Browsing by Subject "Neuroimaging"

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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.
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.
Interplay Between Frontolimbic Resting State Connectivity And Hypothalamic-Pituitary-Adrenal Axis Functioning In Adolescents With And Without Depression
(2019-03) Thai, Michelle
Depression is associated with abnormalities in HPA-axis functioning and neural circuitry that underlie the stress response. Although positive associations have been found between cortisol levels and amygdala metabolism, activation, and volume, the associations between cortisol and resting state functional connectivity (RSFC) has not been examined. RSFC captures intrinsic connections between brain regions that may set the stage for the rallying of the HPA system. The association between frontolimbic RSFC in particular and HPA axis functioning is critical since stress system functioning involves activating to and recovering from threat, processes mediated by limbic and prefrontal activity respectively. The purpose of this study was to examine the association between cortisol and frontolimbic RSFC in healthy controls and adolescents with depression. Overall, healthy controls tended to show positive correlations between frontolimbic connectivity and cortisol levels in the context of the TSST whereas patients with depression showed an inverse relationship. Positive association between neural and HPA stress systems in healthy controls may suggest coordinated upregulation and downregulation of these two stress systems in response to stress. In contrast, in patients with depression, excessive recruitment of the mPFC by the amygdala may interfere with HPA system recruitment efficiency and successful rallying of HPA axis in response to social stress. These findings provide evidence that the intrinsic quality of this frontolimbic channel is related to HPA axis functioning, and patients with MDD show different patterns of associations compared to HC, which may interfere with adaptive stress functioning.
Label-free optical imaging to study brain connectivity and neuropathology
(2018-11) Liu, Chao
The brain is composed of billions of neurons that communicate through an intricate network of axons and dendrites. The difficulty of tracing the 3D neuronal pathways, however, has been a challenge to study the brain connectivity in normal and diseased brains. Polarization-sensitive optical coherence tomography (PS-OCT) provides label-free and depth-resolved contrasts of tissue microstructure. For brain imaging, nerve fiber tracts that are as small as tens of micrometers can be highlighted by polarization-based contrasts due to the birefringent nature of myelin sheath. We applied optical imaging to investigate the anatomical changes associated with neurodegeneration and neuro-oncology. The former includes spinocerebellar ataxia type 1 (SCA1), a fatal inherited genetic disease. The intrinsic optical properties revealed the neuropathology in SCA1 mouse models. To investigate the role of nerve fiber tracts in glioblastoma invasion, we combined PS-OCT with confocal fluorescence microscopy to characterize glioma cell migration behavior in mouse brain slices. Moreover, PS-OCT can be adapted to quantify the inclination angles of nerve fibers and further developed to delineate the complete 3D neuronal pathways. This method and its future advances open up intriguing applications in neurological and psychiatric disorders.
Methods for Analyzing Multi-Subject Resting-State Neuroimaging Time Series Data
(2019-05) Hart, Brian
Resting-state neuroimaging modalities such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) collect data in the form of time series which represent the activity in the brain at rest. This resting-state behavior can be analyzed in different ways to address different research questions and is thought to represent the intrinsic activity of the brain. We discuss three potential avenues of analysis. First, we propose a permutation-based method which tests the longitudinal functional connectivity of fMRI data collected from cognitively normal participants and Alzheimer’s patients. Next, we propose a Bayesian nonparametric model to jointly perform spectral time series analysis on EEG data from 1,116 twins from the Minnesota Twin Family Study (MTFS) and discuss a novel heritability estimator for features of the estimated spectral density curves. Finally, we propose another Bayesian nonparametric model to perform EEG microstate analysis of the MTFS data at the twin pair level. Each method discussed views the resting-state time series data from a different angle. Additionally, in each of these scenarios, we jointly analyze data collected from many different participants while accounting for the design of the study in which the data was collected. Regardless of the analysis method chosen, accounting for the within and between-participant dependence structure yields improved results.
Multi-contrast optical coherence tomography for brain imaging and mapping
(2014-08) Wang, Hui
Although our knowledge of neuronal function and regional activity has been tremendously enriched in the past decades, coordination of these neurons to form the complex behaviors has yet to be understood. The neuronal pathways (also named connectome) form the structural foundation of the dynamic circuits in the brain. The recent interests in connectome and brainwide database have imposed a pressing need for high-resolution imaging techniques that allows large coverage. This dissertation develops a novel multi-contrast optical coherence tomography (MC-OCT) technique for the application of brainwide imaging and architectural mapping in 3D at high spatiotemporal resolution, with an emphasis on the connective tracts. The image contrasts originate from intrinsic optical properties of the brain tissues in which light propagates, back-scatters, attenuates, and changes its polarization state. Due to a birefringence property of the myelin sheath, MC-OCT specially targets the white matter, with qualitative architecture and quantitative orientation maps produced. The fiber tracts with diameters of a few tens of micrometers are visualized and tracked in 3D. As a further advance, a serial optical coherence scanner (SOCS) integrating the MC-OCT and a Vibratome slicer is realized for large-scale brain imaging and mapping at high resolution. The 3D fiber architecture and fiber orientation in rat brain are reconstructed at a resolution of 15 x 15 x 5.5 µm3. SOCS enables systematic validations of diffusion magnetic resonance imaging (dMRI) at microscopic resolution. A cross-validation in a postmortem human medulla sample shows remarkably good agreement on fiber structures and orientations between the two techniques. In addition, SOCS resolves intricate fiber patterns that are not captured by the dMRI. Taken together, the serial MC-OCT technique has the potential to bridge cross-scale investigations for a hierarchical view of neuroanatomical connections, thus opening intriguing applications in brain mapping and neural disorders.
