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- Title
- An Investigation of the Effects of Neurofeedback Training on Attention Deficit-Hyperactivity Disorder (ADHD) Symptoms, Depression, Anxiety, and Academic Self-Efficacy in College Students.
- Creator
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Harris, Shaywanna, Lambie, Glenn, Hundley, Gulnora, Kelchner, Viki, Bai, Haiyan, University of Central Florida
- Abstract / Description
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College students diagnosed with Attention Deficit-Hyperactivity Disorder (ADHD) are at an increased risk of depression, anxiety, and lower academic self-efficacy as compared to college students not diagnosed with ADHD. Additionally, college students with ADHD diagnoses struggle to obtain effective treatment options for their ADHD symptoms. Specifically, pharmacological interventions are effective in mitigating ADHD symptoms; however, adverse effects of stimulant medications (i.e., increased...
Show moreCollege students diagnosed with Attention Deficit-Hyperactivity Disorder (ADHD) are at an increased risk of depression, anxiety, and lower academic self-efficacy as compared to college students not diagnosed with ADHD. Additionally, college students with ADHD diagnoses struggle to obtain effective treatment options for their ADHD symptoms. Specifically, pharmacological interventions are effective in mitigating ADHD symptoms; however, adverse effects of stimulant medications (i.e., increased/decreased appetite, headache) impact medication adherence in college students with ADHD. Neurofeedback is a non-invasive, drug-free intervention that uses the theories of biofeedback and cybernetics to increase self-regulation of brain functions. The purpose of this dissertation study was to examine differences in college student participants' scores on inattention, hyperactivity, impulsivity, self-concept, depression, anxiety, and self-efficacy measures over time when exposed to the neurofeedback intervention. The researcher employed a quasi-experimental, one group, time series design to explore differences in levels of symptomology in 11 participants over four assessment points. The results identified participants' scores in inattention (p = .016), hyperactivity (p = .017), self-concept (p = .008), depression (p = .004), and anxiety (p = .018) significantly decreased of the course of the intervention (16 neurofeedback sessions). Moreover, the participants' self-reported levels of academic self-efficacy increased significantly over time (p (<) .001). The findings for the current study provide practical, professional, and public policy implications, expanding the neurofeedback training and ADHD literature.
Show less - Date Issued
- 2017
- Identifier
- CFE0006600, ucf:51271
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006600
- Title
- EFFICACY AND TOLERABILITY OF ATOMOXETINE USE FOR PATIENTS WITH AUTISM SPECTRUM DISORDERS AND ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) SYMPTOMS: A SYSTEMATIC REVIEW AND META-ANALYSIS.
- Creator
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El-Said, Angie, Cheng, Zixi, University of Central Florida
- Abstract / Description
-
Introduction: Patients with autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD) show more symptoms of ADHD. Since there are more adverse events caused by psychostimulants compared to non-psychostimulants, the use of a non-psychostimulant such as atomoxetine might prove more beneficial for younger patients and/or those with comorbid ADHD. Objective: The aim of this thesis is to determine the efficacy and tolerability of atomoxetine in ASD patients presenting...
