Browsing by Subject "fMRI"

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Artifact Reduction In The Integration Of Neural Electrodes And Extracellular Recording With Ultrahigh Field Magnetic Resonance Imaging
(2020-05) Cruttenden, Corey
The understanding of brain function in humans and animals can be greatly improved by simultaneous recording of electrical neural signals and acquisition of ultrahigh field (UHF) magnetic resonance images. Such simultaneous recordings will enable the study of neurovascular coupling with functional structure specificity and improve our understanding of the circuits and brain function changes associated with deep brain stimulation (DBS). However, integrating neural electrodes with UHF MRI is technically challenging due to electromagnetic interactions between the electrodes and the MRI magnetic fields. These interactions include magnetic field distortions by the electrodes that create image artifacts in MRI, as well as electromagnetic inductive coupling that introduces noise and interferences in the extracellular neural signal recordings made at UHF. This dissertation develops solutions to address both types of interferences. The MRI image artifact issue is addressed through novel neural electrode designs, and the electrical interferences in extracellular neural recordings are addressed using software filtering and estimation techniques. Two types of implantable neural electrodes are presented that significantly reduce artifacts in UHF MRI images due to their improved properties including magnetic susceptibility that better matches the surrounding brain tissue. The improved magnetic susceptibility match with brain tissue reduces distortions to the static magnetic field, which consequently reduces MRI image artifacts. First, carbon nanotube film electrodes are shown to substantially reduce image artifacts in UHF MRI, and second, a novel gold-aluminum microwire neural electrode is developed that is very easy to construct and provides multiple channels for recording or stimulation with reduced artifacts at UHF. The ease of constructing the gold-aluminum microwire electrode increases its potential impact to the field because it can be quickly adopted by other research groups and applied to any MRI field strength. The ability of both types of electrodes to reduce UHF MRI image artifacts is demonstrated using both phantom tissue and in vivo animal studies, and also verified using numerical computations of the magnetic field distortions around a two-dimensional electrode model embedded in a brain tissue substrate. Three major artifact removal algorithms are developed for cleaning neural signal recordings in a UHF MRI scanner. These are for the specific tasks of removing artifacts due to periodic motions including breathing and hardware vibration, eliminating severe scanning artifacts from the gradients of the MRI system during fMRI acquisition, and extracting action potential spike waveforms that are otherwise well below detection thresholds in an UHF 16.4 T MRI animal research scanner. First, reference-free adaptive filtering is implemented for removal of periodic motion induced interferences in extracellular local field potential (LFP) recordings at UHF. Second, a new approach to estimate severe fMRI gradient-induced artifacts using a coefficient shrinkage algorithm based on the first difference of the extracellular neural signal is presented. The first difference of the extracellular neural signal is found to have interesting statistical properties that benefit MRI artifact estimation including a Gaussian probability density function, a near-white power spectral density, an approximate Dirac delta function autocorrelation, and an upper bound on its singular value distribution. Finally, an adaptive virtual referencing approach based on adaptive least mean square (LMS) filters is shown to reduce the noise floor in extracellular unit recordings made both on the benchtop and at UHF. The reduced noise floor allows for identification of additional action potential waveforms that were previously below the detection threshold. This advancement allowed us to detect and classify action potential waveforms during fMRI data acquisition inside a 16.4 T MRI animal research scanner, the highest field strength horizontal-bore small animal scanner currently available. The artifact estimation and removal algorithms developed to improve the extracellular neural signal quality recorded during UHF fMRI could be beneficial in other applications as well. For example, periodic motion artifacts caused by breathing, heart pulsation, chewing, and blinking are often present in extracellular neural recordings made outside of MRI scanners, particularly if they are made in awake/behaving animals. Furthermore, the coefficient shrinkage algorithm used for removing fMRI gradient-induced artifacts could benefit the removal of stimulation artifacts from neural recordings made during electrical or optogenetic brain stimulation. The findings related to the properties of the first difference of the extracellular neural signal that provided statistical advantages in noise estimation and removal might apply to other signals with a 1/f power spectral density profile as well. Finally, adaptive virtual referencing for extraction of action potential spike waveforms is shown in this dissertation to benefit benchtop recordings in addition to recordings made at UHF. The technical contributions of this dissertation enable preclinical animal studies to be undertaken involving the simultaneous use of neural electrodes together with UHF MRI. Such studies can answer questions about the relationship between neuronal signaling and the functional MRI contrast with cortical layer and column specificity. Further, such studies will enable us to conduct fMRI imaging while using DBS electrodes which will help us understand the underlying mechanisms of how DBS successfully treats multiple brain disorders.
