisor Dr. Arthur Wingfield, Second Reader

3 c Copyright by Sylvia Guillory 2012

4 Acknowledgments I would like to extend my thanks and appreciation to my advisor, Dr. Robert Sekuler and Dr. Lisa Payne, who provided guidance and direction. Their insight and knowledge were invaluable and their help indispensable. I am truly appreciative for all that they had done for me. Special thanks to Abigail Noyce, Chad Dube, Stefan Berteau, and Avi Aizenman for their suggestions and support. I would like to acknowledge and thank Drs. Jie Huang and Lisa Payne for collecting the data for Experiment 1 and Experiment 2, respectively, and for making their data available for me to analyze. I would also like to thank the many Brandeis University students who gave their time to be lab rats in my experiment. I am grateful for it. iv

5 Abstract Modulation of Endogenous and Exogenous Mechanisms of Attention A thesis presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts by Sylvia Guillory Selective attention can be guided by voluntary, effortful processes or involuntary and automatic behavior. Though attention is important in everyday functioning, relatively little is known about the neural mechanisms of this cognitive process. Using a visual working memory paradigm, I sought to describe the relationship among preparatory and information processing and behavioral performance using alpha-band power, and the N2 ERP component. A series of three experiments showed that the magnitude of the alpha-band oscillations, a characteristic of attentional engagement, modulates the N2, a component associated with selective attention. v

6 Contents Abstract v 1 Introduction Aims and Objectives Overview Endogenous and Exogenous Attentional Systems Neural Correlates of Attention Experiment Method and Materials Results Discussion Experiment Method and Materials Results Discussion Experiment Method and Materials Results Discussion General Discussion 31 References 33 Appendices 63 A EEG Workflow Routine 64 A.1 Data Pre-Processing MATLAB Files A.2 Data Processing MATLAB Files vi

7 CONTENTS A.3 Data Visualization MATLAB Files A.4 Data Analysis MATLAB Files vii

8 List of Tables 5.1 Experiment 1: Electrodes defining Regions of Interest Experiment 1: Hemisphere by Due Direction Results Experiment 1: Pre-Cue Visual Spatial Task Experiment 2: Electrode Sensors Experiment 2: Cue Meaning by Cue Order Results Experiment 2: ISI by Cue Meaning Results Experiment 2: Visual Memory Task viii

9 List of Figures 5.1 Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 500ms. This was followed by a cue comprised of two arrows that indicated which side the Target Gabor would appear. This was displayed for 500ms. The ISI lasted ms and was followed by the presentation of the Target Gabor and a task-irrelevant Gabor on either side of a central fixation. The encoding period lasted 300ms before a maintenance period of ms. The trial ended with a reproduction period Bar chart showing absolute values of the JNDs for T L in Blue and T R in Red. There were no significant differences between cue directions Grand average ERP waveforms of both cue-locked (top) and stimuluslocked (bottom). Left hemisphere electrode sensors are shown on the left hand column and right hemisphere electrode grand averages on the right hand column. The T L condition is shown in Blue and the T R condition is in Red. Scalp topographies averaged over a 150ms - 250ms period following the onsets are shown on the right. There was a significant difference of hemisphere and cue direction for the cue-locked analysis Grand average Time-Frequency wavelets of the Left (left hand column) and Right hemisphere (right hand column) time-locked to the cue. The T R condition is shown on top and the T L is at bottom. There were no significant differences in alpha-band power between ipsilateral and contralateral sites Grand average Time-Frequency wavelets of the Left (left hand column) and Right hemisphere (right hand column) time-locked to the stimulus. The T R condition is shown on top and the T L is at bottom. There were no significant differences in alpha-band power between ipsilateral and contralateral sites ix

10 LIST OF FIGURES 5.6 Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 300ms. This was followed by a cue that indicated whether the upcoming cue was a Target ( ) or Non-Target ( ). This was displayed for 500ms. The ISI varied in length and was either 300ms, 600ms, or 900ms depending on the block. This was followed by the presentation of a Gabor. The Gabor was presented for 500ms before being followed by a blank screen for 500ms. Another cue-stimulus pair with the same timing as the first preceded a maintenance period of 1000ms. The trial ended with a reproduction period. This design created two different trial types: the Attend First on the left (T 1 NT 2 ) and the Attend Second trial type of the right(nt 1 T 2 ) Bar chart showing absolute values of the JNDs for T 1 in Blue and T 2 in Red over the three ISI conditions (300ms, 600ms, 900ms). There was a significant difference in cue order Grand average ERP waveforms cue-locked for the three ISI conditions (300ms, 600ms, 900ms). Blue waveforms represent the Attend First trial type and the red waveforms the Attend Second trial type. Sold lines show Target conditions and the dashed lines the Non-Target. There was a significant difference in cue order (Cue First versus Cue Second) and cue meaning, Target versus Non-Target Grand average ERP scalp topographies from 150ms - 250ms post-cue onset. Top row shows the topographic map collapsed across CUE 1 and the bottom row shows CUE Grand average ERP scalp topographies from 150ms - 250ms post-cue onset. Top row shows the topographic map collapsed across the Target conditions and the bottom row shows the Non-Target conditions Grand average Time-Frequency wavelets of the Attend First condition (T 1 NT 2 ) and Attend Second (NT 1 T 2 ). Cue onset is marked at 0 seconds with a white line. The ISI conditions of 300ms, 600ms, and 900ms are shown in the left, middle, and right hand columns, respectively.. 57 x

11 LIST OF FIGURES 5.12 Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 300ms. This was followed by a cue that indicated whether the upcoming cue was a Target ( ) or Non-Target ( ). This was displayed for 500ms. The ISI was fixed at 600ms and this was followed by the presentation of a Gabor. The Gabor was presented for 500ms before being followed by a blank screen for 500ms. Another cue-stimulus pair with the same timing as the first preceded a maintenance period of 1000ms. The trial ended with a reproduction period. This design created two different trial types the Attend First on the left (T 1 NT 2 ) and the Attend Second trial (NT 1 T 2 ) Bar chart showing absolute values of the JNDs for T 1 in Blue and T 2 in Red over the two conditions T 80 on the left and T 20 on the right. There was a significant difference in cue order Grand average ERP waveforms cue-locked for the two probability conditions. Blue waveforms represent the Attend First trial type and the red waveforms the Attend Second trial type. Sold lines show the Target condition and the dashed lines the Non-Target conditions Grand average Time-Frequency wavelets of the Cue First condition with T 1 on the left and NT 1 on the right. Cue onset is marked at 0 seconds with a white line. The probability condition of 80 percent is shown on the top and the 20 percent on the bottom Grand average Time-Frequency wavelets of the Cue First condition with T 2 on the left and NT 2 on the right. Cue onset is marked at 0 seconds with a white line. The probability condition of 80 percent is shown on the top and the 20 percent on the bottom A.1 EEG processing workflow. Purple : Pre-Processing EEG data. Blue : Optional Marker Re-assignment. Green : Behavioral data processing. Orange : ERP processing. Red : Time-Frequency processing. Yellow : Data Visualization. Dashed arrows represent optional processing steps. 67 xi

