Processing of nonverbal vocalisations in dementia

Nonverbal emotional vocalisations are fundamental communicative signals used to convey a diverse repertoire of social and emotional information. They transcend the boundaries of language and cultural specificity that hamper many neuropsychological tests, making them ideal candidates for understanding impaired socio-emotional signal processing in dementia. Symptoms related to changes in social behaviour and emotional responsiveness are poorly understood yet have significant impact on patients with dementia and those who care for them. In this thesis, I investigated processing of nonverbal emotional vocalisations in patients with Alzheimer’s disease and frontotemporal dementia (FTD), a disease spectrum encompassing three canonical syndromes characterised by marked socio-emotional and communication difficulties - behavioural variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA) and nonfluent/agrammatic variant primary progressive aphasia (nfvPPA). I demonstrated distinct profiles of impairment in identifying three salient vocalisations (laughter, crying and screaming) and the emotions they convey. All three FTD syndromes showed impairments, with the most marked deficits of emotion categorisation seen in the bvFTD group. Voxel-based morphometry was used to define critical brain substrates for processing vocalisations, identifying correlates of vocal sound processing with auditory perceptual regions (superior temporal sulcus and posterior insula) and emotion identification with limbic and medial frontal regions. The second half of this thesis focused on the more fine-grained distinction of laughter subtypes. I studied cognitive (labelling), affective (valence) and autonomic (pupillometric) processing of laughter subtypes representing dimensions of valence (mirthful versus hostile) and arousal (spontaneous versus posed). Again, FTD groups showed greatest impairment with profiles suggestive of primary perceptual deficits in nfvPPA, cognitive overgeneralisation in svPPA and disordered reward and hedonic valuation in bvFTD. Neuroanatomical correlates of explicit laughter identification included inferior frontal and cingulo-insular cortices whilst implicit processing (indexed as autonomic arousal) was particularly impaired in those conditions associated with insular compromise (nfvPPA and bvFTD). These findings demonstrate the potential of nonverbal emotional vocalisations as a probe of neural mechanisms underpinning socio-emotional dysfunction in neurodegenerative diseases

2014 IMSAloquium, Student Investigation Showcase

The ability to work with professionals is a life-changing experience for our students. Working with world-class scholars and advisors, students have contributed to advances in a variety of fields from science, technology, engineering and mathematics, to the performing arts and history.https://digitalcommons.imsa.edu/archives_sir/1006/thumbnail.jp

05. 2014 IMSAloquium Student Investigation Showcase

https://digitalcommons.imsa.edu/class_of_2015/1003/thumbnail.jp

Clinical and genetic heterogeneity in young onset sporadic Alzheimer’s disease

Alzheimer’s disease, the commonest neurodegenerative condition, is characterised by accumulation of amyloid plaques and neurofibrillary tangles, neuronal loss, brain atrophy and cognitive impairment. Sporadic young onset Alzheimer’s disease shows marked clinical heterogeneity, with non-memory presentations including the syndromes of posterior cortical atrophy, logopenic aphasia and frontal Alzheimer’s disease, seen in around a third of individuals. This variability presents challenges for diagnosis and may confound clinical trial outcomes, but provides an opportunity to explore factors influencing differential selective vulnerability within neural networks which in turn may provide important clues to Alzheimer’s disease pathogenesis. This thesis describes the recruitment of a cohort of a deeply phenotyped patients with sporadic young onset Alzheimer’s disease (n=45) and healthy controls (n=24), and a series of genetic, clinical, neuropsychological, and structural, diffusion and functional magnetic resonance imaging experiments to explore disease heterogeneity and its associations. There are a number of key findings. APOE ε4 genotype contributes to, but does not fully explain clinical heterogeneity, with the youngest ages of onset and most atypical presentations seen in ε4-ve individuals. Heterozygosity of the rare TREM2 genetic variant for late-onset Alzheimer’s disease, p.R47H, is shown to confer risk for young onset Alzheimer’s disease, driving younger age of onset rather than clinical phenotype. Regional brain atrophy profiles in APOE ε4 genotypes are shown to broadly align with the associated neuropsychological deficits. Microstructural damage studied using diffusion tensor imaging, and – applied for the first time to Alzheimer’s disease – Neurite Orientation Dispersion and Density Imaging – provides a fine-grained profile of white matter network breakdown, revealing regional differences based on APOE ε4 genotype, and correlations with focal neuropsychological deficits. Finally, activation fMRI using a music paradigm to probe relationships between cognitive performance and brain function is shown to delineate different patterns of brain activation during memory tasks in different Alzheimer’s disease phenotypes

