The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy.

ObjectiveThe distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.MethodsT1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.ResultsThe SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.ConclusionThe SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance

Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations

Idiopathic Parkinson's Disease (iPD) is a common motor neurodegenerative disorder. It affects more frequently the elderly population, causing a significant emotional burden both for the patient and caregivers, due to the disease-related onset of motor and cognitive disabilities. iPD's clinical hallmark is the onset of cardinal motor symptoms such as bradykinesia, rest tremor, rigidity, and postural instability. However, these symptoms appear when the neurodegenerative process is already in an advanced stage. Furthermore, the greatest challenge is to distinguish iPD from other similar neurodegenerative disorders, "atypical parkinsonisms", such as Multisystem Atrophy, Progressive Supranuclear Palsy and Cortical Basal Degeneration, since they share many phenotypic manifestations, especially in the early stages. The diagnosis of these neurodegenerative motor disorders is essentially clinical. Consequently, the diagnostic accuracy mainly depends on the professional knowledge and experience of the physician. Recent advances in artificial intelligence have made it possible to analyze the large amount of clinical and instrumental information in the medical field. The application machine learning algorithms to the analysis of neuroimaging data appear to be a promising tool for identifying microstructural alterations related to the pathological process in order to explain the onset of symptoms and the spread of the neurodegenerative process. In this context, the search for quantitative biomarkers capable of identifying parkinsonian patients in the prodromal phases of the disease, of correctly distinguishing them from atypical parkinsonisms and of predicting clinical evolution and response to therapy represent the main goal of most current clinical research studies. Our aim was to review the recent literature and describe the current knowledge about the contribution given by machine learning applications to research and clinical management of parkinsonian syndromes

Selective cellular vulnerability and pathology progression patterns in two mouse models of Parkinson’s disease

