Neural mechanisms of psychedelic visual imagery.

Visual alterations under classic psychedelics can include rich phenomenological accounts of eyes-closed imagery. Preclinical evidence suggests agonism of the 5-HT2A receptor may reduce synaptic gain to produce psychedelic-induced imagery. However, this has not been investigated in humans. To infer the directed connectivity changes to visual connectivity underlying psychedelic visual imagery in healthy adults, a double-blind, randomised, placebo-controlled, cross-over study was performed, and dynamic causal modelling was applied to the resting state eyes-closed functional MRI scans of 24 subjects after administration of 0.2 mg/kg of the serotonergic psychedelic drug, psilocybin (magic mushrooms), or placebo. The effective connectivity model included the early visual area, fusiform gyrus, intraparietal sulcus, and inferior frontal gyrus. We observed a pattern of increased self-inhibition of both early visual and higher visual-association regions under psilocybin that was consistent with preclinical findings. We also observed a pattern of reduced inhibition from visual-association regions to earlier visual areas that indicated top-down connectivity is enhanced during visual imagery. The results were analysed with behavioural measures taken immediately after the scans, suggesting psilocybin-induced decreased sensitivity to neural inputs is associated with the perception of eyes-closed visual imagery. The findings inform our basic and clinical understanding of visual perception. They reveal neural mechanisms that, by affecting balance, may increase the impact of top-down feedback connectivity on perception, which could contribute to the visual imagery seen with eyes-closed during psychedelic experiences.

The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance.

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of age and insulin resistance to the association of cerebral blood flow and glucose metabolism; both critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Lower cerebral blood flow was also associated with worse working memory and slower reaction time in tasks requiring cognitive flexibility and response inhibition. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive correlation. In insulin resistant younger adults, the association showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates of and associations between cerebral blood flow and glucose metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

Localized Changes in Dentate Nucleus Shape and Magnetic Susceptibility in Friedreich Ataxia.

BACKGROUND: The dentate nuclei of the cerebellum are key sites of neuropathology in Friedreich ataxia (FRDA). Reduced dentate nucleus volume and increased mean magnetic susceptibility, a proxy of iron concentration, have been reported by magnetic resonance imaging studies in people with FRDA. Here, we investigate whether these changes are regionally heterogeneous. METHODS: Quantitative susceptibility mapping data were acquired from 49 people with FRDA and 46 healthy controls. The dentate nuclei were manually segmented and analyzed using three dimensional vertex-based shape modeling and voxel-based assessments to identify regional changes in morphometry and susceptibility, respectively. RESULTS: Individuals with FRDA, relative to healthy controls, showed significant bilateral surface contraction most strongly at the rostral and caudal boundaries of the dentate nuclei. The magnitude of this surface contraction correlated with disease duration, and to a lesser extent, ataxia severity. Significantly greater susceptibility was also evident in the FRDA cohort relative to controls, but was instead localized to bilateral dorsomedial areas, and also correlated with disease duration and ataxia severity. CONCLUSIONS: Changes in the structure of the dentate nuclei in FRDA are not spatially uniform. Atrophy is greatest in areas with high gray matter density, whereas increases in susceptibility-reflecting iron concentration, demyelination, and/or gliosis-predominate in the medial white matter. These findings converge with established histological reports and indicate that regional measures of dentate nucleus substructure are more sensitive measures of disease expression than full-structure averages. Biomarker development and therapeutic strategies that directly target the dentate nuclei, such as gene therapies, may be optimized by targeting these areas of maximal pathology. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

Neural Mechanisms of Resting-State Networks and the Amygdala Underlying the Cognitive and Emotional Effects of Psilocybin.

