A comparative neuroimaging perspective of olfaction and higher-order olfactory processing: on health and disease.

Olfactory dysfunction is often the earliest indicator of disease in a range of neurological and psychiatric disorders. One tempting working hypothesis is that pathological changes in the peripheral olfactory system where the body is exposed to many adverse environmental stressors may have a causal role for the brain alteration. Whether and how the peripheral pathology spreads to more central brain regions may be effectively studied in rodent models, and there is successful precedence in experimental models for Parkinson's disease. It is of interest to study whether a similar mechanism may underlie the pathology of psychiatric illnesses, such as schizophrenia. However, direct comparison between rodent models and humans includes challenges under light of comparative neuroanatomy and experimental methodologies used in these two distinct species. We believe that neuroimaging modality that has been the main methodology of human brain studies may be a useful viewpoint to address and fill the knowledge gap between rodents and humans in this scientific question. Accordingly, in the present review article, we focus on brain imaging studies associated with olfaction in healthy humans and patients with neurological and psychiatric disorders, and if available those in rodents. We organize this review article at three levels: 1) olfactory bulb (OB) and peripheral structures of the olfactory system, 2) primary olfactory cortical and subcortical regions, and 3) associated higher-order cortical regions. This research area is still underdeveloped, and we acknowledge that further validation with independent cohorts may be needed for many studies presented here, in particular those with human subjects. Nevertheless, whether and how peripheral olfactory disturbance impacts brain function is becoming even a hotter topic in the ongoing COVID-19 pandemic, given the risk of long-term changes of mental status associated with olfactory infection of SARS-CoV-2. Together, in this review article, we introduce this underdeveloped but important research area focusing on its implications in neurological and psychiatric disorders, with several pioneered publications.

Volume Reduction of the Dorsal Lateral Prefrontal Cortex Prior to the Onset of Frank Psychosis in Individuals with an At-Risk Mental State.

Although some individuals with at-risk mental states (ARMS) develop overt psychosis, surrogate markers which can reliably predict a future onset of psychosis are not well established. The dorsal lateral prefrontal cortex (DLPFC) is thought to be involved in psychotic disorders such as schizophrenia. In this study, 73 ARMS patients and 74 healthy controls underwent 1.5-T 3D magnetic resonance imaging scans at three sites. Using labeled cortical distance mapping, cortical thickness, gray matter (GM) volume, and surface area of DLPFC were estimated. These measures were compared across the diagnostic groups. We also evaluated cognitive function among 36 ARMS subjects to clarify the relationships between the DLPFC morphology and cognitive performance. The GM volume of the right DLPFC was significantly reduced in ARMS subjects who later developed frank psychosis (ARMS-P) relative to those who did not (P = 0.042). There was a positive relationship between the right DLPFC volume and the duration prior to the onset of frank psychosis in ARMS-P subjects (r = 0.58, P = 0.018). Our data may suggest that GM reduction of the DLPFC might be a potential marker of future onset of psychosis in individuals with ARMS.

Hearing loss impacts gray and white matter across the lifespan: Systematic review, meta-analysis and meta-regression.

Hearing loss is a heterogeneous disorder thought to affect brain reorganization across the lifespan. Here, structural alterations of the brain due to hearing loss are assessed by using unique effect size metrics based on Cohen's d and Hedges' g. These metrics are used to map coordinates of gray matter (GM) and white matter (WM) alterations from bilateral congenital and acquired hearing loss populations. A systematic review and meta-analysis revealed m = 72 studies with structural alterations measured with magnetic resonance imaging (MRI) (bilateral = 64, unilateral = 8). The bilateral studies categorized hearing loss into congenital and acquired cases (n = 7,445) and control cases (n = 2,924), containing 66,545 datapoint metrics. Hearing loss was found to affect GM and underlying WM in nearly every region of the brain. In congenital hearing loss, GM decreased most in the frontal lobe. Similarly, acquired hearing loss had a decrease in frontal lobe GM, albeit the insula was most decreased. In congenital, WM underlying the frontal lobe GM was most decreased. In congenital, the right hemisphere was more negatively impacted than the left hemisphere; however, in acquired, this was the opposite. The WM alterations most frequently underlined GM alterations in congenital hearing loss, while acquired hearing loss studies did not frequently assess the WM metric. Future studies should use the endophenotype of hearing loss as a prognostic template for discerning clinical outcomes.