12 Chapter 1 Introduction Navigating through a dynamic environment requires maintaining and updating a representation of that environment, in order to enable information processing and behavioral adaptation to the current context. Memory and attention are closely associated and function to enable this updating to occur. The ability to focus and attend to a task while successfully ignoring distractions interacts with memory, serving to limit the amount of information that can be processed (Mayer et al., 2007; Zanto & Gazzaley, 2009). Attention is mediated by both top-down, endogenous, and bottom-up, exogenous, influences. Although differences between endogenous and exogenous attentional mechanisms have been exploited behaviorally, there has been little research that has examined the underlying neural substrates. Recent neurophysiological evidence suggests that endogenous and exogenous mechanisms rely on different neural networks (Hopfinger & West, 2006). Other studies have concluded that these attentional shifts are supported, in part, by the same underlying structure (Mayer, Dorflinger, Rao, & Seidenberg, 2004). Exploring the neural differences between these systems, in a cued 1

13 CHAPTER 1. INTRODUCTION visual memory task, in which exogenous and endogenous attentional processes might exert distinct influences, can provide greater insight into their neural underpinnings. Neural oscillations as recorded with electroencephalography (EEG) within 8-14Hz encompass the alpha-band range. Alpha rhythms are thought to play a role in attentional processing. The growing literature supports the view that alpha-band oscillations are associated with initial stages of stimulus processing, directing information related to attention and anticipation (Fu et al., 2001; Foxe, Simpson, & Ahlfors, 1998; Herrmann, Grigutsch, & Busch, 2005). Growing evidence also suggests that neural oscillations influence the magnitude of event-related potentials (ERPs), which have been used to index both sensory and cognitive processing (Fellinger, Gruber, Zauner, Freunberger, & Klimesch, 2012; Freunberger et al., 2008; Gruber, Klimesch, Sauseng, & Doppelmayr, 2005). This paper attempts to demonstrates the effects that endogenous and exogenous systems have on attentional processing of visual information. My psychophysical data, together with the neurophysiological results, will help create a greater understanding of attentional mechanisms and a more complete picture of visual processing, from which the interaction with attention will emerge. 1.1 Aims and Objectives The main objective of this study is to examine the roles that endogenous and exogenous mechanisms of attention have on visual processing and memory. This objective is achieved through the following goals: - The development of an EEG processing workflow. This pipeline began with contin- 2

14 CHAPTER 1. INTRODUCTION uous raw EEG collected during data acquisition and takes it through preprocessing, averaging at the individual and group level, data visualization, and preparation for data analysis. - The characterization of alpha-frequency network dynamics of exogenously and endogenously driven attentional control mechanisms. This is achieved by testing whether voluntary attention, measured at an expected cue, drives alpha-band oscillations and ERPs differently than involuntary attention, measured at a non-expected cue. - The examination of differences in endogenous and exogenous attentional processes on behavioral performance. This is achieved through testing whether endogenous attentional mechanisms enhance memory recall. To understand exogenous and endogenous shifts in attention, I used visual working memory tasks in which selective attention supresses sensory information that is to be ignored and enhances information cued to be remembered. These tasks have spatial and temporal properties that have has been examined behaviorally and electrophysiologically (Huang & Sekuler, 2010a; Payne, Guillory, & Sekuler, in press). 1.2 Overview In the following section, the general concepts of orienting of attention are described. The behavioral manifestation of neural processes is important for understanding attention and visual working memory as it can reveal the details of how data are composed and processed. 3

15 CHAPTER 1. INTRODUCTION In the next sections, a study of the neurophysiological processing of visual information is examined in closer detail. Alpha-band oscillations and ERPs are described in the context of visual processing. Chapter 2 and Chapter 3 describe previously completed experiments with the analysis performed in this thesis using the pre-existing data. In Chapter 2, the first of three experiments is introduced. In Experiment 1, the lateralization and the time course of alpha-band oscillations using a visual-spatial working memory task is examined. The design, methodology, and implementation of the experiment are discussed and the results and their implications are reviewed. Experiment 2 is described in Chapter 3 where the role of expectancy and anticipation in modulating attentional processing is explored. Experiment 3, described in Chapter 4, further investigates the influence that expectancy, a top-down factor, has in controlling information processing. The thesis concludes with a review of the research design and the methods exercised in these studies. Future research studies and direction of working memory and attention in the visual domain are discussed in Chapter Endogenous and Exogenous Attentional Systems The orienting of attention is comprised of endogenous mechanisms that are topdown, voluntary processes, and exogenous mechanisms that are involuntary and bottom-up driven, by external stimuli (Wolfe & Horowitz, 2004; Desimone & Duncan, 1995). These attentional mechanisms influence how the environment is per- 4

16 CHAPTER 1. INTRODUCTION ceived. Differences between these two systems have been established through behavioral measures that show exogenous mechanisms as less susceptible to interference, are processed faster, and are not sustained over time (Cheal & Lyon, 1991; Müller & Rabbitt, 1989; Posner & Cohen, 1984). Endogenous and exogenous systems modulate performance by directing the flow of information processing. Using a visual-spatial cueing paradigm, the behavioral measure of response latency exposed improvements in information processing when attention is oriented in visual space (Posner & Cohen, 1984). Performance is enhanced when a cue is valid (correctly predicts the location of a target stimulus), and reduced when the cue is invalid (incorrectly predicts the target stimulus location). Orienting of attention refers to the subject s shift of focus based on the cue. 1.4 Neural Correlates of Attention EEG data have been used to identify perceptual processing through the analysis of ERPs. ERPs are a reflection of neural activity time-locked to a specific event that have been generated by networks of neurons. These positive and negative going deflections in the waveform are thought to represent information processing. ERP studies have identified components that are enhanced by attention providing information on their nature and timing (Polich, 2007; Eimer, 1996; Luck, Fan, & Hillyard, 1993). Early ERP components are thought to reflect the initial stages of information processing, such as sensorimotor and attentional activity. In particular, the N2, a negative going waveform that occurs approximately 200ms after stimulus onset, features an enhancement of the amplitude for target items and a suppression for irrelevant items (Luck, 2005b, 2005a). A related component, the N2pc, has also been 5

17 CHAPTER 1. INTRODUCTION shown to be modulated by attentional selection and is commonly used as a metric of attention in the visual-spatial literature (Eimer, 1996; Hickey, McDonald, & Theeuwes, 2006). The N2pc describes the topographic organization of the negative polarity, with a greater magnitude mainly observed over visual cortex (contralateral to attended stimulus). There has been considerable interest in alpha-band oscillations and their relationship to selective attention. EEG time-frequency analysis has revealed that neural oscillations and their synchronization may reflect communication between and within regions. Neural oscillations in the alpha-band frequency (8-14 Hz) have been shown to be actively modulated by attention (Thut, Nietzel, Brandt, & Pascual-Leone, 2006; Yamagishi et al., 2003; Klimesch, Doppelmayr, Russegger, Pachinger, & Schwaiger, 1998). It has been postulated that the inhibition of task-irrelevant processing is accomplished by the rhythmic firing of neurons that results in large amplitude alpha oscillations (Klimesch, Sauseng, & Hanslmayr, 2007). Research has established that task relevant stimuli elicit a reduction in alpha power (event-related desynchronization) associated with attentional anticipation, and an increase in alpha power for task-irrelevant stimuli (Freunberger, Fellinger, Sauseng, Gruber, & Klimesch, 2009; Worden, Foxe, Wang, & Simpson, 2000). ERP waveforms are believed to be the product of neurons firing together leading to neural synchronization. The post-synaptic, extracellular signal that is propagated is a waveform with properties of phase, frequency, and magnitude. The ERPs computed at the scalp are a reflection of this signal. The magnitude of ERP components reflect both the strength of the phase synchronization and the size of the synchronous network (Herrmann et al., 2005; Roach & Mathalon, 2008). Low frequency oscillations in the alpha-band range have been correlated with ERP components such as the 6

