26 research outputs found
An fMRI study of intra-individual functional topography in thehuman cerebellum.
Abstract. Neuroimaging studies report cerebellar activation during both motor and non-motor paradigms, and suggest a functional topography within the cerebellum. Sensorimotor tasks activate the anterior lobe, parts of lobule VI, and lobule VIII, whereas higher-level tasks activate lobules VI and VII in the posterior lobe. To determine whether these activation patterns are evident at a single-subject level, we conducted functional magnetic resonance imaging (fMRI) during five tasks investigating sensorimotor (finger tapping), language (verb generation), spatial (mental rotation), working memory (N-back), and emotional processing (viewing images from the International Affective Picture System). Finger tapping activated the ipsilateral anterior lobe (lobules IV-V) as well as lobules VI and VIII. Activation during verb generation was found in right lobules VII and VIIIA. Mental rotation activated left-lateralized clusters in lobules VII-VIIIA, VI-Crus I, and midline VIIAt. The N-back task showed bilateral activation in right lobules VI-Crus I and left lobules VIIB-VIIIA. Cerebellar activation was evident bilaterally in lobule VI while viewing arousing vs. neutral images. This fMRI study provides the first proof of principle demonstration that there is topographic organization of motor execution vs. cognitive/emotional domains within the cerebellum of a single individual, likely reflecting the anatomical specificity of cerebro-cerebellar circuits underlying different task domains. Inter-subject variability of motor and non-motor topography remains to be determined
Metagenomes of the Picoalga Bathycoccus from the Chile Coastal Upwelling
Among small photosynthetic eukaryotes that play a key role in oceanic food webs, picoplanktonic Mamiellophyceae such as Bathycoccus, Micromonas, and Ostreococcus are particularly important in coastal regions. By using a combination of cell sorting by flow cytometry, whole genome amplification (WGA), and 454 pyrosequencing, we obtained metagenomic data for two natural picophytoplankton populations from the coastal upwelling waters off central Chile. About 60% of the reads of each sample could be mapped to the genome of Bathycoccus strain from the Mediterranean Sea (RCC1105), representing a total of 9 Mbp (sample T142) and 13 Mbp (sample T149) of non-redundant Bathycoccus genome sequences. WGA did not amplify all regions uniformly, resulting in unequal coverage along a given chromosome and between chromosomes. The identity at the DNA level between the metagenomes and the cultured genome was very high (96.3% identical bases for the three larger chromosomes over a 360 kbp alignment). At least two to three different genotypes seemed to be present in each natural sample based on read mapping to Bathycoccus RCC1105 genome
Linking Symptom Inventories using Semantic Textual Similarity
An extensive library of symptom inventories has been developed over time to
measure clinical symptoms, but this variety has led to several long standing
issues. Most notably, results drawn from different settings and studies are not
comparable, which limits reproducibility. Here, we present an artificial
intelligence (AI) approach using semantic textual similarity (STS) to link
symptoms and scores across previously incongruous symptom inventories. We
tested the ability of four pre-trained STS models to screen thousands of
symptom description pairs for related content - a challenging task typically
requiring expert panels. Models were tasked to predict symptom severity across
four different inventories for 6,607 participants drawn from 16 international
data sources. The STS approach achieved 74.8% accuracy across five tasks,
outperforming other models tested. This work suggests that incorporating
contextual, semantic information can assist expert decision-making processes,
yielding gains for both general and disease-specific clinical assessment
Brain Injury in Battered Women: Prevalence and Relationship to Cognitive Functioning and Psychopathology
118 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.The goals of this study were to: (1) examine the prevalence of brain injury in battered women; (2) examine the relationship between brain injury and cognitive functioning in battered women; (3) examine the relationship between brain injury and psychopathology in battered women; and (4) examine the various ways in which brain injury severity, partner abuse severity, cognitive functioning, and psychopathology influence one another. Ninety-nine battered women were assessed using neuropsychological, psychopathology, and abuse history measures. Women were recruited from both shelters and community-based programs. I found that almost three-quarters of the sample sustained at least one partner-related brain injury from their partners and that approximately half of the women sustained multiple brain injuries from their partners. Additionally, there appears to be a continuum of vulnerability to brain injury severity which is related to partner abuse severity. Second, I found that brain injury severity is related to some, but not all, aspects of cognitive functioning. Brain injury is associated with executive processing but is not associated with visual processing speed. Further, this relationship cannot be accounted for by partner abuse severity or psychopathology. Third, I found that brain injury in battered women is related to at least two facets of psychopathology, depression and PTSD symptomatology. This relationship could not be accounted for by partner abuse severity. Finally, I demonstrated that abuse severity was related to executive processing, but primarily via brain injury severity. The results of this study suggest new models for some of the cognitive and psychological problems often reported by battered women. These results have important implications for improving the treatment, services, and our understanding of battered women.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
Brain Injury in Battered Women: Prevalence and Relationship to Cognitive Functioning and Psychopathology
118 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.The goals of this study were to: (1) examine the prevalence of brain injury in battered women; (2) examine the relationship between brain injury and cognitive functioning in battered women; (3) examine the relationship between brain injury and psychopathology in battered women; and (4) examine the various ways in which brain injury severity, partner abuse severity, cognitive functioning, and psychopathology influence one another. Ninety-nine battered women were assessed using neuropsychological, psychopathology, and abuse history measures. Women were recruited from both shelters and community-based programs. I found that almost three-quarters of the sample sustained at least one partner-related brain injury from their partners and that approximately half of the women sustained multiple brain injuries from their partners. Additionally, there appears to be a continuum of vulnerability to brain injury severity which is related to partner abuse severity. Second, I found that brain injury severity is related to some, but not all, aspects of cognitive functioning. Brain injury is associated with executive processing but is not associated with visual processing speed. Further, this relationship cannot be accounted for by partner abuse severity or psychopathology. Third, I found that brain injury in battered women is related to at least two facets of psychopathology, depression and PTSD symptomatology. This relationship could not be accounted for by partner abuse severity. Finally, I demonstrated that abuse severity was related to executive processing, but primarily via brain injury severity. The results of this study suggest new models for some of the cognitive and psychological problems often reported by battered women. These results have important implications for improving the treatment, services, and our understanding of battered women.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
