The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia.

BACKGROUND: Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants. METHODS: Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes). RESULTS: Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant's characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations. CONCLUSIONS: Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.

Temporal lobe perceptual predictions for speech are instantiated in motor cortex and reconciled by inferior frontal cortex.

Humans use predictions to improve speech perception, especially in noisy environments. Here we use 7-T functional MRI (fMRI) to decode brain representations of written phonological predictions and degraded speech signals in healthy humans and people with selective frontal neurodegeneration (non-fluent variant primary progressive aphasia [nfvPPA]). Multivariate analyses of item-specific patterns of neural activation indicate dissimilar representations of verified and violated predictions in left inferior frontal gyrus, suggestive of processing by distinct neural populations. In contrast, precentral gyrus represents a combination of phonological information and weighted prediction error. In the presence of intact temporal cortex, frontal neurodegeneration results in inflexible predictions. This manifests neurally as a failure to suppress incorrect predictions in anterior superior temporal gyrus and reduced stability of phonological representations in precentral gyrus. We propose a tripartite speech perception network in which inferior frontal gyrus supports prediction reconciliation in echoic memory, and precentral gyrus invokes a motor model to instantiate and refine perceptual predictions for speech.

Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records.

BACKGROUND: Dementia develops as cognitive abilities deteriorate, and early detection is critical for effective preventive interventions. However, mainstream diagnostic tests and screening tools, such as CAMCOG and MMSE, often fail to detect dementia accurately. Various graph-based or feature-dependent prediction and progression models have been proposed. Whenever these models exploit information in the patients' Electronic Medical Records, they represent promising options to identify the presence and severity of dementia more precisely. METHODS: The methods presented in this paper aim to address two problems related to dementia: (a) Basic diagnosis: identifying the presence of dementia in individuals, and (b) Severity diagnosis: predicting the presence of dementia, as well as the severity of the disease. We formulate these two tasks as classification problems and address them using machine learning models based on random forests and decision tree, analysing structured clinical data from an elderly population cohort. We perform a hybrid data curation strategy in which a dementia expert is involved to verify that curation decisions are meaningful. We then employ the machine learning algorithms that classify individual episodes into a specific dementia class. Decision trees are also used for enhancing the explainability of decisions made by prediction models, allowing medical experts to identify the most crucial patient features and their threshold values for the classification of dementia. RESULTS: Our experiment results prove that baseline arithmetic or cognitive tests, along with demographic features, can predict dementia and its severity with high accuracy. In specific, our prediction models have reached an average f1-score of 0.93 and 0.81 for problems (a) and (b), respectively. Moreover, the decision trees produced for the two issues empower the interpretability of the prediction models. CONCLUSIONS: This study proves that there can be an accurate estimation of the existence and severity of dementia disease by analysing various electronic medical record features and cognitive tests from the episodes of the elderly population. Moreover, a set of decision rules may comprise the building blocks for an efficient patient classification. Relevant clinical and screening test features (e.g. simple arithmetic or animal fluency tasks) represent precise predictors without calculating the scores of mainstream cognitive tests such as MMSE and CAMCOG. Such predictive model can identify not only meaningful features, but also justifications of classification. As a result, the predictive power of machine learning models over curated clinical data is proved, paving the path for a more accurate diagnosis of dementia.

Machine learning methods applied to genotyping data capture interactions between single nucleotide variants in late onset Alzheimer's disease.

Introduction: Genome-wide association studies (GWAS) in late onset Alzheimer's disease (LOAD) provide lists of individual genetic determinants. However, GWAS do not capture the synergistic effects among multiple genetic variants and lack good specificity. Methods: We applied tree-based machine learning algorithms (MLs) to discriminate LOAD (>700 individuals) and age-matched unaffected subjects in UK Biobank with single nucleotide variants (SNVs) from Alzheimer's disease (AD) studies, obtaining specific genomic profiles with the prioritized SNVs. Results: MLs prioritized a set of SNVs located in genes PVRL2, TOMM40, APOE, and APOC1, also influencing gene expression and splicing. The genomic profiles in this region showed interaction patterns involving rs405509 and rs1160985, also present in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. rs405509 located in APOE promoter interacts with rs429358 among others, seemingly neutralizing their predisposing effect. Discussion: Our approach efficiently discriminates LOAD from controls, capturing genomic profiles defined by interactions among SNVs in a hot-spot region.