Hierarchical network structure as the source of power-law frequency spectra (state-trait continua) in living and non-living systems: how physical traits and personalities emerge from first principles in biophysics

What causes organisms to have different body plans and personalities? We address this question by looking at universal principles that govern the morphology and behavior of living systems. Living systems display a small-world network structure in which many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a power-law cluster size distribution. Their dynamics show similar qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' that are nested within lower frequencies or 'traits'. Here, we argue that the nested modular (power-law) dynamics of living systems results from their nested modular (power-law) network structure: organisms 'vertically encode' the deep spatiotemporal structure of their environments, so that high frequencies (states) are produced by many small clusters at the base of a nested-modular hierarchy and lower frequencies (traits) are produced by fewer larger clusters at its top. These include physical as well as behavioral traits. Nested-modular structure causes higher frequencies to be embedded in lower frequencies, producing power-law dynamics. Such dynamics satisfy the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.g. earthquake dynamics, stock market fluctuations). Thus, we provide a single explanation for power-law frequency spectra in both living and non-living systems. If hierarchical structure indeed produces hierarchical dynamics, the development (e.g. during maturation) and collapse (e.g. during disease) of hierarchical structure should leave specific traces in power-law frequency spectra that may serve as early warning signs to system failure. The applications of this idea range from embryology and personality psychology to sociology, evolutionary biology and clinical medicine

Minimally invasive diagnosis of Alzheimer’s disease by detecting microRNA using a quartz crystal resonator

In 2014, there were 850,000 people living with dementia in the UK, creating an economic burden of £26.3 billion a year. 62% of dementia patients are diagnosed with Alzheimer’s Disease (AD). AD is a slow progressing disease with three phases: a long prodromal stage followed by mild cognitive impairment and then late AD. The prodromal phase of AD is on average 30 years. So, when the first symptoms become apparent, the pathology in the brain is extensive. If Alzheimer’s could be diagnosed early, when the pathological load is lower, this may improve the chances of finding a disease modifying therapy.For diagnosis during the prodromal stage to be viable, patients would need to be diagnosed through mass screening, with the most appropriate diagnosis method being biomarker detection in peripheral blood. There are an increasing number of articles in literature researching the use of non coding RNA sequences called microRNA (miRNA) as biomarkers for AD. However, their viability in diagnosing prodromal AD is unknown and the current miRNA detection method, the polymerase chain reaction (PCR), is time consuming, expensive and requires experienced personnel, making it unsuitable for use in mass screening. Therefore, the aim of the thesis was to investigate miRNA as a prodromal biomarker with a new detection method to determine the usability of miRNA as a prodromal AD biomarker.AD is characterised by the build up of amyloid β and hyper phosphorylated tau in the brain. The movement of tau through the brain is divided into 6 Braak stages. Chapter 4 aimed to determine the point at which miRNAs deregulate in AD. To achieve this, post mortem brain tissue was obtained through all 6 Braak stages. The RNA from the post-mortem brain samples were isolated and the change in miRNA levels were determined using PCR and the ΔΔct method. After comparing miRNA to a spike in control the 4 miRNAs tested showed no significant change in miRNA levels through the progression of AD.One of the first signs of AD is the activation of astrocytes in the brain. The aim of Chapter 5 was to determine the effect of the deregulated miRNAs on astrocytes. An astrocytoma cell line was activated using lipopolysaccharides and TNF α then transfected so specific miRNA were over expressed. The concentration of metabolites, cytokines and growth factors were measured in the cell supernatant. Results showed mir 210 regulated G CSF and mir 223 regulated glutamate consumption.Finally, the feasibility of rapid detection of miRNA was investigated using a quartz crystal microblance (QCM). The QCM, assembled within a custom built microfluidic flow cell, was driven at its fundamental resonance frequency. Shifts in the third Fourier harmonic current and the resonance frequency were measured for a range of concentrations of a single stranded DNA (ssDNA). The results show feasibility for rapid quantitative detection of ssDNA to 60 ng/mL, in an easy to use label free assay. Amplification of the signal was seen with the addition of electrochemical potential and the use of particles.Results looking at the deregulation of miRNA in the temporal cortex showed no significant change, therefore further work is needed looking at alternative miRNA sequences. The results with ssDNA suggest that quartz crystal resonator has the potential for rapid, specific and quantitative miRNA detection. However, amplification strategies would help to achieve the clinically relevant limit of detection in peripheral blood.</div

Investigating the effects of mutations causative for early-onset familial Alzheimer’s disease using zebrafish as a model organism