Meta-analysis of structural imaging findings in Attention-Deficit/Hyperactivity Disorder
Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies
Brain state-based detection of attentional fluctuations and their modulation
In the search for brain markers of optimal attentional focus, the mainstream approach has been to first define attentional states based on behavioral performance, and to subsequently investigate âneural correlatesâ associated with these performance variations. However, this approach constrains the range of contexts in which attentional states can be operationalized by relying on overt behavior, and assumes a one-to-one correspondence between behavior and brain state. Here, we reversed the logic of these previous studies and sought to identify behaviorally-relevant brain states based solely on brain activity, agnostic to behavioral performance. In four independent datasets, we found that the same two brain states were dominant during a sustained attention task. One state was behaviorally optimal, with higher accuracy and stability, but a greater tendency to mind wander (State1). The second state was behaviorally suboptimal, with lower accuracy and instability (State2). We further demonstrate how these brain states were impacted by motivation and attention-deficit/hyperactivity disorder (ADHD). Individuals with ADHD spent more time in suboptimal State2 and less time in optimal State1 than healthy controls. Motivation overcame the suboptimal behavior associated with State2. Our study provides compelling evidence for the existence of two attentional states from the sole viewpoint of brain activity
Integration and segregation across large-scale intrinsic brain networks as a marker of sustained attention and task-unrelated thought
Sustained attention is a fundamental cognitive process that can be decoupled from distinct external events, and instead emerges from ongoing intrinsic large-scale network interdependencies fluctuating over seconds to minutes. Lapses of sustained attention are commonly associated with the subjective experience of mind wandering and task-unrelated thoughts. Little is known about how fluctuations in information processing underpin sustained attention, nor how mind wandering undermines this information processing. To overcome this, we used fMRI to investigate brain activity during subjects' performance (n=29) of a cognitive task that was optimized to detect and isolate continuous fluctuations in both sustained attention (via motor responses) and task-unrelated thought (via subjective reports). We then investigated sustained attention with respect to global attributes of communication throughout the functional architecture, i.e., by the segregation and integration of information processing across large scale-networks. Further, we determined how task-unrelated thoughts related to these global information processing markers of sustained attention. The results show that optimal states of sustained attention favor both enhanced segregation and reduced integration of information processing in several task-related large-scale cortical systems with concurrent reduced segregation and enhanced integration in the auditory and sensorimotor systems. Higher degree of mind wandering was associated with losses of the favored segregation and integration of specific subsystems in our sustained attention model. Taken together, we demonstrate that intrinsic ongoing neural fluctuations are characterized by two converging communication modes throughout the global functional architecture, which give rise to optimal and suboptimal attention states. We discuss how these results might potentially serve as neural markers for clinically abnormal attention. SIGNIFICANCE STATEMENT: Most of our brain activity unfolds in an intrinsic manner, i.e., is unrelated to immediate external stimuli or tasks. Here we use a gradual continuous performance task to map this intrinsic brain activity to both fluctuations of sustained attention and mind wandering. We show that optimal sustained attention is associated with concurrent segregation and integration of information processing within many large-scale brain networks, while task-unrelated thought is related to sub-optimal information processing in specific subsystems of this sustained attention network model. These findings provide a novel information processing framework for investigating the neural basis of sustained attention, by mapping attentional fluctuations to genuinely global features of intra-brain communication
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Neural substrates of impaired sensorimotor timing in adult attention-deficit/hyperactivity disorder
BackgroundâTiming abilities are critical to the successful management of everyday activities and personal safety, and timing abnormalities have been argued to be fundamental to impulsiveness, a core symptom of attention-deficit/hyperactivity disorder (ADHD). Despite substantial evidence of timing deficits in ADHD youth, only two studies have explicitly examined timing in ADHD adults, and only at the supra-second time-scale. Also, the neural substrates of these deficits are largely unknown for both youth and adults with ADHD. The present study examined sub-second sensorimotor timing and its neural substrates in ADHD adults. MethodsâUsing fMRI, we examined paced and unpaced finger tapping in a sample of 20 unmedicated adults with ADHD and 19 controls comparable on age, sex and estimated-IQ. The blood oxygenation level-dependent contrast response was used to estimate task-related neural activity. ResultsâBehavioral data showed no between-group differences in mean tapping rates but greater within-subject variability in tap-to-tap intervals for ADHD adults relative to controls. Importantly, ADHD adults had greater clock rather than motor variability, consistent with a central timing locus for the atypical movements. The imaging results demonstrated that, relative to controls, ADHD adults showed less activity in a number of regions associated with sensorimotor timing, including prefrontal and precentral gyri, basal ganglia, cerebellum, inferior parietal lobule, superior temporal gyri and insula. ConclusionsâOur findings show that sub-second timing abnormalities in ADHD youth persist into adulthood and suggest that abnormalities in the temporal structure of behavior observed in ADHD adults result from atypical function of cortico-cerebellar and cortico-striatal timing systems