A 'Mini Linguistic State Examination' to classify primary progressive aphasia.

There are few available methods for qualitatively evaluating patients with primary progressive aphasia. Commonly adopted approaches are time-consuming, of limited accuracy or designed to assess different patient populations. This paper introduces a new clinical test-the Mini Linguistic State Examination-which was designed uniquely to enable a clinician to assess and subclassify both classical and mixed presentations of primary progressive aphasia. The adoption of a novel assessment method (error classification) greatly amplifies the clinical information that can be derived from a set of standard linguistic tasks and allows a five-dimensional profile to be defined. Fifty-four patients and 30 matched controls were recruited. Five domains of language competence (motor speech, phonology, semantics, syntax and working memory) were assessed using a sequence of 11 distinct linguistic assays. A random forest classification was used to assess the diagnostic accuracy for predicting primary progressive aphasia subtypes and create a decision tree as a guide to clinical classification. The random forest prediction model was 96% accurate overall (92% for the logopenic variant, 93% for the semantic variant and 98% for the non-fluent variant). The derived decision tree produced a correct classification of 91% of participants whose data were not included in the training set. The Mini Linguistic State Examination is a new cognitive test incorporating a novel and powerful, yet straightforward, approach to scoring. Rigorous assessment of its diagnostic accuracy confirmed excellent matching of primary progressive aphasia syndromes to clinical gold standard diagnoses. Adoption of the Mini Linguistic State Examination by clinicians will have a decisive impact on the consistency and uniformity with which patients can be described clinically. It will also facilitate screening for cohort-based research, including future therapeutic trials, and is suitable for describing, quantifying and monitoring language deficits in other brain disorders.

Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool.

Background: Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) affect speech and language as well as motor functions. Clinical and neuropathological data indicate a close relationship between these two disorders and the non-fluent variant of primary progressive aphasia (nfvPPA). We use the recently developed Mini Linguistic State Examination tool (MLSE) to study speech and language disorders in patients with PSP, CBS, and nfvPPA, in combination with structural magnetic resonance imaging (MRI). Methods: Fifty-one patients (PSP N = 13, CBS N = 19, nfvPPA N = 19) and 30 age-matched controls completed the MLSE, the short form of the Boston Diagnostic Aphasia Examination (BDAE), and the Addenbrooke's Cognitive Examination III. Thirty-eight patients and all controls underwent structural MRI at 3 Tesla, with T1 and T2-weighted images processed by surface-based and subcortical segmentation within FreeSurfer 6.0.0 to extract cortical thickness and subcortical volumes. Morphometric differences were compared between groups and correlated with the severity of speech and language impairment. Results: CBS and PSP patients showed impaired MLSE performance, compared to controls, with a similar language profile to nfvPPA, albeit less severe. All patient groups showed reduced cortical thickness in bilateral frontal regions and striatal volume. PSP and nfvPPA patients also showed reduced superior temporal cortical thickness, with additional thalamic and amygdalo-hippocampal volume reductions in nfvPPA. Multivariate analysis of brain-wide cortical thickness and subcortical volumes with MLSE domain scores revealed associations between performance on multiple speech and language domains with atrophy of left-lateralised fronto-temporal cortex, amygdala, hippocampus, putamen, and caudate. Conclusions: The effect of PSP and CBS on speech and language overlaps with nfvPPA. These three disorders cause a common anatomical pattern of atrophy in the left frontotemporal language network and striatum. The MLSE is a short clinical screening tool that can identify the language disorder of PSP and CBS, facilitating clinical management and patient access to future clinical trials.