Show moreIntroduction: Patients with autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD) show more symptoms of ADHD. Since there are more adverse events caused by psychostimulants compared to non-psychostimulants, the use of a non-psychostimulant such as atomoxetine might prove more beneficial for younger patients and/or those with comorbid ADHD. Objective: The aim of this thesis is to determine the efficacy and tolerability of atomoxetine in ASD patients presenting with ADHD, by examining (a) differences in ADHD symptoms for participants receiving atomoxetine versus those receiving placebos, and (b) risk differences in adverse events between these participants. Methods: An electronic search of both PubMed.gov and ClinicalTrials.gov were conducted. To be deemed eligible, studies had to (a) be randomized, double-blind, placebo-controlled trials comparing atomoxetine with a placebo, (b) administer atomoxetine for at least 1 week, and (c) include data on either ADHD outcomes or adverse events. Effect sizes for ADHD outcomes were calculated using Cohen's d, whereas risk differences were calculated for adverse events. For each of these two meta-analyses, effect sizes were aggregated across studies using a random effects method. Results: Overall ADHD outcomes were better for participants who received atomoxetine than for participants who received placebo, =0.297. Participants who received atomoxetine also demonstrated better outcomes in terms of attention and hyperactivity-impulsivity symptoms, =0.345 and 0.393, respectively. Though there were more adverse events for patients taking atomoxetine than placebo, the results were not statistically significant. Discussion: This thesis extends the findings of previous meta-analyses of pharmacological treatments for ASD and ADHD, while addressing the concerns raised in the critique of existing meta-analyses presented in this thesis, e.g., limited studies, length of treatment weeks, and dichotomization of data. It provides evidence that atomoxetine improves ADHD symptoms, with an overall frequency of adverse events that did not sufficiently differ from placebo beyond chance.
Show less - Date Issued
- 2019
- Identifier
- CFH2000534, ucf:45644
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000534
- Title
- HYPERACTIVITY IN BOYS WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER: A UBIQUITOUS CORE SYMPTOM OR MANIFESTATION OF WORKING MEMORY DEFICITS?.
- Creator
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Bolden, Jennifer, Rapport, Mark, University of Central Florida
- Abstract / Description
-
Hyperactivity is currently considered a core and ubiquitous feature of attention-deficit/hyperactivity disorder (ADHD); however, an alternative model challenges this premise and hypothesizes a functional relationship between working memory (WM) and activity level. The current study investigated whether children's activity level is functionally related to WM demands associated with the domain-general central executive and subsidiary storage/rehearsal components using tasks based on...
Show moreHyperactivity is currently considered a core and ubiquitous feature of attention-deficit/hyperactivity disorder (ADHD); however, an alternative model challenges this premise and hypothesizes a functional relationship between working memory (WM) and activity level. The current study investigated whether children's activity level is functionally related to WM demands associated with the domain-general central executive and subsidiary storage/rehearsal components using tasks based on Baddeley's (2007) WM model. Activity level was objectively measured 16 times per second using wrist- and ankle-worn actigraphs while 23 boys between 8 and 12 years of age completed control tasks and visuospatial/phonological WM tasks of increasing memory demands. All children exhibited significantly higher activity rates under all WM relative to control conditions, and children with ADHD (n=12) moved significantly more than typically developing children (n=11) under all conditions. Activity level in all children was associated with central executive but not storage/rehearsal functioning, and higher activity rates exhibited by children with ADHD under control conditions were fully attenuated by removing variance directly related to central executive processes.
Show less - Date Issued
- 2008
- Identifier
- CFE0002455, ucf:47702
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002455
- Title
- IMPROVING FMRI CLASSIFICATION THROUGH NETWORK DECONVOLUTION.
- Creator
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Martinek, Jacob, Zhang, Shaojie, University of Central Florida
- Abstract / Description
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The structure of regional correlation graphs built from fMRI-derived data is frequently used in algorithms to automatically classify brain data. Transformation on the data is performed during pre-processing to remove irrelevant or inaccurate information to ensure that an accurate representation of the subject's resting-state connectivity is attained. Our research suggests and confirms that such pre-processed data still exhibits inherent transitivity, which is expected to obscure the true...
Show moreThe structure of regional correlation graphs built from fMRI-derived data is frequently used in algorithms to automatically classify brain data. Transformation on the data is performed during pre-processing to remove irrelevant or inaccurate information to ensure that an accurate representation of the subject's resting-state connectivity is attained. Our research suggests and confirms that such pre-processed data still exhibits inherent transitivity, which is expected to obscure the true relationships between regions. This obfuscation prevents known solutions from developing an accurate understanding of a subject's functional connectivity. By removing correlative transitivity, connectivity between regions is made more specific and automated classification is expected to improve. The task of utilizing fMRI to automatically diagnose Attention Deficit/Hyperactivity Disorder was posed by the ADHD-200 Consortium in a competition to draw in researchers and new ideas from outside of the neuroimaging discipline. Researchers have since worked with the competition dataset to produce ever-increasing detection rates. Our approach was empirically tested with a known solution to this problem to compare processing of treated and untreated data, and the detection rates were shown to improve in all cases with a weighted average increase of 5.88%.