Parkinson's disease is a highly debilitating disorder classically characterized by the degeneration of dopaminergic midbrain neurons of the substantia nigra. The resulting nigrostriatal dopamine deficiency is thought to be responsible for the onset of the cardinal Parkinson's motor symptomtomatology; bradykinesia, rigidity, and resting tremor. However, recent studies show that Parkinson's disease is a multisystem disorder. Thus, it comes not only to degeneration in the nigrostriatal system, but also to pronounced cell loss in many other brain regions. Histopathologically, Parkinson's disease is characterized by the presence of so-called Lewy bodies or neurites. These are intracytoplasmic proteinaceous inclusions consisting mainly of aggregated α-synuclein. Two neuronal structures that both have pronounced Lewy pathology in Parkinson's disease and prominent neurodegeneration are the noradrenergic locus coeruleus and the neurochemically heterogeneous pedunculopontine nucleus. Remarkably, in the pedunculopontine nucleus Lewy pathology and neurodegeneration are predominantly restricted to the cholinergic cell population, while the GABAergic and glutamatergic cell groups exhibit only minor Lewy pathology and are largely spared of neurodegeneration. The present dissertation pursued two main goals. On the one hand, we investigated whether the selective vulnerability pattern of the cholinergic subpopulation of the pedunculopontine nucleus could be reproduced in a mouse model based on the intracerebral injection of preformed α-synuclein fibrils. Second, the brain-spreading pattern of two focal-induced α-synucleinopathy mouse models were compared with respect to the methodology used to initiate the aggregation process (vector-mediated overexpression vs. α-synuclein fibril model). In the first part of the study, we used a targeted intracerebral injection of preformed α-synuclein fibrils to induce a focal α-synucleinopathy in the pedunculopontine nucleus. Our data show that the injection of α-synuclein fibrils resulted in the recruitment and misfolding of endogenous α-synuclein leading to formation of Lewy body-like aggregates in neuronal perikarya and axons. Interestingly, the observed inclusion bodies were immunoreactive for S129-phosphorylated α-synuclein, p62 positive and resistant to proteinase K digestion. We thereby showed that the experimentally induced α-synuclein pathology possessed several key features of human Lewy pathology. Remarkably, the major burden of Lewy-like pathology and quantified cell loss was limited to the cholinergic subpopulation of the pedunculopontine nucleus, while the non-cholinergic neurons were largely spared of Lewy pathology and degeneration at any investigated time-point. Interestingly, in both fibril and monomer-α-synuclein (control) injected animals, induction of reactive microgliosis occurred, although no α-synuclein pathology was observed in the control group. Our analysis also showed that the formation of α-synuclein pathology was not limited to the immediate vicinity of the site of injection, but propageted over considerable distances to other interconnected brain regions. Since α-synuclein positive aggregates were found in neuronal cell bodies of distant brain regions, which lay all within the neuronal network of the pedunculopontine nucleus, it can be concluded that the α-synucleinopathy spread only within the neural network of the pedunculopontine nucleus. In the second part of the thesis, focal α-synucleinopathy was induced in the locus coeruleus by intracerebral injection of adeno-associated viral vectors containing the gene for human mutant A53T-α-synuclein or luciferase (control protein). The obtained data showed that local overexpression of human α-synuclein led to widespread propagation of the protein consistent with anterograde axonal transport. Analysis of the α-synuclein propagation pattern demonstrated that the brain-wide α-synucleinopathy was confined to the output regions of the noradrenergic locus coeruleus. Furthermore, there was no evidence of cell-to-cell transmission of human α-synuclein. Based on these findings we concluded that the induced Lewy-like pathology did not leave the noradrenergic locus coeruleus system in the studied time frame of 9 weeks. In addition, unbiased stereological quantification of the dopaminergic substantia nigra revealed no significant cell loss at the relatively short time-frame of 9 weeks. In conclusion, the studies presented in this dissertation show that cholinergic pedunculopontine neurons are significantly more vulnerable to α-synuclein fibril-induced α-synucleinopathy than non-cholinergic neurons. In addition, we were able to show that the brain-wide progression pattern of Lewy-like pathology is significantly different between the two studied α-synucleinopathy models. While in the fibril model the α-synucleinopathy pattern was consistent with cell-to-cell transmission of pathological α-synuclein species, we only observed axonal transport of α-synuclein but not cell-to-cell transmission in the overexpression-based model. The studies carried out within this dissertation therefore provide a valuable starting point for the further investigation of cellular vulnerability factors and mechanisms of disease progression

Multiple system atrophy - a clinicopathological update

Multiple system atrophy (MSA) is a fatal, adult-onset neurodegenerative disorder of uncertain etiology, clinically characterized by various combinations of Levo-dopa-unresponsive parkinsonism, and cerebellar, motor, and autonomic dysfunctions. MSA is an α-synucleinopathy with specific glioneuronal degeneration involving striatonigral, olivopontocerebellar, autonomic and peripheral nervous systems. The pathologic hallmark of this unique proteinopathy is the deposition of aberrant α-synuclein (αSyn) in both glia (mainly oligodendroglia) and neurons forming pathological inclusions that cause cell dysfunction and demise. The major variants are striatonigral degeneration (MSA with predominant parkinsonism / MSA-P) and olivopontocerebellar atrophy (MSA with prominent cerebellar ataxia / MSA-C). However, the clinical and pathological features of MSA are broader than previously considered. Studies in various mouse models and human patients have helped to better understand the molecular mechanisms that underlie the progression of the disease. The pathogenesis of MSA is characterized by propagation of disease-specific strains of αSyn from neurons to oligodendroglia and cell-to-cell spreading in a "prion-like" manner, oxidative stress, proteasomal and mitochondrial dysfunctions, myelin dysregulation, neuroinflammation, decreased neurotrophic factors, and energy failure. The combination of these mechanisms results in neurodegeneration with widespread demyelination and a multisystem involvement that is specific for MSA. Clinical diagnostic accuracy and differential diagnosis of MSA have improved by using combined biomarkers. Cognitive impairment, which has been a non-supporting feature of MSA, is not uncommon, while severe dementia is rare. Despite several pharmacological approaches in MSA models, no effective disease-modifying therapeutic strategies are currently available, although many clinical trials targeting disease modification, including immunotherapy and combined approaches, are under way. Multidisciplinary research to elucidate the genetic and molecular background of the noxious processes as the basis for development of an effective treatment of the hitherto incurable disorder are urgently needed