Spanish Version of the Mini-Linguistic State Examination for the Diagnosis of Primary Progressive Aphasia.

BACKGROUND: Primary progressive aphasia (PPA) is a neurodegenerative syndrome with three main clinical variants: non-fluent, semantic, and logopenic. Clinical diagnosis and accurate classification are challenging and often time-consuming. The Mini-Linguistic State Examination (MLSE) has been recently developed as a short language test to specifically assess language in neurodegenerative disorders. OBJECTIVE: Our aim was to adapt and validate the Spanish version of MLSE for PPA diagnosis. METHODS: Cross-sectional study involving 70 patients with PPA and 42 healthy controls evaluated with the MLSE. Patients were independently diagnosed and classified according to comprehensive cognitive evaluation and advanced neuroimaging. RESULTS: Internal consistency was 0.758. The influence of age and education was very low. The area under the curve for discriminating PPA patients and healthy controls was 0.99. Effect sizes were moderate-large for the discrimination between PPA and healthy controls. Motor speech, phonology, and semantic subscores discriminated between the three clinical variants. A random forest classification model obtained an F1-score of 81%for the three PPA variants. CONCLUSION: Our study provides a brief and useful language test for PPA diagnosis, with excellent properties for both clinical routine assessment and research purposes.

Neurological impact of emboli during adult cardiac surgery.

OBJECTIVES: This study draws on advances in Doppler ultrasound bubble sizing to investigate whether high volumes of macro-bubbles entering the brain during cardiac surgery increase the risk of new cerebral microbleeds (CMBs), ischemic MR lesions, or post-operative cognitive decline (POCD). METHODS: Transcranial Doppler (TCD) ultrasound recordings were analysed to estimate numbers of emboli and macrobubbles (>100 µm) entering the brain during cardiac surgery. Logistic regression was used to explore the hypothesis that emboli characteristics affect the incidence of new brain injuries identified through pre- and post-operative MRI and neuropsychological testing. RESULTS: TCD, MRI, and neuropsychological test data were compared between 28 valve and 18 CABG patients. Although valve patients received over twice as many emboli per procedure [median: 1995 vs. 859, p = .004], and seven times as many macro-bubbles [median: 218 vs. 28, p = .001], high volumes of macrobubbles were not found to be significantly associated with new CMBs, new ischaemic lesions, or POCD. The odds of acquiring new CMBs increased by approximately 5% [95% CI: 1 to 10%] for every embolus detected in the first minute after the release of the aortic cross-clamp (AxC). Logistic regression models also confirmed previous findings that cardiopulmonary bypass time and valve surgery were significant predictors for new CMBs (both p = .03). Logistic regression analysis estimated an increase in the odds of acquiring new CMBs of 6% [95% CI: 1 to 12%] for every minute of bypass time over 91 mins. CONCLUSIONS: This small study provides new information about the properties and numbers of bubbles entering the brain during surgery, but found no evidence to substantiate a direct link between large numbers of macrobubbles and adverse cognitive or MR outcome. Clinical Trial Registration URL - http://www.isrctn.com. Unique identifier: 66022965.

How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease.

Natural Language Processing (NLP) is an ever-growing field of computational science that aims to model natural human language. Combined with advances in machine learning, which learns patterns in data, it offers practical capabilities including automated language analysis. These approaches have garnered interest from clinical researchers seeking to understand the breakdown of language due to pathological changes in the brain, offering fast, replicable and objective methods. The study of Alzheimer's disease (AD), and preclinical Mild Cognitive Impairment (MCI), suggests that changes in discourse (connected speech or writing) may be key to early detection of disease. There is currently no disease-modifying treatment for AD, the leading cause of dementia in people over the age of 65, but detection of those at risk of developing the disease could help with the identification and testing of medications which can take effect before the underlying pathology has irreversibly spread. We outline important components of natural language, as well as NLP tools and approaches with which they can be extracted, analysed and used for disease identification and risk prediction. We review literature using these tools to model discourse across the spectrum of AD, including the contribution of machine learning approaches and Automatic Speech Recognition (ASR). We conclude that NLP and machine learning techniques are starting to greatly enhance research in the field, with measurable and quantifiable language components showing promise for early detection of disease, but there remain research and practical challenges for clinical implementation of these approaches. Challenges discussed include the availability of large and diverse datasets, ethics of data collection and sharing, diagnostic specificity and clinical acceptability.