Show less - Date Issued
- 2015
- Identifier
- CFH0004895, ucf:45410
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004895
- Title
- ADHD AND STOP-SIGNAL BEHAVIORAL INHIBITION: IS MEAN REACTION TIME CONTAMINATED BY EXPOSURE TO INTERMITTENT STOP-SIGNALS?.
- Creator
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Alderson, Robert, Rapport, Mark, University of Central Florida
- Abstract / Description
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The current study investigates two recently identified threats to the construct validity of behavioral inhibition as a core deficit of attention-deficit/hyperactivity disorder (ADHD) based on the Stop-signal task: calculation of mean reaction time from go-trials presented adjacent to intermittent stop-trials, and non-reporting of the stop-signal delay metric. Children with ADHD (n=12) and typically developing children (TD) (n=11) were administered the standard stop-signal task and three...
Show moreThe current study investigates two recently identified threats to the construct validity of behavioral inhibition as a core deficit of attention-deficit/hyperactivity disorder (ADHD) based on the Stop-signal task: calculation of mean reaction time from go-trials presented adjacent to intermittent stop-trials, and non-reporting of the stop-signal delay metric. Children with ADHD (n=12) and typically developing children (TD) (n=11) were administered the standard stop-signal task and three variant stop-signal conditions. These included a No-Tone condition administered without the presentation of an auditory tone; an Ignore-Tone condition that presented a neutral (i.e., not associated with stopping) auditory tone; and a second Ignore-Tone condition that presented a neutral auditory tone after the tone had been previously paired with stopping. Children with ADHD exhibited significantly slower and more variable reaction times to go-stimuli, and slower stop-signal reaction times (SSRT) relative to TD controls. Stop-signal delay (SSD) was not significantly different between groups, and both groups' go-trial reaction times slowed following meaningful tones. Collectively, these findings corroborate recent meta-analyses and indicate that previous findings of stop-signal performance deficits in ADHD reflect slower and more variable responding to visually presented stimuli and concurrent processing of a second stimulus, rather than deficits of motor behavioral inhibition.
Show less - Date Issued
- 2008
- Identifier
- CFE0002218, ucf:47881
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002218
- Title
- Applied problem solving in children with ADHD: The mediating roles of working memory and mathematical calculation.
- Creator
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Friedman, Lauren, Rapport, Mark, Beidel, Deborah, Vasquez, Eleazar, University of Central Florida
- Abstract / Description
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The difficulties children with ADHD experience solving applied math problems (i.e., word problems) are well documented; however, the independent and/or interactive contribution of cognitive processes underlying these difficulties is not fully understood and warrant scrutiny. The current study examines two primary cognitive processes integral to children's ability to solve applied math problems: working memory (WM) and math calculation ability (i.e., the ability to utilize specific facts,...
Show moreThe difficulties children with ADHD experience solving applied math problems (i.e., word problems) are well documented; however, the independent and/or interactive contribution of cognitive processes underlying these difficulties is not fully understood and warrant scrutiny. The current study examines two primary cognitive processes integral to children's ability to solve applied math problems: working memory (WM) and math calculation ability (i.e., the ability to utilize specific facts, skills, or processes related to basic math operations stored in long-term memory). Thirty-six boys with ADHD-combined presentation and 33 typically developing (TD) boys aged 8-12 years old were administered multiple counterbalanced tasks to assess upper (central executive [CE]) and lower level (phonological [PH STM] and visuospatial [VS STM] short-term memory) WM processes, and standardized measures of mathematical abilities. Bias-corrected, bootstrapped mediation analyses revealed that CE ability fully mediated between-group differences in applied problem solving whereas math calculation ability partially mediated the relation. Neither PH STM nor VS STM was a significant mediator. When modeled together via serial mediation analysis, CE in tandem with math calculation ability fully mediated the relation, explained 79% of the variance, and provided a more parsimonious explication of ADHD-related deficits in applied math ability. Results suggest that interventions designed to address applied math difficulties in children with ADHD will likely benefit from targeting basic knowledge of math facts and skills while simultaneously promoting the active interplay among these skills and CE processes.