Embracing diversity and inclusivity in an academic setting: Insights from the Organization for Human Brain Mapping.

Scientific research aims to bring forward innovative ideas and constantly challenges existing knowledge structures and stereotypes. However, women, ethnic and cultural minorities, as well as individuals with disabilities, are systematically discriminated against or even excluded from promotions, publications, and general visibility. A more diverse workforce is more productive, and thus discrimination has a negative impact on science and the wider society, as well as on the education, careers, and well-being of individuals who are discriminated against. Moreover, the lack of diversity at scientific gatherings can lead to micro-aggressions or harassment, making such meetings unpleasant, or even unsafe environments for early career and underrepresented scientists. At the Organization for Human Brain Mapping (OHBM), we recognized the need for promoting underrepresented scientists and creating diverse role models in the field of neuroimaging. To foster this, the OHBM has created a Diversity and Inclusivity Committee (DIC). In this article, we review the composition and activities of the DIC that have promoted diversity within OHBM, in order to inspire other organizations to implement similar initiatives. Activities of the committee over the past four years have included (a) creating a code of conduct, (b) providing diversity and inclusivity education for OHBM members, (c) organizing interviews and symposia on diversity issues, and (d) organizing family-friendly activities and providing childcare grants during the OHBM annual meetings. We strongly believe that these activities have brought positive change within the wider OHBM community, improving inclusivity and fostering diversity while promoting rigorous, ground-breaking science. These positive changes could not have been so rapidly implemented without the enthusiastic support from the leadership, including OHBM Council and Program Committee, and the OHBM Special Interest Groups (SIGs), namely the Open Science, Student and Postdoc, and Brain-Art SIGs. Nevertheless, there remains ample room for improvement, in all areas, and even more so in the area of targeted attempts to increase inclusivity for women, individuals with disabilities, members of the LGBTQ+ community, racial/ethnic minorities, and individuals of lower socioeconomic status or from low and middle-income countries. Here, we present an overview of the DIC's composition, its activities, future directions and challenges. Our goal is to share our experiences with a wider audience to provide information to other organizations and institutions wishing to implement similar comprehensive diversity initiatives. We propose that scientific organizations can push the boundaries of scientific progress only by moving beyond existing power structures and by integrating principles of equity and inclusivity in their core values.

Motor cortical thickness is related to effort-based decision-making in humans.

Although motor cortex is integral in driving physical exertion, how its inherent properties influence decisions to exert is unknown. In this study, we examined how anatomical properties of motor cortex are related to participants' subjective valuations of effort and their decisions to exert effort. We used computational modeling to characterize participants' subjective valuation of physical effort during an effort-based decision-making task in which they made choices about exerting different levels of hand-grip exertion. We also acquired structural MRI data from these participants and extracted anatomical measures of each individual's hand knob, the region of motor cortex recruited during hand-grip exertion. We found that individual participants' cortical thickness of hand knob was associated with their effort-based decisions regarding hand exertion. These data provide evidence that the anatomy of an individual's motor cortex is an important factor in decisions to engage in physical activity.NEW & NOTEWORTHY How effortful a task feels is an integral aspect of human decision-making that influences choices to engage in physical activity. We show that properties of motor cortex (the brain region responsible for physical exertion) are related to assessments of effort and decisions to exert. These findings provide a link between the anatomical properties of motor cortex and the cognitive function of effort-based choice.

Visualising the topography of the acoustic radiation in clinical diffusion tensor imaging scans.