18 CHAPTER 1. INTRODUCTION N2, affecting the magnitude of the amplitude (Müller & Anokhin, 2012; Fan et al., 2007; Lee, Yu, Wu, & Chen, 2011). These neural oscillations can be categorized as evoked, induced or spontaneous activity. Calculating total power, which encompasses all three, involves applying time-frequency analysis to the EEG signal capturing activity with similar latency information averaged over trials (evoked power) and activity occurring on an individual trial basis (induced power). Evoked activity is generated by the phase-locking that occurs with the presentation of sensory input, where as induced activity is not phaselocked to the stimulus (Basar, Schurmann, Basar-Eroglu, & Karakas, 1997; Quiroga & Schürmann, 1999). Within the scope of this thesis, total power was used during analysis. The magnitude of alpha-band event related synchronization (ERS) immediately following the presentation of the stimulus was interpreted as reflecting the evoked response because of the close temporal relationship with the sensory input. The alpha ERS preceding a stimulus was indicative of the strength involved in the induced response. The alpha ERS preceding a stimulus was assumed to index the strength of the induced response, an assumption that was confirmed by exploratory analysis. Together ERPs, neural oscillations, and behavioral performance reveal important information about the processing of sensory information and the integration of endogenous and exogenous data. 7

19 Chapter 2 Experiment 1 Our perceptions of the world are not generated by a passive process but are based on attention. Attention can not be distributed everywhere infinitely because of the limited resources that would be required to process the vast amount of sensory input. In selectively focusing attention, resources can be directed using the guidance of current goals. Complex control processes, such as attention, shape perception. Selective attention also plays a pivotal role in memory, directing what information gets processed and subsequently remembered. Deficits in attentional systems that serve as a hallmark for such disorders as Attention-Deficit Hyperactivity Disorder and Schizophrenia emphasize the importance of understanding the underlying mechanisms to mitigate the effects (Schweitzer, Fassbender, Lit, Reeves, & Powell, 2012; Luck & Gold, 2008). Research has also reported on the age related declines with attention and memory and can also benefit from the knowledge of the neural processes (Zanto et al., 2011; Zanto, Toy, & Gazzaley, 2010). The use of a directional cueing paradigm enables the study of neural processing in regard to space. When attention is directed to a particular area in space, this 8

20 CHAPTER 2. EXPERIMENT 1 enhances relevant and inhibits irrelevant spatial information to facilitate information processing through the improvement of the signal-to-noise ratio. As the subject is informed where the target stimulus will appear, anticipation and expectancy help in the deployment of attentional resources. The visual-spatial working memory paradigm used in this experiment uses valid cues to direct attention to the area in space where the target stimulus appears. Using alpha-band power and the N2 component as a marker of attention, the magnitude of the response was used as a measure of attentional processing. Recall during the memory task measured the error in subject s reproduction of the target stimulus. I hypothesize that endogenous attentional mechanisms in the form of expectancy will influence the pre-stimulus alpha band oscillation pattern, where ipsilateral neural activity would have the characteristic markers of unattended information processing (greater alpha power) and the contralateral neural activity would exhibit an enhancement in attentional processing (greater N2 amplitude). I predict that this difference would be more pronounced at the stimulus than at the cue because subjects would have a built up expectancy about the location of the stimulus. 2.1 Method and Materials Subjects. Thirteen subjects participated in Experiment 1. Two subjects were excluded from analysis due to excessive EEG artifact (epoch rejection rate >50%). Of the remaining 11 participants, nine were female (mean age, 23.2 years; range, years; SD, 6.46). All of the participants signed informed consent and received monetary compensation for their participation in the study. Visual acuity was measured using Snellen targets and Pelli-Robson charts. Only subjects with normal or corrected-to- 9

21 CHAPTER 2. EXPERIMENT 1 normal vision proceeded with the experiment. All subjects were right-hand dominant as determined by the Edinburgh Handedness Survey and had no neurological or psychiatric problems. Stimuli and Apparatus. The visual stimuli used in all tasks were one-dimensional (1D) Gabor patches generated and displayed using MATLAB 2007b (MATLAB, 2007) in conjunction with the Psychophysics toolbox version beta (Brainard, 1997). Each Gabor was composed of a vertical sinusodal luminance grating that was windowed using a circular Gaussian carrier. A full description regarding the construction of the Gabor is provided in Huang and Sekuler (2010a). Experimental Paradigm. Each individual s spatial frequency discrimination threshold was determined using an adaptive tracking algorithm called QUEST (Watson & Pelli, 1983). The threshold was established through the presentation of two vertical 1D Gabors serially, where the subject was required to make a forced-choice identification of the Gabor with the higher spatial frequency. For each trial, two Gabors would be displayed for 300ms each at central fixation. The Just Noticeable Difference (JND) calculated the minimum change between two spatial frequencies required for a subject to detect a difference between two Gabors. Each subject s discrimination threshold was used to normalize the recall errors made during the task. Subjects completed three consecutive runs of QUEST, where the lowest score of the three was used as that subject s discrimination threshold. Subjects were presented with a pseudorandom sequence of 160 trials of a visual working memory task. For a given trial, participants were cued to either attend to the right (<<), T R, or the left (>>), T L, for the upcoming Gabor. Subjects first 10

22 CHAPTER 2. EXPERIMENT 1 saw a cue indicating to either attend to the left or the right displayed for 500ms, then following a ms interstimulus interval (ISI), two Gabors were presented simultaneously for 300ms. Following the presentation of both stimuli, the subject then had to reproduce the Gabor from the attended location by adjusting the spatial frequency of a Gabor until it matched the target using a slider bar controlled by the mouse at the bottom of the screen (see Figure 5.1). The difference in spatial frequency between the two Gabors was fixed at four JNDs and was calculated from the subject s discrimination threshold. Data Acquisition and Preprocessing. Scalp EEG was recorded continuously using a high-density, 129-channel Geodesic electrode system, with a sampling rate of 250Hz and a Cz reference. Electrode channels were adjusted for a scalp impedance of <50Ω. EEG was bandpass filtered at 0-125Hz. Electrode channels were re-referenced offline to the average using MATLAB R2011a (MATLAB, 2011). Preprocessing of the data was performed using the EEGLAB toolbox version b extension for MAT- LAB (Delorme & Makeig, 2004). Data was both cue-locked and stimulus-locked. Continuous EEG data was segmented by time-locking to the cue onset with an epoch spanning.5 sec before cue onset to 1.6 sec after it. The stimulus-locked epoch spanned the time window of 1800sec prior to stimulus onset to 600ms after stimulus onset. This range captured initial trial fixation up to stimulus offset. EEG was corrected for eye-blinks using independent component analysis (ICA). Visual inspection of trials was performed to exclude trials with excessive artifact. Individual subject data were then exported to the FieldTrip toolbox version for both spectral and ERP analysis (Oostenveld, Fries, Maris, & Schoffelen, 2011) (see Appendix A). Regions of Interest (ROI) were defined through consultation with previous research 11