The contribution of fear conditioning to pathological anxiety: an investigation of conditioned fear generalization in OCD Traits and PTSD
(2014-08) Kaczkurkin, Antonia
A review of the literature demonstrates a lack of research on fear-generalization processes in many anxiety disorders including obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD). Chapter 2 represents the first study that attempted to investigate the generalization of conditioned fear in individuals with obsessive-compulsive traits using startle EMG and behavioral measures. The results of this study demonstrated that individuals with high levels of Threat Estimation as measured by the Obsessive Beliefs Questionnaire (OBQ-44) displayed overgeneralization of fear responses to a greater range of stimuli resembling the danger cue than those with low levels of Threat Estimation. In addition, despite etiological theories proposing that fear conditioning and overgeneralization of fear play prominent roles in the development and maintenance of PTSD, little research had been done on the neurobiological mechanisms that contribute to fear conditioning processes in PTSD patients and none have been specifically conducted on generalization. Chapter 3 investigated the neurobiological substrates associated with the overgeneralization of conditioned fear in PTSD patients using behavioral, skin conductance, and functional magnetic resonance imaging (fMRI) measures. This study provides evidence that PTSD patients demonstrate overgeneralization of conditioned fear in the dorsal medial prefrontal cortex, bilateral insula, left and right caudate, left inferior parietal lobule, and right superior frontal gyrus. This body of work provides novel evidence regarding the generalization of conditioned fear in OCD and PTSD.
Cortical and Subcortical correlates of emotional control across adolescent development
(2013-08) Porter, James Norby
The neural mechanisms of motivational and emotional processing are of particular interest to the study of adolescent development. Magnetic resonance imaging (MRI) studies show the ventral striatum (especially nucleus accumbens [NAcc]), the amygdala, and the prefrontal cortex (PFC) to be reliable neural correlates of processing stimuli with hedonically valenced content. Current models theorize that the relative levels of maturity of these three regions, from both structural and functional standpoints, strongly influence an individual's tendencies towards impulsive, risky decision-making in the presence of motivationally salient stimuli. This study recruited pre- to early-adolescents, adolescents, and young adults to assess neural correlates of control over emotional reactivity while performing a novel functional MRI (fMRI) task, referred to here as the interval timing task. The task tested individual's abilities to perceive and recreate discrete time intervals, and required deliberate perceptual, cognitive, and motor control in the presence of strongly and weakly valenced visual stimuli. This paper describes the development of the interval timing task and presents comprehensive analyses of alterations due to task parameters as well as inter-individual characteristics of age and sex upon both participants' behavioral performances and their blood-oxygen-level-dependent (BOLD) responses. Additionally, this paper presents an alternative analysis of the fMRI data that can inform the current debate on the extent to which the NAcc displays a specificity for processing positively valenced information or if it is also integral to the processing of negatively valenced information.
Deciding Which Fears to Face: Behavioral and Neural Mechanisms of Costly Avoidance in Clinical Anxiety
(2022-07) Berg, Hannah
Clinical anxiety is often characterized by a behavioral pattern of relinquishing rewards in order to avoid potential threats, a decision-making bias that confers substantial functional impairment. However, the mechanisms of such costly avoidance have received scant attention in the literature. The present work addresses this gap, applying fear-conditioning methodology and functional magnetic resonance imaging (fMRI) to probe the neural and psychological processes contributing to costly avoidance. A sample of 153 adults with and without clinical anxiety underwent fMRI while completing a fear-conditioning and generalization paradigm in which participants decide between risky approach and costly avoidance. Anxious individuals were more likely than others to make costly, unnecessary avoidance decisions in the context of generalized Pavlovian fear, as has been seen previously. Subsequent analyses provide novel insights into this finding. When assessing risk and reward appraisals, anxious individuals demonstrated a greater likelihood of avoidance in the context of moderate expected risk or low expected reward. Brain-wide correlations and multivariate pattern analyses revealed that neural activity during choice deliberation in regions associated with cognitive control, sensory processing, and perception-motor integration scaled with risk and reward appraisals and was predictive of choice. Among anxious individuals, however, these neural processes were less correlated with expected risk and were less predictive of choice, suggesting that the observed avoidance bias may stem from a relatively weak formation of a prepotent approach response, and for a tendency to second-guess or ignore the results of deliberative valuation. Taken together, the present findings represent a significant advance in the conceptualization of costly avoidance in clinical anxiety.