The thalamus as a putative biomarker in neurodegenerative disorders

Objective: This review provides a brief account of the clinically relevant functional neuroanatomy of the thalamus, before considering the utility of various modalities utilised to image the thalamus and technical challenges therein, and going on to provide an overview of studies utilising structural imaging techniques to map thalamic morphology in the spectrum of neurodegenerative disorders. Methods: A systematic search was conducted for peer-reviewed studies involving structural neuroimaging modalities investigating the morphology (shape and/ or size) of the thalamus in the spectrum of neurodegenerative disorders. Results: Whilst the precise role of the thalamus in the healthy brain remains unclear, there is a large body of knowledge accumulating which defines more precisely its functional connectivity within the connectome, and a burgeoning literature implicating its involvement in neurodegenerative disorders. It is proposed that correlation of clinical features with thalamic morphology (as a component of a quantifiable subcortical connectome) will provide a better understanding of neuropsychiatric dysfunction in various neurodegenerative disorders, potentially yielding clinically useful endophenotypes and disease biomarkers. Conclusions: Thalamic biomarkers in the neurodegenerative disorders have great potential to provide clinically meaningful knowledge regarding not only disease onset and progression, but may yield targets of and perhaps a way of gauging response to future disease-modifying modalities

GDNF and Neurturin isoforms in an experimental model of Parkinson's disease

Parkinson’s disease (PD) is a neurodegenerative disease characterized by intracellular proteinaceous inclusions called Lewy bodies and progressive loss of dopaminergic neurons in the substantia nigra (SN). The first symptoms of PD are non-motor, such as hyposmia and gastrointestinal disturbances, followed by motor symptoms, such as tremor and rigidity. Currently available therapies, medication, surgical procedures and supportive therapies, are symptomatic and do not affect the underlying cause of the disease — the neuronal degeneration. Thus, a new therapy which would restore the dopaminergic phenotype of dying neurons and thus slow down or even halt the progress of the disease is needed. Neurotrophic factors are secretory proteins regulating survival and functioning of the neurons as well as the formation of new neuronal contacts. Neurotrophic factors have shown great potential in animal models of PD, but in clinical trials, the results have been contradictory. One possible explanation for this is poor diffusion and bioavailability of the therapeutic proteins in the target tissue. The aim of this study was to explore the neuroprotective effects of the isoforms of two of the most potent dopamine neurotrophic factors, GDNF (glial cell line-derived neurotrophic factor) and its homolog neurturin (NRTN) in an experimental model of PD, and to characterize a new stable low-dose 6-hydroxydopamine (6-OHDA) rat PD model. In the PD model the degeneration of the nigrostriatal pathway was induced by administrating toxic dopamine analog 6-OHDA into the striatum, where the nerve terminals of the dopaminergic neurons are located. We compared several different administration paradigms to find the optimal parameters to induce a stable lesion model with high success rate. The cell loss induced with low doses (6-9 µg) of 6-OHDA was at similar level as the cell loss induced with higher (20 µg) doses of 6-OHDA. The advantage of using low 6-OHDA doses is the avoidance of non-specific damage, which occurs with higher 6-OHDA doses. Moreover, the low-dose induced lesions have high success rate, reducing the number of animals needed in the experiments and increasing the reliability of the obtained results. The spreading of NRTN in the brain tissue was improved by modifying the extracellular matrix binding sequence of the protein. New NRTN variants were biologically active and were able to initiate signaling via tyrosine kinase Ret (rearranged during transfection). In the neuroprotection assay in rat 6-OHDA model of PD NRTN variant N4 protected the dopaminergic neurons in the SN and fibers in the striatum as well as improved the motor behavior of the animals. In neurorestoration assay, N4 showed a trend in improving the behavioral deficits of the animals. GDNF, on the other