Multisensory Integration Sites Identified by Perception of Spatial Wavelet Filtered Visual Speech Gesture Information

Perception of speech is improved when presentation of the audio signal is accompanied by concordant visual speech gesture information. This enhancement is most prevalent when the audio signal is degraded. One potential means by which the brain affords perceptual enhancement is thought to be through the integration of concordant information from multiple sensory channels in a common site of convergence, multisensory integration (MSI) sites. Some studies have identified potential sites in the superior temporal gyrus/sulcus (STG/S) that are responsive to multisensory information from the auditory speech signal and visual speech movement. One limitation of these studies is that they do not control for activity resulting from attentional modulation cued by such things as visual information signaling the onsets and offsets of the acoustic speech signal, as well as activity resulting from MSI of properties of the auditory speech signal with aspects of gross visual motion that are not specific to place of articulation information. This fMRI experiment uses spatial wavelet bandpass filtered Japanese sentences presented with background multispeaker audio noise to discern brain activity reflecting MSI induced by auditory and visual correspondence of place of articulation information that controls for activity resulting from the above-mentioned factors. The experiment consists of a low-frequency (LF) filtered condition containing gross visual motion of the lips, jaw, and head without specific place of articulation information, a midfrequency (MF) filtered condition containing place of articulation information, and an unfiltered (UF) condition. Sites of MSI selectively induced by auditory and visual correspondence of place of articulation information were determined by the presence of activity for both the MF and UF conditions relative to the LF condition. Based on these criteria, sites of MSI were found predominantly in the left middle temporal gyrus (MTG), and the left STG/S (including the auditory cortex). By controlling for additional factors that could also induce greater activity resulting from visual motion information, this study identifies potential MSI sites that we believe are involved with improved speech perception intelligibility

Feasibility of using Arterial Spin Labeling for Detecting Longitudinal Changes in Cerebral Blood Flow

The ability of the perfusion MRI technique, arterial spin labeling (ASL), to quantify cerebral blood flow (CBF) makes it attractive for longitudinal studies of changes in brain function, such as those related to chronic pain. However, ASL\u27s poor spatial resolution makes image alignment between sessions difficult, leading to increased variance and greater Type-I errors. In addition, variability due to differences in basal blood flow between sessions and confounding effects such as the arterial transit time (ATT) have the potential to reduce reproducibility over time. The focus of this thesis is to investigate the ability of ASL to detect long-term changes in regional CBF within an individual on a voxel-wise level. It is hypothesized that ASL has the sensitivity to detect activation-induced CBF changes over periods as long as a month if the sources of variance that degrade between-session comparisons are minimized. To test this hypothesis rest and activation (motor task) CBF images were acquired from healthy subjects on three separate imaging sessions. Registration errors were minimized by using individual head molds to replicate the head position in successive sessions. Variations in resting CBF were controlled for by performing the imaging during the same time of day, and subjects were asked to refrain from using common substances, such as caffeine, that are known to affect CBF. Finally, ATT maps were generated on each session to investigate its stability. From these data sets, the within- and between-session variability in CBF was determined and motor-related activation maps were generated from rest and activation data acquired on from the same session and from sessions separated by a week and a month. The results demonstrated excellent reliability (intraclass correlation coefficients greater than 0.75) both within- (0.89 ± 0.2) and between-session (0.84 ± 0.15), and high reproducibility (within subject coefficient of variation, wsCV, greater than 20%) within- (wsCV = 4.7 ± 4.5%) and between-session (wsCV = 5.7 ± 4.4%). Between-session reproducibility of the ATT was high (wsCV = 5.0 ± 2.7%), suggesting that the confounding effect of ATT over a month was minimal. The similarity in within- and between-session variability and their activation maps indicated that registration errors between sessions were minimal. Measures of precision of activation demonstrated that less than ~20% of between-session activation were false positives. These results demonstrate the feasibility of conducting voxel-wise analysis of CBF images acquired on different days and highlight the potential of this technique for longitudinal studies

A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: replication in elderly and young populations

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders

Individualised Clinical Neuroimaging in the Developing Brain: Abnormality Detection