Disassociating Sensory, Choice, and Attentional Signals to Understand Feature Based Perception and Learning in Small Populations of Intermediate Visual Cortex
(2019-05) Moore, Elisabeth
Perception is integral to how we interact with our visual environment. How perception changes with experience is a function of learning, while how it occurs on a flexible, immediate time scale in relation to dynamic task demands, is mediated by attention. Both of these cognitive phenomena underpin how we perceive and interact with the world around us. Visual perceptual learning (VPL) is the improvement in the ability to perceive our visual environment, and is essential to how humans and other animals learn to interact with the world. Despite an extensive amount of research into the mechanisms of VPL, the neural mechanisms responsible for perceptual improvements remain controversial. A major challenge has been establishing that a particular physiological correlate of learning is actually responsible for learning, as opposed to merely reflecting changes in the properties or populations that are responsible. To address this issue, we employed a perceptual detection task in which neurons in a specific area, V4, are known to have task related responses on a scale of tens of milliseconds that reliably predict the timing and precision of shape detection. We followed population responses using a chronically implanted electrode array while non-human primates learned to detect shapes degraded by noise. Consistent with previous results that examined single neurons and neuronal ensembles, we found that, after the course of learning, variations in the local field potentials of individual electrodes over the course of tens of milliseconds reliably reflected the presentation of degraded shapes, and also predicted detection decisions made by the animal. Moreover, we found that variations in reliability of shape-related signals predicted the up-down fluctuations in performance seen over the course of learning in each animal. Together, these results demonstrate that population signals in area V4 are largely sufficient to explain the timing and reliability of shape detection and how that detection performance increases as a consequence of training. Endogenous feature-based visual attention involves an improvement in neural representations involving the attended feature that is dependent on immediate task dependent demands. How this happens in a specific population, and whether the involved populations overlap with those mediating perception, is not well understood. Due to previous work in our laboratory finding that feature based attention is targeted to specific, task appropriate neural populations in early visual cortex, we asked whether attention is similarly distributed in a task specific way in V4, how this depends on attentional state, and whether such neurons also signal the readout of the perceptual choice, given that choice signals have consistently been found in this area. We designed a demanding stimulus discrimination task where we directed subjects to attend to a specific feature of the task during high-field fMRI scanning. The stimulus alternated continuously at varying frequencies in low and high level features (spatial frequency and shape, due to their expected sensory activation of V1 and V4, respectively). Voxels were measured at high resolution, sampling 1mm of cortex, from V1 to V4, and the stimulus was presented near perceptual threshold in order to disassociate the stimulus from the choice. We used a linear regression analysis to compare continuous BOLD modulation of individual voxels to regressors modeling the continuous stimulus presentation when a given feature was attended to vs when it was not, and assessed how sensory and attention modulations overlapped with modulations containing a relationship to the ongoing perceptual choice. We found clear sensory attention effects in V4 that were specific to certain populations; however this did not appear to depend on initial sensitivity, and we did not see reliable choice signals or choice signals that overlapped with attention signals. We believe this may be due to the experimental design and recommend future approaches to disassociate sensory, attention, and choice signals in visual cortex.
Essays on the Neural basis of consumer choice.
(2008-06) Hedgcock, William
Economists often assume decision makers are hyper-rational agents with few limits to their cognitive capabilities. Sometimes labeled "Homo Economicus", these decision makers learn quickly, perform complex math, have endless information processing capacity, and are exceptionally rational (Thaler 2000). While these assumptions make it easier to model decision making behavior, they are demonstrably false. Decision makers calculate probabilities inaccurately (Allais 1953), dislike ambiguity (Ellsberg 1961), change behavior to avoid negative emotion (Luce, Bettman and Payne 2001), and are affected by the mere presence of alternatives that should be irrelevant to their decision (Huber, Payne and Puto 1982). These violations have led to the development of other models that are better at predicting what consumers actually do. Rank dependent utility theory (Quiggin 1981) took into account imperfect probabilistic calculations. A more recent version of this theory (Schmeidler 1989) extended the model to ambiguous decisions. Prospect theory's weighting function (Kahneman and Tversky 1979) also addressed people's imperfect probabilistic calculations while the theory's editing function accounted for some of the simplification strategies that decision makers use to overcome their cognitive limitations. Still, while better at describing certain behaviors, all of these theories share a common limitation. Like the model of Homo Economicus, these theories model behavior "as-if" humans were performing the functions prescribed by the theory. Rank dependent utility theory predicts probabilistic behavior "as-if" people rank ordered probabilities. Prospect theory's weighting function predicts probabilistic behavior "as-if" people overestimate small probabilities and underestimate large probabilities. Prospect theory's editing function describes some editing processes "as-if" people perform them to simplify decisions, but it does not describe how they actually come to choose a specific editing function (Thaler 2000). Ultimately, all of these theories generate a single equation that predicts consumer choice "as-if" consumers calculated these values and chose the option with maximal value. These models so far have either focused on what consumers should do or have focused on predicting what consumers actually do. Decision making models frequently do not attempt to describe the cognitive processes that are actually used to make a decision. The research described in this dissertation investigates this rarely studied area in human decision making. The research does not focus on what people do. Instead, it focuses on the decision making process itself. Recent advancements in brain imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET) have allowed decision making researchers to examine cognitive processes that were previously thought impossible to observe. This research uses behavior and fMRI to study the decision making process as it actually occurs in human decision makers. The dissertation adopts a theoretical framework developed in economics (Camerer et al. 2005) and psychology (Liberman 2007) to understand neuroscientific studies of behavior. The framework is a 2x2 combination of dual process theories that draws a distinction between cognitive processes that are either automatic or controlled and that are either internally (related to internal body states) or externally (related to sensory states) focused. Research hypotheses are developed and tested based on this framework. This dissertation contributes to the study of decision making in three ways. Theoretically, it tests an alternative model of decision making that emphasizes the cognitive process underlying decision making. Methodologically, the research demonstrates the usefulness of neuroscientific techniques as a complement to more traditional methods used in marketing research. Practically, the research contributes to a better understanding of decision making processes which could ultimately benefit society by helping consumers overcome decision biases that lead to societal problems such as drug use, obesity, and race bias.