BACKGROUND: Serotonergic psychedelics, such as psilocybin, alter perceptual and cognitive systems that are functionally integrated with the amygdala. These changes can alter cognition and emotions that are hypothesized to contribute to their therapeutic utility. However, the neural mechanisms of cognitive and subcortical systems altered by psychedelics are not well understood. METHODS: We used resting-state functional magnetic resonance images collected during a randomized, double-blind, placebo-controlled clinical trial of 24 healthy adults under 0.2 mg/kg psilocybin to estimate the directed (i.e., effective) changes between the amygdala and 3 large-scale resting-state networks involved in cognition. These networks are the default mode network, the salience network, and the central executive network. RESULTS: We found a pattern of decreased top-down effective connectivity from these resting-state networks to the amygdala. Effective connectivity decreased within the default mode network and salience network but increased within the central executive network. These changes in effective connectivity were statistically associated with behavioral measures of altered cognition and emotion under the influence of psilocybin. CONCLUSIONS: Our findings suggest that temporary amygdala signal attenuation is associated with mechanistic changes to resting-state network connectivity. These changes are significant for altered cognition and perception and suggest targets for research investigating the efficacy of psychedelic therapy for internalizing psychiatric disorders. More broadly, our study suggests the value of quantifying the brain's hierarchical organization using effective connectivity to identify important mechanisms for basic cognitive function and how they are integrated to give rise to subjective experiences.

Free-Water Imaging in Friedreich Ataxia Using Multi-Compartment Models.

BACKGROUND: The neurological phenotype of Friedreich ataxia (FRDA) is characterized by neurodegeneration and neuroinflammation in the cerebellum and brainstem. Novel neuroimaging approaches quantifying brain free-water using diffusion magnetic resonance imaging (dMRI) are potentially more sensitive to these processes than standard imaging markers. OBJECTIVES: To quantify the extent of free-water and microstructural change in FRDA-relevant brain regions using neurite orientation dispersion and density imaging (NODDI), and bitensor diffusion tensor imaging (btDTI). METHOD: Multi-shell dMRI was acquired from 14 individuals with FRDA and 14 controls. Free-water measures from NODDI (FISO) and btDTI (FW) were compared between groups in the cerebellar cortex, dentate nuclei, cerebellar peduncles, and brainstem. The relative sensitivity of the free-water measures to group differences was compared to microstructural measures of NODDI intracellular volume, free-water corrected fractional anisotropy, and conventional uncorrected fractional anisotropy. RESULTS: In individuals with FRDA, FW was elevated in the cerebellar cortex, peduncles (excluding middle), dentate, and brainstem (P < 0.005). FISO was elevated primarily in the cerebellar lobules (P < 0.001). On average, FW effect sizes were larger than all other markers (mean ηρ 2 = 0.43), although microstructural measures also had very large effects in the superior and inferior cerebellar peduncles and brainstem (ηρ 2 > 0.37). Across all regions and metrics, effect sizes were largest in the superior cerebellar peduncles (ηρ 2 > 0.46). CONCLUSIONS: Multi-compartment diffusion measures of free-water and neurite integrity distinguish FRDA from controls with large effects. Free-water magnitude in the brainstem and cerebellum provided the greatest distinction between groups. This study supports further applications of multi-compartment diffusion modeling, and investigations of free-water as a measure of disease expression and progression in FRDA. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Improving portable low-field MRI image quality through image-to-image translation using paired low- and high-field images.

Low-field portable magnetic resonance imaging (MRI) scanners are more accessible, cost-effective, sustainable with lower carbon emissions than superconducting high-field MRI scanners. However, the images produced have relatively poor image quality, lower signal-to-noise ratio, and limited spatial resolution. This study develops and investigates an image-to-image translation deep learning model, LoHiResGAN, to enhance the quality of low-field (64mT) MRI scans and generate synthetic high-field (3T) MRI scans. We employed a paired dataset comprising T1- and T2-weighted MRI sequences from the 64mT and 3T and compared the performance of the LoHiResGAN model with other state-of-the-art models, including GANs, CycleGAN, U-Net, and cGAN. Our proposed method demonstrates superior performance in terms of image quality metrics, such as normalized root-mean-squared error, structural similarity index measure, peak signal-to-noise ratio, and perception-based image quality evaluator. Additionally, we evaluated the accuracy of brain morphometry measurements for 33 brain regions across the original 3T, 64mT, and synthetic 3T images. The results indicate that the synthetic 3T images created using our proposed LoHiResGAN model significantly improve the image quality of low-field MRI data compared to other methods (GANs, CycleGAN, U-Net, cGAN) and provide more consistent brain morphometry measurements across various brain regions in reference to 3T. Synthetic images generated by our method demonstrated high quality both quantitatively and qualitatively. However, additional research, involving diverse datasets and clinical validation, is necessary to fully understand its applicability for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.

