Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Same-sex gaze attraction influences mate-choice copying in humans.

Mate-choice copying occurs when animals rely on the mating choices of others to inform their own mating decisions. The proximate mechanisms underlying mate-choice copying remain unknown. To address this question, we tracked the gaze of men and women as they viewed a series of photographs in which a potential mate was pictured beside an opposite-sex partner; the participants then indicated their willingness to engage in a long-term relationship with each potential mate. We found that both men and women expressed more interest in engaging in a relationship with a potential mate if that mate was paired with an attractive partner. Men and women's attention to partners varied with partner attractiveness and this gaze attraction influenced their subsequent mate choices. These results highlight the prevalence of non-independent mate choice in humans and implicate social attention and reward circuitry in these decisions.

Dental microwear in live, wild-trapped Alouatta palliata from Costa Rica.

One problem with dental microwear analyses of museum material is that investigators can never be sure of the diets of the animals in question. An obvious solution to this problem is to work with live animals. Recent work with laboratory primates has shown that high resolution dental impressions can be obtained from live animals. The purpose of this study was to use similar methods to begin to document rates and patterns of dental microwear for primates in the wild. Thirty-three Alouatta palliata were captured during the wet season at Hacienda La Pacifica near Canas, Costa Rica. Dental impressions were taken and epoxy casts of the teeth were prepared using the methods of Teaford and Oyen (1989a). Scanning electron micrographs were taken of the left mandibular second molars at magnifications of 200x and 500x. Lower magnification images were used to calculate rates of wear, and higher magnification images were used to measure the size and shape of microwear features. Results indicate that, while basic patterns of dental microwear are similar in museum samples and samples of live, wild-trapped animals of the same species, ecological differences between collection locales may lead to significant intraspecific differences in dental microwear. More importantly, rates of microwear provide the first direct evidence of differences in molar use between monkeys and humans.

Schema-driven construction of future autobiographical traumatic events: the future is much more troubling than the past.

Research on future episodic thought has produced compelling theories and results in cognitive psychology, cognitive neuroscience, and clinical psychology. In experiments aimed to integrate these with basic concepts and methods from autobiographical memory research, 76 undergraduates remembered past and imagined future positive and negative events that had or would have a major impact on them. Correlations of the online ratings of visual and auditory imagery, emotion, and other measures demonstrated that individuals used the same processes to the same extent to remember past and construct future events. These measures predicted the theoretically important metacognitive judgment of past reliving and future "preliving" in similar ways. On standardized tests of reactions to traumatic events, scores for future negative events were much higher than scores for past negative events. The scores for future negative events were in the range that would qualify for a diagnosis of posttraumatic stress disorder (PTSD); the test was replicated (n = 52) to check for order effects. Consistent with earlier work, future events had less sensory vividness. Thus, the imagined symptoms of future events were unlikely to be caused by sensory vividness. In a second experiment, to confirm this, 63 undergraduates produced numerous added details between 2 constructions of the same negative future events; deficits in rated vividness were removed with no increase in the standardized tests of reactions to traumatic events. Neuroticism predicted individuals' reactions to negative past events but did not predict imagined reactions to future events. This set of novel methods and findings is interpreted in the contexts of the literatures of episodic future thought, autobiographical memory, PTSD, and classic schema theory.

A memory-based model of posttraumatic stress disorder: evaluating basic assumptions underlying the PTSD diagnosis.

In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs objective information about the trauma and peritraumatic emotions but uses retrospective memory reports that can have substantial biases. Negative events and emotions that do not satisfy the current diagnostic criteria for a trauma can be followed by symptoms that would otherwise qualify for PTSD. Predisposing factors that affect the current memory have large effects on symptoms. The inability-to-recall-an-important-aspect-of-the-trauma symptom does not correlate with other symptoms. Loss or enhancement of the trauma memory affects PTSD symptoms in predictable ways. Special mechanisms that apply only to traumatic memories are not needed, increasing parsimony and the knowledge that can be applied to understanding PTSD.

The Basic-Systems Model of Episodic Memory.

Behavior, neuropsychology, and neuroimaging suggest that episodic memories are constructed from interactions among the following basic systems: vision, audition, olfaction, other senses, spatial imagery, language, emotion, narrative, motor output, explicit memory, and search and retrieval. Each system has its own well-documented functions, neural substrates, processes, structures, and kinds of schemata. However, the systems have not been considered as interacting components of episodic memory, as is proposed here. Autobiographical memory and oral traditions are used to demonstrate the usefulness of the basic-systems model in accounting for existing data and predicting novel findings, and to argue that the model, or one similar to it, is the only way to understand episodic memory for complex stimuli routinely encountered outside the laboratory.

A basic-systems approach to autobiographical memory

Memory for complex everyday events involving vision, hearing, smell, emotion, narrative, and language cannot be understood without considering the properties of the separate systems that process and store each of these forms of information. Using this premise as a starting point, my colleagues and I found that visual memory plays a central role in autobiographical memory: The strength of recollection of an event is predicted best by the vividness of its visual imagery, and a loss of visual memory causes a general amnesia. Examination of autobiographical memories in individuals with posttraumatic stress disorder (PTSD) suggests that the lack of coherence often noted in memories of traumatic events is not due to a lack of coherence either of the memory itself or of the narrative that integrates the memory into the life story. Rather, making the traumatic memory central to the life story correlates positively with increased PTSD symptoms. The basic-systems approach has yielded insights into autobiographical memory's phenomenology, neuropsychology, clinical disorders, and neural basis. Copyright © 2005 American Psychological Society.