Psilocybin therapy for treatment resistant depression: prediction of clinical outcome by natural language processing.

RATIONALE: Therapeutic administration of psychedelics has shown significant potential in historical accounts and recent clinical trials in the treatment of depression and other mood disorders. A recent randomized double-blind phase-IIb study demonstrated the safety and efficacy of COMP360, COMPASS Pathways' proprietary synthetic formulation of psilocybin, in participants with treatment-resistant depression. OBJECTIVE: While the phase-IIb results are promising, the treatment works for a portion of the population and early prediction of outcome is a key objective as it would allow early identification of those likely to require alternative treatment. METHODS: Transcripts were made from audio recordings of the psychological support session between participant and therapist 1 day post COMP360 administration. A zero-shot machine learning classifier based on the BART large language model was used to compute two-dimensional sentiment (valence and arousal) for the participant and therapist from the transcript. These scores, combined with the Emotional Breakthrough Index (EBI) and treatment arm were used to predict treatment outcome as measured by MADRS scores. (Code and data are available at https://github.com/compasspathways/Sentiment2D .) RESULTS: Two multinomial logistic regression models were fit to predict responder status at week 3 and through week 12. Cross-validation of these models resulted in 85% and 88% accuracy and AUC values of 88% and 85%. CONCLUSIONS: A machine learning algorithm using NLP and EBI accurately predicts long-term patient response, allowing rapid prognostication of personalized response to psilocybin treatment and insight into therapeutic model optimization. Further research is required to understand if language data from earlier stages in the therapeutic process hold similar predictive power.

Rates of Incidental Findings in Brain Magnetic Resonance Imaging in Children.

Importance: Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives: To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, Setting, and Participants: This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main Outcomes and Measures: Percentage of children with IFs in each category and prevalence of specific IFs. Results: A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and Relevance: Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.

Advantages of short repetition time resting-state functional MRI enabled by simultaneous multi-slice imaging.

BACKGROUND: Recent advancements in simultaneous multi-slice (SMS) imaging techniques have enabled whole-brain resting-state fMRI (rs-fMRI) scanning at sub-second temporal resolution, providing spectral ranges much wider than the typically used range of 0.01-0.1 Hz. However, the advantages of this accelerated acquisition for rs-fMRI have not been evaluated. NEW METHOD: In this study, we used SMS Echo Planar Imaging (EPI) to probe whole-brain functional connectivity with a short repetition time (TR = 350 ms) and compared it with standard EPI with a longer TR of 2000 ms. We determined the effect of scan length and investigated the temporal filtration strategies that optimize results based on metrics of signal-noise separation and test-retest reliability using both seed-based and independent component analysis (ICA). RESULTS: We found that use of either the entire frequency range of 0.01-1.4 Hz or the entire frequency range with the exclusion of typical cardiac and respiratory frequency values tended to provide the best functional connectivity maps. COMPARISON WITH EXISTING METHODS: We found that the SMS-acquired rs-fMRI scans had improved the signal-noise separation, while preserving the same level of test-retest reliability compared to conventional EPI, and enabled the detection of reliable functional connectivity networks with scan times as short as 3 min. CONCLUSIONS: Our findings suggest that whole-brain rs-fMRI studies may benefit from the increased temporal resolution enabled by the SMS-EPI acquisition, leading to drastic scan time reductions, which in turn should enable the more widespread use of rs-fMRI in clinical research protocols.

Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison.

A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the 'White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300 mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.

White matter structure in the uncinate fasciculus: Implications for socio-affective deficits in Autism Spectrum Disorder.

Individuals with Autism Spectrum Disorder (ASD) have social and communication deficits and difficulties regulating emotions. The brain bases of these socio-affective deficits are not yet clear, but one candidate is structural connectivity in the left uncinate fasciculus, which connects limbic temporal and frontal areas thought to be involved in socio-affective processing. In this study, we assessed white matter structure in the left and right uncinate fasciculus in 18 high-functioning individuals with ASD and 18 group-matched typically developing (TD) controls using Diffusion Tensor Imaging. To test specificity of the associations, we also examined the association between both uncinate fasciculi and restricted and repetitive behaviors. Compared to TD individuals, individuals with ASD had significantly lower fractional anisotropy (FA) in the left and right uncinate. Group status significantly moderated the association between left uncinate and socio-affective deficits, indicating that within the ASD group, FA was associated with socio-affective deficits: Individuals with ASD with lower FA in the left uncinate had significantly more social and emotion regulation deficits. There was no association with restricted and repetitive behaviors. This study provides evidence that the left uncinate may play a critical role in socio-affective skills in individuals with ASD.