The shape of things to come. Mapping spatiotemporal progression of striatal morphology in Huntington disease: The IMAGE-HD study.

Mapping the spatiotemporal progression of neuroanatomical change in Huntington's Disease (HD) is fundamental to the development of bio-measures for prognostication. Statistical shape analysis to measure the striatum has been performed in HD, however there have been a limited number of longitudinal studies. To address these limitations, we utilised the Spherical Harmonic Point Distribution Method (SPHARM-PDM) to generate point distribution models of the striatum in individuals, and used linear mixed models to test for localised shape change over time in pre-manifest HD (pre-HD), symp-HD (symp-HD) and control individuals. Longitudinal MRI scans from the IMAGE-HD study were used (baseline, 18 and 30 months). We found significant differences in the shape of the striatum between groups. Significant group-by-time interaction was observed for the putamen bilaterally, but not for caudate. A differential rate of shape change between groups over time was observed, with more significant deflation in the symp-HD group in comparison with the pre-HD and control groups. CAG repeats were correlated with bilateral striatal shape in pre-HD and symp-HD. Robust statistical analysis of the correlates of striatal shape change in HD has confirmed the suitability of striatal morphology as a potential biomarker correlated with CAG-repeat length, and potentially, an endophenotype.

Hippocampal morphology in Huntington's disease, implications for plasticity and pathogenesis: The IMAGE-HD study.

While striatal changes in Huntington's Disease (HD) are well established, few studies have investigated changes in the hippocampus, a key neuronal hub. Using MRI scans obtained from the IMAGE-HD study, hippocampi were manually traced and then analysed with the Spherical Harmonic Point Distribution Method (SPHARM-PDM) in 36 individuals with presymptomatic-HD, 37 with early symptomatic-HD, and 36 healthy matched controls. There were no significant differences in overall hippocampal volume between groups. Interestingly we found decreased bilateral hippocampal volume in people with symptomatic-HD who took selective serotonin reuptake inhibitors compared to those who did not, despite no significant differences in anxiety, depressive symptoms, or motor incapacity between the two groups. In symptomatic-HD, there was also significant shape deflation in the right hippocampal head, showing the utility of using manual tracing and SPHARM-PDM to characterise subtle shape changes which may be missed by other methods. This study confirms previous findings of the lack of hippocampal volumetric differentiation in presymptomatic-HD and symptomatic-HD compared to controls. We also find novel shape and volume findings in those with symptomatic-HD, especially in relation to decreased hippocampal volume in those treated with SSRIs.

Reduced cerebello-cerebral functional connectivity correlates with disease severity and impaired white matter integrity in Friedreich ataxia.