23 CHAPTER 2. EXPERIMENT 1 in the field and visual inspection of scalp topographies (Herrmann et al., 2005). The ROIs encompassed electrode sensors in the parietal region and included 12 sites. To assess lateralized shifts in selective attention, the midline region was excluded from the analysis. Table 5.1 describes the electrodes that were used to define the Left and Right posterior regions using the Geodesic Sensor Net 128 Channel Map. Behavioral Analysis. As described in Huang and Sekuler (2010a), the raw error made on each trial is defined by the difference between (1) the spatial frequency of that trial s target Gabor and (2) the spatial frequency that the subject reproduced. Following the method of Huang and Sekuler (2010b), the raw errors were normalized relative to that subject s Weber fraction. The absolute normalized reproduction error (nre) expressed in JNDs, was used during analysis as the direction of each subject s error was not of interest. EEG Event-Related Potential Analysis. EEG data from the epochs were low-passed filtered at 15Hz and high-passed filtered at.5hz. EEG data were baselined-corrected using the 200ms activity preceding the onset of the cue for the cue-locked analysis and 200ms preceding the onset of the stimulus for the stimulus-locked analysis as recommended by Luck (2011). Averages were calculated, time-locked to cue onset and stimulus onset. Identifying the N2 peak amplitude across the ROIs was done by averaging the electrode sensors of interest for each ROI per subject. Then a time window between 150ms to 250ms was used to search for the most negative peak. For each subject the data were normalized across all conditions. 12

24 CHAPTER 2. EXPERIMENT 1 EEG Spectral Analysis. EEG epochs were analyzed with a complex Morlet wavelet decomposition implemented using FieldTrip to examine alpha response to the cue and stimulus presentation. Focusing on the alpha-band, the frequency range of 8-14 Hz was examined. The time of interest for the cue was limited to 200ms post-cue presentation. Examination of the alpha response at the stimulus was confined to a 200ms pre-stimulus interval. These periods are consistent with previous literature that reported alpha activity associated with anticipation of the stimulus and visual encoding (Freunberger et al., 2009; Klimesch, Fellinger, & Freunberger, 2011). Alpha power was normalized within subject to eliminate between subject differences. 2.2 Results Behavioral Analysis. There were no significant differences in the reproduction error between the cue directions, T R (M = JNDs, SD =.108) and T L (M = JNDs, SD =.160), t (10) = , p =.163. Figure 5.2 shows the errors in JNDs. Similar reproduction errors across cue directions suggest that the cue helped in directing attention to the target location. Event-Related Potential Analysis: cue related activity. A two-way Repeated Measures Analysis of Variance (ANOVA) with factors hemisphere (Left, Right) and cue direction (Left, Right) was calculated using N2 amplitude. There was a significant main effect of hemisphere, F (1,10) = 9.970, p =.010, and cue direction: F (1,10) = p =.039, but not a significant interaction, F (1,10) = p =.715. Figure 5.3 (top), shows that the Left hemisphere had greater negativity over the N2 time period (M = uv, SD =.134) compared to the Right hemisphere (M = 13

25 CHAPTER 2. EXPERIMENT uv, SD =.134) and T R also showed a greater negativity at N2 (M = uv, SD =.115), shown in Red in Figure 5.3, in comparison to T L (M =.273 uv, SD =.115), shown in Blue. The topographical maps shows the average waveform response across the 150ms to 250ms time window following cue onset. Event-Related Potential Analysis: stimulus related activity. A two-way Repeated Measures ANOVA with factors hemisphere (Left, Right) and cue direction (Left, Right) was calculated using N2 amplitude. There were no significant main effects of hemisphere, F (1,10) = 0.088, p =.772 or cue direction, F (1,10) = 1.056, p =.328. There was a significant interaction, F (1,10) = , p <.001. Figure 5.3 shows that in the Left hemisphere, the T L condition showed a greater negativity at N2 compared to the T R condition. Also evident is that the T R condition showed greater negativity at N2 on the Right hemisphere compared to thet L condition (see Figure 5.3). Table 5.2 summarizes condition means for the interaction. These results are inconsistent with the N2pc literature of attentional shift that have reported contralateral enhancement and ipsilateral suppression at the cue. Spectral Analysis: cue related activity. A two-way Repeated Measures ANOVA with the same hemisphere and cue direction parameters described in the ERP analysis were used in this analysis with alpha power. There were no main effects of hemisphere, F (1,10) = 2.572, p =.140 or cue direction F (1,10) = 2.516, p =.144. There was no significant interaction, F (1,10) = 1.53, p =.244. Figure 5.4 shows the time-frequency plots for cue direction, with the T R condition on top and the T L condition on the bottom. The Left Parietal sites defining the Left hemisphere are located in the Left hand column and the Right Parietal sites defining 14

26 CHAPTER 2. EXPERIMENT 1 the Right hemisphere are located on the right with the cue onset marked at 0 seconds. Spectral analysis: stimulus related activity. A two-way Repeated Measures ANOVA with the same parameters used in the analysis of cue activity was used for this analysis measuring alpha power. Figure 5.5 depicts the time-frequency plots for this analysis. There were no main effect of hemisphere, F (1,10) = 4.659, p =.056 (where the Left hemisphere is shown in the left hand column of Figure 5.5 and the Right hemisphere is on the right hand column) or cue direction, F (1,10) =.094, p =.766, with T R shown at the top in Figure 5.5 and T L on the bottom. There was also no significant hemisphere by cue direction interaction, F (1,10) = 3.372, p = Discussion In this cued visual-spatial working memory task, endogenous attentional mechanisms were examined. The deployment of attention associated with the N2pc component was not observed at the presentation of the predictive cue. These results are consistent with a body of literature that failed to find a contralateral/ipsilateral difference, possibly because of the type of stimuli used to cue the subject, such as letters compared to arrows. It could also be the case that this negativity is a reflection of the focus of attention on the cue itself and may not be related to the orienting of spatial attention (Velzen & Eimer, 2003; Woodman, Arita, & Luck, 2009). Other explanations for failing to find an attentional shift could be due to the time of interest. Other studies have focused on different time-windows of interest. The early-directing attention negativity (EDAN) has been found at later latencies during a cue-directing task and possibly is a better representation of shifts in attention com- 15