Show less - Date Issued
- 2017
- Identifier
- CFE0006593, ucf:51300
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006593
- Title
- Inattentive behavior in boys with ADHD during classroom instruction: The mediating role of working memory processes.
- Creator
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Orban, Sarah, Rapport, Mark, Beidel, Deborah, Cassisi, Jeffrey, University of Central Florida
- Abstract / Description
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Children with ADHD exhibit clinically impairing inattentive behavior during classroom instruction and other cognitively demanding contexts. However, there have been surprisingly few attempts to validate anecdotal parent/teacher reports of intact sustained attention during 'preferred' activities such as watching movies. The current investigation addresses this omission, and provides an initial test of how ADHD-related working memory deficits contribute to inattentive behavior during classroom...
Show moreChildren with ADHD exhibit clinically impairing inattentive behavior during classroom instruction and other cognitively demanding contexts. However, there have been surprisingly few attempts to validate anecdotal parent/teacher reports of intact sustained attention during 'preferred' activities such as watching movies. The current investigation addresses this omission, and provides an initial test of how ADHD-related working memory deficits contribute to inattentive behavior during classroom instruction. Boys ages 8-12 (M=9.62, SD=1.22) with ADHD (n=32) and typically developing children (TD; n=30) completed a counterbalanced series of working memory tests and two videos on separate assessment days: an analogue math instructional video, and a non-instructional video selected to match the content and cognitive demands of parent/teacher-described 'preferred' activities. Objective, reliable observations of attentive behavior revealed no between-group differences during the non-instructional video (d=-0.02), and attentive behavior during the non-instructional video was unrelated to all working memory variables (r=-.11 to .19,ns). In contrast, the ADHD group showed disproportionate attentive behavior decrements during analogue classroom instruction (d=-0.71). Bias-corrected, bootstrapped, serial mediation revealed that 59% of this between-group difference was attributable to ADHD-related impairments in central executive working memory, both directly (ER=41%) and indirectly via its role in coordinating phonological short-term memory (ER=15%). Between-group attentive behavior differences were no longer detectable after accounting for ADHD-related working memory impairments (d=-0.29, ns). Results confirm anecdotal reports of intact sustained attention during activities that place minimal demands on working memory, and indicate that ADHD children's inattention during analogue classroom instruction is related, in large part, to their underdeveloped working memory abilities.
Show less - Date Issued
- 2017
- Identifier
- CFE0006633, ucf:51290
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006633
- Title
- Reading comprehension deficits in children with ADHD: The mediating roles of working memory and orthographic conversion.
- Creator
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Friedman, Lauren, Rapport, Mark, Beidel, Deborah, Vasquez, Eleazar, University of Central Florida
- Abstract / Description
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Reading comprehension deficits in children with ADHD are well-established; however, limited information exists concerning the cognitive mechanisms that contribute to these deficits and the extent to which they interact with one another. The current study examines two broad cognitive processes known to be involved in children's reading comprehension abilities(-)(a) working memory (i.e., central executive processes [CE], phonological short-term memory [PH STM], and visuospatial short-term...