hand, was administered to the brain with viral vectors, enabling long-term protein expression in the target tissue. GDNF has been widely studied, but the research has focused on the full-length constitutively secreted α-isoform, whereas the biology of the shorter and activity-dependently secreted β-GDNF has not been studied in vivo before. In the non-lesioned striatum, both isoforms increased striatal dopamine transporter-immunoreactivity. Both isoforms also protected the dopaminergic neurons in SN from 6-OHDA-induced degeneration. The results show that these new and less studied neurotrophic factor isoforms are able to slow down the degeneration of the midbrain dopaminergic neurons. In other words, both NRTN variant N4 and β-GDNF are potential disease-modifying factors for PD.Parkinsonin tauti on etenevä hermorappeumasairaus, jossa substantia nigran dopamiinia tuottavat hermosolut tuhoutuvat. Parkinsonin taudin ensimmäiset oireet ovat nonmotorisia, kuten hajuaistin tai suoliston toimintahäiriöitä, joita seuraavat motoriset oireet, kuten lepovapina ja raajojen jäykkyys. Tällä hetkellä tarjolla olevat hoitomuodot, lääkehoito, kirurginen toimenpide ja fysioterapia, ainoastaan lievittävät Parkinsonin taudin oireita, mutta ne eivät pysäytä tai hidasta oireiden syynä olevaa hermosolujen tuhoutumista. Uusi terapia, joka palauttaisi rappeutuvien hermosolujen dopaminergisen fenotyypin ja siten hidastaisi tai jopa pysäyttäisi taudin etenemisen, mullistaisi Parkinsonin taudin hoidon. Hermokasvutekijät ovat elimistön omia proteiineja, jotka säätelevät hermosolujen eloonjäämistä, uusien kontaktien muodostamista ja hermosolujen toimintaa. Hermokasvutekijät ovat osoittautuneet potentiaalisiksi uusiksi lääkemolekyyleiksi Parkinsonin taudin eläinmalleissa, mutta positiiviset tulokset eivät ole toistuneet kliinisissä kokeissa. Yhtenä syynä tähän on pidetty proteiinien heikkoa leviämistä kohdekudoksessa. Tämän tutkimuksen tarkoituksena oli tutkia kahden hermokasvutekijän, gliasolulinjaperäisen hermokasvutekijän GDNF:n (engl. glial cell line-derived neurotrophic factor) ja sen sukulaisproteiinin neurturiinin (NRTN) eri muotojen kykyä suojata keskiaivojen dopamiinia tuottavia hermosoluja Parkinsonin taudin kokeellisessa eläinmallissa sekä karakterisoida matalalla 6-hydroksidopamiini(6-OHDA)annoksella indusoitu Parkinsonin taudin eläinmalli. Eläinmallissa nigrostriataalisen hermoradan osittainen tuhoutuminen aiheutettiin annostelemalla hermovälittäjäaine dopamiinin myrkyllistä analogia, 6-OHDA:a, striatumiin, jossa dopamiinia tuottavien hermosolujen hermopäätteet sijaitsevat. Vertailemalla erilaisia injektioasetuksia löysimme tavan, jolla annosteltuna hermosolujen tuho oli pysyvä ja toistettava. Matalilla 6-OHDA annoksilla (6-9 µg) aiheutettu solutuho osoittautui yhtä suureksi kuin suurilla annoksilla (20 µg) aiheutettu solutuho. Pienten 6-OHDA-annosten aiheuttaman solutuhon on kuitenkin osoitettu olevan spesifisempi kuin suurten 6-OHDA-annosten aiheuttama solutuho. Toistettava eläinmalli vähentää kokeissa käytettävien eläinten lukumäärää ja lisää tulosten luotettavuutta. NRTN:n leviämistä kudoksessa parannettiin muokkaamalla jaksoa, jolla neurturiini sitoutuu soluväliaineeseen. Uudet neurturiinivariantit ovat biologisesti aktiivisia ja voivat aloittaa signaalivälityksen. 6-OHDA-eläinmallissa aivoihin annosteltu NRTN-variantti N4 suojasi substantia nigran dopamiinia tuottavia hermosoluja ja niiden hermopäätteitä striatumissa sekä kohensi eläinten motorista toimintakykyä. Myös myöhemmin annosteltuna N4 osoitti potentiaalia palauttaa eläinten motorinen toimintakyky. GDNF sen sijaan annosteltiin aivoihin virusvektorin avulla, mahdollistaen terapeuttisen proteiinin pitkäkestoisen tuotannon kohdekudoksessa. GDNF on laajalti tutkittu proteiini, mutta tutkimus on keskittynyt vain täyspitkään ja jatkuvasti soluista erittyvään α-muotoon ja lyhyempi, aktiivisuusriippuvaisesti soluista erittyvä β-muoto on vaikutuksiltaan tuntemattomampi. Ehjään striatumiin annosteltuna kumpikin muoto lisäsi dopamiinikuljettajaimmunoreaktiivisuutta striatumissa. Lisäksi kumpikin muoto suojasi keskiaivojen dopamiinia tuottavia hermosoluja 6-OHDA:n aiheuttamalta tuhoutumiselta. Tulokset osoittavat uusien ja vähemmän tutkittujen hermokasvutekijämuotojen hidastavan keskiaivojen dopamiinia tuottavien hermosolujen tuhoutumista. Toisin sanoen, sekä neurturiinivarianti N4 että β-GDNF ovat potentiaalisia terapeuttisia proteiineja Parkinsonin taudin hoitoon

