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Biomedical subjects

Nigel H Goddard

Publications and source records attributed to Nigel H Goddard.

6 recordsLinked to original sources

Functional imaging as a predictor of schizophrenia.

BACKGROUND: Prospective studies of young individuals at high risk of schizophrenia allow the investigation of whether neural abnormalities predate development of illness and, if present, have the potential to identify those who may become ill. METHODS: We studied young individuals with at least two relatives with the disorder. At baseline functional magnetic resonance imaging (fMRI) scan, none met criteria for any psychiatric disorder, but four subjects subsequently developed schizophrenia. We report the baseline functional imaging findings in these subjects performing a sentence completion task compared with normal control subjects (n = 21) and those at high risk with (n = 21) and without (n = 41) psychotic symptoms who have not developed the disorder. RESULTS: High-risk subjects who became ill demonstrated increased activation of the parietal lobe, decreased activation of the anterior cingulate, and smaller increases in activation with increasing task difficulty in the right lingual gyrus and bilateral temporal regions. The hypothesized predictive power of parietal activation was supported only in combination with lingual gyrus activity, which gave a positive predictive value in this sample of .80. CONCLUSIONS: Although these findings should be considered cautiously, as only four subjects who had an fMRI scan subsequently became ill, they suggest functional abnormalities are present in high-risk subjects who later became ill, which distinguish them not only from normal control subjects but also those at high risk who had not developed the disorder. These differences are detectable with fMRI and may have clinical utility.

Adolescent↗

Event-related fMRI of word classification and successful word recognition in subjects at genetically enhanced risk of schizophrenia.

BACKGROUND: Verbal declarative memory is a core deficit in schizophrenia patients, seen to a lesser extent in unaffected biological relatives. Neuroimaging studies suggest volumetric differences and aberrant function in prefrontal and temporal regions in schizophrenia patients compared to controls. These deficits are also reflected in the small number of similar investigations in unaffected biological relatives. However, it is unclear the extent to which dysfunction is genetically mediated or a feature of the established illness. METHOD: Event-related blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was used to measure brain activation in 68 biological relatives of schizophrenia patients (of whom 27 experienced transient or isolated psychotic symptoms) and 21 controls during verbal classification and recognition. RESULTS: During word classification, the high-risk group showed a greater response relative to controls in the right inferior frontal gyrus. During correct recognition (relative to correct rejection), the high-risk group showed significantly greater response relative to controls in the right cerebellum. When the high-risk group was split into those with (HR+) and without (HR-) psychotic symptoms, the increased response in the right inferior frontal gyrus was only seen when the HR+ were compared to controls. The greater cerebellar response was seen when both HR groups were compared to controls. CONCLUSIONS: Activation increases in the right inferior frontal gyrus and cerebellum in high-risk subjects compared to controls during a relatively low-load memory task are likely to represent compensation for genetically mediated abnormalities. This is consistent with a leftward shift of the inverted 'U' load-response model of cognitive function in schizophrenia.

Adolescent↗

Functional disconnectivity in subjects at high genetic risk of schizophrenia.

Schizophrenia is a highly heritable psychotic disorder. It has been suggested that deficits of the established state arise from abnormal interactions between brain regions. We sought to examine whether such connectivity abnormalities would be present in subjects at high genetic risk for the disorder. Functional connectivity analysis was carried out on functional MRI images from 21 controls and 69 high risk subjects performing the Hayling sentence completion task; 27 high risk subjects reported isolated psychotic symptoms, the remaining high risk subjects and controls did not. There were no significant differences in task performance between the groups. Based on previous findings we hypothesized: (i) state-related differences in connectivity between dorsolateral prefrontal cortex and lateral temporal lobe; (ii) genetically mediated reductions in a medial prefrontal-thalamic-cerebellar network; and (iii) increased prefrontal-parietal connectivity in high risk subjects (to a greater extent in those with isolated psychotic symptoms). Connectivity analysis was performed in two ways: with and without variance associated with task effects modelled and removed from the data. We did not find evidence to support our first hypothesis with either analysis method. However, consistent with hypothesis (ii), decreased connectivity between right medial prefrontal regions and contralateral cerebellum was found. This was only statistically significant in the analysis with task effects modelled and removed from the data. Finally, consistent with hypothesis (iii), increased connectivity between the left parietal and left prefrontal regions in high risk subjects was found in both analyses. These results, all in a situation uncontaminated by the effects of anti-psychotic medication, performance differences and prolonged illness, suggest there are abnormalities in functional connectivity over and above those attributable to task effects in high risk subjects. These connectivity abnormalities may underlie the diverse deficits seen in the established condition and the more subtle deficits seen in close relatives of those with the disorder.

Adolescent↗

Axiope tools for data management and data sharing.

Many areas of biological research generate large volumes of very diverse data. Managing this data can be a difficult and time-consuming process, particularly in an academic environment where there are very limited resources for IT support staff such as database administrators. The most economical and efficient solutions are those that enable scientists with minimal IT expertise to control and operate their own desktop systems. Axiope provides one such solution, Catalyzer, which acts as flexible cataloging system for creating structured records describing digital resources. The user is able specify both the content and structure of the information included in the catalog. Information and resources can be shared by a variety of means, including automatically generated sets of web pages. Federation and integration of this information, where needed, is handled by Axiope's Mercat server. Where there is a need for standardization or compatibility of the structures usedby different researchers this canbe achieved later by applying user-defined mappings in Mercat. In this way, large-scale data sharing can be achieved without imposing unnecessary constraints or interfering with the way in which individual scientists choose to record and catalog their work. We summarize the key technical issues involved in scientific data management and data sharing, describe the main features and functionality of Axiope Catalyzer and Axiope Mercat, and discuss future directions and requirements for an information infrastructure to support large-scale data sharing and scientific collaboration.

Animals↗

Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience.

There is significant interest amongst neuroscientists in sharing neuroscience data and analytical tools. The exchange of neuroscience data and tools between groups affords the opportunity to differently re-analyze previously collected data, encourage new neuroscience interpretations and foster otherwise uninitiated collaborations, and provide a framework for the further development of theoretically based models of brain function. Data sharing will ultimately reduce experimental and analytical error. Many small Internet accessible database initiatives have been developed and specialized analytical software and modeling tools are distributed within different fields of neuroscience. However, in addition large-scale international collaborations are required which involve new mechanisms of coordination and funding. Provided sufficient government support is given to such international initiatives, sharing of neuroscience data and tools can play a pivotal role in human brain research and lead to innovations in neuroscience, informatics and treatment of brain disorders. These innovations will enable application of theoretical modeling techniques to enhance our understanding of the integrative aspects of neuroscience. This article, authored by a multinational working group on neuroinformatics established by the Organization for Economic Co-operation and Development (OECD), articulates some of the challenges and lessons learned to date in efforts to achieve international collaborative neuroscience.

Computational Biology↗