Show moreReading comprehension deficits in children with ADHD are well-established; however, limited information exists concerning the cognitive mechanisms that contribute to these deficits and the extent to which they interact with one another. The current study examines two broad cognitive processes known to be involved in children's reading comprehension abilities(-)(a) working memory (i.e., central executive processes [CE], phonological short-term memory [PH STM], and visuospatial short-term memory [VS STM]) and (b) orthographic conversion(-)to elucidate their unique and interactive contribution to ADHD-related reading comprehension deficits. Thirty-one children with ADHD and 30 typically developing (TD) children aged 8 to 12 years (M = 9.64, SD = 1.22) were administered multiple counterbalanced tasks assessing WM and orthographic conversion processes. Relative to TD children, children with ADHD exhibited significant deficits in PH STM (d = -0.66), VS STM (d = -0.84), CE (d = -1.24) and orthographic conversion (d = -0.85). Bias-corrected, bootstrapped mediation analyses revealed that CE and orthographic conversion processes modeled separately, partially mediated ADHD-related reading comprehension impairments, whereas PH STM and VS STM did not. CE and orthographic conversion modeled jointly fully mediated ADHD-related reading comprehension deficits wherein orthographic conversion's large magnitude influence on reading comprehension occurred indirectly through CE's impact on the orthographic system. The findings suggest that adaptive cognitive interventions designed to improve reading-related outcomes in children with ADHD may benefit by including modules that train CE and orthographic conversion processes independently and interactively.
Show less - Date Issued
- 2016
- Identifier
- CFE0006103, ucf:51210
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006103
- Title
- HOW SYMPTOMS OF ANXIETY, DEPRESSION, ATTENTION DEFICIT DISORDER (ADD) OR ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD) CONTRIBUTE TO STUDENTS SELF-MEDICATING VIA MARIJUANA AND NON-MEDICAL PRESCRIPTION DRUGS.
- Creator
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Thomas, Maria, Donley, Dr. Amy, University of Central Florida
- Abstract / Description
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This study examines student's nonmedical prescription drug (NMPD) and marijuana use and whether anxiety, depression, ADD or ADHD symptoms are associated with their use and if students are self-medicating to alleviate symptoms. The method of obtaining this information was provided by a total of 278 college students who voluntarily and anonymously completed a Web-based survey. This study fills in the gaps of previous research and reveals the most frequent NMPD's used by students and their...
Show moreThis study examines student's nonmedical prescription drug (NMPD) and marijuana use and whether anxiety, depression, ADD or ADHD symptoms are associated with their use and if students are self-medicating to alleviate symptoms. The method of obtaining this information was provided by a total of 278 college students who voluntarily and anonymously completed a Web-based survey. This study fills in the gaps of previous research and reveals the most frequent NMPD's used by students and their overall perceptions of their intended effects of the drug and answers why students do not seek professional help for their anxiety, depression and impulsivity symptoms. Results from the survey indicate that students who report NMPD use self- reported higher symptoms of anxiety, depression and impulsivity. NMPD users reported higher percentages of other substance abuse compared to nonusers. The most prominent NMPD's used by students are Adderall and Vicoden or Codeine. Data also indicates student's primary reasons for their NMPD use are related to academic purposes; as opposed to nonacademic. This analysis is further supported by the fact that the majority of NMPD users did not use before they began college and do not use while classes are not is session. Furthermore, students perceive their overall intended effects of their NMPD use to be beneficial, despite the known risks associated with their drug use. By examining college student's current NMPD use we can provide alternative solutions to students who are self-medicating as a coping mechanism for underlying issues or mental health disorders. Also, we can provide them with the necessary services in order to address their problems professionally.
Show less - Date Issued
- 2013
- Identifier
- CFH0004445, ucf:45114
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004445
- Title
- Automatic Detection of Brain Functional Disorder Using Imaging Data.
- Creator
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Dey, Soumyabrata, Shah, Mubarak, Jha, Sumit, Hu, Haiyan, Weeks, Arthur, Rao, Ravishankar, University of Central Florida
- Abstract / Description
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Recently, Attention Deficit Hyperactive Disorder (ADHD) is getting a lot of attention mainly for two reasons. First, it is one of the most commonly found childhood behavioral disorders. Around 5-10% of the children all over the world are diagnosed with ADHD. Second, the root cause of the problem is still unknown and therefore no biological measure exists to diagnose ADHD. Instead, doctors need to diagnose it based on the clinical symptoms, such as inattention, impulsivity and hyperactivity,...