PURPOSE: It has long been thought that the acoustic radiation (AR) white matter fibre tract from the medial geniculate body of the thalamus to the Heschl's gyrus cannot be reconstructed via single-fibre analysis of clinical diffusion tensor imaging (DTI) scans. A recently developed single-fibre probabilistic method suggests otherwise. The method uses dynamic programming (DP) to compute the most probable paths between two regions of interest. This study aims to observe the ability of single-fibre probabilistic analysis via DP to visualise the AR in clinical DTI scans from legacy pilot cohorts of subjects with normal hearing (NH) and profound hearing loss (HL). METHODS: Single-fibre probabilistic analysis via DP was applied to reconstruct 3D models of the AR in the two cohorts. DTI and T1 data at 1.5 T for subjects with NH (n = 11) and HL (n = 5), as well as 3 T for NH (n = 1) and HL (n = 1), were used. RESULTS: The topographical features of AR previously observed in post-mortem and multi-fibre analyses can be visualised in DTI scans of 16 subjects and 2 atlases with a success rate of 100%. Relative to MNI coordinates, there was no significant difference in the varifold distances between the topography of the tracts in the 1.5 T cohort. CONCLUSION: The AR can be visualised in clinical 1.5 T and 3 T DTI scans using single-fibre probabilistic analysis via DP, hence, the potential for DP to visualise the AR in medical and pre-surgical applications in pathologies such as vestibular schwannoma, multiple sclerosis, thalamic tumours and stroke as well as hearing loss.

Regional subcortical shape analysis in premanifest Huntington's disease.

Huntington's disease (HD) involves preferential and progressive degeneration of striatum and other subcortical regions as well as regional cortical atrophy. It is caused by a CAG repeat expansion in the Huntingtin gene, and the longer the expansion the earlier the age of onset. Atrophy begins prior to manifest clinical signs and symptoms, and brain atrophy in premanifest expansion carriers can be studied. We employed a diffeomorphometric pipeline to contrast subcortical structures' morphological properties in a control group with three disease groups representing different phases of premanifest HD (far, intermediate, and near to onset) as defined by the length of the CAG expansion and the participant's age (CAG-Age-Product). A total of 1,428 magnetic resonance image scans from 694 participants from the PREDICT-HD cohort were used. We found significant region-specific atrophies in all subcortical structures studied, with the estimated abnormality onset time varying from structure to structure. Heterogeneous shape abnormalities of caudate nuclei were present in premanifest HD participants estimated furthest from onset and putaminal shape abnormalities were present in participants intermediate to onset. Thalamic, hippocampal, and amygdalar shape abnormalities were present in participants nearest to onset. We assessed whether the estimated progression of subcortical pathology in premanifest HD tracked specific pathways. This is plausible for changes in basal ganglia circuits but probably not for changes in hippocampus and amygdala. The regional shape analyses conducted in this study provide useful insights into the effects of HD pathology in subcortical structures.

Relationship of medial temporal lobe atrophy, APOE genotype, and cognitive reserve in preclinical Alzheimer's disease.

This study evaluated the utility of baseline and longitudinal magnetic resonance imaging (MRI) measures of medial temporal lobe brain regions collected when participants were cognitively normal and largely in middle age (mean age 57 years) to predict the time to onset of clinical symptoms associated with mild cognitive impairment (MCI). Furthermore, we examined whether the relationship between MRI measures and clinical symptom onset was modified by apolipoprotein E (ApoE) genotype and level of cognitive reserve (CR). MRI scans and measures of CR were obtained at baseline from 245 participants who had been followed for up to 18 years (mean follow-up 11 years). A composite score based on reading, vocabulary, and years of education was used as an index of CR. Cox regression models showed that lower baseline volume of the right hippocampus and smaller baseline thickness of the right entorhinal cortex predicted the time to symptom onset independently of CR and ApoE-ɛ4 genotype, which also predicted the onset of symptoms. The atrophy rates of bilateral entorhinal cortex and amygdala volumes were also associated with time to symptom onset, independent of CR, ApoE genotype, and baseline volume. Only one measure, the left entorhinal cortex baseline volume, interacted with CR, such that smaller volumes predicted symptom onset only in individuals with lower CR. These results suggest that MRI measures of medial temporal atrophy, ApoE-ɛ4 genotype, and the protective effects of higher CR all predict the time to onset of symptoms associated with MCI in a largely independent, additive manner during the preclinical phase of Alzheimer's disease.