Aging-Resilient Associations between the Arcuate Fasciculus and Vocabulary Knowledge: Microstructure or Morphology?

UNLABELLED: Vocabulary knowledge is one of the few cognitive functions that is relatively preserved in older adults, but the reasons for this relative preservation have not been well delineated. We tested the hypothesis that individual differences in vocabulary knowledge are influenced by arcuate fasciculus macrostructure (i.e., shape and volume) properties that remain stable during the aging process, rather than white matter microstructure that demonstrates age-related declines. Vocabulary was not associated with age compared to pronounced age-related declines in cognitive processing speed across 106 healthy adults (19.92-88.29 years) who participated in this neuroimaging experiment. Fractional anisotropy in the left arcuate fasciculus was significantly related to individual variability in vocabulary. This effect was present despite marked age-related differences in a T1-weighted/T2-weighted ratio (T1w/T2w) estimate of myelin that were observed throughout the left arcuate fasciculus and associated with age-related differences in cognitive processing speed. However, atypical patterns of arcuate fasciculus morphology or macrostructure were associated with decreased vocabulary knowledge. These results suggest that deterioration of tissue in the arcuate fasciculus occurs with normal aging, while having limited impact on tract organization that underlies individual differences in the acquisition and retrieval of lexical and semantic information. SIGNIFICANCE STATEMENT: Vocabulary knowledge is resilient to widespread age-related declines in brain structure that limit other cognitive functions. We tested the hypothesis that arcuate fasciculus morphology, which supports the development of reading skills that bolster vocabulary, could explain this relative preservation. We disentangled (1) the effects of age-related declines in arcuate microstructure (mean diffusivity; myelin content estimate) that predicted cognitive processing speed but not vocabulary, from (2) relatively stable arcuate macrostructure (shape/volume) that explained significant variance in an age-independent association between fractional anisotropy and vocabulary. This latter result may reflect differences in fiber trajectory and organization that are resilient to aging. We propose that developmental sculpting of the arcuate fasciculus determines acquisition, storage, and access of lexical information across the adult lifespan.

Profiles of aberrant white matter microstructure in fragile X syndrome.

Previous studies attempting to quantify white matter (WM) microstructure in individuals with fragile X syndrome (FXS) have produced inconsistent findings, most likely due to the various control groups employed, differing analysis methods, and failure to examine for potential motion artifact. In addition, analyses have heretofore lacked sufficient specificity to provide regional information. In this study, we used Automated Fiber-tract Quantification (AFQ) to identify specific regions of aberrant WM microstructure along WM tracts in patients with FXS that differed from controls who were matched on age, IQ and degree of autistic symptoms. Participants were 20 patients with FXS, aged 10 to 23 years, and 20 matched controls. Using Automated Fiber-tract Quantification (AFQ), we created Tract Profiles of fractional anisotropy and mean diffusivity along 18 major WM fascicles. We found that fractional anisotropy was significantly increased in the left and right inferior longitudinal fasciculus (ILF), right uncinate fasciculus, and left cingulum hippocampus in individuals with FXS compared to controls. Conversely, mean diffusivity was significantly decreased in the right ILF in patients with FXS compared to controls. Age was significantly negatively associated with MD values across both groups in 11 tracts. Taken together, these findings indicate that FXS results in abnormal WM microstructure in specific regions of the ILF and uncinate fasciculus, most likely caused by inefficient synaptic pruning as a result of decreased or absent Fragile X Mental Retardation Protein (FMRP). Longitudinal studies are needed to confirm these findings.

Hybrid-Space SENSE Reconstruction for Simultaneous Multi-Slice MRI.

