Great Gray Owls hunting voles under snow hover to defeat an acoustic mirage.

How do Great Gray Owls (Strix nebulosa) capture voles (Cricetidae) through a layer of snow? As snow is a visual barrier, the owls locate voles by ear alone. To test how snow absorbs and refracts vole sound, we inserted a loudspeaker under the snowpack and analysed sound from the loudspeaker, first buried, then unburied. Snow attenuation coefficients rose with frequency (0.3 dB cm-1 at 500 Hz, 0.6 dB cm-1 at 3 kHz) such that low-frequency sound transmitted best. The Great Gray Owl has the largest facial disc of any owl, suggesting they are adapted to use this low-frequency sound. We used an acoustic camera to spatially localize sound source location, and show that snow also refracts prey sounds (refractive index: 1.16). To an owl not directly above the prey, this refraction creates an 'acoustic mirage': prey acoustic position is offset from its actual location. Their hunting strategy defeats this mirage because they hover directly over prey, which is the listening position with least refraction and least attenuation. Among all birds, the Great Gray Owl has the most extreme wing morphologies associated with quiet flight. These extreme wing traits may function to reduce the sounds of hovering, with implications for bioinspiration.

Novel KV7 ion channel openers for the treatment of epilepsy and implications for detrusor tissue contraction.

Neuronal voltage-gated potassium channels, KV7s, are the molecular mediators of the M current and regulate membrane excitability in the central and peripheral neuronal systems. Herein, we report novel small molecule KV7 openers that demonstrate anti-seizure activities in electroshock and pentylenetetrazol-induced seizure models without influencing Rotarod readouts in mice. The anti-seizure activity was determined to be proportional to the unbound concentration in the brain. KV7 channels are also expressed in the bladder smooth muscle (detrusor) and activation of these channels may cause localized undesired effects. Therefore, the impact of individual KV7 isoforms was investigated in human detrusor tissue using a panel of KV7 openers with distinct activity profiles among KV7 isoforms. KCNQ4 and KCNQ5 mRNA were highly expressed in detrusor tissue, yet a compound that has significantly reduced activity on homomeric KV7.4 did not reduce detrusor contraction. This may suggest that the homomeric KV7.4 channel plays a less significant role in bladder contraction and further investigation is needed.

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.

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.

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.

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.

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.

Differential electrophysiological response during rest, self-referential, and non-self-referential tasks in human posteromedial cortex.

The electrophysiological basis for higher brain activity during rest and internally directed cognition within the human default mode network (DMN) remains largely unknown. Here we use intracranial recordings in the human posteromedial cortex (PMC), a core node within the DMN, during conditions of cued rest, autobiographical judgments, and arithmetic processing. We found a heterogeneous profile of PMC responses in functional, spatial, and temporal domains. Although the majority of PMC sites showed increased broad gamma band activity (30-180 Hz) during rest, some PMC sites, proximal to the retrosplenial cortex, responded selectively to autobiographical stimuli. However, no site responded to both conditions, even though they were located within the boundaries of the DMN identified with resting-state functional imaging and similarly deactivated during arithmetic processing. These findings, which provide electrophysiological evidence for heterogeneity within the core of the DMN, will have important implications for neuroimaging studies of the DMN.

Frontostriatal white matter integrity mediates adult age differences in probabilistic reward learning.

Frontostriatal circuits have been implicated in reward learning, and emerging findings suggest that frontal white matter structural integrity and probabilistic reward learning are reduced in older age. This cross-sectional study examined whether age differences in frontostriatal white matter integrity could account for age differences in reward learning in a community life span sample of human adults. By combining diffusion tensor imaging with a probabilistic reward learning task, we found that older age was associated with decreased reward learning and decreased white matter integrity in specific pathways running from the thalamus to the medial prefrontal cortex and from the medial prefrontal cortex to the ventral striatum. Further, white matter integrity in these thalamocorticostriatal paths could statistically account for age differences in learning. These findings suggest that the integrity of frontostriatal white matter pathways critically supports reward learning. The findings also raise the possibility that interventions that bolster frontostriatal integrity might improve reward learning and decision making.

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.

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.

Frontoparietal white matter diffusion properties predict mental arithmetic skills in children.

Functional MRI studies of mental arithmetic consistently report blood oxygen level-dependent signals in the parietal and frontal regions. We tested whether white matter pathways connecting these regions are related to mental arithmetic ability by using diffusion tensor imaging (DTI) to measure these pathways in 28 children (age 10-15 years, 14 girls) and assessing their mental arithmetic skills. For each child, we identified anatomically the anterior portion of the superior longitudinal fasciculus (aSLF), a pathway connecting parietal and frontal cortex. We measured fractional anisotropy in a core region centered along the length of the aSLF. Fractional anisotropy in the left aSLF positively correlates with arithmetic approximation skill, as measured by a mental addition task with approximate answer choices. The correlation is stable in adjacent core aSLF regions but lower toward the pathway endpoints. The correlation is not explained by shared variance with other cognitive abilities and did not pass significance in the right aSLF. These measurements used DTI, a structural method, to test a specific functional model of mental arithmetic.

The development of cortical sensitivity to visual word forms.