A Neuroimaging Approach to Noninvasive Brain-Computer Interface Control
(2018-02) Edelman, Bradley
Detecting mental intent through brain-computer interface (BCI) technology has significantly improved the lives of patients suffering from various neurological disorders such as amyotrophic lateral sclerosis and spinal cord injury. BCIs utilizing intracortical signals have achieved closed-loop control of robotic devices for completing everyday actions by performing various motor imagery (MI) tasks. However, the substantial cost and high risk of electrode implantation limits the widespread use of these systems in clinical and recreational settings. A noninvasive counterpart using electroencephalography (EEG) attaining similar levels of performance would profoundly impact the translation of these systems towards everyday life. Nevertheless, ineffective training protocols and poor signal quality significantly hinders EEG-based neural decoding. Here, I present a unique framework for driving EEG BCI towards everyday use, leveraging on (1) increasing cognitive arousal with a novel task paradigm and (2) improving neural decoding through noninvasive neuroimaging techniques. I developed an online continuous tracking task and demonstrated that healthy human users can achieve scalp-recorded neural control competitive with that of invasive work reported in literature. Through enhancing user engagement, this task additionally proved to be a more effective training tool than traditional center-out tasks for driving BCI skill acquisition and the physiological correlates thereof. I additionally reveal the utility of electrical source imaging (ESI), an imaging technique used to reconstruct cortical activity, for significantly improving both offline and online EEG-based neural decoding. Notably, real-time ESI-based control facilitated a profound improvement over scalp control for online CP BCI control in naïve and experienced users. Finally, I created a multimodal BCI using MI and visual attention tasks to test users’ ability to multitask during BCI control as would be needed in practical situations. In all, this thesis presents an encompassing introduction and evaluation of novel EEG BCI techniques that may help bring the technology to daily life.
Visual mode switching: Behavior & Neuroimaging
(2023-04) Li, Yanjun
"Color context effects" describe empirical results or phenomena where a surround, either in space or time, changes perception of the color of a target. The strength of color context effects may be influenced by our familiarity with the specific context. We term stronger and faster context-dependent processing under familiar contexts “visual mode switching”. Mode switching could help to stabilize vision in the changing visual environment and aid many perceptual goals, including improving the detection or discrimination of objects and their properties, and making neural codes more efficient. This dissertation presents three behavioral studies investigating whether visual mode switching can be learned through experience with a context, and whether it affects many stimuli in a given environment. Study 1 explored whether mode switching can occur after wearing strongly tinted glasses for five 1-hr periods per day for five days. We found that over days the tint faded more and more rapidly upon donning the glasses, indicating that the visual system learned to rapidly adjust to the tinted environment, switching modes to stabilize color vision. Study 2 tested whether wearing tinted glasses for a single 5-hr period each day for five days suffices for learning to switch visual modes. We found that mode switching can be acquired from a once-daily experience. In study 1 and 2, we tested for changes in the perception of unique yellow, which contains neither red nor green. Study 3 explored whether effects of mode switching can apply to many stimuli affected by the environmental change. We used a dissimilarity rating task to measure and track perception of many different colors, and found that colors across the color space appeared more and more normal immediately after putting on the glasses. These findings may help to predict when and how mode switching occurs outside the laboratory. Lastly, in study 4 we conducted a pilot functional MRI (fMRI) experiment to investigate the neural mechanisms of visual mode switching. We adopted a similar paradigm as in the behavioral studies. The fMRI design worked well and allowed us to identify brain regions that had changes in their responses to colors seen while wearing the red glasses before and after five days of experience with them. We found that both the primary and extrastriate visual cortex may be involved in mode switching. Taken together, these findings help us better understand how experience alters both visual perception and cortical processing of color.
Visuo-haptic integration process during object size discrimination: an fMRI study
(2013-03) Lu, Chia-hao
When exploring objects during every day activities, visual and haptic cues provide information about their properties such as size, shape and texture. How these two streams of sensory information are integrated by the brain to form a single percept is still not fully understood. Specifically, there is still a debate which regions of the brain are activated during visuo-haptic perception and whether one can identify areas that are uniquely activated during visuo-haptic integration, but not during unimodal perception. Previous research indicated that the lateral occipital complex (LOC) might be such a region. In an attempt to fill this knowledge gap, this study investigated the cortical activation patterns that underlie object size perception based unimodal visual or haptic information, and when both forms of information were available (bimodal). Brain imaging data were obtained from 12 healthy participants in a size perception task using visual and haptic stimuli. In each trial, a 6 cm reference object was judged against a comparison object (heights: 5.2-6.8 cm) and participants verbally indicated which object was perceived as taller. Unimodal and bimodal stimulus presentations were tested. Based on their responses size discrimination thresholds (DT) at the 75% correct response rate were obtained. In addition, functional brain activation volumes were derived during each condition for contrast analysis. Thresholds and associated correct response rates were not significantly different between unimodal and bimodal conditions. Bimodal visuo-haptic size discrimination was associated with super-additive activation in the dorsolateral prefrontal cortex (DLPFC), supplementary motor area (SMA) and inferior parietal cortices, while the LOC revealed no significant activation. In addition, during crossmodal stimulation the left SMA and primary sensorimotor cortex revealed significant activations when the visual cue was presented first. That is, during crossmodal visuo-haptic object perception having a prior visual experience activates different areas than having a prior haptic experience of the object. To our knowledge, this is the first direct comparison of unimodal and bimodal visuohaptic size perception that combined brain imaging and psychophysical data to identify sites of multisensory integration. The finding of a fronto-parietal network involved in visuo-haptic processing challenges a previous notion of the LOC as the sole locus of visuo-haptic integration. Our results suggest that the underlying visuo-haptic perceptual process seems to be task dependent.

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Browsing by Subject "Neuroimaging"