27 CHAPTER 2. EXPERIMENT 1 pared to early components that may represent the focus of attention. The anterior directing attention negativity (ADAN) that is present in the frontal electrode sites has also been shown to capture shifts in attention (Talsma, Sikkens, & Theeuwes, 2011; Talsma, Slagter, Nieuwenhuis, Hage, & Kok, 2005). Previous research involving split-brain patients suggest that visual-spatial information processing has more of a right hemisphere lateralization (Gazzaniga, 1970). This can perhaps explain some of the observed differences in N2 amplitude between the left and right hemispheres. In this present study, no difference in alpha-band power at the cue was found. It could be that each direction was equally likely to be presented and therefore the alpha-band power response observed at the cue is a response to the presentation of the arrows (evoked power) and not a reflection of the anticipation of which visual field the target Gabor would appear. The current analysis differs in several way from the analysis in Huang and Sekuler (2010a), which used the same task. These differences are outlined in Table 5.3. In examining the time period associated with peri-stimulus activity, a clearer picture of anticipatory alpha-band power was sought. Inconsistent with results from other spatial cueing paradigms, no increase in alpha power over the ipsilateral side of the stimulus was seen. These results could be attributed to the electrodes that were selected and collapsed across. Using group grand-averages, the areas that were observed to a show pronounced response over occipital-parietal sites were selected. In using grand-averages, this could have inadvertently obscured the differences in scalp topographies of individual subjects, who might have greater latencies before reaching the maximum alpha-band power peak. These results show that the stimulus and cue evoke an N2 response, an indicator of attentional processing. The N2 is most likely the result of exogenous influences as 16

28 a response to sensory information. CHAPTER 2. EXPERIMENT 1 17

29 Chapter 3 Experiment 2 In order to understand the temporal dynamics of selective attention, a second experiment was conducted. By examining visual attention over time, top-down expectancies about an entire trial can be used. In taking a macrolevel approach to each trial, the first cue in the series of a two cue-stimulus pair is unpredictable, but when that information is known, the second cue then serves as a completely predictable attentional marker, providing no additional information for the trial. In terms of economic trade offs, a subject might be best served by taking advantage of the endogenous information of the trial, conserving attentional resources by not attending to the second cue. I predicted that the neural response to the second cue would be characteristic of neural activity observed when sensory information is not attended to. 18

30 CHAPTER 3. EXPERIMENT Method and Materials Subjects. Fourteen new subjects were recruited and participated in Experiment 2. Two subjects were excluded from analysis due to excessive EEG artifact (epoch rejection rate >50%) and of the remaining 12 participants, seven were female (mean age, 22 years; range, years; SD, 3.54). All of the participants signed informed consent and received monetary compensation for their participation in the study. Visual acuity was measured using Snellen targets. Only subjects with normal or corrected-to-normal vision proceeded with the experiment. All subjects were righthand dominant as determined by Edinburgh Handedness Survey and reported no neurological or psychiatric problems. Stimuli and Apparatus. The stimuli used in this experiment were 1D Gabors calculated in the same manner as Experiment 1. Experimental Paradigm. The same thresholding procedures that were used for Experiment 1 were also applied to this experiment. Subjects were presented with a pseudorandom sequence of 160 trials of a visual working memory task. For a given trial, participants were cued to either attend ( ) or ignore ( ) the upcoming Gabor. For a single trial, subjects first saw a cue indicating to either attend to the next stimulus or to ignore the upcoming stimulus, the stimulus would be presented followed by another cue instructing the subject again to either ignore or attend the next stimulus. This resulted in two types of trials, one in which the first cue in the sequence was an attend cue with the second an ignore cue (T 1 NT 2 ). As shown in Figure 5.6, the other trial type consisted of an ignore cue proceeded 19

31 CHAPTER 3. EXPERIMENT 2 by an attend cue, NT 1 T 2. Following the presentation of both stimuli, the subject then reproduced the target Gabor from the attend condition. This was achieved by adjusting the spatial frequency of a Gabor until it matched the target using a slider bar controlled by the mouse at the bottom of the screen. The trial dynamics created a situation where the subject could predict the first cue with a 50 percent probability to be either an attend to or ignore cue. The second cue in the series could then be predicted with a hundred precent accuracy, establishing an expectancy for the second cue. Subjects completed three separate sessions that differed in the pre-stimulus window length. Counter-balanced across subjects, the inter-stimulus interval (ISI) varied as 300ms, 600ms, and 900ms. Data Acquisition and preprocessing. This experiment used the same data acquisition and preprocessing procedures as that described for Experiment 1. Continuous EEG data was segmented by time-locking to the cue onset with an epoch spanning.5 sec before cue onset to 2.5 sec following it. Behavioral Analysis. Behavioral performance was calculated using the methods described for Experiment 1. EEG Event-Related Potential Analysis. As described in Experiment 1, this experiment contained the same EEG ERP analysis and procedures with the exception that the analysis was confined to activity at the cue. The number of electrodes used in the analysis included 23 parietal-occipital electrodes shown in Table 5.4. EEG Spectral Analysis. As described in Experiment 1, this experiment contained the 20

32 CHAPTER 3. EXPERIMENT 2 same EEG Time-Frequency analysis and procedures with the exception that analysis was confined to the cue. The number of electrodes used for the analysis involved 23 parietal-occipital electrodes listed in Table Results Behavioral Analysis. A repeated measures ANOVA with two factors, ISI (300ms, 600ms, 600ms) and cue order (First, Second) was analyzed using JNDs. There was a main effect of order, F (1,11) = p <.001, where subjects performed with greater accuracy at reproducing the target Gabor when it was presented Second in the series (M = JNDs, SD =.070) in comparison to the First (M = JNDs, SD =.079), as shown in Figure 5.7. There was no main effect of ISI, F (2,22) = 1.034, p =.372. That is, subjects performance across the three ISI intervals were comparable. There was no significant interaction effect between cue order and the ISI, F (2,22) = 0.209, p =.813. Event-Related Potential Analysis: cue related activity. A Repeated Measures ANOVA with three factors, ISI (300ms, 600ms, 900ms), cue meaning (Target, Non-Target) and cue order (First, Second) was run using the N2 amplitude. There wasn t a main effect of ISI, F (2,22) =.454, p =.641. There were main effects of both cue meaning, F (1,11) = 7.010, p =.023 and cue order, F (1,11) = , p =.001. As shown in Figure 5.8 with the ERP waveforms, and in Figure 5.9 with the topographical maps, the response to the First cue had a greater N2 magnitude (M = uv, SD =.082) compared to the ERP N2 response to the Second cue (M =.497 uv, SD =.082). The Target cues generated a greater N2 magnitude (M = uv, 21

