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Human decisions about when to act originate within a basal forebrain-nigral circuit.

Decisions about when to act are critical for survival in humans as in animals, but how a desire is translated into the decision that an action is worth taking at any particular point in time is incompletely understood. Here we show that a simple model developed to explain when animals decide it is worth taking an action also explains a significant portion of the variance in timing observed when humans take voluntary actions. The model focuses on the current environment's potential for reward, the timing of the individual's own recent actions, and the outcomes of those actions. We show, by using ultrahigh-field MRI scanning, that in addition to anterior cingulate cortex within medial frontal cortex, a group of subcortical structures including striatum, substantia nigra, basal forebrain (BF), pedunculopontine nucleus (PPN), and habenula (HB) encode trial-by-trial variation in action time. Further analysis of the activity patterns found in each area together with psychophysiological interaction analysis and structural equation modeling suggested a model in which BF integrates contextual information that will influence the decision about when to act and communicates this information, in parallel with PPN and HB influences, to nigrostriatal circuits. It is then in the nigrostriatal circuit that action initiation per se begins.

Ultra-high temporal resolution 4D angiography using arterial spin labeling with subspace reconstruction.

PURPOSE: To achieve ultra-high temporal resolution non-contrast 4D angiography with improved spatiotemporal fidelity. METHODS: Continuous data acquisition using 3D golden-angle sampling following an arterial spin labeling preparation allows for flexibly reconstructing 4D dynamic angiograms at arbitrary temporal resolutions. However, k-space data is often temporally "binned" before image reconstruction, negatively affecting spatiotemporal fidelity and limiting temporal resolution. In this work, a subspace was extracted by linearly compressing a dictionary constructed from simulated curves of an angiographic kinetic model. The subspace was used to represent and reconstruct the voxelwise signal timecourse at the same temporal resolution as the data acquisition without temporal binning. Physiological parameters were estimated from the resulting images using a Bayesian fitting approach. A group of eight healthy subjects were scanned and the in vivo results reconstructed by different methods were compared. Because of the difficulty of obtaining ground truth 4D angiograms with ultra-high temporal resolution, the in vivo results were cross-validated with numerical simulations. RESULTS: The proposed method enables 4D time-resolved angiography with much higher temporal resolution (14.7 ms) than previously reported (˜50 ms) while maintaining high spatial resolution (1.1 mm isotropic). Blood flow dynamics were depicted in greater detail, thin vessel visibility was improved, and the estimated physiological parameters also exhibited more realistic spatial patterns with the proposed method. CONCLUSION: Incorporating a subspace compressed kinetic model into the reconstruction of 4D ASL angiograms notably improved the temporal resolution and spatiotemporal fidelity, which was subsequently beneficial for accurate physiological modeling.

Progression and life expectancy in primary lateral sclerosis

Objectives To characterise the clinical characteristics and longitudinal outcomes in primary lateral sclerosis (PLS), including median survival from symptom onset and age at death. Methods The authors retrospectively reviewed electronic health records of patients diagnosed with PLS referred to a specialised motor neuron disorders clinic from 2002 to 2024, analysed longitudinal Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) assessments using joint models and used Kaplan-Meier methods and life tables to calculate median survival and age at death compared with population-based values. Results Of 52 patients, 34 (65%) were male, 41 (79%) first noted symptoms in the lower limbs and 10 (19%) in corticobulbar function. Median age of symptom onset was 53 years. The mean annual rate of functional decline was -1.92 ALSFRS-R points (95% CI -3.03 to -0.78), with equal highest rates of decline in fine and gross motor subscores. Five patients (10%) received gastrostomy and three (6%) non-invasive ventilation. Median survival from symptom onset was 23.1 years (22.7 to not reached), and median age at death was 79.5 years (77.8 to not reached) compared with a population-based reference mean of 81.9 years (81.1 to 82.8). Discussion PLS may be commensurate with near-normal life expectancy. Significant disability arises from limb motor dysfunction, with a minority of patients requiring nutritional or respiratory support. This has important implications for counselling and trial design.

