Comparison of Neurological Activation Patterns of Children with and without Autism Spectrum Disorders When Verbally Responding to a Pragmatic Task

This study examined the neurological activation of children with autism spectrum disorders (ASD) while performing a pragmatic judgment task. In this study, children between the ages of 9 and 15 years responded to questions regarding a social situation, taken from the Comprehensive Assessment of Spoken Language, while concurrently having their brain activity measured. We targeted four brain regions for analysis: dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), superior temporal gyrus (STG), and the inferior parietal lobule (IPL). Ten children with ASD and 20 typically developing (TD) children participated. Matching occurred in a bracketing manner with each child in the ASD group being matched to two control children to account for natural variability. Neuroimgaging was conducted utilizing functional Near‐Infrared Spectroscopy (fNIRS). Oxygenated and deoxygenated blood concentration levels were measured through Near‐Infrared light cap with 44 channels. The cap was placed over frontal lobe and the left lateral cortex. The placement was spatially registered using the Polhemus. Analysis indicated that children in the ASD group performed significantly poorer than their controls on the pragmatic judgment task. Mixed repeated measures analysis of variance of neurological data indicated that the children with ASD had lower concentration levels of oxygenated and total hemoglobin across the four regions. There were significantly higher concentration levels for oxygenated and total hemoglobin in the STG. Analysis of correct and incorrect responses revealed significantly more activation in the OFC when responses were correct. Additionally, there was a significant interaction of Accuracy and Group in left DLPFC. Children with ASD presented higher oxygenated hemoglobin concentration values when responding correctly, while children in the control group presented higher oxygenated hemoglobin concentration values for the incorrect items. Statistical Parametric Mapping was performed for each triad to assess the diffusion of neural activation across the frontal cortex and the left lateral cortex. Individual comparisons revealed that 7 out of 10 children with ASD demonstrated patterns consistent with more diffuse brain activation than their TD controls. Findings from this study suggest that an fNIRS study can provide important information about the level and diffusion of neural processing of verbal children and adolescents with ASD

Speech Processes for Brain-Computer Interfaces

Speech interfaces have become widely used and are integrated in many applications and devices. However, speech interfaces require the user to produce intelligible speech, which might be hindered by loud environments, concern to bother bystanders or the general in- ability to produce speech due to disabilities. Decoding a usera s imagined speech instead of actual speech would solve this problem. Such a Brain-Computer Interface (BCI) based on imagined speech would enable fast and natural communication without the need to actually speak out loud. These interfaces could provide a voice to otherwise mute people. This dissertation investigates BCIs based on speech processes using functional Near In- frared Spectroscopy (fNIRS) and Electrocorticography (ECoG), two brain activity imaging modalities on opposing ends of an invasiveness scale. Brain activity data have low signal- to-noise ratio and complex spatio-temporal and spectral coherence. To analyze these data, techniques from the areas of machine learning, neuroscience and Automatic Speech Recog- nition are combined in this dissertation to facilitate robust classification of detailed speech processes while simultaneously illustrating the underlying neural processes. fNIRS is an imaging modality based on cerebral blood flow. It only requires affordable hardware and can be set up within minutes in a day-to-day environment. Therefore, it is ideally suited for convenient user interfaces. However, the hemodynamic processes measured by fNIRS are slow in nature and the technology therefore offers poor temporal resolution. We investigate speech in fNIRS and demonstrate classification of speech processes for BCIs based on fNIRS. ECoG provides ideal signal properties by invasively measuring electrical potentials artifact- free directly on the brain surface. High spatial resolution and temporal resolution down to millisecond sampling provide localized information with accurate enough timing to capture the fast process underlying speech production. This dissertation presents the Brain-to- Text system, which harnesses automatic speech recognition technology to decode a textual representation of continuous speech from ECoG. This could allow to compose messages or to issue commands through a BCI. While the decoding of a textual representation is unparalleled for device control and typing, direct communication is even more natural if the full expressive power of speech - including emphasis and prosody - could be provided. For this purpose, a second system is presented, which directly synthesizes neural signals into audible speech, which could enable conversation with friends and family through a BCI. Up to now, both systems, the Brain-to-Text and synthesis system are operating on audibly produced speech. To bridge the gap to the final frontier of neural prostheses based on imagined speech processes, we investigate the differences between audibly produced and imagined speech and present first results towards BCI from imagined speech processes. This dissertation demonstrates the usage of speech processes as a paradigm for BCI for the first time. Speech processes offer a fast and natural interaction paradigm which will help patients and healthy users alike to communicate with computers and with friends and family efficiently through BCIs