33 CHAPTER 3. EXPERIMENT 2 SD =.096) compared with the cue for the Non-Target (M =.253 uv, SD =.096), as seen in Figure There were no significant interactions of cue meaning by ISI, F (2,22) = 0.288, p =.753, cue order by ISI, F (2,22) = 0.576, p =.570, cue order by cue meaning, F (1,11) = 0.175, p =.684, or cue order by cue meaning and ISI, F (2,22) = 1.006, p =.382. Spectral Analysis: cue related activity. An overall ANOVA for repeated measures using alpha power showed a significant difference between alpha power for cue meaning, F (1,11) = 6.716, p = Shown in Figure 5.11, the mean alpha power during the Target cue decreased (M =.160 power, SD =.062) during the Non-Target cue (M = power, SD =.062). There was no significant difference in cue order, F (1,11) = 0.0, p =.996 or the ISI, F (2,22) =.064, p =.938. There were significant interactions between cue order and cue meaning, F (1,11) = , p =.006 (shown in Table 5.5), and cue meaning by ISI, F (2,22) = 3.53, p =.047, as summarized in Table 5.6. No significant interactions were found between cue order by ISI, F (2,22) =.547, p =.568, or among cue order by cue meaning and ISI, F (2,22) = 0.988, p = Discussion In this experiment the role of expectancy was examined over time using a visual working memory task. Using a set of two cue-stimulus pairs, subjects can obtain all the relevant information about the dynamics of the trial from the presentation of the first cue and setting up an expectancy for the second cue. Table 5.7 shows the differences in data analysis performed by Payne et al. (in press), which focused on 22

34 CHAPTER 3. EXPERIMENT 2 the alpha-band power at the stimulus. In assessing expectancy over time, a difference in task difficulty was introduced that was reflected in the behavioral results. In a trial where the First cue (T 1 NT 2 ) instructed participants to attend to the upcoming stimulus, there was the addition of distractor stimulus as well as the task of holding the Gabor pattern in memory over a longer period of time. A subject then had to work to suppress the irrelevant information in addition to maintaining the Target Gabor in memory until it was to be reproduced. The second type of trial (NT 1 T 2 ), involved less cognitive load in that the first Gabor could be passively viewed until the presentation of the second Gabor, where upon the subject had to actively view and remember the Target s spatial frequency. The N2 component appears to be sensitive to attention, where the amplitude is attenuated for the predictable, expected Second cue compared to the unpredictable First cue. This difference is consistent with the proposition that a cue (First Cue) whose meaning is unpredictable tends to demand greater attention than does a predictable cue (Second Cue). Across Cue Meaning (Target vs. Non-Target) the difference in N2 amplitude is also consistent with the literature on selective attention. There is a suppression in the amplitude for task-irrelevant stimuli. The processing of color occurs within the first 100 ms and elicits a positive deflection on the ERP, P1 component (Hillyard & Münte, 1984). This gives the subject enough time to assess the meaning of the cue and its relevance to the upcoming stimuli. It seems unlikely that the difference in N2 amplitude is related to the color of the cue, but involves the processing of the cue meaning. Alpha-band power at the cue reflects both the predictability of the Second cue versus the First, but also the difference in cue meaning of a Target cue and the Non- 23

35 CHAPTER 3. EXPERIMENT 2 Target cue. The greater alpha-band power of the cue meaning and order captures the association between alpha power and the N2 ERP component, where the total alpha-band power modulates the amplitude. The relationship between event-related oscillations and event-related potentials is a new area of research that has been gaining interest (Balconi & Pozzoli, 2007). 24

36 Chapter 4 Experiment 3 In Experiment 3, the probability of trial type (Attend First versus Attend Second) was manipulated on a block level. This manipulation was designed to follow-up on the results of Experiment 2 and determine if probability and predictability modulate selective attention within a trial. I hypothesized that the probability would effect expectancy and anticipation of the first cue presented in the trial. 4.1 Method and Materials Subjects. Twelve new subjects participated in Experiment 3. Six were female (mean age, 30 years; range, years; SD, 2.87). All of the participants signed informed consent and received monetary compensation for their participation in the study. Visual acuity was measured using Snellen targets and Pelli-Robson charts. Only subjects with normal or corrected-to-normal vision proceeded with the experiment. All subjects were right-hand dominant as determined by Edinburgh Handedness Survey and had no neurological or psychiatric problems. Two subjects were excluded from 25

37 CHAPTER 4. EXPERIMENT 3 further data analysis because in two of the the four conditions they made large errors in reproduction (SD >2). Stimuli and Apparatus. The stimuli used in this experiment were the 1D Gabors calculated in the same manner as Experiment 1. Experimental Paradigm. The same thresholding procedures that were used for Experiment 1 were also applied to this experiment. The design of this experiment was similar to Experiment 2, but with some notable exceptions. Instead of the three ISI conditions, ISI was fixed at 600ms. The probability of trial type, Attend First (T 1 NT 2 ) and Attend Second (NT 1 T 2 ), varied according to blocks, where in a single block 80% of the trials would be of T 1 NT 2 and the remaining 20% of NT 1 T 2 trial type. In the other block 80% of the trials were NT 1 T 2 and 20% were T 1 NT 2. In varying the probability, to ensure that there were enough trials in the 20% condition, 80 trials seemed sufficient as that corresponded to the number of trials per condition in Experiment 2. The 80% condition, thus contained 320 trials. Subjects were informed before the start of each block that there would be more of one type of trial than the other. The experimental paradigm is shown in Figure Data Acquisition and preprocessing. This experiment used the same data acquisition and preprocessing procedures as described for Experiment 1. Continuous EEG data was segmented by time-locking to the cue onset with an epoch spanning.5 sec before cue onset to 2.5 sec after it. 26

38 CHAPTER 4. EXPERIMENT 3 Behavioral Analysis. Behavioral performance was calculated using the methods described for Experiment 1. EEG Event-Related Potential Analysis. As described for Experiment 1, this experiment contained the same EEG ERP analysis and procedures. The 23 parietaloccipital electrodes used in this experiment are listed in Table 5.4. EEG Spectral Analysis. As described for Experiment 1, this experiment contained the same EEG Time-Frequency analysis and procedures. The 23 parietal-occipital electrodes used in this experiment are listed in Table Results Behavioral Data. A repeated measures ANOVA with two factors, cue order (First, Second) and probability (80%, 20%) was analyzed using JNDs. There was a significant main effect of cue order, F (1,9) = 5.117, p =.050. Figure 5.13 shows the that First cue was greater in the normalized reproduction error (M = JNDs, SD =.181) than the Second cue (M = JNDs, SD =.196). This might be attributed to task difficulty. There was no significant main effect of probability, F (1,9) =.243, p =.634 or interaction of cue order by probability, F (1,9) =.597, p =.459. Event-Related Potential Analysis: cue related activity. A three-way Repeated Measures ANOVA with factors probability (80%, 20%), cue meaning (Target, Non-Target), and cue order (First, Second) was run using N2 amplitude. There was a main effect of 27