Friedreich ataxia (FRDA) is a rare, inherited neurodegenerative disease characterised in most cases by progressive and debilitating motor dysfunction. Degeneration of cerebellar white matter pathways have been previously reported, alongside indications of cerebello-cerebral functional alterations. In this work, we examine resting-state functional connectivity changes within cerebello-cerebral circuits, and their associations with disease severity (Scale for the Assessment and Rating of Ataxia [SARA]), psychomotor function (speeded and paced finger tapping), and white matter integrity (diffusion tensor imaging) in 35 adults with FRDA and 45 age and sex-matched controls. Voxel-wise seed-based functional connectivity was assessed for three cerebellar cortical regions (anterior lobe, lobules I-V; superior posterior lobe, lobules VI-VIIB; inferior posterior lobe, lobules VIIIA-IX) and two dentate nucleus seeds (dorsal and ventral). Compared to controls, people with FRDA showed significantly reduced connectivity between the anterior cerebellum and bilateral pre/postcentral gyri, and between the superior posterior cerebellum and left dorsolateral PFC. Greater disease severity correlated with lower connectivity in these circuits. Lower anterior cerebellum-motor cortex functional connectivity also correlated with slower speeded finger tapping and less fractional anisotropy in the superior cerebellar peduncles, internal capsule, and precentral white matter in the FRDA cohort. There were no significant between-group differences in inferior posterior cerebellar or dentate nucleus connectivity. This study indicates that altered cerebello-cerebral functional connectivity is associated with functional status and white matter damage in cerebellar efferent pathways in people with FRDA, particularly in motor circuits.

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging.

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

The maternal brain is more flexible and responsive at rest: effective connectivity of the parental caregiving network in postpartum mothers.

The field of neuroscience has largely overlooked the impact of motherhood on brain function outside the context of responses to infant stimuli. Here, we apply spectral dynamic causal modelling (spDCM) to resting-state fMRI data to investigate differences in brain function between a group of 40 first-time mothers at 1-year postpartum and 39 age- and education-matched women who have never been pregnant. Using spDCM, we investigate the directionality (top-down vs. bottom-up) and valence (inhibition vs excitation) of functional connections between six key left hemisphere brain regions implicated in motherhood: the dorsomedial prefrontal cortex, ventromedial prefrontal cortex, posterior cingulate cortex, parahippocampal gyrus, amygdala, and nucleus accumbens. We show a selective modulation of inhibitory pathways related to differences between (1) mothers and non-mothers, (2) the interactions between group and cognitive performance and (3) group and social cognition, and (4) differences related to maternal caregiving behaviour. Across analyses, we show consistent disinhibition between cognitive and affective regions suggesting more efficient, flexible, and responsive behaviour, subserving cognitive performance, social cognition, and maternal caregiving. Together our results support the interpretation of these key regions as constituting a parental caregiving network. The nucleus accumbens and the parahippocampal gyrus emerging as 'hub' regions of this network, highlighting the global importance of the affective limbic network for maternal caregiving, social cognition, and cognitive performance in the postpartum period.

Metabolic and functional connectivity provide unique and complementary insights into cognition-connectome relationships.

A major challenge in current cognitive neuroscience is how functional brain connectivity gives rise to human cognition. Functional magnetic resonance imaging (fMRI) describes brain connectivity based on cerebral oxygenation dynamics (hemodynamic connectivity), whereas [18F]-fluorodeoxyglucose functional positron emission tomography (FDG-fPET) describes brain connectivity based on cerebral glucose uptake (metabolic connectivity), each providing a unique characterization of the human brain. How these 2 modalities differ in their contribution to cognition and behavior is unclear. We used simultaneous resting-state FDG-fPET/fMRI to investigate how hemodynamic connectivity and metabolic connectivity relate to cognitive function by applying partial least squares analyses. Results revealed that although for both modalities the frontoparietal anatomical subdivisions related the strongest to cognition, using hemodynamic measures this network expressed executive functioning, episodic memory, and depression, whereas for metabolic measures this network exclusively expressed executive functioning. These findings demonstrate the unique advantages that simultaneous FDG-PET/fMRI has to provide a comprehensive understanding of the neural mechanisms that underpin cognition and highlights the importance of multimodality imaging in cognitive neuroscience research.

Progressive Spinal Cord Degeneration in Friedreich's Ataxia: Results from ENIGMA-Ataxia.