Quantifying axonal features of human superficial white matter from three-dimensional multibeam serial electron microscopy data assisted by deep learning.

Short-range association fibers located in the superficial white matter play an important role in mediating higher-order cognitive function in humans. Detailed morphological characterization of short-range association fibers at the microscopic level promises to yield important insights into the axonal features driving cortico-cortical connectivity in the human brain yet has been difficult to achieve to date due to the challenges of imaging at nanometer-scale resolution over large tissue volumes. This work presents results from multi-beam scanning electron microscopy (EM) data acquired at 4 × 4 × 33 nm3 resolution in a volume of human superficial white matter measuring 200 × 200 × 112 μm (Braitenberg and Schüz, 2013), leveraging automated analysis methods. Myelin and myelinated axons were automatically segmented using deep convolutional neural networks (CNNs), assisted by transfer learning and dropout regularization techniques. A total of 128,285 myelinated axons were segmented, of which 70,321 and 2,102 were longer than 10 and 100 μm, respectively. Marked local variations in diameter (i.e., beading) and direction (i.e., undulation) were observed along the length of individual axons. Myelinated axons longer than 10 μm had inner diameters around 0.5 µm, outer diameters around 1 µm, and g-ratios around 0.5. This work fills a gap in knowledge of axonal morphometry in the superficial white matter and provides a large 3D human EM dataset and accurate segmentation results for a variety of future studies in different fields.

Dynamic B0field shimming for improving pseudo-continuous arterial spin labeling at 7 Tesla

Early neurological deterioration in patients with minor stroke: A single-center study conducted in Vietnam

A minor ischemic stroke is associated with a higher likelihood of poor clinical outcomes at 90 days when there is early neurological deterioration (END). The objective of this case-control study conducted in a comprehensive stroke facility in Vietnam is to examine the frequency, forecast, and outcomes of patients with END in minor strokes. The study employs a descriptive observational design, longitudinally tracking patients with minor strokes admitted to Bach Mai Hospital’s Stroke Center between December 1, 2023, and August 31, 2024. Hospitalized within 24 hours of symptom onset, minor stroke patients with National Institutes of Health Stroke Scale (NIHSS) scores ≤ 5 and items 1a, 1b, and 1c on the NIHSS scale, each equal to 0, were included in the study. The primary measure of interest is the END rate, defined as a rise of 2 or more points in the NIHSS score during the first 72 hours after admission. We conduct a logistic regression analysis to identify forecasting factors for END. Out of 839 patients, 88 (10.5%) had END. In the END group, we found that most patients had complications within the first 24 hours of stroke, accounting for 43.2%; the 24 – 48-hour window accounted for 35.2%, and the 48 – 72-hour window accounted for 21.6%. END was associated with a higher likelihood of poor outcomes (mRS 2 – 6) at discharge (OR = 22.76; 95% CI 11.22 – 46.20; p < 0.01), 30 days post-stroke(OR = 24.38; 95% CI 14.40 – 41.29; p < 0.01), and 90 days post-stroke (OR = 21.74; 95% CI 12.63 – 37.43; p < 0.01). Some of the prognostic factors for END were admission NIHSS score (OR = 1.24; 95% CI 1.03 – 1.49; p = 0.02), admission systolic blood pressure greater than 150mmHg (OR = 1.70; 95% CI 1.03 – 2.81; p = 0.04), admission blood glucose (OR = 1.07; 95% CI 1.01 – 1.14; p = 0.02), reperfusion therapy (OR = 3.35; 95% CI 1.50 – 7.49; p < 0.01), use of antiplatelet monotherapy (OR = 3.69; 95% CI 2.24 – 6.08; p < 0.01), internal capsule infarction (OR = 2.54; 95% CI 1.37 – 4.71; p < 0.01), hemorrhagic transformation (OR = 5.72; 95% CI 1.07 – 30.45; p = 0.04), corresponding extracranial carotid artery occlusion (OR = 4.84; 95% CI 1.26 – 18.65; p = 0.02), and middle cerebral artery occlusion OR = 3.06; 95% CI 1.29 – 7.30; p = 0.01). END in minor stroke patients accounts for 10.5% and is a risk factor for poor neurological outcomes. Admission NIHSS score, higher systolic blood pressure, admission blood glucose, reperfusion therapy, use of antiplatelet monotherapy, internal capsule infarction, hemorrhagic transformation, corresponding extracranial carotid artery occlusion, and middle cerebral artery occlusion were some of the prognostic factors for END in our observational study.