Validation of Diffusion Kurtosis Imaging as an Early-Stage Biomarker of Parkinson's Disease in Animal Models

Diffusion kurtosis imaging (DKI), which is a mathematical extension of diffusion tensor imaging (DTI), assesses non-Gaussian water diffusion in the brain. DKI proved to be effective in supporting the diagnosis of different neurodegenerative disorders. Its sensitively detects microstructural changes in the brain induced by either protein accumulation, glial cell activation or neurodegeneration as observed in mouse models of Parkinson's disease. We applied two experimental models of Parkinson's disease to validate the diagnostic utility of DKI in early and late stage of disease pathology. We present two DKI analysis methods: (1) tract based spatial statistics (TBSS), which is a hypothesis independent data driven approach intended to evaluate white matter changes; and (2) region of interest (ROI) based analysis based on hypothesis of ROIs relevant for Parkinson's disease, which is specifically used for gray matter changes. The main aim of this chapter is to provide detailed information of how to perform the DKI imaging acquisition and analysis in the mouse brain, which can be, to some extent translated to humans

Changes in MEG resting-state networks are related to cognitive decline in type 1 diabetes mellitus patients

OBJECTIVE: Integrity of resting-state functional brain networks (RSNs) is important for proper cognitive functioning. In type 1 diabetes mellitus (T1DM) cognitive decrements are commonly observed, possibly due to alterations in RSNs, which may vary according to microvascular complication status. Thus, we tested the hypothesis that functional connectivity in RSNs differs according to clinical status and correlates with cognition in T1DM patients, using an unbiased approach with high spatio-temporal resolution functional network.; METHODS: Resting-state magnetoencephalographic (MEG) data for T1DM patients with (n=42) and without (n=41) microvascular complications and 33 healthy participants were recorded. MEG time-series at source level were reconstructed using a recently developed atlas-based beamformer. Functional connectivity within classical frequency bands, estimated by the phase lag index (PLI), was calculated within eight commonly found RSNs. Neuropsychological tests were used to assess cognitive performance, and the relation with RSNs was evaluated.; RESULTS: Significant differences in terms of RSN functional connectivity between the three groups were observed in the lower alpha band, in the default-mode (DMN), executive control (ECN) and sensorimotor (SMN) RSNs. T1DM patients with microvascular complications showed the weakest functional connectivity in these networks relative to the other groups. For DMN, functional connectivity was higher in patients without microangiopathy relative to controls (all p<0.05). General cognitive performance for both patient groups was worse compared with healthy controls. Lower DMN alpha band functional connectivity correlated with poorer general cognitive ability in patients with microvascular complications.; DISCUSSION: Altered RSN functional connectivity was found in T1DM patients depending on clinical status. Lower DMN functional connectivity was related to poorer cognitive functioning. These results indicate that functional connectivity may play a key role in T1DM-related cognitive dysfunction

Degradation of cognitive timing mechanisms in behavioural variant frontotemporal dementia.