Simultaneous Multi-Slice (SMS) magnetic resonance imaging (MRI) is a rapidly evolving technique for increasing imaging speed. Controlled aliasing techniques utilize periodic undersampling patterns to help mitigate the loss in signal-to-noise ratio (SNR) in SMS MRI. To evaluate the performance of different undersampling patterns, a quantitative description of the image SNR loss is needed. Additionally, eddy current effects in echo planar imaging (EPI) lead to slice-specific Nyquist ghosting artifacts. These artifacts cannot be accurately corrected for each individual slice before or after slice-unaliasing. In this work, we propose a hybrid-space sensitivity encoding (SENSE) reconstruction framework for SMS MRI by adopting a three-dimensional representation of the SMS acquisition. Analytical SNR loss maps are derived for SMS acquisitions with arbitrary phase encoding undersampling patterns. Moreover, we propose a matrix-decoding correction method that corrects the slice-specific Nyquist ghosting artifacts in SMS EPI acquisitions. Brain images demonstrate that the proposed hybrid-space SENSE reconstruction generates images with comparable quality to commonly used split-slice-generalized autocalibrating partially parallel acquisition reconstruction. The analytical SNR loss maps agree with those calculated by a Monte Carlo based method, but require less computation time for high quality maps. The analytical maps enable a fair comparison between the performances of coherent and incoherent SMS undersampling patterns. Phantom and brain SMS EPI images show that the matrix-decoding method performs better than the single-slice and slice-averaged Nyquist ghosting correction methods under the hybrid-space SENSE reconstruction framework.

Quantitative analysis of the myelin g-ratio from electron microscopy images of the macaque corpus callosum.

We provide a detailed morphometric analysis of eight transmission electron micrographs (TEMs) obtained from the corpus callosum of one cynomolgus macaque. The raw TEM images are included in the article, along with the distributions of the axon caliber and the myelin g-ratio in each image. The distributions are analyzed to determine the relationship between axon caliber and g-ratio, and compared against the aggregate metrics (myelin volume fraction, fiber volume fraction, and the aggregate g-ratio), as defined in the accompanying research article entitled 'In vivo histology of the myelin g-ratio with magnetic resonance imaging' (Stikov et al., NeuroImage, 2015).

Pictionary-based fMRI paradigm to study the neural correlates of spontaneous improvisation and figural creativity.

A novel game-like and creativity-conducive fMRI paradigm is developed to assess the neural correlates of spontaneous improvisation and figural creativity in healthy adults. Participants were engaged in the word-guessing game of Pictionary(TM), using an MR-safe drawing tablet and no explicit instructions to be "creative". Using the primary contrast of drawing a given word versus drawing a control word (zigzag), we observed increased engagement of cerebellum, thalamus, left parietal cortex, right superior frontal, left prefrontal and paracingulate/cingulate regions, such that activation in the cingulate and left prefrontal cortices negatively influenced task performance. Further, using parametric fMRI analysis, increasing subjective difficulty ratings for drawing the word engaged higher activations in the left pre-frontal cortices, whereas higher expert-rated creative content in the drawings was associated with increased engagement of bilateral cerebellum. Altogether, our data suggest that cerebral-cerebellar interaction underlying implicit processing of mental representations has a facilitative effect on spontaneous improvisation and figural creativity.

In vivo histology of the myelin g-ratio with magnetic resonance imaging.

The myelin g-ratio, defined as the ratio between the inner and the outer diameter of the myelin sheath, is a fundamental property of white matter that can be computed from a simple formula relating the myelin volume fraction to the fiber volume fraction or the axon volume fraction. In this paper, a unique combination of magnetization transfer, diffusion imaging and histology is presented, providing a novel method for in vivo magnetic resonance imaging of the axon volume fraction and the myelin g-ratio. Our method was demonstrated in the corpus callosum of one cynomolgus macaque, and applied to obtain full-brain g-ratio maps in one healthy human subject and one multiple sclerosis patient. In the macaque, the g-ratio was relatively constant across the corpus callosum, as measured by both MRI and electron microscopy. In the human subjects, the g-ratio in multiple sclerosis lesions was higher than in normal appearing white matter, which was in turn higher than in healthy white matter. Measuring the g-ratio brings us one step closer to fully characterizing white matter non-invasively, making it possible to perform in vivo histology of the human brain during development, aging, disease and treatment.

Disrupted fornix integrity in children with chromosome 22q11.2 deletion syndrome.

The fornix is the primary subcortical output fiber system of the hippocampal formation. In children with 22q11.2 deletion syndrome (22q11.2DS), hippocampal volume reduction has been commonly reported, but few studies as yet have evaluated the integrity of the fornix. Therefore, we investigated the fornix of 45 school-aged children with 22q11.2DS and 38 matched typically developing (TD) children. Probabilistic diffusion tensor imaging (DTI) tractography was used to reconstruct the body of the fornix in each child׳s brain native space. Compared with children, significantly lower fractional anisotropy (FA) and higher radial diffusivity (RD) was observed bilaterally in the body of the fornix in children with 22q11.2DS. Irregularities were especially prominent in the posterior aspect of the fornix where it emerges from the hippocampus. Smaller volumes of the hippocampal formations were also found in the 22q11.2DS group. The reduced hippocampal volumes were correlated with lower fornix FA and higher fornix RD in the right hemisphere. Our findings provide neuroanatomical evidence of disrupted hippocampal connectivity in children with 22q11.2DS, which may help to further understand the biological basis of spatial impairments, affective regulation, and other factors related to the ultra-high risk for schizophrenia in this population.