The language profile of progressive supranuclear palsy.

A progressive speech/language disorder, such as the non fluent/agrammatic variant of primary progressive aphasia and progressive apraxia of speech, can be due to neuropathologically verified Progressive Supranuclear Palsy (PSP). The prevalence of linguistic deficits and the linguistic profile in PSP patients who present primarily with a movement disorder is unknown. In the present study, we investigated speech and language performance in a sample of clinically diagnosed PSP patients using a comprehensive language battery, including, besides traditional language tests, a detailed analysis of connected speech (picture description task assessing 26 linguistic features). The aim was to identify the most affected linguistic levels in seventeen PSP with a movement disorder presentation, compared to 21 patients with Parkinson's disease and 27 healthy controls. Machine learning methods were used to detect the most relevant language tests and linguistic features characterizing the language profile of PSP patients. Our results indicate that even non-clinically aphasic PSP patients have subtle language deficits, in particular involving the lexical-semantic and discourse levels. Patients with the Richardson's syndrome showed a lower performance in the word comprehension task with respect to the other PSP phenotypes with predominant frontal presentation, parkinsonism and progressive gait freezing. The present findings support the usefulness of a detailed language assessment in all patients in the PSP spectrum.

Perioperative Cerebral Microbleeds After Adult Cardiac Surgery.

Background and Purpose- Cerebral microbleeds (CMBs) have been observed using magnetic resonance imaging in patients with cardiovascular risk factors, cognitive deterioration, small vessel disease, and dementia. They are a well-known consequence of cerebral amyloid angiopathy, chronic hypertension, and diffuse axonal injury, among other causes. However, the frequency and location of new CMBs postadult cardiac surgery, in association with cognition and perioperative risk factors, have yet to be studied. Methods- Pre- and postsurgery magnetic resonance susceptibility-weighted images and neuropsychological tests were analyzed from a total of 75 patients undergoing cardiac surgery (70 men; mean age, 63±10 years). CMBs were identified by a neuroradiologist blinded to clinical details who independently assessed the presence and location of CMBs using standardized criteria. Results- New CMBs were identified in 76% of patients after cardiac surgery. The majority of new CMBs were located in the frontal lobe (46%) followed by the parietal lobe (15%), cerebellum (13%), occipital lobe (12%), and temporal lobe (8%). Patients with new CMBs typically began with a higher prevalence of preexisting CMBs ( P=0.02). New CMBs were associated with longer cardiopulmonary bypass times ( P=0.003), and there was a borderline association with lower percentage hematocrit ( P=0.04). Logistic regression analysis suggested a ≈2% increase in the odds of acquiring new CMBs during cardiac surgery for every minute of bypass time (odds ratio, 1.02; 95% CI, 1.00-1.05; P=0.04). Postoperative neuropsychological decline was observed in 44% of patients and seemed to be unrelated to new CMBs. Conclusions- New CMBs identified using susceptibility-weighted images were found in 76% of patients who underwent cardiac surgery. CMBs were globally distributed with the highest numbers in the frontal and parietal lobes. Our regression analysis indicated that length of cardiopulmonary bypass time and lowered hematocrit may be significant predictors for new CMBs after cardiac surgery. Clinical Trial Registration- URL: http://www.isrctn.com . Unique identifier: 66022965.

Screening for Aphasia in NeuroDegeneration for the Diagnosis of Patients with Primary Progressive Aphasia: Clinical Validity and Psychometric Properties.

