• Other research productsclose
• CA close
• EBRAINS close
• Neuroinformatics close

Hypothalamic control of food intake may be overridden by cortical and limbic brain regions that process reward and the hedonic aspect of food, affecting the ability to discriminate between homeostatic and hedonic feeding. Women, in particular may be affected since cognition and perception of reward change during the menstrual cycle. Changes in estrogen and progesterone levels during the menstrual cycle induce changes in appetite and eating behavior. Food intake declines in the peri-ovulatory period when estrogen levels peak, but increases in the luteal phase when progesterone levels increase. In this novel study we introduce a different context in which to study appetite regulation; the menstrual cycle. The two main study objectives were: 1) to compare the BOLD response between the peri-ovulatory and luteal phases of the menstrual cycle and 2) to compare the BOLD response between women in a negative and positive affect state in response to visual food stimuli using functional magnetic resonance imaging. Pictures of food, regardless of their caloric content stimulated greater activation during the follicular phase compared to the luteal phase in the orbitofrontal cortex, fusiform, amygdala and inferior operculum. Activity was present in the hippocampus, ventral tegmental area and nucleus accumbens in response to high calorie images but not low calorie images during the follicular phase. The insula showed selective activity responding to high calorie pictures in the luteal phase and low calorie pictures in the follicular phase. High calorie food cues elicited greater BOLD signal for women reporting negative affect in the putamen, amygdala, pulvinar, prefrontal cortex, pallidum, fusiform and ventral tegmental area. In summary, visual food cues produced a more robust response during the follicular phase of the menstrual cycle and during a negative mood state in brain regions modulating the rewarding and motivational effects of food images. An increased understanding of how appetite-regulating brain regions respond during the menstrual cycle and in different mood states may facilitate the development of new therapies to reduce the incidence of obesity.

Fetal Alcohol Spectrum Disorder (FASD) can occur when a mother drinks alcohol during pregnancy. The full spectrum of adverse effects on the brain induced by prenatal alcohol exposure ranges from mild to severe brain dysfunction in executive functions, learning, memory, social communication, and sensory-motor skills. The goals of this thesis were to assess the functional outcomes of children with FASD using psychometric testing and eye movement control tasks and relate these to measures obtained from diffusion tensor imaging (DTI). Results from the eye movement studies successfully differentiated those with FASD from controls on both sensory-motor and behavioural outcomes. Children with FASD showed deficits in response inhibition, working memory, saccadic reaction time, and saccade metrics on three eye movement tasks. A sexually dimorphic impact of prenatal alcohol exposure on eye movement control was also found. The psychometric tests revealed deficits in set shifting, response inhibition, selective and sustained attention, working memory, and visuospatial processing. The DTI results revealed significantly higher mean diffusivity in the splenium of the corpus callosum. These measures were then correlated to one another to search for common brain pathways utilized to complete these tasks. Working memory measures obtained from the memory-guided eye movement task significantly correlated with three psychometric tests which measured working memory in the FASD group. The prosaccade eye movement task which measures basic sensory-motor processing was also correlated with a visuospatial processing psychometric task in the FASD group. Finally, response inhibition measures from the eye movement tasks correlated with response inhibition measures obtained from the psychometric testing in the FASD group. Additionally, eye movement inhibition measures correlated negatively to fractional anisotropy and positively to mean diffusivity of the splenium in the control, but not the FASD group. Therefore, brain function of typically developing controls and children with FASD can be successfully assessed using eye movement tasks, psychometric testing and DTI. These functional measures help identify specific brain regions affected by prenatal alcohol exposure which can lead to more specific interventions. These findings can also help streamline the diagnostic process by pointing to efficient and effective tools that differentiates children with FASD from controls.