Abnormal white matter properties in adolescent girls with anorexia nervosa.

Anorexia nervosa (AN) is a serious eating disorder that typically emerges during adolescence and occurs most frequently in females. To date, very few studies have investigated the possible impact of AN on white matter tissue properties during adolescence, when white matter is still developing. The present study evaluated white matter tissue properties in adolescent girls with AN using diffusion MRI with tractography and T1 relaxometry to measure R1 (1/T1), an index of myelin content. Fifteen adolescent girls with AN (mean age = 16.6 years ± 1.4) were compared to fifteen age-matched girls with normal weight and eating behaviors (mean age = 17.1 years ± 1.3). We identified and segmented 9 bilateral cerebral tracts (18) and 8 callosal fiber tracts in each participant's brain (26 total). Tract profiles were generated by computing measures for fractional anisotropy (FA) and R1 along the trajectory of each tract. Compared to controls, FA in the AN group was significantly decreased in 4 of 26 white matter tracts and significantly increased in 2 of 26 white matter tracts. R1 was significantly decreased in the AN group compared to controls in 11 of 26 white matter tracts. Reduced FA in combination with reduced R1 suggests that the observed white matter differences in AN are likely due to reductions in myelin content. For the majority of tracts, group differences in FA and R1 did not occur within the same tract. The present findings have important implications for understanding the neurobiological factors underlying white matter changes associated with AN and invite further investigations examining associations between white matter properties and specific physiological, cognitive, social, or emotional functions affected in AN.

Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging.

Here, we describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent quantitative estimate of MTV can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second, we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.

Human trichromacy revisited.

The presence of a photopigment (melanopsin) within certain retinal ganglion cells was a surprising and significant discovery. This pigment is routinely described as "nonvisual" to highlight its signaling role in pupil dilation and circadian rhythms. Here we asked whether light absorbed by melanopsin can be seen by healthy human subjects. To answer this requires delivering intense (above rod saturation), well-controlled lights using four independent primaries. We collected detection thresholds to many four-primary stimuli. Threshold measurements in the fovea are explained by trichromatic theory, with no need to invoke a fourth photopigment. In the periphery, where melanopsin is present, threshold measurements deviate from trichromatic theory; at high photopic levels, sensitivity is explained by absorptions in four, not three, photopigment classes. We consider a series of hypotheses to explain the tetrasensitivity at high photopic levels in the human peripheral field. The most likely hypothesis is that in healthy human subjects melanopsin absorptions influence visibility.

GLMdenoise: a fast, automated technique for denoising task-based fMRI data.

In task-based functional magnetic resonance imaging (fMRI), researchers seek to measure fMRI signals related to a given task or condition. In many circumstances, measuring this signal of interest is limited by noise. In this study, we present GLMdenoise, a technique that improves signal-to-noise ratio (SNR) by entering noise regressors into a general linear model (GLM) analysis of fMRI data. The noise regressors are derived by conducting an initial model fit to determine voxels unrelated to the experimental paradigm, performing principal components analysis (PCA) on the time-series of these voxels, and using cross-validation to select the optimal number of principal components to use as noise regressors. Due to the use of data resampling, GLMdenoise requires and is best suited for datasets involving multiple runs (where conditions repeat across runs). We show that GLMdenoise consistently improves cross-validation accuracy of GLM estimates on a variety of event-related experimental datasets and is accompanied by substantial gains in SNR. To promote practical application of methods, we provide MATLAB code implementing GLMdenoise. Furthermore, to help compare GLMdenoise to other denoising methods, we present the Denoise Benchmark (DNB), a public database and architecture for evaluating denoising methods. The DNB consists of the datasets described in this paper, a code framework that enables automatic evaluation of a denoising method, and implementations of several denoising methods, including GLMdenoise, the use of motion parameters as noise regressors, ICA-based denoising, and RETROICOR/RVHRCOR. Using the DNB, we find that GLMdenoise performs best out of all of the denoising methods we tested.

