Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Emergence of an early SARS-CoV-2 epidemic in the United States.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi sublining fibroblasts, IL1B+ pro-inflammatory monocytes, ITGAX+TBX21+ autoimmune-associated B cells and PDCD1+ peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+ T cells characterized by GZMK+, GZMB+, and GNLY+ phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.

Cross-Neutralizing and Protective Human Antibody Specificities to Poxvirus Infections.

Monkeypox (MPXV) and cowpox (CPXV) are emerging agents that cause severe human infections on an intermittent basis, and variola virus (VARV) has potential for use as an agent of bioterror. Vaccinia immune globulin (VIG) has been used therapeutically to treat severe orthopoxvirus infections but is in short supply. We generated a large panel of orthopoxvirus-specific human monoclonal antibodies (Abs) from immune subjects to investigate the molecular basis of broadly neutralizing antibody responses for diverse orthopoxviruses. Detailed analysis revealed the principal neutralizing antibody specificities that are cross-reactive for VACV, CPXV, MPXV, and VARV and that are determinants of protection in murine challenge models. Optimal protection following respiratory or systemic infection required a mixture of Abs that targeted several membrane proteins, including proteins on enveloped and mature virion forms of virus. This work reveals orthopoxvirus targets for human Abs that mediate cross-protective immunity and identifies new candidate Ab therapeutic mixtures to replace VIG.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

Outbreak.info Research Library: a standardized, searchable platform to discover and explore COVID-19 resources.

Outbreak.info Research Library is a standardized, searchable interface of coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) publications, clinical trials, datasets, protocols and other resources, built with a reusable framework. We developed a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public application programming interface (API) and R package.

Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations.

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info , a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.

Neurophysiological consequences of synapse loss in progressive supranuclear palsy.

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from preclinical to clinical models of pathology and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations such as EEG and magnetoencephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by 11C-UCB-J PET, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar-specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.

Presumed Lacrimal Gland Pleomorphic Adenoma With Extensive Ossification and Necrosis.

Calcification within pleomorphic adenomas of the lacrimal gland is well recognized but uncommon, being seen more readily in lacrimal gland carcinomas. Bony formation, ossification, in pleomorphic adenomas of the lacrimal glands is even rarer. Together with extensive sclerosis, or "coagulative necrosis," ossification and necrosis should alert the clinician to the risk of malignant transformation. However, both can mimic carcinomatous change, leading to misinterpretation of malignancy in an otherwise benign lacrimal gland neoplasm. We present 2 case reports of patients with clinically presumed pleomorphic adenomas of the lacrimal gland whose histopathology demonstrated lacrimal gland ossification and necrosis without features of malignancy or invasive disease.

Neurophysiological and Brain Structural Markers of Cognitive Frailty Differ from Alzheimer's Disease.

With increasing life span and prevalence of dementia, it is important to understand the mechanisms of cognitive aging. Here, we focus on a subgroup of the population we term "cognitively frail," defined by reduced cognitive function in the absence of subjective memory complaints, or a clinical diagnosis of dementia. Cognitive frailty is distinct from cognitive impairment caused by physical frailty. It has been proposed to be a precursor to Alzheimer's disease, but may alternatively represent one end of a nonpathologic spectrum of cognitive aging. We test these hypotheses in humans of both sexes, by comparing the structural and neurophysiological properties of a community-based cohort of cognitive frail adults, to people presenting clinically with diagnoses of Alzheimer's disease or mild cognitive impairment, and community-based cognitively typical older adults. Cognitive performance of the cognitively frail was similar to those with mild cognitive impairment. We used a novel cross-modal paired-associates task that presented images followed by sounds, to induce physiological responses of novelty and associative mismatch, recorded by EEG/MEG. Both controls and cognitively frail showed stronger mismatch responses and larger temporal gray matter volume, compared with people with mild cognitive impairment and Alzheimer's disease. Our results suggest that community-based cognitively frail represents a spectrum of normal aging rather than incipient Alzheimer's disease, despite similar cognitive function. Lower lifelong cognitive reserve, hearing impairment, and cardiovascular comorbidities might contribute to the etiology of the cognitive frailty. Critically, community-based cohorts of older adults with low cognitive performance should not be interpreted as representing undiagnosed Alzheimer's disease.SIGNIFICANCE STATEMENT The current study investigates the neural signatures of cognitive frailty in relation to healthy aging and Alzheimer's disease. We focus on the cognitive aspect of frailty and show that, despite performing similarly to the patients with mild cognitive impairment, a cohort of community-based adults with poor cognitive performance do not show structural atrophy or neurophysiological signatures of Alzheimer's disease. Our results call for caution before assuming that cognitive frailty represents latent Alzheimer's disease. Instead, the cognitive underperformance of cognitively frail adults could result in cumulative effects of multiple psychosocial risk factors over the lifespan, and medical comorbidities.

Causal Evidence for the Multiple Demand Network in Change Detection: Auditory Mismatch Magnetoencephalography across Focal Neurodegenerative Diseases.

