Frontal Lobe Function and Performance Monitoring following Total Sleep Deprivation

Imaging studies have shown reduced frontal lobe resources following total sleep deprivation (TSD). The anterior cingulate cortex (ACC) in the frontal region plays a role in performance monitoring and cognitive control; both error detection and response inhibition are impaired following sleep loss. Event-related potentials (ERPs) are an electrophysiological tool used to index the brain's response to stimuli and information processing. In the Flanker task, the error-related negativity (ERN) and error positivity (Pe) ERPs are elicited after erroneous button presses. In a Go/NoGo task, NoGo-N2 and NoGo-P3 ERPs are elicited during high conflict stimulus processing. Research investigating the impact of sleep loss on ERPs during performance monitoring is equivocal, possibly due to task differences, sample size differences and varying degrees of sleep loss. Based on the effects of sleep loss on frontal function and prior research, it was expected that the sleep deprivation group would have lower accuracy, slower reaction time and impaired remediation on performance monitoring tasks, along with attenuated and delayed stimulus- and response-locked ERPs. In the current study, 49 young adults (24 male) were screened to be healthy good sleepers and then randomly assigned to a sleep deprived (n = 24) or rested control (n = 25) group. Participants slept in the laboratory on a baseline night, followed by a second night of sleep or wake. Flanker and Go/NoGo tasks were administered in a battery at 1O:30am (i.e., 27 hours awake for the sleep deprivation group) to measure performance monitoring. On the Flanker task, the sleep deprivation group was significantly slower than controls (p's <.05), but groups did not differ on accuracy. No group differences were observed in post-error slowing, but a trend was observed for less remedial accuracy in the sleep deprived group compared to controls (p = .09), suggesting impairment in the ability to take remedial action following TSD. Delayed P300s were observed in the sleep deprived group on congruent and incongruent Flanker trials combined (p = .001). On the Go/NoGo task, the hit rate (i.e., Go accuracy) was significantly lower in the sleep deprived group compared to controls (p <.001), but no differences were found on false alarm rates (i.e., NoGo Accuracy). For the sleep deprived group, the Go-P3 was significantly smaller (p = .045) and there was a trend for a smaller NoGo-N2 compared to controls (p = .08). The ERN amplitude was reduced in the TSD group compared to controls in both the Flanker and Go/NoGo tasks. Error rate was significantly correlated with the amplitude of response-locked ERNs in control (r = -.55, p=.005) and sleep deprived groups (r = -.46, p = .021); error rate was also correlated with Pe amplitude in controls (r = .46, p=.022) and a trend was found in the sleep deprived participants (r = .39, p =. 052). An exploratory analysis showed significantly larger Pe mean amplitudes (p = .025) in the sleep deprived group compared to controls for participants who made more than 40+ errors on the Flanker task. Altered stimulus processing as indexed by delayed P3 latency during the Flanker task and smaller amplitude Go-P3s during the Go/NoGo task indicate impairment in stimulus evaluation and / or context updating during frontal lobe tasks. ERN and NoGoN2 reductions in the sleep deprived group confirm impairments in the monitoring system. These data add to a body of evidence showing that the frontal brain region is particularly vulnerable to sleep loss. Understanding the neural basis of these deficits in performance monitoring abilities is particularly important for our increasingly sleep deprived society and for safety and productivity in situations like driving and sustained operations.