Development of an effective therapeutic for Alzheimer’s disease (AD) is currently a global health priority. To prevent, or at least delay, the onset of AD, we must understand the initial cellular stresses/changes that drive the disease. These initiating changes are likely subtle and occur decades before symptom onset. We cannot easily investigate these changes in humans, as pre-symptomatic brain material from individuals genetically pre-disposed to AD is inaccessible for detailed molecular analyses. For this, we must utilise animal models. The most frequently used animal models of AD are mice expressing one or more transgenes containing the sequences of human genes bearing mutations which cause AD. These transgenic models have been useful in elucidating some aspects of the pathogenic mechanisms of AD. However, they have not led to development of successful therapeutics. Mutations in a small number of genes cause early-onset familial forms of AD (EOfAD). These mutations can be introduced into the orthologous, endogenous genes of an animal (i.e. knock-in models). However, relatively few papers describe research with knock-in models. Transcriptome analysis is currently the most detailed form of molecular phenotyping and can give a largely unbiased view of the molecular state of the brains of young knock-in models of EOfAD. Surprisingly, this has not previously been performed using knock-in models of EOfAD-like mutations. To address this gap in our knowledge, the work presented in this thesis (along with previous work from the Alzheimer’s Disease Genetics Laboratory (ADGL)), describes the generation, and/or characterisation of a collection of zebrafish knock-in models of EOfAD-like mutations. The power of zebrafish as a model organism lies in this species’ ability to generate large families of synchronous siblings which can be raised together in the same tank. This has allowed the assessment of the effects of heterozygosity for EOfAD-like mutations (closely mimicking the genetic state of human EOfAD) or the effects of non-EOfAD-like mutations (such as frameshift mutations in presenilin genes) on the brain transcriptome with minimal external sources of “noise.” These analyses have revealed that the only cellular process predicted to be affected by EOfAD-like mutations in the heterozygous state, and not by non-AD-related mutations, is oxidative phosphorylation. Comparison of these transcriptomes with recent, publicly available brain transcriptomes from two knock-in mouse models of late onset AD risk alleles revealed similar affected processes, thereby supporting the findings from the zebrafish models. Preliminary non-transcriptomic characterisations of previously generated/novel zebrafish models were also performed. The effects of heterozygosity for EOfAD-like mutations on brain vasculature were assessed, as well as effects on spatial working memory. Only limited differences were observed in these studies. However, future work with greater statistical power and/or alternate study designs is recommended. Overall, the research described in this thesis demonstrates the value of unbiased, transcriptome analyses of young, knock-in animals models for understanding the early stages of AD pathogenesis.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 202

Proceedings of the 2016 Berry Summer Thesis Institute

Thanks to a gift from the Berry Family Foundation and the Berry family, the University Honors Program launched the Berry Summer Thesis Institute in 2012. The institute introduces students in the University Honors Program to intensive research, scholarship opportunities and professional development. Each student pursues a 12-week summer thesis research project under the guidance of a UD faculty mentor. This contains the product of the students\u27 research

The cognition of non-verbal sound in dementia

A growing body of functional imaging studies provides considerable insight into cortical networks for non-verbal auditory processing. However, determination of the essential cognitive and anatomical components of these networks depends upon the study of damaged brains, and yet, auditory neuropsychology is little studied and poorly understood. Whilst naturally occurring lesions that selectively disrupt auditory processes are rare, increasing evidence suggests that degenerative diseases target functional networks implicated in non-verbal auditory processing. Furthermore, a small but significant auditory neuropsychological literature shows that dementia can lead to impairments of non-verbal sound processing. This thesis comprises a series of studies designed to reveal deficits of non-verbal auditory processing in four distinct dementia syndromes: three variants of primary progressive aphasia (semantic dementia, SD; progressive non-fluent aphasia, PNFA; logopenic aphasia, LPA), and typical Alzheimer’s disease (AD). The first two studies (Chapters 2 and 3) involve the development of two novel non-verbal auditory neuropsychological batteries, including tests to examine perceptual property, apperceptive, and semantic stages of processing; the subsequent use of these batteries reveals syndrome-specific profiles of non-verbal auditory impairment. Next, a detailed psychoacoustic assessment of two single cases (Chapter 4) provides evidence for specific disorders of auditory property and object processing. A further study (Chapter 5) comprises the examination of non-verbal auditory object processing in SD using functional magnetic resonance imaging (fMRI); results suggest that auditory object recognition depends upon a distributed temporo-parietal network involving closely associated mechanisms of perceptual and semantic processing. Finally, novel neuropsychological assessments are used to reveal the selective impairment of auditory scene analysis in AD (Chapter 6). Together, these neuropsychological findings provide novel insights into the organisation of cortical networks for non-verbal auditory cognition