An fMRI investigation of perceptual impairments on the DS-CPT in Schizophrenia patients.
(2010-12) Force, Rachel Brook
The Degraded-Stimulus Continuous Performance Task (DS-CPT) has been utilized to examine vigilance deficits in schizophrenia patients for decades. However, recent evidence suggests sustained attention may not be the foremost cognitive process underlying task performance. Through the use of functional magnetic resonance imaging (fMRI) and manipulating the perceptual load of the objects in a pseudorandomized order regions of interest that are involved in the creation and maintenance of novel mental representations as well as the implementation of unambiguous cues were identified. Whole-brain exploratory analysis resulted in statistical regions of interest that were further categorized as to their response patterns as involved in task performance, task difficulty, object perception, and the default mode network. Group differences were found in each category of response and correlations with behavioral indices indicated several mechanisms that may underlie cognitive deficits. As areas identified as providing top-down feedback such the dorsolateral prefrontal cortex, anterior cingulate cortex, and orbitofrontal cortex exhibited atypical activation, functional compensatory mechanisms may contribute to the lack of performance deficits observed in this sample. Increasing the understanding of the brain mechanisms involved in DS-CPT performance in schizophrenia patients may offer greater insight into the nature of visual perceptual deficits in the disorder.
An fMRI study of emotional face processing in adolescent major depression
(2013-02) Jappe, Leah Marie
OBJECTIVE: Major Depressive Disorder (MDD) is a serious, often chronic illness associated with significant impairment and suicide. MDD often begins during adolescence when brain areas that regulate emotion processing are still maturing. To expand upon our limited understanding of the neurobiological underpinnings of MDD early on in development, this study examined function within fronto-limbic neural circuits in response to an emotional faces task among depressed adolescents and healthy controls (HC) using functional magnetic resonance imaging (fMRI). METHOD: 34 adolescents with MDD (12 medicated, 22 unmedicated) and 16 healthy age and gender matched controls completed an emotional faces task where BOLD response was examined when viewing happy and fearful faces (presented in a block design) during fMRI. Scanning was completed using a 3.0 Tesla scanner. Data preprocessing and analysis was carried out using FEAT in FSL. Whole brain group level analyses were conducted using a mixed-effects model (FLAME) with cluster-wise significant testing (min Z=2.32; cluster significance = p<0.05, corrected). RESULTS: In response to viewing fearful versus happy faces, MDD showed reduced activation in areas of the right thalamus, right insula, and right hippocampus compared to HC. CONCLUSION: Results suggest that emotion processing in adolescent MDD is associated with abnormalities in subcortical and paralimbic brain regions within the broader fronto-limbic neural network. It is possible that these findings reflect deficits in depressed adolescents' ability to elicit cognitive control from higher cortical regions and to accurately respond to and process the emotional significance of fearful stimuli.
Fronto-limbic Neural Activity in Response to Basic Emotion Cues in Adults and Adolescents with Anorexia Nervosa: An fMRI Study
(2015-07) Hall, Leah
BACKGROUND: Anorexia Nervosa (AN) is a severe mental illness associated with chronicity, poor treatment outcome, high rates of morbidity and mortality, and significant individual and societal costs. Behavioral research studies show that AN is associated with deficits in several aspects of emotional processing, including emotional learning/memory, awareness, recognition, and regulation. It is possible that emotional processing abnormalities, driven by underlying genetic and neurobiological factors, contribute to AN development and persistence. Therefore, better understanding disruptions in basic emotional functioning in AN and the neural correlates that underlie them is critically important. METHOD: 19 adolescent and adult females with restricting-type AN (10 medicated, 9 unmedicated) and 19 healthy age and gender matched controls underwent functional MRI in conjunction with an emotional faces task where BOLD response was examined when viewing images of happy and fearful faces (presented in a block design format). Scanning was completed using a 3.0 Tesla scanner. Data preprocessing and analysis was carried out using FEAT in FSL. Whole brain group level analyses were conducted using a mixed-effects model (FLAME) with cluster-wise significant testing (min Z=2.32; cluster significance = p<0.05, corrected). Between group differences in eight regions of interest (ROIs: bilateral amygdala, insula, pregenual anterior cingulate, and subgenual anterior cingulate) were also examined (MANCOVA). Correlational analyses then investigated the relationships between brain response and self-reported eating disorder symptoms as well as between brain response and participant age. RESULTS: Whole brain comparisons showed that, in response to viewing fearful versus happy faces, participants with AN had lower activation in areas of the pregenual anterior cingulate and ventral prefrontal cortex. When examining ROIs, participants also showed reduced activity in pregenual anterior cingulate regions, which remained when controlling for body mass index and self-reported depression and anxiety. Findings did not appear to be a consequence of psychotropic medication use. Greater severity of eating disorder, depression, and anxiety symptoms was associated with lower activation in left ventral prefrontal regions. In addition, brain response in the left insula correlated with participant age and measures of eating disorder severity. No significant correlations were observed between clinical data and other ROIs, including the amygdala. CONCLUSION: Findings from the current study suggest that, during the ill state of restricting-type AN, fearful facial expressions elicit decreased functional activity in anterior cingulate and ventral prefrontal regions, areas of the brain that are central to emotional processing. Disruptions in neural activity may contribute to deficits in emotional awareness, recognition, and unconscious emotional regulation which have been widely observed within behavioral studies in AN. Future research is needed to further examine how fronto-limbic deficits in this disorder may be related to disease vulnerability and symptom maintenance. Such studies may guide identification of treatment targets and development of novel interventions, which are severely limited in this disorder.