Knowledge-based automated reconstruction of human brain white matter tracts using a path-finding approach with dynamic programming.

It has been shown that the anatomy of major white matter tracts can be delineated using diffusion tensor imaging (DTI) data. Tract reconstruction, however, often suffers from a large number of false-negative results when a simple line propagation algorithm is used. This limits the application of this technique to only the core of prominent white matter tracts. By employing probabilistic path-generation algorithms, connectivity between a larger number of anatomical regions can be studied, but an increase in the number of false-positive results is inevitable. One of the causes of the inaccuracy is the complex axonal anatomy within a voxel; however, high-angular resolution (HAR) methods have been proposed to ameliorate this limitation. However, HAR data are relatively rare due to the long scan times required and the low signal-to-noise ratio. In this study, we tested a probabilistic path-finding method in which two anatomical regions with known connectivity were pre-defined and a path that maximized agreement with the DTI data was searched. To increase the accuracy of the trajectories, knowledge-based anatomical constraints were applied. The reconstruction protocols were tested using DTI data from 19 normal subjects to examine test-retest reproducibility and cross-subject variability. Fifty-two tracts were found to be reliably reconstructed using this approach, which can be viewed on our website.

Regionally selective atrophy of subcortical structures in prodromal HD as revealed by statistical shape analysis.

Huntington disease (HD) is a neurodegenerative disorder that involves preferential atrophy in the striatal complex and related subcortical nuclei. In this article, which is based on a dataset extracted from the PREDICT-HD study, we use statistical shape analysis with deformation markers obtained through "Large Deformation Diffeomorphic Metric Mapping" of cortical surfaces to highlight specific atrophy patterns in the caudate, putamen, and globus pallidus, at different prodromal stages of the disease. On the basis of the relation to cortico-basal ganglia circuitry, we propose that statistical shape analysis, along with other structural and functional imaging studies, may help expand our understanding of the brain circuitry affected and other aspects of the neurobiology of HD, and also guide the most effective strategies for intervention.

Normal and equivolumetric coordinate systems for cortical areas.

We describe coordinate systems adapted for the space between two surfaces, such as those delineating the highly folded cortex in mammalian brains. These systems are estimated in order to satisfy geometric priors, including streamline normality or equivolumetric conditions on layers. We give a precise mathematical formulation of these problems, and present numerical simulations based on diffeomorphic registration methods, comparing them with recent approaches. Our method involves•Diffeomorphic registration of inner and outer folded folded surfaces.•Followed by equivolumetric reparametrization of layers to yield coordinate system.

Multidimensional Alternating Kernel Method for cortical layer segmentation in 3D reconstructed histology.

The neocortex of the brain can be divided into six layers each with a distinct cell composition and connectivity pattern. Recently, sensory deprivation, including congenital deafness, has been shown to alter cortical structure (e.g. the cortical thickness) of the feline auditory cortex with variable and inconsistent results. Thus, understanding these complex changes will require further study of the constituent cortical layers in three-dimensional space. Further progress crucially depends on the use of objective computational techniques that can reliably characterize spatial properties of the complex cortical structure. Here a method for cortical laminar segmentation is derived and applied to the three-dimensional cortical areas reconstructed from a series of histological sections from four feline brains. In this approach, the Alternating Kernel Method was extended to fit a multi-variate Gaussian mixture model to a feature space consisting of both staining intensity and a biologically plausible equivolumetric depth map. This research method•Extends the Alternating Kernel Method to multi-dimensional feature spaces.•Uses it to segment the cortical layers in reconstructed histology volume. Segmentation features include staining intensity and a biologically plausible equivolumetric depth map.•Validates results in auditory cortical areas of feline brains, two with normal hearing and two with congenital deafness.

Structural-functional correlations between hippocampal volume and cortico-limbic emotional responses in depressed children.