Mapping of validated apathy scales onto the apathy diagnostic criteria for neurocognitive disorders.

BACKGROUND: Diagnostic criteria for apathy in neurocognitive disorders (DCA-NCD) have recently been updated. OBJECTIVES: We investigated whether validated scales measuring apathy severity capture the three dimensions of the DCA-NCD (diminished initiative, diminished interest, diminished emotional expression). MEASUREMENTS: Degree of mapping ("not at all", "weakly", or "strongly") between items on two commonly used apathy scales, the Neuropsychiatric Inventory-Clinician (NPI-C) apathy and Apathy Evaluation Scale (AES), with the DCA-NCD overall and its 3 dimensions was evaluated by survey. DESIGN: Survey participants, either experts (n = 12, DCA-NCD authors) or scientific community members (n = 19), rated mapping for each item and mean scores were calculated. Interrater reliability between expert and scientific community members was assessed using Cohen's kappa. RESULTS: According to experts, 9 of 11 (81.8%) NPI-C apathy items and 6 of 18 (33.3%) AES items mapped strongly onto the DCA-NCD overall. For the scientific community group, 10 of 11 (90.9%) NPI-C apathy items and 7 of 18 (38.8%) AES items mapped strongly onto the DCA-NCD overall. The overall mean mapping scores were higher for the NPI-C apathy compared to the AES for both expert (t (11) = 3.13, p = .01) and scientific community (t (17) = 3.77, p = .002) groups. There was moderate agreement between the two groups on overall mapping for the NPI-C apathy (kappa= 0.74 (0.57, 1.00)) and AES (kappa= 0.63 (0.35, 1.00)). CONCLUSIONS: More NPI-C apathy than AES items mapped strongly and uniquely onto the DCA-NCD and its dimensions. The NPI-C apathy may better capture the DCA-NCD and its dimensions compared with the AES.

TRANSLATING 5-HT4R AGONISM INTO MENTAL ILLNESS: POTENTIAL CLINICAL APPLICATIONS FOR MOOD DISORDER AND COGNITIVE IMPAIRMENT

ZFP36-family RNA-binding proteins in regulatory T cells reinforce immune homeostasis

RNA binding proteins (RBP) of the ZFP36 family limit the differentiation and effector functions of CD4 and CD8 T cells, but little is known of their expression or function in regulatory T (Treg) cells. By using Treg cell-restricted deletion of Zfp36 family members we identify the role of Zfp36l1 and Zfp36l2 in Treg cells to maintain immune homeostasis. Mice with Treg cells deficient in these RBP display an inflammatory phenotype with an expansion in the numbers of type-2 conventional dendritic cells, T effector cells, T follicular helper and germinal center B cells and elevated serum cytokines and immunoglobulins. In the absence of Zfp36l1 and Zfp36l2, the pool of cycling CTLA-4 in naïve Treg cells is reduced, Treg cells are less sensitive to IL-2 and IL-7 but are more sensitive to IFNγ. In mice lacking both RBP in Treg cells, the deletion of a single allele of Ifng is sufficient to ameliorate the pathology. Our results indicate that ZFP36L1 and ZFP36L2 regulate the availability of IFNγ and are required for the maintenance of Treg cell stability. Thus, ZFP36L1 and ZFP36L2 regulate multiple pathways that enable Treg cells to enforce immune homeostasis.