Electrophysiological investigations of the timing of face processing

As important social stimuli, faces playa critical role in our lives. Much of our interaction with other people depends on our ability to recognize faces accurately. It has been proposed that face processing consists of different stages and interacts with other systems (Bruce & Young, 1986). At a perceptual level, the initial two stages, namely structural encoding and face recognition, are particularly relevant and are the focus of this dissertation. Event-related potentials (ERPs) are averaged EEG signals time-locked to a particular event (such as the presentation of a face). With their excellent temporal resolution, ERPs can provide important timing information about neural processes. Previous research has identified several ERP components that are especially related to face processing, including the N 170, the P2 and the N250. Their nature with respect to the stages of face processing is still unclear, and is examined in Studies 1 and 2. In Study 1, participants made gender decisions on a large set of female faces interspersed with a few male faces. The ERP responses to facial characteristics of the female faces indicated that the N 170 amplitude from each side of the head was affected by information from eye region and by facial layout: the right N 170 was affected by eye color and by face width, while the left N 170 was affected by eye size and by the relation between the sizes of the top and bottom parts of a face. In contrast, the P100 and the N250 components were largely unaffected by facial characteristics. These results thus provided direct evidence for the link between the N 170 and structural encoding of faces. In Study 2, focusing on the face recognition stage, we manipulated face identity strength by morphing individual faces to an "average" face. Participants performed a face identification task. The effect of face identity strength was found on the late P2 and the N250 components: as identity strength decreased from an individual face to the "average" face, the late P2 increased and the N250 decreased. In contrast, the P100, the N170 and the early P2 components were not affected by face identity strength. These results suggest that face recognition occurs after 200 ms, but not earlier. Finally, because faces are often associated with social information, we investigated in Study 3 how group membership might affect ERP responses to faces. After participants learned in- and out-group memberships of the face stimuli based on arbitrarily assigned nationality and university affiliation, we found that the N170 latency differentiated in-group and out-group faces, taking longer to process the latter. In comparison, without group memberships, there was no difference in N170 latency among the faces. This dissertation provides evidence that at a neural level, structural encoding of faces, indexed by the N170, occurs within 200 ms. Face recognition, indexed by the late P2 and the N250, occurs shortly afterwards between 200 and 300 ms. Social cognitive factors can also influence face processing. The effect is already evident as early as 130-200 ms at the structural encoding stage.

Individual Differences in Global/Local Processing Bias and the Attentional Blink

When the second of two targets (T2) is presented temporally close to the first target (T1) in rapid serial visual presentation, accuracy to detect/identify T2 is markedly reduced as compared to longer target separations. This is known as the attentional blink (AB), and is thought to reflect a limitation of selective attention. While most individuals show an AB, research has demonstrated that individuals are variously susceptible to this effect. To explain these differences, Dale and Arnell (2010) examined whether dispositional differences in attentional breadth, as measured by the Navon letter task, could predict individual AB magnitude. They found that individuals who showed a natural bias toward the broad, global level of Navon letter stimuli were less susceptible to the AB as compared to individuals who showed a natural bias toward the detailed, local aspects of Navon letter stimuli. This suggests that individuals who naturally broaden their attention can overcome the AB. However, it was unclear how stable these individual differences were over time, and whether a variety of global/local tasks could predict AB performance. As such, the purpose of this dissertation was to investigate, through four empirical studies, the nature of individual differences in both global/local bias and the AB, and how these differences in attentional breadth can modulate AB performance. Study 1 was designed to examine the stability of dispositional global/local biases over time, as well as the relationships among three different global/local processing measures. Study 2 examined the stability of individual differences in the AB, as well as the relationship among two distinct AB tasks. Study 3 examined whether the three distinct global/local tasks used in Study 1 could predict performance on the two AB tasks from Study 2. Finally, Study 4 explored whether individual differences in global/local bias could be manipulated by exposing participants to high/low spatial frequencies and Navon stimuli. In Study 1, I showed that dispositional differences in global/local bias were reliable over a period of at least a week, demonstrating that these individual biases may be trait-like. However, the three tasks that purportedly measure global/local bias were unrelated to each other, suggesting that they measure unique aspects of global/local processing. In Study 2, I found that individual variation in AB performance was also reliable over a period of at least a week, and that the two AB task versions were correlated. Study 3 showed that dispositional global/local biases, as measured by the three tasks from Study 1, predicted AB magnitude, such that individuals who were naturally globally biased had smaller ABs. Finally, in Study 4 I demonstrated that these dispositional global/local biases are resistant to both spatial frequency and Navon letter manipulations, indicating that these differences are robust and intractable. Overall, the results of the four studies in this dissertation help clarify the role of individual differences in attentional breadth in selective attention.