Although hippocampal atrophy and altered functional brain responses to emotional stimuli have been found in major depressive disorder (MDD), the relationship between the two is not yet well understood. The present study focused on children with and without a history of preschool onset MDD (PO-MDD) and directly examined the relations between hippocampal volume and functional brain activation to affect-eliciting stimuli. Children completed annual diagnostic assessments starting at preschool. When children were school-aged, high-resolution structural MRI and task-related functional MRI data were acquired from N = 64 nonmedicated children. During fMRI, subjects were shown emotional faces. Results from the total sample indicated that smaller bilateral hippocampal volumes were associated with greater cortico-limbic (e.g., amygdala, hippocampus, dorsolateral prefrontal cortex) activation to sad or negative faces versus neutral faces. Left hippocampal volume was negatively associated with the cortico-limbic activation in both the PO-MDD and healthy children. Right hippocampal volume was negatively correlated with amygdala responses in the PO-MDD group, but not in the healthy comparison group. These findings suggest that there may be important interrelationships between reduced hippocampal volume and hyperactivation of brain responses in children, both those with and those without a history of PO-MDD.

Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease.

Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.

Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease.

Huntington's disease is caused by a CAG repeat expansion in the Huntingtin gene (HTT), coding for polyglutamine in the Huntingtin protein, with longer CAG repeats causing earlier age of onset. The variable 'Age' × ('CAG'-L), where 'Age' is the current age of the individual, 'CAG' is the repeat length and L is a constant (reflecting an approximation of the threshold), termed the 'CAG Age Product' (CAP) enables the consideration of many individuals with different CAG repeat expansions at the same time for analysis of any variable and graphing using the CAG Age Product score as the X axis. Structural MRI studies have showed that progressive striatal atrophy begins many years prior to the onset of diagnosable motor Huntington's disease, confirmed by longitudinal multicentre studies on three continents, including PREDICT-HD, TRACK-HD and IMAGE-HD. However, previous studies have not clarified the relationship between striatal atrophy, atrophy of other basal ganglia structures, and atrophy of other brain regions. The present study has analysed all three longitudinal datasets together using a single image segmentation algorithm and combining data from a large number of subjects across a range of CAG Age Product score. In addition, we have used a strategy of normalizing regional atrophy to atrophy of the whole brain, in order to determine which regions may undergo preferential degeneration. This made possible the detailed characterization of regional brain atrophy in relation to CAG Age Product score. There is dramatic selective atrophy of regions involved in the basal ganglia circuit-caudate, putamen, nucleus accumbens, globus pallidus and substantia nigra. Most other regions of the brain appear to have slower but steady degeneration. These results support (but certainly do not prove) the hypothesis of circuit-based spread of pathology in Huntington's disease, possibly due to spread of mutant Htt protein, though other connection-based mechanisms are possible. Therapeutic targets related to prion-like spread of pathology or other mechanisms may be suggested. In addition, they have implications for current neurosurgical therapeutic approaches, since delivery of therapeutic agents solely to the caudate and putamen may miss other structures affected early, such as nucleus accumbens and output nuclei of the striatum, the substantia nigra and the globus pallidus.

Effects of protocol and obesity on dose conversion factors in adult body CT.