Functional Brain Networks and the Openness-Psychosis Continuum
(2019-10) Blain, Scott
Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance, were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.
Functional Magnetic Resonance Imaging of Goal Maintenance in Schizophrenia: Activation, Functional Connectivity, and Reliability
(2016-06) Poppe, Andrew
Cognitive deficits are some of the most debilitating and difficult to treat symptoms of schizophrenia. Goal maintenance is a facet of cognitive control that has been shown to be impaired in schizophrenia patients as well as their unaffected first-degree relatives. Previous fMRI activation studies found less activation in dorsolateral prefrontal cortex (dlPFC) in schizophrenia patients compared with healthy controls during the completion of a goal maintenance task. This dissertation consisted of a series of studies employing a large, multisite retest dataset of schizophrenia patients and healthy control subjects. These studies sought to replicate previous activation findings using a newer goal maintenance task, to use group independent component analysis (ICA) to determine if schizophrenia patients also exhibited dysfunctional functional connectivity or functional network connectivity (FNC) compared with healthy controls during the performance of that task, and to evaluate the test-retest reliability of each of these metrics, directly compare them, and assess the influence of subject group and data collection site on reliability estimates. It replicated previous activation study findings of reduced dlPFC activity during goal maintenance. It additionally found that the temporal association between a frontoparietal executive control network and a salience network was stronger in healthy controls than in schizophrenia patients and that the strength of this relationship predicted performance on the goal maintenance task. It also found that the task-modulation of the relationship between left- and right-lateralized executive control networks was stronger in healthy controls than in schizophrenia patients and that the strength of this task-modulation predicted goal maintenance task performance in healthy controls. Finally, reliability estimates found that ICA and tonic FNC had acceptable overall reliability and that they minimized site-related variance in reliability compared with dynamic FNC and general linear model. These results indicate that ICA and tonic FNC may provide better tools for group contrast fMRI studies examining schizophrenia, especially those that incorporate a multisite design.
Functional Neuroimaging of Electrophysiological Rhythms in Pathological and Normal Brains
(2012-07) Yang, Lin
Imaging of electrophysiological activity in the brain plays a critical role in neuroscience research. Shown by emerging neuroimaging studies, rhythmic oscillations in electrophysiology reflect important functional changes in the brain. More importantly, the mapping of electrophysiological neural signals can serve as a diagnostic tool for neurological diseases. One typical example is the electroencephalography (EEG) technique, which has been established as a core component of pre-surgical evaluation in epilepsy treatment. However, despite the recent advances of functional neuroimaging techniques, a non-invasive, high resolution, electrophysiological imaging approach still remains challenging. In the clinical application of epilepsy, there is not an established protocol that can image, non-invasively, the electrophysiological signals during the most important epileptic event - epileptic seizures. The present dissertation research aims at developing electrophysiological imaging approaches with focus on the rhythmic activity in pathological and normal brains. Towards this goal, we have developed a spatiotemporal EEG imaging method, which is suited to image dynamic changes of ictal discharges during epileptic seizures. As evaluated in a group of epilepsy patients in clinical environment, such a non-invasive seizure imaging approach could potentially translate into a more precise and less risky pre-surgical imaging tool for epilepsy diagnosis. In addition to the direct impact of seizures, we have studied the electrophysiological changes in the widespread brain networks. The spatial and spectral features of EEG rhythms can reflect important correlation with the impact of seizures and the change of cognitive functions. The electrophysiological imaging in epilepsy, therefore, can serve as a useful tool in a pathological model to study cognition and consciousness in human brains. In order to achieve higher spatial resolution, we also improved the EEG source imaging by adding a multimodal component of functional MRI. From all the results we have obtained so far in these studies, it is suggested that the spatiotemporal EEG source imaging has the potential to improve clinical diagnosis and treatment of neurological disorders. It can also advance our understanding of basic neuroscience questions.