Low-Rank Conjugate Gradient-Net for Accelerated Cardiac MR Imaging

Cardiovascular diseases (CVDs) remain the leading cause of mortality and morbidity worldwide. Both diagnosis and prognosis of these diseases benefit from high-quality imaging, which cardiac magnetic resonance imaging provides. CMR imaging requires lengthy acquisition times and multiple breath-holds for a complete exam, which can lead to patient discomfort and frequently results in image artifacts. In this work, we present a Low-rank tensor U-Net method (LowRank-CGNet) that rapidly reconstructs highly undersampled data with a variety of anatomy, contrast, and undersampling artifacts. The model uses conjugate gradient data consistency to solve for the spatial and temporal bases and employs a U-Net to further regularize the basis vectors. Currently, model performance is superior to a standard U-Net, but inferior to conventional compressed sensing methods. In the future, we aim to further improve model performance by increasing the U-Net size, extending the training duration, and dynamically updating the tensor rank for different anatomies.

Combined Angiographic, Structural and Perfusion Radial Imaging using Arterial Spin Labeling

Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD): An RCT of Memory Bias Modification Training vs. Cognitive Control Training vs. Attention Bias Modification Training in remitted recurrently depressed patients with 1.5 year follow-up.

BACKGROUND: Major Depressive Disorder (MDD) has a 50-80% recurrence rate highlighting the urgent need for more efficient recurrence prevention programs. Currently, recurrences are often identified too late, while existing preventive strategies may not sufficiently address ethio-patho-physiological mechanisms for recurrence. Negative memory bias (the tendency to better remember negative than positive events), negative attention bias (selective attention favoring mood-congruent information), and cognitive control deficits are important factors involved in the onset, maintenance, and recurrence of depressive episodes. METHODS: Here we describe the protocol for the Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD) study, aiming to investigate different forms of cognitive training programs administered via smartphones, in order to develop a second-generation recurrence prevention program. In addition, we will gather Experience Sampling Method (ESM) assessments during a 6-day period, and during the follow-up period we will obtain behavioral data on (social) activities with BEHAPP, a smartphone-based Mobile Passive Monitoring application for remote behavioral monitoring to identify behavioral changes indicative of an imminent depressive episode. In a randomized controlled trial, SMARD will compare the effects of a smartphone-based Memory Bias Modification Training (MBT), Cognitive Control Training (CCT), and Attention Bias Modification Training (ABT) versus cognitive domain-specific (active-) sham trainings in 120 remitted MDD-patients with recurrent-MDD. Over the course of three weeks, participants receive multiple daily training sessions. Thereafter, participants will be followed up for 1.5 years with 3-monthly interviews to assess recurrences. DISCUSSION: The SMARD study aims to 1. assess the effects of the cognitive training programs versus their training-specific (active-) sham conditions on changes in memory, cognitive control dysfunction and attention; 2. relate training effects to neural networks previously identified in (recurrence of) MDD (therefore we obtain functional Magnetic Resonance Imaging ((f)MRI) scans before and after the training in a subset of participants); 3. link baseline and change in memory, cognitive control, attention and neural functioning, and ESM data to prospective recurrences; 4. examine whether passive smartphone-use monitoring can be used for prediction of recurrences. TRIAL REGISTRATION: NL-OMON26184 and NL-OMON27513. Registered 12 August 2021-Retrospectively registered,  https://onderzoekmetmensen.nl/en/trial/26184 en https://onderzoekmetmensen.nl/en/trial/27513 .

Vascular health has an impact on brain health

Responses to ‘On the responsibilities of intellectuals and the rise of bullshit jobs in universities’

Cholinergic degeneration in prodromal and early Parkinson's: a link to present and future disease states.