A Brain Computer Interface (BCI) system can bypass impaired systems in the brain, nervous system, and muscles to enable alternate function and allow the user to reconnect with the outside environment. Measurements for these systems usually include the collection of brain signal activity from sensors mounted on the surface of the scalp. Electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) are two commonly used non-invasive brain imaging modalities in BCI systems. EEG records the electrical activity produced by neuronal activations whereas fNIRS measures the concentration changes of oxy- (HbO) and deoxyhemoglobin (HbR) molecules in the brain cortex. In this thesis, both EEG and fNIRS data collected during a bilateral right- and left-hand motor imagery task were used to detect brain signals that suggest intent to move. Feature extraction and classification are two important components of a BCI in which discriminant features are extracted from the brain signals and then decoded to interpret the user’s intent. Using the fNIRS data in the first part of this thesis, different features were extracted (mean, peak, minimum, skewness, and kurtosis) and classification algorithms (linear (LDA) and quadratic discriminant analysis (QDA), support vector machine (SVM), Logistic Regression, and Naïve Bayes) were compared to find the set of features and classifiers with the highest accuracy. The mean, peak, and minimum of HbO, as well as the mean of HbR and mean of difference between HbO and HbR produced the highest accuracies among features, whereas skewness and kurtosis of HbO resulted in the lowest accuracies. Furthermore, QDA and SVM with polynomial and Gaussian kernel functions resulted in the highest accuracies compared to other classifiers. Using QDA and SVM, this study assessed a channel selection algorithm to reduce the number of sensors in the BCI examining a strategy to use fNIRS results to target the placement of EEG electrodes. Lastly, the feasibility of hybrid EEG and fNIRS system was investigated by comparing corresponding classification accuracies to EEG and fNIRS alone. The combined EEG and fNIRS system resulted in significant improvements in classification accuracies compared to EEG or fNIRS alone.

The experience of pain is a highly complex and personal experience, characterized by tremendous inter-individual variability. Pain perception can differ substantially across individuals due to many factors such as age, gender, genetics, cognition and emotionality etc. Some individuals are very sensitive to pain whereas others tolerate pain well. Athletes can play competitive sports even with significant injuries while other people feel tremendous pain while getting a flu shot. This phenomenon of inter-individual variability in pain responses has challenged scientists and clinicians alike. It is difficult to determine whether subjective reports of pain reflect true individual experiences of pain. However, the development of neuroimaging techniques has dramatically progressed our understanding of pain processing. This project investigated the neural correlates of inter-individual differences in pain responses in healthy individuals, by means of functional magnetic resonance imaging (fMRI) of the entire central nervous system. Twenty-healthy participants were asked to rate their pain following a noxious thermal stimulus, while undergoing functional MRI, and considerable inter-individual variability was observed. Results from this project demonstrated central mechanisms in the brain, brainstem and spinal cord that contribute to this variability. Participants that reported higher pain to the noxious stimulus showed greater fMRI responses in some brain, brainstem and spinal cord structures involved in processing the emotional, cognitive and motivational aspects of pain. This showed that the subjective reports of pain are a reliable indicator, and inter-individual differences in pain responses truly reflect variability in pain experience. It is expected that this knowledge will contribute to a better understanding of the neuronal processes, as well as substantial inter-individual variability observed in chronic neuropathic pain populations such as fibromyalgia, patients with spinal cord injuries etc.

Background: The study of impact biomechanics in contact sports has improved our current understanding of concussion mechanisms and the cumulative effects of subconcussive impacts on brain health. Impact exposure is often described by the total insults an athlete sustains or peak magnitude, however, these metrics do not consider underlying properties of the acceleration-time impact profile. It remains unknown whether additional kinematic information can better differentiate impact exposure across positions and session types or characterize subclinical brain changes. Purpose: The objective of this project was to examine potential differences in the biomechanical properties of impacts sustained by collegiate football athletes. These parameters were also used to evaluate changes in functional connectivity and resting perfusion over a season of football. Methods: Helmet accelerometer data were analyzed to characterize subconcussive impact exposure among collegiate football athletes. Impact frequency (per session), peak linear and rotational magnitude, impact duration, area under the acceleration-time curve, impulse, and peak head jerk were used to differentiate mechanical loading events between positional groups, as well as across session types. Resting-state neuroimaging was also used to evaluate the relationship between positional group, impact biomechanics, and concussion history with changes in functional connectivity and resting perfusion in a subset of athletes following subconcussive impact exposure. Results: Biomechanical differences were found in all parameters of interest between session types and positional groups. Several properties of the linear acceleration profile, in addition to rotational velocity, highlighted alterations in regional hemodynamics and functional connectivity within the brain, whereas no such differences were observed using impact count or peak linear acceleration alone. Scaling the functional connectivity data by resting perfusion altered the observed differences in some regions of the brain, highlighting the shared variance that exists between functional network re-organization and perturbations to local physiology following subconcussive impact exposure. Conclusion: These findings indicate that kinematic profile analyses may provide novel insight beyond impact count or peak magnitude that allows for a more complete characterization of impact biomechanics. Altogether, this approach creates a strong paradigm for future studies to examine how these impact parameters relate to injury risk following exposure to repetitive subconcussive head impacts.

Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to map extensive networks within the cortex, but its use to study resting-state connectivity in the brainstem (BS) and spinal cord (SC) has been limited. This is because of the challenge associated with using fMRI in this region. One reason for this is the small cross sectional area of the SC. The proximity of the BS and SC to the heart and lungs increases the amount of noise arising from physiological sources. The noise has a larger effect on the MR data acquired from the BS and SC than the cortex. Therefore, having a larger source of noise makes it harder to identify the source and separate from the data. The studies presented in this thesis try to tackle this problem. Data for both studies in chapters two and three, were obtained from 16 healthy participants. The study in chapter two used axially acquired images at the level of the periaqueductal gray, the rostral ventro-medial medulla and the sixth cervical SC segment. The study presented in chapter three used sagittal slice images from the thalamus to the T1/T2 vertebral disk spanning 9 sagittal slices centered on the SC. The results of the study in chapter two identify specific sources of noise and quantify their contribution to the overall signal variance. The largest contributor to the signal variance was bulk motion (19%). Cardiac-related motion accounted for 14% of the signal variance followed by non-specific signal variations detected in white matter (10%), respiratory-related motion (2.6%), and end-tidal CO2 variations (0.7%). Significant left-right connectivity was detected in the dorsal horns and ventral horns of the SC after the noise was removed from the data. The study presented in the chapter three saw extensive connectivity within and across the BS and SC. Resting-state networks were observed between the BS and SC which involved primarily dorsal or ventral SC regions, and included specific anatomical regions within the BS as well. These results demonstrate the presence of resting-state connectivity within the BS and SC and are an important step towards developing rs-fMRI in this region.

Generalized Anxiety Disorder (GAD) is a highly prevalent anxiety disorder, characterized by chronic, excessive worry. Physical symptoms are prevalent in GAD, but physiological data are often inconsistent. The goal of the present research is to investigate the neural responses to threat in GAD versus healthy controls (HC). To achieve this goal, we collected data from the largest span of the central nervous system to-date, using functional magnetic resonance imaging (fMRI). This work was broken down into the following three aims: to identify neural activity differences between GAD and HC groups in response to threat in Aim 1) the brain, Aim 2) the cervical spinal cord, and Aim 3) the thoracic spinal cord. All three aims use data acquired from a single sample of 16 participants with GAD and 14 HC. The thesis begins with an introduction to relevant topics including GAD, physiology, and MRI technology. Aim 1) is addressed in two parts. Aim 1a is an in-depth systematic review and meta-analysis on previous neuroimaging research to identify the known neural correlates of GAD, yielding results from the dorsolateral prefrontal cortex, anterior cingulate cortex, amygdala, hippocampus, and culmen of the cerebellum, among others. Aim 1b includes a brain fMRI study in which GAD and HC participants view emotion-evoking images. First, region-of-interest analyses are conducted using regions identified in the systematic review, but results are not significant for these analyses. A follow-up whole brain analysis yields significant results for the main effect of group, corroborating many of the findings from the systematic review. Aims 2 and 3 are considered together in an identical fMRI task as Aim 1b, this time looking at the cervical and thoracic spinal cord. Spinal cord results include increased activity in ventral rostral cervical cord (innervating the neck, shoulders, and trapezius muscles) and mediolateral thoracic cord (innervating the adrenal medulla and gut) for the GAD group as compared to HC. These results provide neurological evidence for increased muscle tension and autonomic activity in the gut and adrenal glands for those with GAD. This work provides the most comprehensive fMRI study of the neurophysiological underpinnings of GAD to-date.

Over the course of a football season the athletes are subject to a large number of impacts ranging in magnitude. With these impacts failing to cause any clinical signs of concussion, they often get disregarded as non-injurious. Recent evidence shows that the cumulative effects of these impacts may cause microstructural damage within the brain. This study set out to examine the effects of these subconcussive impacts on two specific white matter tracts in the brain: the corpus callosum (CC) and the corticospinal tract (CST). 20 Canadian Univeristy level football players were followed for one season. These players were examined using diffusion tensor imaging at three time points: prior to any team sessions (preseason), following training camp (post-training camp), and following the last session of the season (post-season). Four DTI measures were analyzed: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), in order to asses white matter integrity. Players were separated into two groups based on impact exposure throughout the season. Results showed that the high exposure group had significantly lower FA (main effect of Group) in the CC and the bottom-left section of the CST. There was a significant decrease in FA over time in the top section of the left CST. There were no observed changes in MD, AD or RD. The changes found in this study indicate that despite no outward symptoms of injury (SRC), “silent” changes are occurring within the brain’s microstructures as a result of receiving numerous subconcussive impacts during a season of football.