An Utterance Verification System for Word Naming Therapy in Aphasia

Anomia (word finding difficulties) is the hallmark of aphasia an acquired language disorder, most commonly caused by stroke. Assessment of speech performance using picture naming tasks is therefore a key method for identification of the disorder and monitoring patient’s response to treatment interventions. Currently, this assessment is conducted manually by speech and language therapists (SLT). Surprisingly, despite advancements in ASR and artificial intelligence with technologies like deep learning, research on developing automated systems for this task has been scarce. Here we present an utterance verification system incorporating a deep learning element that classifies ‘correct’/‘incorrect’ naming attempts from aphasic stroke patients. When tested on 8 native British-English speaking aphasics the system’s performance accuracy ranged between 83.6% to 93.6%, with a 10 fold cross validation mean of 89.5%. This performance was not only significantly better than one of the leading commercially available ASRs (Google speech-to-text service) but also comparable in some instances with two independent SLT ratings for the same dataset

NUVA: A Naming Utterance Verifier for Aphasia Treatment

Anomia (word-finding difficulties) is the hallmark of aphasia, an acquired language disorder most commonly caused by stroke. Assessment of speech performance using picture naming tasks is a key method for both diagnosis and monitoring of responses to treatment interventions by people with aphasia (PWA). Currently, this assessment is conducted manually by speech and language therapists (SLT). Surprisingly, despite advancements in automatic speech recognition (ASR) and artificial intelligence with technologies like deep learning, research on developing automated systems for this task has been scarce. Here we present NUVA, an utterance verification system incorporating a deep learning element that classifies 'correct' versus' incorrect' naming attempts from aphasic stroke patients. When tested on eight native British-English speaking PWA the system's performance accuracy ranged between 83.6% to 93.6%, with a 10-fold cross-validation mean of 89.5%. This performance was not only significantly better than a baseline created for this study using one of the leading commercially available ASRs (Google speech-to-text service) but also comparable in some instances with two independent SLT ratings for the same dataset

Efficacy of a gamified digital therapy for speech production in people with chronic aphasia (iTalkBetter): behavioural and imaging outcomes of a phase II item-randomised clinical trial

Background Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this ‘dosage’ problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them. However, response to therapy is variable and no clinical trial has yet identified the key brain regions required to engage with word-retrieval therapy. Methods Between Sep 7, 2020 and Mar 1, 2022 at University College London in the UK, we carried out a phase II, item-randomised clinical trial in 27 PWA using a novel, self-led app, ‘iTalkBetter’, which utilises confrontation naming therapy. Unlike previously reported apps, it has a real-time utterance verification system that drives its adaptive therapy algorithm. Therapy items were individually randomised to provide balanced lists of ‘trained’ and ‘untrained’ items matched on key psycholinguistic variables and baseline performance. PWA practised with iTalkBetter over a 6-week therapy block. Structural and functional MRI data were collected to identify therapy-related changes in brain states. A repeated-measures design was employed. The trial was registered at ClinicalTrials.gov (NCT04566081). Findings iTalkBetter significantly improved naming ability by 13% for trained items compared with no change for untrained items, an average increase of 29 words (SD = 26) per person; beneficial effects persisted at three months. PWA’s propositional speech also significantly improved. iTalkBetter use was associated with brain volume increases in right auditory and left anterior prefrontal cortices. Task-based fMRI identified dose-related activity in the right temporoparietal junction. Interpretation Our findings suggested that iTalkBetter significantly improves PWAs’ naming ability on trained items. The effect size is similar to a previous RCT of computerised therapy, but this is the first study to show transfer to a naturalistic speaking task. iTalkBetter usage and dose caused observable changes in brain structure and function to key parts of the surviving language perception, production and control networks. iTalkBetter is being rolled-out as an app for all PWA and anomia: https://www.ucl.ac.uk/icn/research/research-groups/neurotherapeutics/projects/digital-interventions-neuro-rehabilitation-0 so that they can increase their dosage of practice-based SLT

Color and stellar population gradients in galaxies. Correlation with mass

We analyze the color gradients (CGs) of ~50000 nearby SDSS galaxies. From synthetic spectral models based on a simplified star formation recipe, we derive the mean spectral properties, and explain the observed radial trends of the color as gradients of the stellar population age and metallicity (Z). The most massive ETGs (M_* > 10^{11} Msun) have shallow CGs in correspondence of shallow (negative) Z gradients. In the stellar mass range 10^(10.3-10.5) < M_* < 10^(11) Msun, the Z gradients reach their minimum of ~ -0.5 dex^{-1}. At M_* ~ 10^{10.3-10.5} Msun, color and Z gradient slopes suddenly change. They turn out to anti-correlate with the mass, becoming highly positive at the very low masses. We have also found that age gradients anti-correlate with Z gradients, as predicted by hierarchical cosmological simulations for ETGs. On the other side, LTGs have gradients which systematically decrease with mass (and are always more negative than in ETGs), consistently with the expectation from gas infall and SN feedback scenarios. Z is found to be the main driver of the trend of color gradients, especially for LTGs, but age gradients are not negligible and seem to play a significant role too. We have been able to highlight that older galaxies have systematically shallower age and Z gradients than younger ones. Our results for high-mass galaxies are in perfect agreement with predictions based on the merging scenario, while the evolution of LTGs and younger and less massive ETGs seems to be mainly driven by infall and SN feedback. (Abridged)Comment: 20 pages, 16 figures, accepted for publication on MNRAS. This version includes revisions after the referee's report