The ability to extract visual word forms quickly and efficiently is essential for using reading as a tool for learning. We describe the first longitudinal fMRI study to chart individual changes in cortical sensitivity to written words as reading develops. We conducted four annual measurements of brain function and reading skills in a heterogeneous group of children, initially 7-12 years old. The results show age-related increase in children's cortical sensitivity to word visibility in posterior left occipito-temporal sulcus (LOTS), nearby the anatomical location of the visual word form area. Moreover, the rate of increase in LOTS word sensitivity specifically correlates with the rate of improvement in sight word efficiency, a measure of speeded overt word reading. Other cortical regions, including V1, posterior parietal cortex, and the right homologue of LOTS, did not demonstrate such developmental changes. These results provide developmental support for the hypothesis that LOTS is part of the cortical circuitry that extracts visual word forms quickly and efficiently and highlight the importance of developing cortical sensitivity to word visibility in reading acquisition.

Anatomical properties of the arcuate fasciculus predict phonological and reading skills in children.

For more than a century, neurologists have hypothesized that the arcuate fasciculus carries signals that are essential for language function; however, the relevance of the pathway for particular behaviors is highly controversial. The primary objective of this study was to use diffusion tensor imaging to examine the relationship between individual variation in the microstructural properties of arcuate fibers and behavioral measures of language and reading skills. A second objective was to use novel fiber-tracking methods to reassess estimates of arcuate lateralization. In a sample of 55 children, we found that measurements of diffusivity in the left arcuate correlate with phonological awareness skills and arcuate volume lateralization correlates with phonological memory and reading skills. Contrary to previous investigations that report the absence of the right arcuate in some subjects, we demonstrate that new techniques can identify the pathway in every individual. Our results provide empirical support for the role of the arcuate fasciculus in the development of reading skills.

Bound pool fractions complement diffusion measures to describe white matter micro and macrostructure.

Diffusion imaging and bound pool fraction (BPF) mapping are two quantitative magnetic resonance imaging techniques that measure microstructural features of the white matter of the brain. Diffusion imaging provides a quantitative measure of the diffusivity of water in tissue. BPF mapping is a quantitative magnetization transfer (qMT) technique that estimates the proportion of exchanging protons bound to macromolecules, such as those found in myelin, and is thus a more direct measure of myelin content than diffusion. In this work, we combined BPF estimates of macromolecular content with measurements of diffusivity within human white matter tracts. Within the white matter, the correlation between BPFs and diffusivity measures such as fractional anisotropy and radial diffusivity was modest, suggesting that diffusion tensor imaging and bound pool fractions are complementary techniques. We found that several major tracts have high BPF, suggesting a higher density of myelin in these tracts. We interpret these results in the context of a quantitative tissue model.

Cross-relaxation imaging of human articular cartilage.

In this article, cross-relaxation imaging is applied to human ex vivo knee cartilage, and correlations of the cross-relaxation imaging parameters with macromolecular content in articular cartilage are reported. We show that, unlike the more commonly used magnetization transfer ratio, the bound pool fraction, the cross-relaxation rate (k) and the longitudinal relaxation time (T(1)) vary with depth and can therefore provide insight into the differences between the top and bottom layers of articular cartilage. Our cross-relaxation imaging model is more sensitive to macromolecular content in the top layers of cartilage, with bound pool fraction showing moderate correlations with proteoglycan content, and k and T(1) exhibiting moderate correlations with collagen.

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.

COMT genotype affects prefrontal white matter pathways in children and adolescents.

Diffusion tensor imaging is widely used to evaluate the development of white matter. Information about how alterations in major neurotransmitter systems, such as the dopamine (DA) system, influence this development in healthy children, however, is lacking. Catechol-O-metyltransferase (COMT) is the major enzyme responsible for DA degradation in prefrontal brain structures, for which there is a corresponding genetic polymorphism (val158met) that confers either a more or less efficient version of this enzyme. The result of this common genetic variation is that children may have more or less available synaptic DA in prefrontal brain regions. In the present study we examined the relation between diffusion properties of frontal white matter structures and the COMT val158met polymorphism in 40 children ages 9-15. We found that the val allele was associated with significantly elevated fractional anisotropy values and reduced axial and radial diffusivities. These results indicate that the development of white matter in healthy children is related to COMT genotype and that alterations in white matter may be related to the differential availability of prefrontal DA. This investigation paves the way for further studies of how common functional variants in the genome might influence the development of brain white matter.

Resting-state functional connectivity reflects structural connectivity in the default mode network.

Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level-dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions--including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)--implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.

Empirical null and false discovery rate analysis in neuroimaging.

Current strategies for thresholding statistical parametric maps in neuroimaging include control of the family-wise error rate, control of the false discovery rate (FDR) and thresholding of the posterior probability of a voxel being active given the data, the latter derived from a mixture model of active and inactive voxels. Correct inference using any of these criteria depends crucially on the specification of the null distribution of the test statistics. In this article we show examples from fMRI and DTI data where the theoretical null distribution does not match well the observed distribution of the test statistics. As a solution, we introduce the use of an empirical null, a null distribution empirically estimated from the data itself, allowing for global corrections of theoretical null assumptions. The theoretical null distributions considered are normal, t, chi(2) and F, all commonly encountered in neuroimaging. The empirical null estimate is accompanied by an estimate of the proportion of non-active voxels in the data. Based on the two-class mixture model, we present the equivalence between the strategies of controlling FDR and thresholding posterior probabilities in the context of neuroimaging and show that the FDR estimates derived from the empirical null can be seen as empirical Bayes estimates.