Interpreting Quantifier Scope Ambiguity: Evidence of Heuristic First, Algorithmic Second Processing

The present work suggests that sentence processing requires both heuristic and algorithmic processing streams, where the heuristic processing strategy precedes the algorithmic phase. This conclusion is based on three self-paced reading experiments in which the processing of two-sentence discourses was investigated, where context sentences exhibited quantifier scope ambiguity. Experiment 1 demonstrates that such sentences are processed in a shallow manner. Experiment 2 uses the same stimuli as Experiment 1 but adds questions to ensure deeper processing. Results indicate that reading times are consistent with a lexical-pragmatic interpretation of number associated with context sentences, but responses to questions are consistent with the algorithmic computation of quantifier scope. Experiment 3 shows the same pattern of results as Experiment 2, despite using stimuli with different lexicalpragmatic biases. These effects suggest that language processing can be superficial, and that deeper processing, which is sensitive to structure, only occurs if required. Implications for recent studies of quantifier scope ambiguity are discussed.

Morphonotactic and phonotactic processing in German-speaking adults

Based on the theoretical framework of Dressler and Dziubalska-Kołaczyk (2006a,b), the Strong Morphonotactic Hypothesis will be tested. It assumes that phonotactics helps in decomposition of words into morphemes: if a certain sequence occurs only or only by default over a morpheme boundary and is thus a prototypical morphonotactic sequence, it should be processed faster and more accurately than a purely phonotactic sequence. Studies on typical and atypical first language acquisition in English, Lithuanian and Polish have shown significant differences between the acquisition of morphonotactic and phonotactic consonant clusters: Morphonotactic clusters are acquired earlier and faster by typically developing children, but are more problematic for children with Specific Language Impairment. However, results on acquisition are less clear for German. The focus of this contribution is whether and how German-speaking adults differentiate between morphonotactic and phonotactic consonant clusters and vowel-consonant sequences in visual word recognition. It investigates whether sub-lexical letter sequences are found faster when the target sequence is separated from the word stem by a morphological boundary than when it is a part of a morphological root. An additional factor that is addressed concerns the position of the target cluster in the word. Due to the bathtub effect, sequences in peripheral positions in a word are more salient and thus facilitate processing more than word-internal positions. Moreover, for adults the primacy effect most favors word-initial position (whereas for young children the recency effect most favors word- final position). Our study discusses effects of phonotactic vs. morphonotactic cluster status and of position within the word.

Psychocentricity and participant profiles: implications for lexical processing among multilinguals

Lexical processing among bilinguals is often affected by complex patterns of individual experience. In this paper we discuss the psychocentric perspective on language representation and processing, which highlights the centrality of individual experience in psycholinguistic experimentation. We discuss applications to the investigation of lexical processing among multilinguals and explore the advantages of using high-density experiments with multilinguals. High density experiments are designed to co-index measures of lexical perception and production, as well as participant profiles. We discuss the challenges associated with the characterization of participant profiles and present a new data visualization technique, that we term Facial Profiles. This technique is based on Chernoff faces developed over 40 years ago. The Facial Profile technique seeks to overcome some of the challenges associated with the use of Chernoff faces, while maintaining the core insight that recoding multivariate data as facial features can engage the human face recognition system and thus enhance our ability to detect and interpret patterns within multivariate datasets. We demonstrate that Facial Profiles can code participant characteristics in lexical processing studies by recoding variables such as reading ability, speaking ability, and listening ability into iconically-related relative sizes of eye, mouth, and ear, respectively. The balance of ability in bilinguals can be captured by creating composite facial profiles or Janus Facial Profiles. We demonstrate the use of Facial Profiles and Janus Facial Profiles in the characterization of participant effects in the study of lexical perception and production.

The time-course of lexical activation in Japanese morphographic word recognition: Evidence for a character-driven processing model

This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers’ locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level.

Payment for the Cogswell, Sample and Howard accounts

Payment for the Cogswell, Sample and Howard accounts, Feb. 29, 1884.

Payment for the Cogswell, Howard and Sample accounts

Payment for the Cogswell, Howard and Sample accounts, Aug. 29, 1884.

Payment for the Cogswell, Howard and Sample accounts

Payment for the Cogswell, Howard and Sample accounts, Feb. 27, 1885.