The multiple demand (MD) system is a network of fronto-parietal brain regions active during the organization and control of diverse cognitive operations. It has been argued that this activation may be a nonspecific signal of task difficulty. However, here we provide convergent evidence for a causal role for the MD network in the "simple task" of automatic auditory change detection, through the impairment of top-down control mechanisms. We employ independent structure-function mapping, dynamic causal modeling (DCM), and frequency-resolved functional connectivity analyses of MRI and magnetoencephalography (MEG) from 75 mixed-sex human patients across four neurodegenerative syndromes [behavioral variant fronto-temporal dementia (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), posterior cortical atrophy (PCA), and Alzheimer's disease mild cognitive impairment with positive amyloid imaging (ADMCI)] and 48 age-matched controls. We show that atrophy of any MD node is sufficient to impair auditory neurophysiological response to change in frequency, location, intensity, continuity, or duration. There was no similar association with atrophy of the cingulo-opercular, salience or language networks, or with global atrophy. MD regions displayed increased functional but decreased effective connectivity as a function of neurodegeneration, suggesting partially effective compensation. Overall, we show that damage to any of the nodes of the MD network is sufficient to impair top-down control of sensation, providing a common mechanism for impaired change detection across dementia syndromes.SIGNIFICANCE STATEMENT Previous evidence for fronto-parietal networks controlling perception is largely associative and may be confounded by task difficulty. Here, we use a preattentive measure of automatic auditory change detection [mismatch negativity (MMN) magnetoencephalography (MEG)] to show that neurodegeneration in any frontal or parietal multiple demand (MD) node impairs primary auditory cortex (A1) neurophysiological response to change through top-down mechanisms. This explains why the impaired ability to respond to change is a core feature across dementias, and other conditions driven by brain network dysfunction, such as schizophrenia. It validates theoretical frameworks in which neurodegenerating networks upregulate connectivity as partially effective compensation. The significance extends beyond network science and dementia, in its construct validation of dynamic causal modeling (DCM), and human confirmation of frequency-resolved analyses of animal neurodegeneration models.

Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.

BACKGROUND: Biomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging Schema.org could benefit biomedical research resource providers, but it can be challenging to apply Schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize Schema.org or other biomedical schema projects. RESULTS: Our browser-based tool includes features which can help address many of the barriers towards Schema.org-compliance such as: The ability to easily browse for relevant Schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema-a large multi-class schema for harmonizing various COVID-19 related resources. CONCLUSIONS: We have created a browser-based tool to empower biomedical research resource providers to leverage Schema.org classes to make their research outputs more FAIR.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy.

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

Early Detection and Surveillance of the SARS-CoV-2 Variant BA.2.86 - Worldwide, July-October 2023.

Early detection of emerging SARS-CoV-2 variants is critical to guiding rapid risk assessments, providing clear and timely communication messages, and coordinating public health action. CDC identifies and monitors novel SARS-CoV-2 variants through diverse surveillance approaches, including genomic, wastewater, traveler-based, and digital public health surveillance (e.g., global data repositories, news, and social media). The SARS-CoV-2 variant BA.2.86 was first sequenced in Israel and reported on August 13, 2023. The first U.S. COVID-19 case caused by this variant was reported on August 17, 2023, after a patient received testing for SARS-CoV-2 at a health care facility on August 3. In the following month, eight additional U.S. states detected BA.2.86 across various surveillance systems, including specimens from health care settings, wastewater surveillance, and traveler-based genomic surveillance. As of October 23, 2023, sequences have been reported from at least 32 countries. Continued variant tracking and further evidence are needed to evaluate the full public health impact of BA.2.86. Timely genomic sequence submissions to global public databases aided early detection of BA.2.86 despite the decline in the number of specimens being sequenced during the past year. This report describes how multicomponent surveillance and genomic sequencing were used in real time to track the emergence and transmission of the BA.2.86 variant. This surveillance approach provides valuable information regarding implementing and sustaining comprehensive surveillance not only for novel SARS-CoV-2 variants but also for future pathogen threats.

Enhancement and Comparison of (Ceftazidime-)Avibactam Plus Aztreonam Susceptibility Tests for Stenotrophomonas maltophilia in Clinical Diagnostics.

Stenotrophomonas maltophilia is naturally resistant to many antimicrobials. We evaluated the in vitro activity and reproducibility of two different super-position methods of aztreonam in combination with ceftazidime-avibactam for S. maltophilia and compared these results with the recently available aztreonam-avibactam gradient strip. We recommend an improved super-position method that avoids the possible risk of handling a contaminated aztreonam strip. In addition, we report that the cefazidime-avibactam and aztreonam super-position method showed increased in vitro activity in comparison with aztreonam-avibactam indicating activity of the ceftazidime component in vitro.

The moment is now: Strengthening communities and families for the future of our nation.

COVID-19 has highlighted the historical lack of investment in the conditions that children need to thrive, and demonstrates how a crisis can exacerbate children's vulnerability to disease and violence. Exposure to early adversity already affects millions of children across the country and puts them at risk for poor outcomes. With the uncertainty of the pandemic, many more families are struggling and subsequently, more children are at risk for exposure to adversity. Preventing early adversity and promoting the prosperity of our nation requires assuring that all children, regardless of sociodemographic characteristics, have what they need to reach their full health and life potential. Now is the time to address the social and structural conditions that contribute to the inequitable distribution of risk for some families and which contribute to their unequal burden and impacts of adversity, COVID-19, racial injustice, and other health crises. While many look forward to "a return to normal," returning to normal would be a missed opportunity to learn from our mistakes and ensure a bright future for our nation. We must invest in children and families for the future health of Americans.

Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Alpha Variant-United States, 2021.

BACKGROUND: In Spring 2021, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.7 (Alpha) became the predominant variant in the United States. Research suggests that Alpha has increased transmissibility compared with non-Alpha lineages. We estimated household secondary infection risk (SIR), assessed characteristics associated with transmission, and compared symptoms of persons with Alpha and non-Alpha infections. METHODS: We followed households with SARS-CoV-2 infection for 2 weeks in San Diego County and metropolitan Denver, January to April 2021. We collected epidemiologic information and biospecimens for serology, reverse transcription-polymerase chain reaction (RT-PCR), and whole-genome sequencing. We stratified SIR and symptoms by lineage and identified characteristics associated with transmission using generalized estimating equations. RESULTS: We investigated 127 households with 322 household contacts; 72 households (56.7%) had member(s) with secondary infections. SIRs were not significantly higher for Alpha (61.0% [95% confidence interval, 52.4-69.0%]) than non-Alpha (55.6% [44.7-65.9%], P = .49). In households with Alpha, persons who identified as Asian or Hispanic/Latino had significantly higher SIRs than those who identified as White (P = .01 and .03, respectively). Close contact (eg, kissing, hugging) with primary cases was associated with increased transmission for all lineages. Persons with Alpha infection were more likely to report constitutional symptoms than persons with non-Alpha (86.9% vs 76.8%, P = .05). CONCLUSIONS: Household SIRs were similar for Alpha and non-Alpha. Comparable SIRs may be due to saturation of transmission risk in households due to extensive close contact, or true lack of difference in transmission rates. Avoiding close contact within households may reduce SARS-CoV-2 transmission for all lineages among household members.

A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset.

Early detection of Alzheimer's Disease (AD) is vital to reduce the burden of dementia and for developing effective treatments. Neuroimaging can detect early brain changes, such as hippocampal atrophy in Mild Cognitive Impairment (MCI), a prodromal state of AD. However, selecting the most informative imaging features by machine-learning requires many cases. While large publically-available datasets of people with dementia or prodromal disease exist for Magnetic Resonance Imaging (MRI), comparable datasets are missing for Magnetoencephalography (MEG). MEG offers advantages in its millisecond resolution, revealing physiological changes in brain oscillations or connectivity before structural changes are evident with MRI. We introduce a MEG dataset with 324 individuals: patients with MCI and healthy controls. Their brain activity was recorded while resting with eyes closed, using a 306-channel MEG scanner at one of two sites (Madrid or Cambridge), enabling tests of generalization across sites. A T1-weighted MRI is provided to assist source localisation. The MEG and MRI data are formatted according to international BIDS standards and analysed freely on the DPUK platform (https://portal.dementiasplatform.uk/Apply). Here, we describe this dataset in detail, report some example (benchmark) analyses, and consider its limitations and future directions.

Household Transmission and Symptomology of Severe Acute Respiratory Syndrome Coronavirus 2 Alpha Variant among Children-California and Colorado, 2021.

OBJECTIVE: To assess the household secondary infection risk (SIR) of B.1.1.7 (Alpha) and non-Alpha lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among children. STUDY DESIGN: During January to April 2021, we prospectively followed households with a SARS-CoV-2 infection. We collected questionnaires, serial nasopharyngeal swabs for reverse transcription polymerase chain reaction testing and whole genome sequencing, and serial blood samples for serology testing. We calculated SIRs by primary case age (pediatric vs adult), household contact age, and viral lineage. We evaluated risk factors associated with transmission and described symptom profiles among children. RESULTS: Among 36 households with pediatric primary cases, 21 (58%) had secondary infections. Among 91 households with adult primary cases, 51 (56%) had secondary infections. SIRs among pediatric and adult primary cases were 45% and 54%, respectively (OR, 0.79; 95% CI, 0.41-1.54). SIRs among pediatric primary cases with Alpha and non-Alpha lineage were 55% and 46%, respectively (OR, 1.52; 95% CI, 0.51-4.53). SIRs among pediatric and adult household contacts were 55% and 49%, respectively (OR, 1.01; 95% CI, 0.68-1.50). Among pediatric contacts, no significant differences in the odds of acquiring infection by demographic or household characteristics were observed. CONCLUSIONS: Household transmission of SARS-CoV-2 from children and adult primary cases to household members was frequent. The risk of secondary infection was similar among child and adult household contacts. Among children, household transmission of SARS-CoV-2 and the risk of secondary infection was not influenced by lineage. Continued mitigation strategies (eg, masking, physical distancing, vaccination) are needed to protect at-risk groups regardless of virus lineage circulating in communities.

Evidence and implications of abnormal predictive coding in dementia.

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of 'memory centres' or 'language centres', or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.