Human central auditory plasticity: A review of functional nearâ infrared spectroscopy (fNIRS) to measure cochlear implant performance and tinnitus perception

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146915/1/lio2185_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146915/2/lio2185.pd

Neural Activity During Audiovisual Speech Processing: Protocol For a Functional Neuroimaging Study.

BACKGROUND The field of health information management (HIM) focuses on the protection and management of health information from a variety of sources. The American Health Information Management Association (AHIMA) Council for Excellence in Education (CEE) determines the needed skills and competencies for this field. AHIMA's HIM curricula competencies are divided into several domains among the associate, undergraduate, and graduate levels. Moreover, AHIMA's career map displays career paths for HIM professionals. What is not known is whether these competencies and the career map align with industry demands. OBJECTIVE The primary aim of this study is to analyze HIM job postings on a US national job recruiting website to determine whether the job postings align with recognized HIM domains, while the secondary aim is to evaluate the AHIMA career map to determine whether it aligns with the job postings. METHODS A national job recruitment website was mined electronically (web scraping) using the search term "health information management." This cross-sectional inquiry evaluated job advertisements during a 2-week period in 2021. After the exclusion criteria, 691 job postings were analyzed. Data were evaluated with descriptive statistics and natural language processing (NLP). Soft cosine measures (SCM) were used to determine correlations between job postings and the AHIMA career map, curricular competencies, and curricular considerations. ANOVA was used to determine statistical significance. RESULTS Of all the job postings, 29% (140/691) were in the Southeast, followed by the Midwest (140/691, 20%), West (131/691,19%), Northeast (94/691, 14%), and Southwest (73/691, 11%). The educational levels requested were evenly distributed between high school diploma (219/691, 31.7%), associate degree (269/691, 38.6%), or bachelor's degree (225/691, 32.5%). A master's degree was requested in only 8% (52/691) of the postings, with 72% (42/58) preferring one and 28% (16/58) requiring one. A Registered Health Information Technologist (RHIT) credential was the most commonly requested (207/691, 29.9%) in job postings, followed by Registered Health Information Administrator (RHIA; 180/691, 26%) credential. SCM scores were significantly higher in the informatics category compared to the coding and revenue cycle (P=.006) and data analytics categories (P<.001) but not significantly different from the information governance category (P=.85). The coding and revenue cycle category had a significantly higher SCM score compared to the data analytics category (P<.001). Additionally, the information governance category was significantly higher than the data analytics category (P<.001). SCM scores were significantly different between each competency category, except there were no differences in the average SCM score between the information protection and revenue cycle management categories (P=.96) and the information protection and data structure, content, and information governance categories (P=.31). CONCLUSIONS Industry job postings primarily sought a high school diploma and associate degrees, with a master's degree a distant third. NLP analysis of job postings suggested that the correlation between the informatics category and job postings was higher than that of the coding, revenue cycle, and data analytics categories. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/38407

Temporal Mapping and Connectivity using NIRS for Language Related Tasks

Near infrared spectroscopy (NIRS) is an emerging neuroimaging modality with high temporal and good spatial resolution. In this thesis, NIRS was applied to understand functionality of the fronto-temporal cortex in response to language-related tasks. A 32-channel NIRS system (Imagent ISS Inc.) was used to perform experimental studies on 15 right-handed normal adults. Block-design based Word Expression and Word Reception paradigms were independently presented to participants. Activation, functional connectivity and cortical lateralization analyses were performed. From word expression studies, results showed left anterior region (encompassing Broca) is majorly involved over right homologue and posterior regions. From the word reception studies, results showed that right posterior region (encompassing right homologue of Wernicke) is highly involved in language reception, with right anterior region (encompassing right homologue of Broca) also involved. The current study has potential future applications in surgical evaluation of language regions in populations with neurological disorders such as epilepsy, and schizophrenia