Show moreRecently, Attention Deficit Hyperactive Disorder (ADHD) is getting a lot of attention mainly for two reasons. First, it is one of the most commonly found childhood behavioral disorders. Around 5-10% of the children all over the world are diagnosed with ADHD. Second, the root cause of the problem is still unknown and therefore no biological measure exists to diagnose ADHD. Instead, doctors need to diagnose it based on the clinical symptoms, such as inattention, impulsivity and hyperactivity, which are all subjective.Functional Magnetic Resonance Imaging (fMRI) data has become a popular tool to understand the functioning of the brain such as identifying the brain regions responsible for different cognitive tasks or analyzing the statistical differences of the brain functioning between the diseased and control subjects. ADHD is also being studied using the fMRI data. In this dissertation we aim to solve the problem of automatic diagnosis of the ADHD subjects using their resting state fMRI (rs-fMRI) data.As a core step of our approach, we model the functions of a brain as a connectivity network, which is expected to capture the information about how synchronous different brain regions are in terms of their functional activities. The network is constructed by representing different brain regions as the nodes where any two nodes of the network are connected by an edge if the correlation of the activity patterns of the two nodes is higher than some threshold. The brain regions, represented as the nodes of the network, can be selected at different granularities e.g. single voxels or cluster of functionally homogeneous voxels. The topological differences of the constructed networks of the ADHD and control group of subjects are then exploited in the classification approach.We have developed a simple method employing the Bag-of-Words (BoW) framework for the classification of the ADHD subjects. We represent each node in the network by a 4-D feature vector: node degree and 3-D location. The 4-D vectors of all the network nodes of the training data are then grouped in a number of clusters using K-means; where each such cluster is termed as a word. Finally, each subject is represented by a histogram (bag) of such words. The Support Vector Machine (SVM) classifier is used for the detection of the ADHD subjects using their histogram representation. The method is able to achieve 64% classification accuracy.The above simple approach has several shortcomings. First, there is a loss of spatial information while constructing the histogram because it only counts the occurrences of words ignoring the spatial positions. Second, features from the whole brain are used for classification, but some of the brain regions may not contain any useful information and may only increase the feature dimensions and noise of the system. Third, in our study we used only one network feature, the degree of a node which measures the connectivity of the node, while other complex network features may be useful for solving the proposed problem.In order to address the above shortcomings, we hypothesize that only a subset of the nodes of the network possesses important information for the classification of the ADHD subjects. To identify the important nodes of the network we have developed a novel algorithm. The algorithm generates different random subset of nodes each time extracting the features from a subset to compute the feature vector and perform classification. The subsets are then ranked based on the classification accuracy and the occurrences of each node in the top ranked subsets are measured. Our algorithm selects the highly occurring nodes for the final classification. Furthermore, along with the node degree, we employ three more node features: network cycles, the varying distance degree and the edge weight sum. We concatenate the features of the selected nodes in a fixed order to preserve the relative spatial information. Experimental validation suggests that the use of the features from the nodes selected using our algorithm indeed help to improve the classification accuracy. Also, our finding is in concordance with the existing literature as the brain regions identified by our algorithms are independently found by many other studies on the ADHD. We achieved a classification accuracy of 69.59% using this approach. However, since this method represents each voxel as a node of the network which makes the number of nodes of the network several thousands. As a result, the network construction step becomes computationally very expensive. Another limitation of the approach is that the network features, which are computed for each node of the network, captures only the local structures while ignore the global structure of the network.Next, in order to capture the global structure of the networks, we use the Multi-Dimensional Scaling (MDS) technique to project all the subjects from an unknown network-space to a low dimensional space based on their inter-network distance measures. For the purpose of computing distance between two networks, we represent each node by a set of attributes such as the node degree, the average power, the physical location, the neighbor node degrees, and the average powers of the neighbor nodes. The nodes of the two networks are then mapped in such a way that for