39 CHAPTER 4. EXPERIMENT 3 cue meaning, F (1,9) = 5.396, p =.045, with Target cues eliciting a larger N2 response (M = uv, SD =.104) than Non-Target cues (M =.241 uv, SD =.104). There was a main effect of cue order, F (1,9) = p =.015. As shown in Figure 5.14, the First cue (M =.410 uv, SD =.136) generated a larger N2 response in comparison to the Second cue (M =.410 uv, SD =.136). There was no significant main effect of probability, F (1,9) = , p =.065. There were no significant interaction between probability by cue meaning (F (1,9) =.001, p =.971), cue order by probability (F (1,9) =.687, p =.429), cue order by cue meaning (F (1,10) = 0.028, p =.871), or cue order by cue meaning and probability (F (1,9) = 1.912, p =.20). Spectral Analysis: cue related activity. A repeated measures ANOVA with the same factors as mentioned in the ERP analysis was used to analyze the alpha-band activity at the cue. There was a main effect of cue meaning, F (1,9) = , p =.001, with greater alpha-band power for the Target cue (M = 191 power, SD =.038) than for the Non-Target cue (M = power, SD =.038), as shown in Figure 5.15 and There was no main effect of cue order, F (1,9) = 1.627, p =.234 or probability, F (1,9) =.110, p =.748. There were no significant interaction effects of cue order by probability (F (1,9) = 2.630, p =.139), probability by cue meaning (F (1,9) =.023, p =.882), cue order by cue meaning (F (1,9) = 2.733, p =.133), or cue order by cue meaning and probability (F (1,9) =.004, p =.954). 28

40 4.3 Discussion CHAPTER 4. EXPERIMENT 3 In this experiment the role of expectancy was examined over time using a visual working memory task. Using a set of two cue-stimulus pairs, subjects can obtain all the relevant information about the dynamics of the trial from the presentation of the first cue. In addition, the probability of trial type was varied between blocks to manipulate expectancy for the first cue. The difference in performance based on cue order is significant and, as in Experiment 2, could be attributed to task difficulty. A surprising result was that the effect of trial type probability was not significant. A difference in performance based on the probability manipulation could have influenced errors in two ways: (1) having a greater percentage of a trial type could have led to more passive viewing where errors in performance increase from sustained attention or (2) the greater probability of a trial type is used to help in gaining experience and diminish differences in task difficulty. The ERP N2 analysis showed similar results there were obtained in Experiment 2. N2 enhancement was observed for Target versus Non-Target cues. There was also an enhancement of the N2 seen in the First cue compared to the Second cue. The main effect of probability, though not significant, trended towards significance at p =.065. It could be the case that subjects did not use the overall block expectation, but relied more on the mircolevel of trial expectancies, where there was greater emphasis on single trial and not on how the trials were blocked together. It could also be the case that the probabilities of 80/20 were not extreme enough. These results provide further evidence that expectancy influences attention and that these influences are robust on a single trial level, but in abstracting to a greater domain such as a 29

41 CHAPTER 4. EXPERIMENT 3 block-level, these expectancies might not be influential. 30

42 Chapter 5 General Discussion The present study investigated the neurophysiological correlates of selective attention. Using spatial and temporal visual memory paradigms, ERPs and oscillatory behavior were examined. The results from these experiments demonstrate that attentional engagement, driven by both context and expectancy, modulate alpha-band power. Disengagement occurs when an event is predictable, as in the case of the temporal cued memory task, and when the context of the cue informs of upcoming task-irrelevant information, as in the case of a Non-Target cue. The N2 ERP component appears to be a more sensitive measure of attentional engagement though driven in part by event-related oscillations, that exhibit a phase resetting at the onset of a stimulus. There is an ongoing debate on what generates the ERP components. The traditional view regarding ERPs holds that these components are rigid in nature with features, such as latency and amplitude, that are relatively fixed. New evidence is emerging that shows not only are the latencies variable, but so are the polarities involved. The wide body of literature on ERPs has flexible definitions of these com- 31

43 CHAPTER 5. GENERAL DISCUSSION ponents with the N1 occurring in the range of 100ms - 250ms. A new model involving oscillations as a mechanism for generating ERPs finds that a phase reset is involved (Sauseng et al., 2007; Klimesch, Sauseng, Hanslmayr, Gruber, & Freunberger, 2007). No longer viewed as a reflection of idling, rhythms in the alpha-band range are now considered to be in response to or in anticipation of an event. Our experiments provide additional evidence of the relationship between neural oscillations and ERPs. The research involved in this study demonstrated that ERPs associated with attentional engagement are in part generated by alpha-band oscillations. The experimental paradigms were able to capture the changes in selective attention associated with expectancy to a certain degree. The levels of expectancy varied from a single cue-pair, to a more holistic approach using information about an entire trial, concluding on a block level. General limitations encountered in this set of experiments involved the low number of subjects that participated. This is a possible contribution to the lack of power during the analysis in Experiment 3. As mentioned earlier, the analysis involving neural oscillations was based on total power, which captures both evoked and induced. To tease apart the interaction between cue meaning and cue expectancy, future analysis should separate the evoked and induced power. It is postulated that cue meaning would be driven more by evoked power and that anticipation related to expectancy would involve more of the induced alpha-band power. Research in this field can build on my data and address this phenomenon applying the principles described within this thesis to other tasks that exploit expectancies. These results provide a basis for investigating the neural underpinnings of alpha-band oscillations associated with attentional mechanisms. 32

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51 REFERENCES Table 5.1: Experiment 1: Electrodes defining Regions of Interest ROI Electrode Sensors Left Posterior 42, 47, 51, 52, 53, 59, 60 Right Posterior 85, 86, 91, 92, 93, 97, 98 40

52 REFERENCES Table 5.2: Experiment 1: Hemisphere by Due Direction Results Hemisphere Cue Direction Mean (uv) SD Left Left Right Right Left Right

53 REFERENCES Table 5.3: Experiment 1: Pre-Cue Visual Spatial Task Previous Analysis Current Analysis Electrodes Collapsed across sites Interval of Interest Stimulus Stimulus/Cue Method Time-frequency Time-frequency, ERPs 42

54 REFERENCES Table 5.4: Experiment 2: Electrode Sensors HydroCel Geodesic Sensor Net: 128 Channel Sensors:

55 REFERENCES Table 5.5: Experiment 2: Cue Meaning by Cue Order Results Cue Meaning Cue Order Mean (power) SD Target First Second Non-Target First Second

56 REFERENCES Table 5.6: Experiment 2: ISI by Cue Meaning Results ISI Cue Meaning Mean (power) SD 300ms Target Non-Target ms Target Non-Target ms Target Non-Target

57 REFERENCES Table 5.7: Experiment 2: Visual Memory Task Previous Analysis Current Analysis Electrodes sites Time of Interest peri-stimulus cue Method TF ERP and TF Behavioral Parameters Non-Target Effect/Errors(JNDs) Errors(JNDs) 46

58 REFERENCES Figure 5.1: Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 500ms. This was followed by a cue comprised of two arrows that indicated which side the Target Gabor would appear. This was displayed for 500ms. The ISI lasted ms and was followed by the presentation of the Target Gabor and a task-irrelevant Gabor on either side of a central fixation. The encoding period lasted 300ms before a maintenance period of ms. The trial ended with a reproduction period. 47

59 REFERENCES Figure 5.2: Bar chart showing absolute values of the JNDs for T L in Blue and T R in Red. There were no significant differences between cue directions. 48

60 REFERENCES Figure 5.3: Grand average ERP waveforms of both cue-locked (top) and stimuluslocked (bottom). Left hemisphere electrode sensors are shown on the left hand column and right hemisphere electrode grand averages on the right hand column. The T L condition is shown in Blue and the T R condition is in Red. Scalp topographies averaged over a 150ms - 250ms period following the onsets are shown on the right. There was a significant difference of hemisphere and cue direction for the cue-locked analysis. 49