The neuropathological process in Parkinson's disease (PD) and Lewy body disorders has been shown to extend well beyond the degeneration of the dopaminergic system, affecting other neuromodulatory systems in the brain which play crucial roles in the clinical expression and progression of these disorders. Here, we investigate the role of the macrostructural integrity of the nucleus basalis of Meynert (NbM), the main source of cholinergic input to the cerebral cortex, in cognitive function, clinical manifestation, and disease progression in non-demented subjects with PD and individuals with isolated REM sleep behaviour disorder (iRBD). Using structural MRI data from 393 early PD patients, 128 iRBD patients, and 186 controls from two longitudinal cohorts, we found significantly lower NbM grey matter volume in both PD (β=-12.56, p=0.003) and iRBD (β=-16.41, p=0.004) compared to controls. In PD, higher NbM volume was associated with better higher-order cognitive function (β=0.10, p=0.045), decreased non-motor (β=-0.66, p=0.026) and motor (β=-1.44, p=0.023) symptom burden, and lower risk of future conversion to dementia (Hazard ratio (HR)<0.400, p<0.004). Higher NbM volume in iRBD was associated with decreased future risk of phenoconversion to PD or dementia with Lewy bodies (DLB) (HR<0.490, p<0.016). However, despite similar NbM volume deficits to those seen in PD, associations between NbM structural deficits and current disease burden or clinical state were less pronounced in iRBD. These findings identify NbM volume as a potential biomarker with dual utility: predicting cognitive decline and disease progression in early PD, while also serving as an early indicator of phenoconversion risk in prodromal disease. The presence of structural deficits before clear clinical correlates in iRBD suggests complex compensatory mechanisms may initially mask cholinergic dysfunction, with subsequent failure of these mechanisms potentially contributing to clinical conversion.

The Effects of Facilitation and Inhibition During Multimodal Somatosensory Integration

The somatosensory system, including modalities such as touch, temperature, and pain, is essential for perceiving and interacting with the environment. When individuals encounter different somatosensory modalities, they interact through a process called multimodal somatosensory integration. This integration is essential for accurate perception, motor coordination, pain management, and adaptive behavior. Disruptions in this process can lead to a variety of sensory disorders and complicate rehabilitation efforts. However, research on the behavioral patterns and neural mechanisms underlying multimodal somatosensory integration remains limited. According to previous studies, multimodal somatosensory integration can result in facilitative or inhibitory effects depending on factors like stimulus type, intensity, and spatial proximity. Facilitative effects are observed primarily when stimuli from the same sensory modality (e. g., two touch or temperature stimuli) are presented simultaneously, leading to amplified perceptual strength and quicker reaction times. Additionally, certain external factors, such as cooling, can increase sensitivity to other sensory inputs, further promoting facilitative integration. In contrast, inhibitory effects may also emerge when stimuli from different sensory modalities interact, particularly between touch and pain. Under such conditions, one sensory input (e.g., vibration or non-noxious temperature stimulation) can effectively reduce the perceived intensity of the other, often resulting in reduced pain perception. These facilitative and inhibitory interactions are critical for efficient processing in a multi-stimulus environment and play a role in modulating the experience of somatosensory inputs in both normal and clinical contexts. The neural mechanisms underlying multimodal somatosensory integration are multi-tiered, encompassing peripheral receptors, the spinal cord, and various cortical structures. Facilitative integration relies on the synchronous activation of peripheral receptors, which transmit enhanced signals to higher processing centers. At the cortical level, areas such as the primary and secondary somatosensory cortex, through multimodal neuron responses, facilitate combined representation and amplification of sensory signals. In particular, the thalamus is a significant relay station where multisensory neurons exhibit superadditive responses, contributing to facilitation by enhancing signal strength when multiple inputs are present. Inhibitory integration, on the other hand, is mediated by mechanisms within the spinal cord, such as gating processes that limit transmission of competing sensory signals, thus diminishing the perceived intensity of certain inputs. At the cortical level, lateral inhibition within the somatosensory cortex plays a key role in reducing competing signals from non-target stimuli, enabling prioritized processing of the most relevant sensory input. This layered neural architecture supports the dynamic modulation of sensory inputs, balancing facilitation and inhibition to optimize perception. Understanding the neural pathways involved in somatosensory integration has potential clinical implications for diagnosing sensory disorders and developing therapeutic strategies. Future research should focus on elucidating the specific neural circuitry and mechanisms that contribute to these complex interactions, providing insights into the broader implications of somatosensory integration on behavior and cognition. In summary, this review highlights the importance of multimodal somatosensory integration in enhancing sensory perception. It also underscores the need for further exploration into the neural underpinnings of these processes to advance our understanding of sensory integration and its applications in clinical settings.