BACKGROUND: We evaluated the psychometric proprieties of the Screening for Aphasia in NeuroDegeneration (SAND) battery in Italian primary progressive aphasia (PPA) and movement disorder (MD) patients. METHODS: The sample included 30 consecutive PPA and 45 MD patients who completed the SAND battery together with a clinical interview and a neurological/neuropsychological examination and 130 healthy controls (HC). RESULTS: The SAND battery showed good internal consistency and good convergent and divergent validity. receiver operating characteristic analysis revealed an area under the curve of 0.978 for PPA versus HC and of 0.786 for PPA versus MD. A cutoff ≥3 gave a sensitivity of 0.933% and a specificity of 0.946% for discriminating PPA versus HC, whereas a cutoff ≥5 gave a sensitivity of 0.767% and a specificity of 0.667% for discriminating PPA versus MD. CONCLUSION: These results indicate that the SAND battery is an adequate, reliable, and valid diagnostic tool for PPA.

Development of a core outcome set for disease modification trials in mild to moderate dementia: a systematic review, patient and public consultation and consensus recommendations.

BACKGROUND: There is currently no disease-modifying treatment available to halt or delay the progression of the disease pathology in dementia. An agreed core set of the best-available and most appropriate outcomes for disease modification would facilitate the design of trials and ensure consistency across disease modification trials, as well as making results comparable and meta-analysable in future trials. OBJECTIVES: To agree a set of core outcomes for disease modification trials for mild to moderate dementia with the UK dementia research community and patient and public involvement (PPI). DATA SOURCES: We included disease modification trials with quantitative outcomes of efficacy from (1) references from related systematic reviews in workstream 1; (2) searches of the Cochrane Dementia and Cognitive Improvement Group study register, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, EMBASE, Latin American and Caribbean Health Sciences Literature and PsycINFO on 11 December 2015, and clinical trial registries [International Standard Randomised Controlled Trial Number (ISRCTN) and clinicaltrials.gov] on 22 and 29 January 2016; and (3) hand-searches of reference lists of relevant systematic reviews from database searches. REVIEW METHODS: The project consisted of four workstreams. (1) We obtained related core outcome sets and work from co-applicants. (2) We systematically reviewed published and ongoing disease modification trials to identify the outcomes used in different domains. We extracted outcomes used in each trial, recording how many used each outcome and with how many participants. We divided outcomes into the domains measured and searched for validation data. (3) We consulted with PPI participants about recommended outcomes. (4) We presented all the synthesised information at a conference attended by the wider body of National Institute for Health Research (NIHR) dementia researchers to reach consensus on a core set of outcomes. RESULTS: We included 149 papers from the 22,918 papers screened, referring to 125 individual trials. Eighty-one outcomes were used across trials, including 72 scales [31 cognitive, 12 activities of daily living (ADLs), 10 global, 16 neuropsychiatric and three quality of life] and nine biological techniques. We consulted with 18 people for PPI. The conference decided that only cognition and biological markers are core measures of disease modification. Cognition should be measured by the Mini Mental State Examination (MMSE) or the Alzheimer's Disease Assessment Scale - Cognitive subscale (ADAS-Cog), and brain changes through structural magnetic resonance imaging (MRI) in a subset of participants. All other domains are important but not core. We recommend using the Neuropsychiatric Inventory for neuropsychiatric symptoms: the Disability Assessment for Dementia for ADLs, the Dementia Quality of Life Measure for quality of life and the Clinical Dementia Rating scale to measure dementia globally. LIMITATIONS: Most of the trials included participants with Alzheimer's disease, so recommendations may not apply to other types of dementia. We did not conduct economic analyses. The PPI consultation was limited to members of the Alzheimer's Society Research Network. CONCLUSIONS: Cognitive outcomes and biological markers form the core outcome set for future disease modification trials, measured by the MMSE or ADAS-Cog, and structural MRI in a subset of participants. FUTURE WORK: We envisage that the core set may be superseded in the future, particularly for other types of dementia. There is a need to develop an algorithm to compare scores on the MMSE and ADAS-Cog. STUDY REGISTRATION: The project was registered with Core Outcome Measures in Effectiveness Trials [ www.comet-initiative.org/studies/details/819?result=true (accessed 7 April 2016)]. The systematic review protocol is registered as PROSPERO CRD42015027346. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

SAND: a Screening for Aphasia in NeuroDegeneration. Development and normative data.