61 REFERENCES Figure 5.4: Grand average Time-Frequency wavelets of the Left (left hand column) and Right hemisphere (right hand column) time-locked to the cue. The T R condition is shown on top and the T L is at bottom. There were no significant differences in alpha-band power between ipsilateral and contralateral sites. 50

62 REFERENCES Figure 5.5: Grand average Time-Frequency wavelets of the Left (left hand column) and Right hemisphere (right hand column) time-locked to the stimulus. The T R condition is shown on top and the T L is at bottom. There were no significant differences in alpha-band power between ipsilateral and contralateral sites. 51

63 REFERENCES Figure 5.6: Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 300ms. This was followed by a cue that indicated whether the upcoming cue was a Target ( ) or Non-Target ( ). This was displayed for 500ms. The ISI varied in length and was either 300ms, 600ms, or 900ms depending on the block. This was followed by the presentation of a Gabor. The Gabor was presented for 500ms before being followed by a blank screen for 500ms. Another cue-stimulus pair with the same timing as the first preceded a maintenance period of 1000ms. The trial ended with a reproduction period. This design created two different trial types: the Attend First on the left (T 1 NT 2 ) and the Attend Second trial type of the right(nt 1 T 2 ) 52

64 REFERENCES Figure 5.7: Bar chart showing absolute values of the JNDs for T 1 in Blue and T 2 in Red over the three ISI conditions (300ms, 600ms, 900ms). There was a significant difference in cue order. 53

65 REFERENCES Figure 5.8: Grand average ERP waveforms cue-locked for the three ISI conditions (300ms, 600ms, 900ms). Blue waveforms represent the Attend First trial type and the red waveforms the Attend Second trial type. Sold lines show Target conditions and the dashed lines the Non-Target. There was a significant difference in cue order (Cue First versus Cue Second) and cue meaning, Target versus Non-Target 54

66 REFERENCES Figure 5.9: Grand average ERP scalp topographies from 150ms - 250ms post-cue onset. Top row shows the topographic map collapsed across CUE 1 and the bottom row shows CUE 2. 55

67 REFERENCES Figure 5.10: Grand average ERP scalp topographies from 150ms - 250ms post-cue onset. Top row shows the topographic map collapsed across the Target conditions and the bottom row shows the Non-Target conditions. 56

68 REFERENCES Figure 5.11: Grand average Time-Frequency wavelets of the Attend First condition (T 1 NT 2 ) and Attend Second (NT 1 T 2 ). Cue onset is marked at 0 seconds with a white line. The ISI conditions of 300ms, 600ms, and 900ms are shown in the left, middle, and right hand columns, respectively. 57

69 REFERENCES Figure 5.12: Diagram showing the events of a single trial in the experiment. Each trial began with a fixation at center that was displayed for 300ms. This was followed by a cue that indicated whether the upcoming cue was a Target ( ) or Non-Target ( ). This was displayed for 500ms. The ISI was fixed at 600ms and this was followed by the presentation of a Gabor. The Gabor was presented for 500ms before being followed by a blank screen for 500ms. Another cue-stimulus pair with the same timing as the first preceded a maintenance period of 1000ms. The trial ended with a reproduction period. This design created two different trial types the Attend First on the left (T 1 NT 2 ) and the Attend Second trial (NT 1 T 2 ). 58

70 REFERENCES Figure 5.13: Bar chart showing absolute values of the JNDs for T 1 in Blue and T 2 in Red over the two conditions T 80 on the left and T 20 on the right. There was a significant difference in cue order. 59

71 REFERENCES Figure 5.14: Grand average ERP waveforms cue-locked for the two probability conditions. Blue waveforms represent the Attend First trial type and the red waveforms the Attend Second trial type. Sold lines show the Target condition and the dashed lines the Non-Target conditions. 60

72 REFERENCES Figure 5.15: Grand average Time-Frequency wavelets of the Cue First condition with T 1 on the left and NT 1 on the right. Cue onset is marked at 0 seconds with a white line. The probability condition of 80 percent is shown on the top and the 20 percent on the bottom. 61

73 REFERENCES Figure 5.16: Grand average Time-Frequency wavelets of the Cue First condition with T 2 on the left and NT 2 on the right. Cue onset is marked at 0 seconds with a white line. The probability condition of 80 percent is shown on the top and the 20 percent on the bottom. 62

74 Appendices 63

75 Appendix A EEG Workflow Routine A.1 Data Pre-Processing MATLAB Files pre processing : Reads in continuous.raw EEG data, configures electrode channels, re-references, applies butter-notch filtering, and saves the data as a continuous processed.set file export events eeglab : Exports all events occurring in the EEG data and saves the event number, event type duration, and urevent data as a text file read event file : Imports data from text file created by export events eeglab and relabels/add events, saving new events as a text file add events eeglab : Imports events created by read event file adding new events to the continuous EEG data and overriding old events segment ica : Segments continuous EEG data into epochs based on trigger parameters (trigger name, epoch size in sec.) and saves segmented data files run ica : Runs ICA analysis on segmented EEG data saving ICA files ica rejection : Using a text file identifying ICA components to be removed, removes 64

76 APPENDIX A. EEG WORKFLOW ROUTINE ICA components and saves EEG data art rejection : Performs trial rejection based on a text file with a list of artifact rejected trials and saves cleaned data A.2 Data Processing MATLAB Files convert eeglab fieldtrip : Converts EEGLAB.set files to Fieldtrip friendly.mat files and saves.mat files erp : Performs individual subject ERP averaging using the cleaned.set files from art rejection and saves subject files as a.mat file wavelets : Performs individual subject Time-Frequency averaging using Fieldtrip friendly.mat files from convert eeglab fieldtrip and saves subject files as a.mat file A.3 Data Visualization MATLAB Files erp quick version : Loads the averaged ERP subject data and computes group grand averages making ERP waveform figures and ERP topographical maps wavelet quick version : Loads the averaged Time-Frequency subject data and computes group grand averages making Time-Frequency wavetets and Time-Frequency topographical maps channel mean alphawave : Loads the averaged Time-Frequency subject data and computes group grand averages making Time-Frequency waveform figures 65

77 APPENDIX A. EEG WORKFLOW ROUTINE A.4 Data Analysis MATLAB Files beh cal : Calculates mean and median Behavioral data from individual subject.mat files and saves as a.mat file read beh prob : Using the.mat file created by beh cal creates a text file to be used for SPSS analysis channel mean normal eeglabdata T1vsT2 : Loads individual subject ERP averaged.mat file and calculates group means and saves as a text file to be used for SPSS analysis channel mean normal erp T1vsT2 : Loads individual subject Time-Frequency averaged.mat file and calculates group means and saves as a text file to be used for SPSS analysis 66

78 APPENDIX A. EEG WORKFLOW ROUTINE Figure A.1: EEG processing workflow. Purple : Pre-Processing EEG data. Blue : Optional Marker Re-assignment. Green : Behavioral data processing. Orange : ERP processing. Red : Time-Frequency processing. Yellow : Data Visualization. Dashed arrows represent optional processing steps. 67