Exploration of brain-spinal cord-gut axis abnormalities and the mechanism of acupuncture therapy in irritable bowel syndrome based on magnetic resonance imaging

Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder triggered by the disorder of brain-gut interaction and characterized by abdominal pain, bloating, and altered bowel habits. It is estimated to affect between 5% and 10% of the global population. Although IBS does not have an excessive mortality rate, the disease significantly affects the quality of life and can lead to significant disability. Current treatments mainly focus on relieving abdominal pain and improving bowel habits. However, the effect of drug therapy on the overall symptoms of patients is limited, and the majority of therapeutic drugs are associated with the risk of adverse reactions. Consequently, many patients turn to complementary and alternative therapies to achieve more favorable treatment outcomes. Acupuncture, as a complementary and alternative therapy, has shown potential in the treatment of IBS. Although clinical trials have confirmed the therapeutic effect of acupuncture, its mechanism of action remains unclear, leading to controversy in the global medical community. Researchers, leveraging magnetic resonance imaging (MRI) technology, strive to delve deeply into the biological mechanisms underlying the alleviation of irritable bowel syndrome symptoms through acupuncture therapy, aiming to provide solid support for the scientific basis and efficacy of this treatment method. However, current imaging research primarily focuses on changes in brain structure and function, relatively neglecting the close connection between spinal structure and function and IBS. The spinal cord plays a crucial role in brain-gut interaction, and the development of MRI technology provides a new perspective for exploring the pathogenesis of IBS and the mechanism of acupuncture based on the brain-spinal cord-gut axis. This paper reviews MRI-based studies on abnormalities in brain-spinal cord-gut axis interaction in IBS and acupuncture treatment. Although there have been significant advancements in understanding the causes and using acupuncture to treat IBS, there are still several limitations that need to be addressed. One limitation is the insufficient number of imaging studies on the spinal cord, which hinders our comprehensive understanding of the development of IBS and the underlying mechanisms of acupuncture therapy. In the future, it is necessary to enhance the imaging study of the spinal cord and conduct a thorough analysis of the brain-spinal cord-gut axis mechanism. This will enable us to establish a scientific foundation for understanding the pathogenesis of IBS and the effectiveness of acupuncture treatment. Furthermore, the current research on the impact of acupuncture on IBS primarily concentrates on describing the phenomenon and comparing data but fails to incorporate the principles of neuroscience pain theory. In the future, it is important to prioritize the integration of pain theory and thoroughly investigate the impact of acupuncture on the primary pathways of pain transmission and processing. This will help us understand the intricate mechanism of acupuncture analgesia and facilitate the broader application of acupuncture therapy.

AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Feature Space-Guided Inversion

Deep learning models have demonstrated exceptional performance in a variety of real-world applications. These successes are often attributed to strong base models that can generalize to novel tasks with limited supporting data while keeping prior knowledge intact. However, these impressive results are based on the availability of a large amount of high-quality data, which is often lacking in specialized biomedical applications. In such fields, models are usually developed with limited data that arrive incrementally with novel categories. This requires the model to adapt to new information while preserving existing knowledge. Few-Shot Class-Incremental Learning (FSCIL) methods offer a promising approach to addressing these challenges, but they also depend on strong base models that face the same aforementioned limitations. To overcome these constraints, we propose AnchorInv following the straightforward and efficient buffer-replay strategy. Instead of selecting and storing raw data, AnchorInv generates synthetic samples guided by anchor points in the feature space. This approach protects privacy and regularizes the model for adaptation. When evaluated on three public physiological time series datasets, AnchorInv exhibits efficient knowledge forgetting prevention and improved adaptation to novel classes, surpassing state-of-the-art baselines.