Blocking Top-down awareness of Kanizsa Figures: An ERP Investigation into Bottom-up Processing of Illusory Contours

Neural models of the processing of illusory contour (ICs) diverge from one another in terms of their emphasis on bottom-up versus top-down constituents. The current study uses a dichoptic fusion paradigm to block top-down awareness of ICs in order to examine possible bottom-up effects. Group results indicate that the N170 ERP component is particularly sensitive to ICs at central occipital sites when top-down awareness of the stimulus is permitted. Furthermore, single-subject statistics reveal that the IC N170 ERP effect is highly variable across individuals in terms of timing and topographical spread. The results suggest that the ubiquitous N170 effect to ICs found in the literature depends, at least in part, on participants’ awareness of the stimulus. Therefore a strong bottom-up model of IC processing at the time of the N170 is unlikely.

Empathy and Emotion Processing in Mild Head Injury and Sub-clinical Psychopathy

The current study sought to investigate the nature of empathic responding and emotion processing in persons who have experienced Mild Head Injury (MHI) and how this relationship between empathetic responding and head injury status may differ in those with higher psychopathic characteristics (i.e., subclinical psychopathy). One-hundred university students (36% reporting having a previous MHI) completed an Emotional Processing Task (EPT) using images of neutral and negative valence (IAPS, 2008) designed to evoke empathy; physiological responses were recorded. Additionally, participants completed measures of cognitive competence and various individual differences (empathy - QCAE; Reniers, 2011; Psychopathy - SRP-III, Williams, Paulhus & Hare, 2007) and demographics questionnaires. MHI was found to be associated with lower affective empathy and physiological reactivity (pulse rate) while viewing images irrespective of valence, reflecting a pattern of generalized underarousal. The empathic deficits observed correlated with the individual’s severity of injury such that the greater number of injury characteristics and symptoms endorsed by a subject, the more dampened the affective and cognitive empathy reactions to stimuli and the lower his/her physiological reactivity. Importantly, psychopathy interacted with head injury status such that the effects of psychopathy were significant only for individuals indicating a MHI. This group, i.e., MHI subjects who scored higher on psychopathy, displayed the greatest compromise in empathic responding. Interestingly, the Callous Affect component of psychopathy was found to account for the empathic and emotion processing deficits observed for individuals who report a MHI; in contrast, the Interpersonal Manipulation component emerged as a better predictor of empathic and emotion deficits observed in the No MHI group. These different patterns may indicate the involvement of different underlying processes in the manifestation of empathic deficits associated with head injury or subclinical psychopathy. It also highlights the importance of assessing for prior head injury in populations with higher psychopathic characteristics due to the possible combined/enhanced influences. The results of this study have important social implications for persons who have experienced a concussion or limited neural trauma since even subtle injury to the head may be sufficient to produce dampened emotion processing, thereby impacting one’s social interactions and engagement (i.e., at risk for social isolation or altered interpersonal success). Individuals who experience MHI in conjunction with certain personality profiles (e.g., higher psychopathic characteristics) may be particularly at risk for being less capable of empathic compassion and socially-acceptable pragmatics and, as a result, may not be responsive to another person’s emotional well-being.

Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.

Simulation-Based Finite-Sample Tests for Heteroskedasticity and ARCH Effects.

A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literature. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control in finite samples. There has been a number of recent studies that seek to improve the reliability of common heteroskedasticity tests using Edgeworth, Bartlett, jackknife and bootstrap methods. Yet the latter remain approximate. In this paper, we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts. We study procedures based on the standard test statistics [e.g., the Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White and Szroeter criteria] as well as tests for autoregressive conditional heteroskedasticity (ARCH-type models). We also suggest several extensions of the existing procedures (sup-type of combined test statistics) to allow for unknown breakpoints in the error variance. We exploit the technique of Monte Carlo tests to obtain provably exact p-values, for both the standard and the new tests suggested. We show that the MC test procedure conveniently solves the intractable null distribution problem, in particular those raised by the sup-type and combined test statistics as well as (when relevant) unidentified nuisance parameter problems under the null hypothesis. The method proposed works in exactly the same way with both Gaussian and non-Gaussian disturbance distributions [such as heavy-tailed or stable distributions]. The performance of the procedures is examined by simulation. The Monte Carlo experiments conducted focus on : (1) ARCH, GARCH, and ARCH-in-mean alternatives; (2) the case where the variance increases monotonically with : (i) one exogenous variable, and (ii) the mean of the dependent variable; (3) grouped heteroskedasticity; (4) breaks in variance at unknown points. We find that the proposed tests achieve perfect size control and have good power.