Language assessment has a critical role in the clinical diagnosis of neurodegenerative diseases, in particular, in the case of Primary Progressive Aphasia (PPA). The current diagnostic criteria (Gorno-Tempini et al., 2011) identify three main variants on the basis of clinical features and patterns of brain atrophy. Widely accepted tools to diagnose, clinically classify, and follow up the heterogeneous language profiles of PPA are still lacking. In this study, we develop a screening battery, composed of nine tests (picture naming, word and sentence comprehension, word and sentence repetition, reading, semantic association, writing and picture description), following the recommendations of current diagnostic guidelines and taking into account recent research on the topic. All tasks were developed with consideration of the psycholinguistic factors that can affect performance, with the aim of achieving sensitivity to the language deficit to which each task was relevant, and to allow identification of the selective characteristic impairments of each PPA variant. Normative data on 134 Italian subjects pooled across homogeneous subgroups for age, sex, and education are reported. Although further work is still needed, this battery represents a first step towards a concise multilingual standard language examination, a fast and simple tool to help clinicians and researchers in the diagnosis of PPA.

Core outcome measures for interventions to prevent or slow the progress of dementia for people living with mild to moderate dementia: Systematic review and consensus recommendations.

BACKGROUND: There are no disease-modifying treatments for dementia. There is also no consensus on disease modifying outcomes. We aimed to produce the first evidence-based consensus on core outcome measures for trials of disease modification in mild-to-moderate dementia. METHODS AND FINDINGS: We defined disease-modification interventions as those aiming to change the underlying pathology. We systematically searched electronic databases and previous systematic reviews for published and ongoing trials of disease-modifying treatments in mild-to-moderate dementia. We included 149/22,918 of the references found; with 81 outcome measures from 125 trials. Trials involved participants with Alzheimer's disease (AD) alone (n = 111), or AD and mild cognitive impairment (n = 8) and three vascular dementia. We divided outcomes by the domain measured (cognition, activities of daily living, biological markers, neuropsychiatric symptoms, quality of life, global). We calculated the number of trials and of participants using each outcome. We detailed psychometric properties of each outcome. We sought the views of people living with dementia and family carers in three cities through Alzheimer's society focus groups. Attendees at a consensus conference (experts in dementia research, disease-modification and harmonisation measures) decided on the core set of outcomes using these results. Recommended core outcomes were cognition as the fundamental deficit in dementia and to indicate disease modification, serial structural MRIs. Cognition should be measured by Mini Mental State Examination or Alzheimer's Disease Assessment Scale-Cognitive Subscale. MRIs would be optional for patients. We also made recommendations for measuring important, but non-core domains which may not change despite disease modification. LIMITATIONS: Most trials were about AD. Specific instruments may be superseded. We searched one database for psychometric properties. INTERPRETATION: This is the first review to identify the 81 outcome measures the research community uses for disease-modifying trials in mild-to-moderate dementia. Our recommendations will facilitate designing, comparing and meta-analysing disease modification trials in mild-to-moderate dementia, increasing their value. TRIAL REGISTRATION: PROSPERO no. CRD42015027346.

Neuromyelitis optica: Application of computer diagnostics to historical case reports.

The retrospective diagnosis of illnesses by medical historians can often be difficult and prone to bias, although knowledge of the medical disorders of historical figures is key to the understanding of their behavior and reactions. The recent application of computer diagnostics to historical figures allows an objective differential diagnosis to be accomplished. Taking an example from clinical neurology, we analyzed the earliest reported cases of Devic's disease (neuromyelitis optica) that commonly affects the optic nerve and spinal cord and was previously often confused with multiple sclerosis. We conclude that in most identified cases the software concurred with the contemporary physicians' interpretation, but some claimed cases either had insufficient data to provide a diagnosis or other possible diagnoses were suggested that had not been considered. Computational methods may, therefore, help historians to diagnose the ailments of historical figures with greater objectivity.