The current study examined motor timing in frontotemporal dementia (FTD), which manifests as progressive deterioration in social, behavioural and cognitive functions. Twenty-patients fulfilling consensus clinical criteria for behavioural variant FTD (bvFTD), 11 patients fulfilling consensus clinical criteria for semantic-variant primary progressive aphasia (svPPA), four patients fulfilling criteria for nonfluent/agrammatic primary progressive aphasia (naPPA), eight patients fulfilling criteria for Alzheimer׳s disease (AD), and 31 controls were assessed on both an externally- and self-paced finger-tapping task requiring maintenance of a regular, 1500 ms beat over 50 taps. Grey and white matter correlates of deficits in motor timing were examined using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). bvFTD patients exhibited significant deficits in aspects of both externally- and self-paced tapping. Increased mean inter-response interval (faster than target tap time) in the self-paced task was associated with reduced grey matter volume in the cerebellum bilaterally, right middle temporal gyrus, and with increased axial diffusivity in the right superior longitudinal fasciculus, regions and tracts which have been suggested to be involved in a subcortical-cortical network of structures underlying timing abilities. This suggests that such structures can be affected in bvFTD, and that impaired motor timing may underlie some characteristics of the bvFTD phenotype

Synaptic loss in the primary tauopathies of Progressive Supranuclear Palsy and Corticobasal Degeneration

In this thesis I address the debilitating symptom of cognitive dysfunction in the primary tauopathies of Progressive Supranuclear Palsy (PSP) and Corticobasal Degeneration (CBD). Both PSP and CBD are associated with an accumulation of 4-repeat tau in cortical and subcortical areas. As well as movement disorders, they impair cognitive function, even where there is minimal atrophy. Neurophysiological studies have also identified electrophysiological changes associated with cognitive dysfunction, in areas without atrophy. I propose that synaptic loss prior to cell loss contributes to these effects of disease. Chapter two summarises my cohort and principal methods. I quantify synaptic density in vivo with dynamic [11C]UCB-J PET, and molecular pathology with [18F]AV1451 PET. Brain structural changes are quantified by MRI. Disease severity and cognition are assessed with the PSP rating scale, and neuropsychological tests. Patients with CBD are negative on amyloid-imaging ([11C]PiB PET) to exclude those with Alzheimer’s pathology. In chapter three, [11C]UCB-J PET reveals widespread loss of synapses in PSP and CBD including areas with minimal atrophy. The loss of synapses correlated with cognition and disease severity. In chapter four, I test whether presynaptic changes (from [11C]UCB-J PET) are correlated with postsynaptic abnormalities (i.e. changes to postsynaptic dendritic microstructural integrity quantified by MRI using the Neurite Orientation and Dispersion Index, NODDI). In accordance with in vitro and animal models, I confirm that loss of dendritic complexity is tightly coupled with presynaptic density, over and above the effects of atrophy. In chapter five, I test the relationship between the molecular pathology in primary tauopathies (tau burden) and synaptic loss, using [18F]AV-1451 and [11C]UCB-J PET. The use of the “tau” ligand [18F]AV-1451 has become controversial in PSP. With due consideration to the caveats, I report that brain regions with a higher synaptic density have higher [18F]AV-1451 binding, consistent with the hypothesis of connectivity-based progression of tauopathy. I further show that accrual of pathology in any given area is associated with loss of synapses, consistent with synaptic injury from tauopathy. I conclude my thesis in chapter 6, by discussing and highlighting the importance of synaptic density in primary tauopathies. The findings are relevant to other neurodegenerative disorders, and support early interventional studies targeting synaptic maintenance and restoration.Association of British Neurologists - Patrick Berthoud Charitable Trus