Automated quality control of T1-weighted brain MRI scans for clinical research datasets: methods comparison and design of a quality prediction classifier

Abstract T1-weighted (T1w) MRI is widely used in clinical neuroimaging for studying brain structure and its changes, including those related to neurodegenerative diseases, and as anatomical reference for analysing other modalities. Ensuring high-quality T1w scans is vital as image quality affects reliability of outcome measures. However, visual inspection can be subjective and time-consuming, especially with large datasets. The effectiveness of automated quality control (QC) tools for clinical cohorts remains uncertain. In this study, we used T1w scans from elderly participants within ageing and clinical populations to test the accuracy of existing QC tools with respect to visual QC and to establish a new quality prediction framework for clinical research use. Four datasets acquired from multiple scanners and sites were used (N = 2438, 11 sites, 39 scanner manufacturer models, 3 field strengths – 1.5T, 3T, 2.9T, patients and controls, average age 71 ± 8 years). All structural T1w scans were processed with two standard automated QC pipelines (MRIQC and CAT12). The agreement of the accept-reject ratings was compared between the automated pipelines and with visual QC. We then designed a quality prediction framework that combines the QC measures from the existing automated tools and is trained on clinical research datasets. We tested the classifier performance using cross-validation on data from all sites together, also examining the performance across diagnostic groups. We then tested the generalisability of our approach when leaving one site out and explored how well our approach generalises to data from a different scanner manufacturer and/or field strength from those used for training, as well as on an unseen new dataset of healthy young participants with movement related artefacts. Our results show significant agreement between automated QC tools and visual QC (Kappa=0.30 with MRIQC predictions; Kappa=0.28 with CAT12’s rating) when considering the entire dataset, but the agreement was highly variable across datasets. Our proposed robust undersampling boost (RUS) classifier achieved 87.7% balanced accuracy on the test data combined from different sites (with 86.6% and 88.3% balanced accuracy on scans from patients and controls respectively). This classifier was also found to be generalisable on different combinations of training and test datasets (average balanced accuracy of leave-one-site-out = 78.2%; exploratory models on field strengths and manufacturers = 77.7%; movement related artefact dataset when including 1% scans in the training = 88.5%). While existing QC tools may not be robustly applicable to datasets comprised of older adults, they produce quality metrics that can be leveraged to train a more robust quality control classifiers for ageing and clinical cohorts.

Working memory filtering at encoding and maintenance in healthy ageing, Alzheimer's and Parkinson's disease.

The differential impact on working memory (WM) performance of distractors presented at encoding or during maintenance was investigated in Alzheimer's Disease (AD), Parkinson's Disease (PD) patients, elderly (EHC) and young healthy controls (YHC), (n = 28 per group). Participants reported the orientation of an arrow from a set of either two or three items, with a distractor present either at encoding or at maintenance. MRI data with hippocampal volumes was also acquired. Mean absolute error and mixture model metrics i.e., memory precision, target detection, misbinding (swapping the features of an object with another probed item) and guessing were computed. EHC and PD patients showed good filtering abilities both at encoding and maintenance. However, AD patients exhibited significant filtering deficits specifically when the distractor appeared during maintenance. In healthy ageing there was a prominent decline in WM memory precision, whilst in AD lower target detection and higher guessing were the main sources of error. Conversely, PD was associated only with higher guessing rates. Hippocampal volume was significantly correlated with filtering during maintenance - but not at encoding. These findings demonstrate how healthy ageing and neurodegenerative diseases exhibit distinct patterns of WM impairment, including when filtering irrelevant material either at encoding and maintenance.