The acute mania of King George III: A computational linguistic analysis.

We used a computational linguistic approach, exploiting machine learning techniques, to examine the letters written by King George III during mentally healthy and apparently mentally ill periods of his life. The aims of the study were: first, to establish the existence of alterations in the King's written language at the onset of his first manic episode; and secondly to identify salient sources of variation contributing to the changes. Effects on language were sought in two control conditions (politically stressful vs. politically tranquil periods and seasonal variation). We found clear differences in the letter corpus, across a range of different features, in association with the onset of mental derangement, which were driven by a combination of linguistic and information theory features that appeared to be specific to the contrast between acute mania and mental stability. The paucity of existing data relevant to changes in written language in the presence of acute mania suggests that lexical, syntactic and stylometric descriptions of written discourse produced by a cohort of patients with a diagnosis of acute mania will be necessary to support the diagnosis independently and to look for other periods of mental illness of the course of the King's life, and in other historically significant figures with similarly large archives of handwritten documents.

Motif Discovery in Speech: Application to Monitoring Alzheimer's Disease.

BACKGROUND: Perseveration - repetition of words, phrases or questions in speech - is commonly described in Alzheimer's disease (AD). Measuring perseveration is difficult, but may index cognitive performance, aiding diagnosis and disease monitoring. Continuous recording of speech would produce a large quantity of data requiring painstaking manual analysis, and risk violating patients' and others' privacy. A secure record and an automated approach to analysis are required. OBJECTIVES: To record bone-conducted acoustic energy fluctuations from a subject's vocal apparatus using an accelerometer, to describe the recording and analysis stages in detail, and demonstrate that the approach is feasible in AD. METHODS: Speech-related vibration was captured by an accelerometer, affixed above the temporomandibular joint. Healthy subjects read a script with embedded repetitions. Features were extracted from recorded signals and combined using Principal Component Analysis to obtain a one-dimensional representation of the feature vector. Motif discovery techniques were used to detect repeated segments. The equipment was tested in AD patients to determine device acceptability and recording quality. RESULTS: Comparison with the known location of embedded motifs suggests that, with appropriate parameter tuning, the motif discovery method can detect repetitions. The device was acceptable to patients and produced adequate signal quality in their home environments. CONCLUSION: We established that continuously recording bone-conducted speech and detecting perseverative patterns were both possible. In future studies we plan to associate the frequency of verbal repetitions with stage, progression and type of dementia. It is possible that the method could contribute to the assessment of disease-modifying treatments.

The role of working memory and verbal fluency in autobiographical memory in early Alzheimer's disease and matched controls.

Retrieval of autobiographical memories (AMs) is important for "sense of self". Previous research and theoretical accounts suggest that working memory (WM) and semantic and phonemic fluency abilities facilitate the hierarchical search for, and reliving of past, personal events in the mind's eye. However, there remains a lack of consensus as to the nature of the relationships between these cognitive functions and the truly episodic aspects of AM. The present study therefore aimed to explore the associations between these variables in a sample with a wide range of cognitive abilities. The study incorporated a between-groups component, and a correlational component with multiple regression. Participants with Alzheimer's disease (n=10) and matched healthy controls (n=10) were assessed on measures of semantic and episodic AM search and retrieval, auditory and spatial WM, and semantic and phonemic fluency. The AD group produced less episodic AM content compared to controls. Semantic fluency predicted episodic AM retrieval independent of age effects but there were no significant relationships between measures of phonemic fluency, WM and episodic AM. The results suggest that the ability to maintain hierarchical search of the semantic knowledge-base is important for truly episodic reliving, and interventions for people with AM impairment might therefore benefit from incorporating structured, individualised external memory-aids to facilitate AM search and retrieval.