Heritability of Behavioral and Brain Measures in a Large Cohort of Healthy Twin and non-Twin Subjects
(2020-01) Joseph, Jasmine
This research investigated comprehensively the effects of genetics on behavioral traits, brain structure and function, and their associations in a large cohort of monozygotic (MZ) twins, dizygotic (DZ) twins, non-twin siblings (SIB) and non related (NR) individuals (N = 1206, total) provided by the Human Connectome Project (HCP). All primary measures available are of the highest quality and quantitatively assessed. They include the following for each individual: (a) Measures of behavioral traits in 5 domains (motor, sensory, cognitive, emotion, and personality); (b) volumes of 70 cortical brain areas extracted from high-resolution (0.7 mm isotropic) structural magnetic resonance imaging (sMRI) data; (c) resting-state blood oxygenation level dependent (BOLD) activity of the same areas extracted from long-duration (1200 volumes), fast-acquisition (every 0.72 s), high-resolution (2 mm isotropic) functional MRI (fMRI) data; and (d) white matter integrity measures (fractional anisotropy [FA] and mean diffusivity [MD] for 7 brain regions regions) derived from high angular resolution diffusion imaging (HARDI) MRI (dMRI) data at 1.25 mm spatial resolution and very strong magnetic field gradients at (100 mT/m). Data extraction and preprocessing was performed using a dedicated 704-processor high-performance computer cluster at the Brain Sciences Center using Matlab. Univariate and multivariate statistical analyses were carried out in personal computers using Matlab and IBM-SPSS (version 24). These analyses include the following. (a) Computation of common univariate statistics (mean, variance, etc.); (b) computation of intra class correlation (ICC) for each of the 4 genetic groups (MZ, DZ, SIB, NR) and its z-transform [zICC = atanh(ICC)] for each primary measure above; (c) analysis of variance (ANOVA) of zICC across genetic groups for each measure; (d) computation of heritability using Falconer’s formula; (e) multidimensional scaling (MDS) and hierarchical tree clustering (HTC) of this heritability for the different data sets (behavioral, sMRI, fMRI, dMRI). These analyses yielded substantial new information on the effects of genetics on brain and behavior, and partially elucidated underlying associations among the various diverse measures above. To our knowledge, this is the first such comprehensive study carried out.
Highly Selective Attentional Modulation of Task-Appropriate Neural Populations in Primary Visual Cortex
(2017-06) Warren, Scott
A wide variety of different forms of attention have been described in the human and non-human literature, however the recently developed Input Gain Model of visual attention proposes that a simple neural mechanism, multiplicative gain, may be employed to explain much of the available data on visual attentional modulations. On this basis, we hypothesized that a better explanation for distinct forms of attention may be that this simple attentional mechanism is in fact highly specific: attentional modulations are only present within task-appropriate neurons or neuron groups, and it is the location (and not nature) of these modulations which defines the observer’s current attentive state. We present the results of two orthogonal attention tasks, both targeting distinct but specific and well defined sub-populations of primary visual cortical (V1) neurons. In both experiments we observe that attentional modulations are grossly targeted to neural populations that are selectively tuned for the cue. When humans attend to one orientation, voxels reflecting orientation selective neurons tuned toward that orientation are selectively enhanced. When monkeys were trained to attend to a very small region of space, attention modulated the V1 representation of stimulus elements near that location in space. In both studies, these modulations are predictive of observer behavior, providing evidence that attentional modulation of V1 meaningfully impacts the perceptibility of the attended stimuli. Systematic imprecision in these modulations suggest that attentional modulations of V1 are mediated through corticocortical feedback, hypothetically from secondary visual cortex. This provides a strong constraint for further refinement of general models of attention.
Human neurophysiological mechanisms of contextual modulation in primary visual cortex.