all pair of nodes, the sum of the attribute distances, which is the inter-network distance, is minimized. To reduce the network computation cost, we enforce that the maximum relevant information is preserved with minimum redundancy. To achieve this, the nodes of the network are constructed with clusters of highly active voxels while the activity levels of the voxels are measured based on the average power of their corresponding fMRI time-series. Our method shows promise as we achieve impressive classification accuracies (73.55%) on the ADHD-200 data set. Our results also reveal that the detection rates are higher when classification is performed separately on the male and female groups of subjects.So far, we have only used the fMRI data for solving the ADHD diagnosis problem. Finally, we investigated the answers of the following questions. Do the structural brain images contain useful information related to the ADHD diagnosis problem? Can the classification accuracy of the automatic diagnosis system be improved combining the information of the structural and functional brain data? Towards that end, we developed a new method to combine the information of structural and functional brain images in a late fusion framework. For structural data we input the gray matter (GM) brain images to a Convolutional Neural Network (CNN). The output of the CNN is a feature vector per subject which is used to train the SVM classifier. For the functional data we compute the average power of each voxel based on its fMRI time series. The average power of the fMRI time series of a voxel measures the activity level of the voxel. We found significant differences in the voxel power distribution patterns of the ADHD and control groups of subjects. The Local binary pattern (LBP) texture feature is used on the voxel power map to capture these differences. We achieved 74.23% accuracy using GM features, 77.30% using LBP features and 79.14% using combined information.In summary this dissertation demonstrated that the structural and functional brain imaging data are useful for the automatic detection of the ADHD subjects as we achieve impressive classification accuracies on the ADHD-200 data set. Our study also helps to identify the brain regions which are useful for ADHD subject classification. These findings can help in understanding the pathophysiology of the problem. Finally, we expect that our approaches will contribute towards the development of a biological measure for the diagnosis of the ADHD subjects.
Show less - Date Issued
- 2014
- Identifier
- CFE0005786, ucf:50060
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005786
- Title
- THE IMPACT OF MEDITATION AND MINDFULNESS IN THE ELEMENTARY CLASSROOM: A REVIEW OF RESEARCH LITERATURE ACROSS FIVE DISCIPLINES.
- Creator
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Routhier-Martin, Kayli, Killingsworth Roberts, Sherron, University of Central Florida
- Abstract / Description
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Mindfulness meditation programs, benefits, and outcomes were examined through research previously conducted and published by professionals within five differing disciplines: health and wellness, psychology, elementary education, exceptional education, and medicine. The goal was to find common themes within the differing disciplines in order to gather information about the effectiveness of a mindfulness meditation program to be used in an elementary classroom. In this thesis, the chapter of...
Show moreMindfulness meditation programs, benefits, and outcomes were examined through research previously conducted and published by professionals within five differing disciplines: health and wellness, psychology, elementary education, exceptional education, and medicine. The goal was to find common themes within the differing disciplines in order to gather information about the effectiveness of a mindfulness meditation program to be used in an elementary classroom. In this thesis, the chapter of Health and Wellness is a review of literature that tells the benefits found within meditators, which are not found within non-meditators. The chapter of Psychology explains the social-emotional needs of students, the causes of stress and anxieties amongst students, and the benefits that meditation provides in order to counter the negative effects of stress, anxiety, poverty, etc. The chapter of Elementary Education reviews research literature on the existing mindfulness meditation programs within the United States. This chapter also describes the implementation of such a program in an elementary school, as well as the documented data of the outcomes of the programs. The chapter of Exceptional Education is a review of the research literature on the benefits mindfulness meditation has on students with exceptionalities, such as specific learning disabilities, attention deficit hyperactivity disorder, and autism spectrum disorder. The chapter of Medicine is a retelling of previously published scholarly articles that list the neurological benefits of meditation, and also references the negative side effects to the currently prescribed medications that are being used in the treatment of ADHD.
Show less - Date Issued
- 2015
- Identifier
- CFH0004877, ucf:45424
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004877