PURPOSE: In computed tomography (CT), organ dose, effective dose, and risk index can be estimated from volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) using conversion coefficients. Studies have investigated how these coefficients vary across scanner models, scan parameters, and patient size. However, their variability across CT protocols has not been systematically studied. Furthermore, earlier studies of the effect of patient size have not included obese individuals, which currently represent more than one-third of U.S. adults. The purpose of this study was to assess the effects of protocol and obesity on dose and risk conversion coefficients in adult body CT. METHODS: Whole-body computational phantoms were created from clinical CT images of six adult patients (three males, three females), representing normal-weight patients and patients of three obesity classes. Body CT protocols at our institution were selected and categorized into ten examination categories based on anatomical region examined. A validated Monte Carlo program was used to estimate organ dose. Organ dose estimates were normalized by CTDI(vol) and size-specific dose estimate (SSDE) to obtain organ dose conversion coefficients (denoted as h and h(ss) factors, respectively). Assuming each phantom to be 20, 40, and 60 years old, effective dose and risk index were calculated and normalized by DLP to obtain effective dose and risk index conversion coefficients (denoted as k and q factors, respectively). Coefficient of variation was used to quantify the variability of each conversion coefficient across examination categories. The effect of obesity was assessed by comparing each obese phantom with the normal-weight phantom of the same gender. RESULTS: For a given organ, the variability of h factor across examination categories that encompassed the entire organ volume was generally within 15%. However, k factor varied more across examination categories (15%-27%). For all three ages, the variability of q factor was small for male (<10%), but large for female phantoms (21%-43%). Relative to the normal-weight phantoms, the reduction in h factor (an average across fully encompassed organs) was 17%-42%, 17%-40%, and 51%-63% for obese-class-I, obese-class-II, and obese-class-III phantoms, respectively. h(ss) factor was not independent of patient diameter and generally decreased with increasing obesity. Relative to the normal-weight phantoms, the reduction in k factor was 12%-40%, 14%-46%, and 44%-59% for obese-class-I, obese-class-II, and obese-class-III phantoms, respectively. The respective reduction in q factor was 11%-36%, 17%-42%, and 48%-59% at 20 years of age and similar at other ages. CONCLUSIONS: In adult body CT, dose to an organ fully encompassed by the primary radiation beam can be estimated from CTDI(vol) using a protocol-independent conversion coefficient. However, fully encompassed organs only account for 50% ± 19% of k factor and 46% ± 24% of q factor. Dose received by partially encompassed organs is also substantial. To estimate effective dose and risk index from DLP, it is necessary to use conversion coefficients specific to the anatomical region examined. Obesity has a significant effect on dose and risk conversion coefficients, which cannot be predicted using body diameter alone. SSDE-normalized organ dose is not independent of diameter. SSDE itself generally overestimates organ dose for obese patients.

Ontological labels for automated location of anatomical shape differences.

A method for automated location of shape differences in diseased anatomical structures via high resolution biomedical atlases annotated with labels from formal ontologies is described. In particular, a high resolution magnetic resonance image of the myocardium of the human left ventricle was segmented and annotated with structural terms from an extracted subset of the Foundational Model of Anatomy ontology. The atlas was registered to the end systole template of a previous study of left ventricular remodeling in cardiomyopathy using a diffeomorphic registration algorithm. The previous study used thresholding and visual inspection to locate a region of statistical significance which distinguished patients with ischemic cardiomyopathy from those with nonischemic cardiomyopathy. Using semantic technologies and the deformed annotated atlas, this location was more precisely found. Although this study used only a cardiac atlas, it provides a proof-of-concept that ontologically labeled biomedical atlases of any anatomical structure can be used to automate location-based inferences.

Visualization of Speech Perception Analysis via Phoneme Alignment: A Pilot Study.

Objective: Speech tests assess the ability of people with hearing loss to comprehend speech with a hearing aid or cochlear implant. The tests are usually at the word or sentence level. However, few tests analyze errors at the phoneme level. So, there is a need for an automated program to visualize in real time the accuracy of phonemes in these tests. Method: The program reads in stimulus-response pairs and obtains their phonemic representations from an open-source digital pronouncing dictionary. The stimulus phonemes are aligned with the response phonemes via a modification of the Levenshtein Minimum Edit Distance algorithm. Alignment is achieved via dynamic programming with modified costs based on phonological features for insertion, deletions and substitutions. The accuracy for each phoneme is based on the F1-score. Accuracy is visualized with respect to place and manner (consonants) or height (vowels). Confusion matrices for the phonemes are used in an information transfer analysis of ten phonological features. A histogram of the information transfer for the features over a frequency-like range is presented as a phonemegram. Results: The program was applied to two datasets. One consisted of test data at the sentence and word levels. Stimulus-response sentence pairs from six volunteers with different degrees of hearing loss and modes of amplification were analyzed. Four volunteers listened to sentences from a mobile auditory training app while two listened to sentences from a clinical speech test. Stimulus-response word pairs from three lists were also analyzed. The other dataset consisted of published stimulus-response pairs from experiments of 31 participants with cochlear implants listening to 400 Basic English Lexicon sentences via different talkers at four different SNR levels. In all cases, visualization was obtained in real time. Analysis of 12,400 actual and random pairs showed that the program was robust to the nature of the pairs. Conclusion: It is possible to automate the alignment of phonemes extracted from stimulus-response pairs from speech tests in real time. The alignment then makes it possible to visualize the accuracy of responses via phonological features in two ways. Such visualization of phoneme alignment and accuracy could aid clinicians and scientists.