(2010-05) Schumacher, Jennifer Frances
This dissertation examines visual processing of contextually modulated artificial and natural stimuli in primary visual cortex on a local scale. Understanding how local features are integrated into a global structure or ignored as irrelevant background is a critical step in comprehending human vision. To investigate these mechanisms, first it was necessary to measure the relationship between inferred neural responses, such as those obtained with blood oxygenation level-dependent (BOLD) fMRI, and local stimuli. From this point, orientation-dependent contextual modulation was analyzed locally or with a contour. While focusing on primary visual cortex, these experiments with stimuli of increasing complexity provide a foundation for how local features are grouped into global structures. BOLD fMRI provides a non-invasive method to measure the inferred neural response in humans. Because BOLD fMRI is a result of interaction between neural activity, blood flow, and deoxyhemoglobin concentration, it is not obvious that there is a linear relationship between these mechanisms as well as established functions, like the contrast response function (CRF). Chapter 2 measures the BOLD response to single Gabor patches of increasing contrast with two pulse sequences: Gradient Echo (GE) and Spin Echo (SE). GE measurements include signals from large and small veins while SE measurements eliminate the signal from large veins. Comparing these signals, at ultra-high field strength (7 Tesla) found the relationship between the CRF and BOLD fMRI for local stimuli is not linear with GE measurements. Chapters 3 and 4 focus on orientation-dependent contextual modulation of a single Gabor patch or of a vertical line of Gabor patches. In the periphery, surrounds of parallel orientation suppress the center stimulus while surrounds of orthogonal orientation facilitate the center stimulus. The relationship between the BOLD response and these suppressive or facilitative mechanisms was measured on a local scale (Chapter 3). Then, to compare the mechanisms for orientation-dependent contextual modulation and contour integration, performance in a contour detection task was measured over an extensive parameter space (Chapter 4). These data show that the BOLD response to suppressive stimuli do not behave as predicted by psychophysical results and that orientation-dependent contextual modulation and contour integration operate over different spatial scales, and likely different neural mechanisms. This dissertation provides data on the relationship between the BOLD response and local stimuli as well as data on the neural mechanisms behind orientation-dependent contextual modulation, contour integration, and texture classification. An over-arching theme is that inferred neural responses, such as those measured with BOLD fMRI, behave differently on a local scale than a global scale. However, other non-invasive measures provide details for how local stimuli are processed and further integrated into a global structure. Future work can incorporate computational models of neural activity and the BOLD response to clarify why measured responses differ on a local scale compared to a global scale.
The impact of executive function on reward processing in children: neural correlates and individual differences.
(2011-09) Langworthy, Sara Elizabeth
Executive function (EF) involves the integration of cognitive processes in order to support and sustain goal-directed behaviors that are crucial in the development of behavioral regulation (Sergeant, Geurts, & Oosterlaan, 2002). Motivational and rewarding information may alter the underlying cognitive processes surrounding the implementation of these goal-directed behaviors. Previous research indicates that both behavior and brain systems associated with reward and executive function (EF) processes may be interacting in children with ADHD (Luman, Van Meel, Oosterlaan, Sergeant, & Geurts, 2009b; Scheres, Milham, Knutson, & Castellanos, 2007). However, little research has been conducted within middle childhood to explore the intersection of EF and reward processing in typical development. Furthermore, little is know about the degree to which reward processing may be interacting with low EF ability on a behavioral and neural level during middle childhood. The current study examined behavioral performance as well as functional and structural Magnetic Resonance Imaging (MRI) data to address the degree to which executive function (EF) ability may be related to reward processing behaviors and brain circuitry in middle childhood. Chapter 2 addresses the overlap of EF and reward processing in behavioral task performance and parent questionnaire measures. Chapter 3 describes brain activation pattern differences in children with high versus low EF ability in a reward processing task. This portion of the study was conducted to determine whether children with lower EF ability process reward information similarly to children with high EF ability. In Chapter 4, the links between behavioral performance on EF and reward processing measures and structural volumes of related brain areas are discussed. Finally, in Chapter 5, general conclusions, limitations and future directions are outlined.
Individual Differences in Social Cognition and Behavior: a Personality Psychology Framework
(2021-08) Blain, Scott
Though humans are universally social, we vary considerably in our ability and motivation to form and maintain relationships. One approach to explaining this variation looks to identify the mechanisms that facilitate social behavior, including social cognition and reward sensitivity. Much of this work, however, is methodologically lacking and fails to provide comprehensive explanatory frameworks. This dissertation applies insights from personality psychology to improve our understanding of individual differences in social cognition and interpersonal functioning, focusing on the broad traits most descriptive of social behavior: Agreeableness, Extraversion, and Trait Affiliation. Across four studies attempting to elucidate the neurocognitive mechanisms of these traits, various methods—including questionnaires, behavioral tasks, fMRI, and psychometric techniques—were used to elucidate how and why individuals vary in their social abilities, behaviors, and associated outcomes. Study 1 was a multi-task investigation of how three Agreeableness-Antagonism subfactors differentially predict social cognitive ability. Study 2 used fMRI, along with personality questionnaires and behavioral tasks, to examine associations among Agreeableness, social cognitive ability, and function of the brain’s default network, applying structural equation modeling and a Bayesian individualized cortical parcellation approach. Study 3 failed to replicate classic associations demonstrated between measures of depressivity and reward sensitivity, suggesting that instead, reward sensitivity is related primarily to Extraversion. Finally, Study 4 explored Trait Affiliation, an important dimension at the intersection of Agreeableness and Extraversion, and presents a new Trait Affiliation Scale, along with evidence for its reliability, validity, and practical utility. Collectively, this work represents a high standard of statistical power and methodological rigor, utilizing a total of eight independent samples ranging from N = 195 to N = 25,732. Across these studies, social cognitive ability and reward sensitivity are further established as important psychological mechanisms underlying individual differences in social functioning. The work presented here also offers methodological contributions and broader theoretical insights into the understanding of personality and its relation to psychopathology. In sum, this dissertation paves the way to a better understanding of how and why individuals vary in our social abilities, interpersonal interactions, and relationship success, in addition to serving as an argument for the broad utility of personality psychology’s methods and theories.