BACKGROUND: Spinal cord damage is a hallmark of Friedreich's ataxia (FRDA), but its progression and clinical correlates remain unclear. OBJECTIVE: The objective of this study was to perform a characterization of cervical spinal cord structural damage in a large multisite FRDA cohort. METHODS: We performed a cross-sectional analysis of cervical spinal cord (C1-C4) cross-sectional area (CSA) and eccentricity using magnetic resonance imaging data from eight sites within the ENIGMA-Ataxia initiative, including 256 individuals with FRDA and 223 age- and sex-matched control subjects. Correlations and subgroup analyses within the FRDA cohort were undertaken based on disease duration, ataxia severity, and onset age. RESULTS: Individuals with FRDA, relative to control subjects, had significantly reduced CSA at all examined levels, with large effect sizes (d > 2.1) and significant correlations with disease severity (r < -0.4). Similarly, we found significantly increased eccentricity (d > 1.2), but without significant clinical correlations. Subgroup analyses showed that CSA and eccentricity are abnormal at all disease stages. However, although CSA appears to decrease progressively, eccentricity remains stable over time. CONCLUSIONS: Previous research has shown that increased eccentricity reflects dorsal column (DC) damage, while decreased CSA reflects either DC or corticospinal tract (CST) damage, or both. Hence our data support the hypothesis that damage to the DC and damage to CST follow distinct courses in FRDA: developmental abnormalities likely define the DC, while CST alterations may be both developmental and degenerative. These results provide new insights about FRDA pathogenesis and indicate that CSA of the cervical spinal cord should be investigated further as a potential biomarker of disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging-State-of-the-Art and Challenges.

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical diagnoses and research which underpin many recent breakthroughs in medicine and biology. The post-processing of reconstructed MR images is often automated for incorporation into MRI scanners by the manufacturers and increasingly plays a critical role in the final image quality for clinical reporting and interpretation. For image enhancement and correction, the post-processing steps include noise reduction, image artefact correction, and image resolution improvements. With the recent success of deep learning in many research fields, there is great potential to apply deep learning for MR image enhancement, and recent publications have demonstrated promising results. Motivated by the rapidly growing literature in this area, in this review paper, we provide a comprehensive overview of deep learning-based methods for post-processing MR images to enhance image quality and correct image artefacts. We aim to provide researchers in MRI or other research fields, including computer vision and image processing, a literature survey of deep learning approaches for MR image enhancement. We discuss the current limitations of the application of artificial intelligence in MRI and highlight possible directions for future developments. In the era of deep learning, we highlight the importance of a critical appraisal of the explanatory information provided and the generalizability of deep learning algorithms in medical imaging.

Lower brain glucose metabolism in normal ageing is predominantly frontal and temporal: A systematic review and pooled effect size and activation likelihood estimates meta-analyses.

This review provides a qualitative and quantitative analysis of cerebral glucose metabolism in ageing. We undertook a systematic literature review followed by pooled effect size and activation likelihood estimates (ALE) meta-analyses. Studies were retrieved from PubMed following the PRISMA guidelines. After reviewing 635 records, 21 studies with 22 independent samples (n = 911 participants) were included in the pooled effect size analyses. Eight studies with eleven separate samples (n = 713 participants) were included in the ALE analyses. Pooled effect sizes showed significantly lower cerebral metabolic rates of glucose for older versus younger adults for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes. Among the sub-cortical structures, the caudate showed a lower metabolic rate among older adults. In sub-group analyses controlling for changes in brain volume or partial volume effects, the lower glucose metabolism among older adults in the frontal lobe remained significant, whereas confidence intervals crossed zero for the other lobes and structures. The ALE identified nine clusters of lower glucose metabolism among older adults, ranging from 200 to 2640 mm3 . The two largest clusters were in the left and right inferior frontal and superior temporal gyri and the insula. Clusters were also found in the inferior temporal junction, the anterior cingulate and caudate. Taken together, the results are consistent with research showing less efficient glucose metabolism in the ageing brain. The findings are discussed in the context of theories of cognitive ageing and are compared to those found in neurodegenerative disease.