Executive Functioning and Brain Activation in Young Monolingual and Bilingual Children: An fNIRS Study

Over the past 40 years, the prevalence of bilingualism in the United States has increased. As bilingualism is increasing, it is important to examine potential benefits or drawbacks that early household bilingual exposure has on child development and how bilingualism may facilitate those benefits or drawbacks. This study included 5 monolingual and 6 bilingual children and compared differences in brain activation location and executive functioning skills. Results from this project show a trend of activation differences where the monolingual children had less activation of the middle area of the prefrontal cortex while there was similar activation in both the left and right side of the prefrontal cortex for both groups. Also shown is a pattern of better performance on the executive functioning tasks for the bilingual group. This could potentially be explained by the greater use of that middle area of the prefrontal cortex for the bilingual group compared to the monolingual group. The implications of this project suggest that there may be differences in abilities between bilingual and monolingual children and warrant further exploration of these trends

Differences in cortical activation with live music compared to recorded music: an fNIRS study

2020 Spring.Includes bibliographical references.The purpose of this study was to compare and assess the neural activations during live music and recorded music engagement in neurotypical adults aged eighteen to sixty years old within a social context. The research questions sought to answer if cortical activations in areas of the brain involved with social interaction would be different in the live music conditions compared to the recorded music conditions and if blood oxygenation levels across the entire cortical surface would be different in any area across the four conditions. This study was a within-subjects quasi-experimental design where each of the 32 recruited participants were exposed to all four conditions while mirroring the CR (clinician-researcher) in a tapping task. The four conditions were: recorded sung, recorded spoken, live sung, and live spoken. Participants were exposed to the four conditions as well as a rest condition in pseudo-randomized order. Each participant underwent five trials of each condition using a block design. Cortical activation was measured using functional near-infrared spectroscopy (fNIRS). A total of 27 participants were included in the analyses. Imaging results revealed significant differences in inferred cortical activation during live stimuli compared to recorded stimuli, live music compared to recorded music, music stimuli compared to non-music stimuli, live music compared to all other conditions, and live spoken stimuli compared to recorded spoken stimuli in brain regions of interest and globally. Results support the possibility that live music may have a greater effect than recorded music in regions of the brain that process social responses. Future research could better illuminate the comparisons of neural activations between live and recorded auditory stimuli

Neuronal Correlates of Diacritics and an Optimization Algorithm for Brain Mapping and Detecting Brain Function by way of Functional Magnetic Resonance Imaging

The purpose of this thesis is threefold: 1) A behavioral examination of the role of diacritics in Arabic, 2) A functional magnetic resonance imaging (fMRI) investigative study of diacritics in Arabic, and 3) An optimization algorithm for brain mapping and detecting brain function. Firstly, the role of diacritics in Arabic was examined behaviorally. The stimulus was a lexical decision task (LDT) that constituted of low, mid, and high frequency words and nonwords; with and without diacritics. Results showed that the presence of vowel diacritics slowed reaction time but did not affect word recognition accuracy. The longer reaction times for words with diacritics versus without diacritics suggest that the diacritics may contribute to differences in word recognition strategies. Secondly, an Event-related fMRI experiment of lexical decisions associated with real words with versus without diacritics in Arabic readers was done. Real words with no diacritics yielded shorter response times and stronger activation than with real words with diacritics in the hippocampus and middle temporal gyrus possibly reflecting a search from among multiple meanings associated with these words in a semantic store. In contrast, real words with diacritics had longer response times than real words without diacritics and activated the insula and frontal areas suggestive of phonological and semantic mediation in lexical retrieval. Both the behavioral and fMRI results in this study appear to support a role for diacritics in reading in Arabic. The third research work in this thesis is an optimization algorithm for fMRI data analysis. Current data-driven approaches for fMRI data analysis, such as independent component analysis (ICA), rely on algorithms that may have low computational expense, but are much more prone to suboptimal results. In this work, a genetic algorithm (GA) based on a clustering technique was designed, developed, and implemented for fMRI ICA data analysis. Results for the algorithm, GAICA, showed that although it might be computationally expensive; it provides global optimum convergence and results. Therefore, GAICA can be used as a complimentary or supplementary technique for brain mapping and detecting brain function by way of fMRI