Introducing Novel Relationships in Time Series Data
(2018-12) Agrawal, Saurabh
In many scientific and engineering domains such as climate, neuroscience, transportation, etc. measurements are collected from sensors installed in different parts of a complex dynamical system over regular intervals of time, resulting in a collection of large volumes of time series data. Automated data-driven approaches that can mine relationships between different time series could potentially lead to discovery of previously unknown physical processes which could further aid in designing policies and solutions to critical problems such as climate change, severe mental disorders, traffic congestion etc. This thesis defines novel relationships and patterns that can be studied in the time series data. In particular, the proposed definitions can capture two new types of relationships: i) multivariate relationships involving more than two time series, and ii) sub-interval relationships, that only exist during certain sub-intervals of time and are absent or occur very feebly during rest of the time. The other major contributions of this thesis include designing new automated data-driven approaches to find most interesting instances of defined relationships from the data in a computationally efficient manner, and proposing empirical approaches to assess the statistical significance of obtained relationships. The proposed approaches were applied to real-world datasets from two scientific domains: i) climate, and ii) neuroscience, and led to discovery of several new instances of relationships. Many of these instances are found to be statistically significant and reproducible in multiple time series datasets that are independent of the original dataset. One such instance led to the discovery of a climate phenomenon that was previously unknown to climate scientists.
Investigating the Neural Networks Involved in Externalizing and Conscientious Behavior
(2019-06) Rueter, Amanda Rae
Conscientiousness and impulsivity are traits that affect how well an individual is able to achieve their goals. Individuals high in Conscientiousness are described as being more industrious, maintaining order in their life, and having high self-discipline (Ozer & Benet-Martínez, 2006) and would likely score low on disinhibited externalizing. Individuals who score high on disinhibited externalizing behavior show lack of constraint, have higher sensation seeking behavior and are more prone to substance use (Miller, Lynam, & Jones, 2008). However, the neural systems underlying variation in these traits are not well understood. Functional connectivity is a way to study neural networks of the brain and can be used to assess whether or not individual differences are associated with connectivity in the brain. Previous research shows positive associations between Conscientiousness and functional connectivity in the goal priority network (GPN; Rueter et al., 2018). Few studies have investigated associations between functional connectivity and Conscientiousness and disinhibited externalizing. In this dissertation, I: (1) attempted to replicate findings from a previous study with a larger sample to investigate associations between connectivity and Conscientiousness while extending the analysis to include disinhibited externalizing behavior and (2) apply the same functional connectivity methodology to a task-based fMRI data set to see if the traits of interest and connectivity remain associated during a cognitive task requiring inhibition. I hypothesized that the GPN and the central executive network (CEN) would be negatively associated with disinhibited externalizing behavior and that only the GPN would be positively associated with Conscientiousness. Results from study one and study two suggest that the CEN is negatively associated with disinhibited externalizing, while only study two suggests that the GPN is negatively associated with disinhibited externalizing. Study two supported the hypothesis that the GPN is associated with Conscientiousness, while Study 1 did not. This dissertation provides an integrated investigation of how Conscientiousness and externalizing behavior are related on a biological level. Resisting impulses and orienting oneself towards goals are both important behaviors implicated in successfully navigating life. Further research on these networks may help us create therapies or treatments to increase Conscientiousness and reduce self-compromising, maladaptive, externalizing behaviors.
Local and Iterative Visual Processing Deficits in Schizophrenia
(2017-05) Espensen-Sturges, Tori
Evidence of dysfunctional visual processing in schizophrenia patients has been noted in all stages of the visual processing pathway. The iterative nature of vision- with hierarchical feedforward signals, modulating feedback signals, and horizontal intracortical connections- makes it difficult to pinpoint exact loci that are driving these deficits. This dissertation uses several contextual modulation paradigms in an effort to isolate and explain the nature of disruptions in iterative visual processing in schizophrenia. Chapter 1 provides an overview of visual processing dysfunctions in schizophrenia, and examines a variety of mechanisms that may play a role. These include neurotransmitters, magnocellular versus parvocellular processing streams, abnormal local connections, and abnormal long-range feedback connections. These are presented in the context of several theoretical perspectives of visual neuroscience. Chapter 2 provides functional magnetic resonance imaging data from a fractured ambiguous object task that probes the role of high-level qualities in primary visual cortex activation and interregional connectivity, and how these may be disrupted in psychosis. Chapter 3 introduces a computational model that attempts to fit parameters to psychophysical data to isolate disrupted mechanisms in schizophrenia. This model focuses on the role of gain control and segmentation of center and surround stimuli in a tilt illusion paradigm. Chapter 4 presents previous work, examining the modulatory effect of the NMDA receptor agonist d-cycoserine on conditioned fear generalization. This work was done in healthy controls as a step in expanding our knowledge of the function of d-cycloserine in increasing specificity and efficacy in the fear learning process.

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