Effective Connectivity of Functionally Anticorrelated Networks Under Lysergic Acid Diethylamide.

BACKGROUND: Classic psychedelic-induced ego dissolution involves a shift in the sense of self and a blurring of the boundary between the self and the world. A similar phenomenon is identified in psychopathology and is associated with the balance of anticorrelated activity between the default mode network, which directs attention inward, and the salience network, which recruits the dorsal attention network to direct attention outward. METHODS: To test whether changes in anticorrelated networks underlie the peak effects of lysergic acid diethylamide (LSD), we applied dynamic causal modeling to infer effective connectivity of resting-state functional magnetic resonance imaging scans from a study of 25 healthy adults who were administered 100 µg of LSD or placebo. RESULTS: We found that inhibitory effective connectivity from the salience network to the default mode network became excitatory, and inhibitory effective connectivity from the default mode network to the dorsal attention network decreased under the peak effect of LSD. CONCLUSIONS: The effective connectivity changes we identified may reflect diminution of the functional anticorrelation between resting-state networks that may be a key neural mechanism of LSD and underlie ego dissolution. Our findings suggest that changes to the sense of self and subject-object boundaries across different states of consciousness may depend upon the organized balance of effective connectivity of resting-state networks.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging.

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

Early predictors of visual and axonal outcomes after acute optic neuritis.

Background: Predicting long-term visual outcomes and axonal loss following acute optic neuritis (ON) is critical for choosing treatment. Predictive models including all clinical and paraclinical measures of optic nerve dysfunction following ON are lacking. Objectives: Using a prospective study method, to identify 1 and 3 months predictors of 6 and 12 months visual outcome (low contrast letter acuity 2.5%) and axonal loss [retinal nerve fiber layer thickness and multifocal evoked potential (mfVEP) amplitude] following acute ON. Methods: In total, 37 patients of acute ON onset were evaluated within 14 days using between-eye asymmetry of visual acuity, color vision (Ishihara plates), optical coherence tomography, mfVEP, and optic nerve magnetic resonance imaging [magnetic transfer ratio (MTR) and diffusion tensor imaging (DTI)]. Results: Visual outcome at 6 and 12 months was best predicted by Ishihara asymmetry at 1 and 3 months following ON onset. Axonal loss at 6 and 12 months was reliably predicted by Ishihara asymmetry at 1 month. Optic nerve MTR and DTI at 3 months post-acute ON could predict axonal loss at 6 and 12 months. Conclusions: Simple Ishihara asymmetry testing 1 month after acute ON onset can best predict visual outcome and axonal loss at 6 and 12 months in a clinical or research setting.

Evidence of Subjective, But Not Objective, Cognitive Deficit in New Mothers at 1-Year Postpartum.

Background: The experience and even existence of cognitive deficits in the postpartum period is uncertain, with only a few scientific studies, reporting inconsistent results. Methods: In this study, we investigate cognition in 86 women (43 first-time mothers 1 year postpartum and 43 non-mothers). Results: Mothers and non-mothers showed no significant differences on measures of objective cognition (verbal memory, working memory, and processing speed or theory of mind). Despite the absence of objective differences, mothers self-reported significantly worse subjective memory than non-mothers. To interpret the difference between objective and subjective measures of memory, we investigated relationships between subjective memory, objective memory, and wellbeing. Mothers, but not non-mothers, showed a positive correlation between subjective and objective measures of memory, indicating mothers are "in-tune" with their memory performance. Mothers also demonstrated a positive relationship between subjective memory and wellbeing (sleep, anxiety, and depression), where better wellbeing correlated with higher subjective memory. This relationship was not apparent in non-mothers. The results suggest that poorer sleep, higher anxiety, and higher depression are related to reports of poorer self-reported memory in mothers. Conclusion: Our results add to our growing understanding of maternal cognition at 1 year postpartum, with no evidence of cognitive differences between mothers and non-mothers.