Radial Variation of Optical and Near-Infrared Colours in Luminous Early-Type Galaxies in ABELL 2199

We performed K band surface photometry for luminous early-type galaxies in a nearby rich cluster ABELL 2199. Combining it with B and R band surface photometry, radial variations of B-R and R-K colours in the galaxies were investigated. It is found that the inner regions of the galaxies are redder in both of B-R and R-K colours. Comparing the radial variations of both of the colours with predictions of Simple Stellar Population (SSP) models for a range of ages and metallicities, it is suggested that the cluster ellipticals have negative metallicity gradients but their age gradients are consistent with zero, although our sample is small; the typical metallicity gradient is estimated to be -0.16+- 0.09 in dlogZ/dlogr, while the age gradient is estimated to be -0.10 +- 0.14 in dlog(age)/dlogr. Considering that similar results have also been derived in the other recent studies using samples of ellipticals in the Coma cluster and less dense environments, it seems that there is no strong dependence on galaxy environment in radial gradient of stellar population in elliptical galaxy.Comment: 11 pages, accepted for publication in MNRAS. A version with higher quality figures is available as a PDF file at http://star-www.dur.ac.uk/~naoyuki/a2199brk.pd

White matter hyperintensities and working memory: an explorative study

Contains fulltext : 73317.pdf (publisher's version ) (Closed access)White matter hyperintensities (WMH) are commonly observed in elderly people and may have the most profound effect on executive functions, including working memory. Surprisingly, the Digit Span backward, a frequently employed working memory task, reveals no association with WMH. In the present study, it was investigated whether more detailed analyses of WMH variables and study sample selection are important when establishing a possible relationship between the Digit Span backward and WMH. To accomplish this, the Digit Span backward and additional working memory tests, WMH subscores, and cardiovascular risk factors were examined. The results revealed that performance on the Digit Span backward test is unrelated to WMH, whereas a relationship between other working memory tests and WMH was confirmed. Furthermore, a division between several white matter regions seems important; hyperintensities in the frontal deep white matter regions were the strongest predictor of working memory performance.16 p

Color and Stellar Population Gradients in Passively Evolving Galaxies at z~2 from HST/WFC3 Deep Imaging in the Hubble Ultra Deep Field

We report the detection of color gradients in six massive (stellar mass > 10^{10} M_{sun}) and passively evolving (specific SFR < 10^{-11}/yr) galaxies at redshift 1.3<z<2.5 identified in the HUDF using HST ACS and WFC3/IR images. After matching different PSFs, we obtain color maps and multi-band optical/near-IR photometry (BVizYJH) in concentric annuli, from the smallest resolved radial (~1.7 kpc) up to several times the H-band effective radius. We find that the inner regions of these galaxies have redder rest-frame UV--optical colors than the outer parts. The slopes of the color gradients mildly depend on the overall dust obscuration and rest-frame (U-V) color, with more obscured or redder galaxies having steeper color gradients. The z~2 color gradients are also steeper than those of local early-types. The gradient of a single parameter (age, extinction or metallicity) cannot fully explain the observed color gradients. Fitting spatially resolved HST seven-band photometry to stellar population synthesis models, we find that, regardless of assumptions for metallicity gradient, the redder inner regions of the galaxies have slightly higher dust obscuration than the bluer outer regions, although the magnitude depends on the assumed extinction law. The derived age gradient depends on the assumptions for metallicity gradient. We discuss the implications of a number of assumptions for metallicity gradient on the formation and evolution of these galaxies. We find that the evolution of the mass--size relationship from z~2 to z~0 cannot be driven by in--situ extended star formation, implying that accretion or merger is mostly responsible for the evolution. The lack of a correlation between color gradient and stellar mass argues against the metallicity gradient predicted by the monolithic collapse, which would require significant major mergers to evolve into the one observed at z~0. (Abridged)Comment: Minor changes to address referee's comments, accepted by Ap

The stellar content of the XMM-Newton Bright Serendipitous Survey

Context: The comparison of observed counts in a given sky direction with predictions by Galactic models yields constraints to the spatial distribution and the stellar birthrate of young stellar populations. In this work we present the results of the analysis of the stellar content of the XMM-Newton Bright Serendipitous Survey (XBSS). This unbiased survey includes a total of 58 stellar sources selected in the 0.5 -- 4.5 keV energy band, having a limiting sensitivity of $10^{-2}$ cnt s$^{-1}$ and covering an area of 28.10 sq. deg. Aims: Our main goal is to understand the recent star formation history of the Galaxy in the vicinity of the Sun. Methods: We compare the observations with the predictions obtained with XCOUNT, a model of the stellar X-ray content of the Galaxy. The model predicts the number and properties of the stars to be observed in terms of magnitude, colour, population and $f_\mathrm{x}/f_\mathrm{v}$ ratio distributions of the coronal sources detected with a given instrument and sensitivity in a specific sky direction. Results: As in other shallow surveys, we observe an excess of stars not predicted by our Galaxy model. Comparing the colours of the identified infrared counterparts with the model predictions, we observe that this excess is produced by yellow (G+K) stars. The study of the X-ray spectrum of each source reveals a main population of stars with coronal temperature stratification typical of intermediate-age stars. As no assumptions have been made for the selection of the sample, our results must be representative of the entire Solar Neighbourhood. Some stars show excess circumstellar absorption indicative of youth.Comment: Accepted for publication in Astronomy and Astrophysics: 02/10/200