Tract profiles of white matter properties: automating fiber-tract quantification.

Tractography based on diffusion weighted imaging (DWI) data is a method for identifying the major white matter fascicles (tracts) in the living human brain. The health of these tracts is an important factor underlying many cognitive and neurological disorders. In vivo, tissue properties may vary systematically along each tract for several reasons: different populations of axons enter and exit the tract, and disease can strike at local positions within the tract. Hence quantifying and understanding diffusion measures along each fiber tract (Tract Profile) may reveal new insights into white matter development, function, and disease that are not obvious from mean measures of that tract. We demonstrate several novel findings related to Tract Profiles in the brains of typically developing children and children at risk for white matter injury secondary to preterm birth. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects. Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather than along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy population to elucidate unique features of that patient's clinical condition. Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group reading ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies significantly along the Tract Profiles. We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Tract Profiles have potential for informing clinical management and decision-making.

Development of white matter and reading skills.

White matter tissue properties are highly correlated with reading proficiency; we would like to have a model that relates the dynamics of an individual's white matter development to their acquisition of skilled reading. The development of cerebral white matter involves multiple biological processes, and the balance between these processes differs between individuals. Cross-sectional measures of white matter mask the interplay between these processes and their connection to an individual's cognitive development. Hence, we performed a longitudinal study to measure white-matter development (diffusion-weighted imaging) and reading development (behavioral testing) in individual children (age 7-15 y). The pattern of white-matter development differed significantly among children. In the left arcuate and left inferior longitudinal fasciculus, children with above-average reading skills initially had low fractional anisotropy (FA) that increased over the 3-y period, whereas children with below-average reading skills had higher initial FA that declined over time. We describe a dual-process model of white matter development comprising biological processes with opposing effects on FA, such as axonal myelination and pruning, to explain the pattern of results.

Plasticity and stability of the visual system in human achiasma.

The absence of the optic chiasm is an extraordinary and extreme abnormality in the nervous system. The abnormality produces highly atypical functional responses in the cortex, including overlapping hemifield representations and bilateral population receptive fields in both striate and extrastriate visual cortex. Even in the presence of these large functional abnormalities, the effect on visual perception and daily life is not easily detected. Here, we demonstrate that in two achiasmic humans the gross topography of the geniculostriate and occipital callosal connections remains largely unaltered. We conclude that visual function is preserved by reorganization of intracortical connections instead of large-scale reorganizations of the visual cortex. Thus, developmental mechanisms of local wiring within cortical maps compensate for the improper gross wiring to preserve function in human achiasma.

Hippocampal CA1 apical neuropil atrophy and memory performance in Alzheimer's disease.

Memory loss is often the first and most prominent symptom of Alzheimer's disease (AD), coinciding with the spread of neurofibrillary pathology from the entorhinal cortex (ERC) to the hippocampus. The apical dendrites of hippocampal CA1 pyramidal neurons, in the stratum radiatum/stratum lacunosum-moleculare (SRLM), are among the earliest targets of this pathology, and atrophy of the CA1-SRLM is apparent in postmortem tissue from patients with mild AD. We previously demonstrated that CA1-SRLM thinning is also apparent in vivo, using ultra-high field 7-Tesla (7T) MRI to obtain high-resolution hippocampal microstructural imaging. Here, we hypothesized that CA1-SRLM thickness would correlate with episodic memory performance among patients with mild AD. We scanned nine patients, using an oblique coronal T2-weighted sequence through the hippocampal body with an in-plane resolution of 220 µm, allowing direct visual identification of subfields - dentate gyrus (DG)/CA3, CA2, CA1, and ERC - and hippocampal strata - SRLM and stratum pyramidale (SP). We present a novel semi-automated method of measuring stratal width that correlated well with manual measurements. We performed multi-domain neuropsychological evaluations that included three tests of episodic memory, yielding composite scores for immediate recall, delayed recall, and delayed recognition memory. Strong correlations occurred between delayed recall performance and the widths of CA1-SRLM (r(2)=0.69; p=0.005), CA1-SP (r(2)=0.5; p=0.034), and ERC (r(2)=0.62; p=0.012). The correlation between CA1-SRLM width and delayed recall lateralized to the left hemisphere. DG/CA3 size did not correlate significantly with any aspect of memory performance. These findings highlight a role for 7T hippocampal microstructural imaging in revealing focal structural pathology that correlates with the central cognitive feature of AD.