A 7 Tesla Amygdalar-Hippocampal Shape Analysis of Lithium Response in Bipolar Disorder.

Research to discover clinically useful predictors of lithium response in patients with bipolar disorder has largely found them to be elusive. We demonstrate here that detailed neuroimaging may have the potential to fill this important gap in mood disorder therapeutics. Lithium treatment and bipolar disorder have both been shown to affect anatomy of the hippocampi and amygdalae but there is no consensus on the nature of their effects. We aimed to investigate structural surface anatomy changes in amygdala and hippocampus correlated with treatment response in bipolar disorder. Patients with bipolar disorder (N = 14) underwent lithium treatment, were classified by response status at acute and long-term time points, and scanned with 7 Tesla structural MRI. Large Deformation Diffeomorphic Metric Mapping was applied to detect local differences in hippocampal and amygdalar anatomy between lithium responders and non-responders. Anatomy was also compared to 21 healthy comparison participants. A patch of the ventral surface of the left hippocampus was found to be significantly atrophied in non-responders as compared to responders at the acute time point and was associated at a trend-level with long-term response status. We did not detect an association between response status and surface anatomy of the right hippocampus or amygdala. To the best of our knowledge, this is the first shape analysis of hippocampus and amygdala in bipolar disorder using 7 Tesla MRI. These results can inform future work investigating possible neuroimaging predictors of lithium response in bipolar disorder.

An mHealth App (Speech Banana) for Auditory Training: App Design and Development Study.

BACKGROUND: With the growing adult population using electronic hearing devices such as cochlear implants or hearing aids, there is an increasing worldwide need for auditory training (AT) to promote optimal device use. However, financial resources and scheduling conflicts make clinical AT infeasible. OBJECTIVE: To address this gap between need and accessibility, we primarily aimed to develop a mobile health (mHealth) app called Speech Banana for AT. The app would be substantially more affordable and portable than clinical AT; would deliver a validated training model that is reflective of modern techniques; and would track users' progress in speech comprehension, providing greater continuity between periodic in-person visits. To improve international availability, our secondary aim was to implement the English language training model into Korean as a proof of concept for worldwide usability. METHODS: A problem- and objective-centered Design Science Research Methodology approach was adopted to develop the Speech Banana app. A review of previous literature and computer-based learning programs outlined current AT gaps, whereas interviews with speech pathologists and users clarified the features that were addressed in the app. Past and present users were invited to evaluate the app via community forums and the System Usability Scale. RESULTS: Speech Banana has been implemented in English and Korean languages for iPad and web use. The app comprises 38 lessons, which include analytic exercises pairing visual and auditory stimuli, and synthetic quizzes presenting auditory stimuli only. During quizzes, users type the sentence heard, and the app provides visual feedback on performance. Users may select a male or female speaker and the volume of background noise, allowing for training with a range of frequencies and signal-to-noise ratios. There were more than 3200 downloads of the English iPad app and almost 100 downloads of the Korean app; more than 100 users registered for the web apps. The English app received a System Usability Scale rating of "good" from 6 users, and the Korean app received a rating of "OK" from 16 users. CONCLUSIONS: Speech Banana offers AT accessibility with a validated curriculum, allowing users to develop speech comprehension skills with the aid of a mobile device. This mHealth app holds potential as a supplement to clinical AT, particularly in this era of global telemedicine.