Perinatal neuroanatomical structure is incredibly intricate and, at time of birth, is undergoing continuous change due to interweaving developmental processes (growth, myelination and gyrification). While there is some small variability in structure and rates of development, all follow proscribed pathways with well documented milestones. Brain injury or other disruption of these processes can result in poor neurodevelopmental outcomes or mortality, making their early identification critical to estimate, and potentially forestall, negative effects. MRI is an increasingly used method of investigating suspected neonatal encephalopathies and injuries.Identification of these injuries and malformations is more challenging in neonates compared to adults due to the brain’s continuously evolving appearance. This makes radiological review of neonatal MRI an intensive and time-consuming task which, in an ideal setting, requires a team of highly skilled clinicians and radiologists with complementary training and extensive experience. To assist this review process, some localisation method that highlights areas likely to contain tissue abnormalities would be highly desirable, as it could quickly draw attention to these locations. In addition, identifying neonates whose MRI is likely to contain some form of pathology could allow for review prioritisation.In this thesis, I first investigated using normative models of neonatal tissue intensity for brain tissue abnormality detection. I applied voxel-wise Gaussian process (GP) regression to a training cohort of neonates with no obvious lesions, all born preterm (<37 weeks) but imaged between 28-55 weeks. Gestational age at birth (GA), postmenstrual age at scan (PMA) and sex were used as input variables and voxel intensity as the output variable. GPs output a mean value and its variance inferred from neonates within the training cohort whose demographic information most closely matched those of the prediction target. The voxel specific models were put together to form a synthesised typical image and standard deviation image derived from the variance outputs. Z-score abnormality maps were constructed by taking the difference between neonates actual MRI and GP-calculated synthetic image and scaling by their standard deviation map. Higher Z-score map values indicate voxels more likely to contain abnormal tissue intensity. Using manually delineated masks of common brain injuries seen in a subset of neonates, these abnormality Z-score maps demonstrated good detection performance using area under the curve of receiver operating characteristic scores, with the exception of small punctate lesions.The initial voxel-wise models had substantial false positives around the edges of the brain where there is large typical heterogeneity. I next investigated if incorporating local structural information into predictive models could improve their ability to accommodate typical anatomical heterogeneity seen across individual brains and improve the accuracy of synthetic images and abnormality detection. To achieve this, voxel intensity values in a patch surrounding the prediction target were appended to the design matrix, alongside GMA, PMA and sex. The patch-based synthetic images were able to match an individual’s brain structure more closely and had lower false positives in normal appearing tissue. However, a weakness was that the centre of some larger lesions was included in the predictions (thereby classified as ‘healthy’ tissue), having a deleterious effect on their coverage, increasing false negatives. This was offset by much better coverage of smaller, more subtle lesions, to the extent that overall performance was higher compared to that seen in the earlier model.I also investigated if the Z-score abnormality maps could be used to classify neonates with MRI positive brain injury from those with normal appearing brains. While many machine learning algorism see frequent use in neuroimaging classification tasks, I opted for a logistic regression model due to its high levels of interpretability and simple implementation. Using the histograms of the Z-score abnormality maps as inputs, the model demonstrated good performance, being able to correctly identify neonates with injuries, but not those with subtle lesions like punctate lesions, whilst minimising false identification of neonates with normal appearing brains.To ascertain if performance could be improved, I explored multiple classification methods. Specifically, the use of other more complex classifiers (random forest, support vector machines, GP classification) and the use of a regional abnormal voxel count, that allowed localisation of lesioned tissue rather than the more global detection ability of the Z-score histograms. Using these innovations, I investigated their application towards a specific pathology; hypoxic ischemic encephalopathy (HIE). This is a good test for the system, as HIE has high incidence rates, multiple associated lesion types and a time dependant appearance. Further, I wanted to know if, given a positive HIE diagnosis, the Z-score abnormality maps could be used to predict long-term outcomes (normal vs poor). Several models demonstrated an excellent ability to separate HIE and healthy control neonates achieving >90% accuracy, a statistically significant result even after false discovery rate (FDR) correction (p-value < 0.05). While the outcome prediction models achieved reasonable accuracy, >70% in multiple models, none of these were statistically significant after FDR correction.Overall, this work demonstrates how normative modelling can be used to create individual voxel-wise / image-wise estimation of tissue abnormality for neonatal MRI across a range of gestational ages. It further demonstrates that these abnormality maps can be utilised for additional tasks, in this instance, three increasingly challenging neurological classification problems. These include the separation of neonates with and without MRI positive lesions, identification of neonates with a specific pathological condition (HIE) and prediction of long-term functional outcome (normal vs poor). Within a radiological setting, these classifications task can be considered analogous to three radiological challenges, image triage, diagnostic detection and estimation of developmental prognosis, important for the clinical team but also infants and their families

Influence of Early Bilingual Exposure in the Developing Human Brain.

190 p.La adquisición del lenguaje es un proceso que ese encuentra determinado tanto por mecanismos de desarrollo cognitivo, como por la experiencia lingüística durante los primeros años de vida. Aunque se trata de un proceso relativamente complejo, los bebés muestran una gran habilidad para el aprendizaje del lenguaje. Un entorno de aprendizaje lingüístico bilingüe podría considerarse aun más complejo, ya que los bebés están expuestos a las características lingüísticas de dos lenguas simultáneamente. En primer lugar, los bebés que crecen en un entorno bilingüe tienen que ser capaces de darse cuenta de que están expuestos a dos lenguas diferentes, y posteriormente deben separar y aprender las características especificas de cada una de ellas; por ejemplo, los distintos fonemas, palabras o estructuras gramaticales. Aunque la exposición lingüística total de los bebés bilingües debería ser comparable a la de los bebés monolingües, es probable que la exposición a cada una de las lenguas de su entorno sea menor, ya que tienen que dividir su tiempo de exposición entre ambas. Si bien los bebés bilingües parecen no tener problemas para enfrentarse a un contexto de aprendizaje potencialmente más complejo, ya que alcanzan las distintas etapas de adquisición del lenguaje a un ritmo similar a los bebés monolingües, sí se han observado adaptaciones a nivel conductual y a nivel de funcionamiento cerebral que podrían producirse como consecuencia de este contexto.Basque Center on cognition, brain and languag