Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia

<p>Abstract</p> <p>Background:</p> <p>It has been proposed that different types of psychopathology in schizophrenia may reflect distinguishable pathological processes. In the current study we aimed to address such associations in the absence of confounders such as medication and disease chronicity by examining specific relationships between fMRI activation and individual symptom severity scores in un-medicated subjects at high genetic risk of schizophrenia.</p> <p>Methods:</p> <p>Associations were examined across two functional imaging paradigms: the Hayling sentence completion task, and an encoding/retrieval task, comprising encoding (at word classification) and retrieval (old word/new word judgement). Symptom severity was assessed using the positive and negative syndrome scale (PANSS). Items examined were hallucinations, delusions, and suspiciousness/persecution.</p> <p>Results:</p> <p>Associations were seen in the anterior middle temporal gyrus in relation to hallucination scores during the sentence completion task, and in the medial temporal lobe in association with suspiciousness/persecution scores in the encoding/retrieval task. Cerebellar activation was associated with delusions and suspiciousness/persecution scores across both tasks with differing patterns of laterality.</p> <p>Conclusion:</p> <p>These results support a role for the lateral temporal cortex in hallucinations and medial temporal lobe in positive psychotic symptoms. They also highlight the potential role of the cerebellum in the formation of delusions. That the current results are seen in un-medicated high risk subjects indicates these associations are not specific to the established illness and are not related to medication effects.</p

Imperfect abstraction

Structural equation models can be seen as an extension of Gaussian belief networks to cyclic graphs, and we show they can be understood generatively as the model for the joint distribution of long term average equilibrium activity of Gaussian dynamic belief networks. Most use of structural equation models in fMRI involves postulating a particular structure and comparing learnt parameters across different groups. In this paper it is argued that there are situations where priors about structure are not firm or exhaustive, and given sufficient data, it is worth investigating learning network structure as part of the approach to connectivity analysis. First we demonstrate structure learning on a toy problem. We then show that for particular fMRI data the simple models usually assumed are not supported. We show that is is possible to learn sensible structural equation models that can provide modelling benefits, but that are not necessarily going to be the same as a true causal model, and suggest the combination of prior models and learning or the use of temporal information from dynamic models may provide more benefits than learning structural equations alone.

The functional anatomy of inspection time: an event-related fMRI study

Twenty healthy young adults underwent functional magnetic resonance imaging (fMRI) of the brain while performing a visual inspection time task. Inspection time is a forced-choice, two-alternative visual backward-masking task in which the subject is briefly shown two parallel vertical lines of markedly different lengths and must decide which is longer. As stimulus duration decreases, performance declines to chance levels. Individual differences in inspection time correlate with higher cognitive functions. An event-related design was used. The hemodynamic (blood oxygenation level-dependent; BOLD) response was computed as both a function of the eight levels of stimulus duration, from 6 ms (where performance is almost at chance) to 150 ms (where performance is nearly perfect), and a function of the behavioral responses. Random effects analysis showed that the difficulty of the visual discrimination was related to bilateral activation in the inferior fronto-opercular cortex, superior/medial frontal gyrus, and anterior cingulate gyrus, and bilateral deactivation in the posterior cingulate gyrus and precuneus. Examination of the time courses of BOLD responses showed that activation was related specifically to the more difficult, briefer stimuli and that deactivation was found across most stimulus levels. Functional connectivity suggested the existence of two networks. One comprised the fronto-opercular area, intrasylvian area, medial frontal gyrus, and the anterior cingulate cortex (ACC), possibly associated with processing of visually degraded percepts. A posterior network of sensory-related and associative regions might subserve processing of a visual discrimination task that has high processing demands and combines several fundamental cognitive domains. fMRI can thus reveal information about the neural correlates of mental events which occur over very short durations

Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia-0

<p><b>Copyright information:</b></p><p>Taken from "Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia"</p><p>http://www.biomedcentral.com/1471-244X/7/61</p><p>BMC Psychiatry 2007;7():61-61.</p><p>Published online 29 Oct 2007</p><p>PMCID:PMC2169235.</p><p></p>symptom dimensions were as follows: Delusions × hallucinations r = 0.34 (p < 0.01); delusions × suspiciousness/persecution r = 0.48 (p < 0.01); hallucinations × suspiciousness/persecution r = 0.32 (p < 0.01)

Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia-1

<p><b>Copyright information:</b></p><p>Taken from "Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia"</p><p>http://www.biomedcentral.com/1471-244X/7/61</p><p>BMC Psychiatry 2007;7():61-61.</p><p>Published online 29 Oct 2007</p><p>PMCID:PMC2169235.</p><p></p>esenting increasing activation with increasing difficulty. For the encoding/retrieval task, contrasts shown are (c) word classification versus experimental baseline, (d) correct recognition versus experimental baseline, and (e) correct rejection versus experimental baseline. For illustration purposes maps are thresholded at T = 4.5, 4, 6, 5, 5 respectively, extent threshold = 50 voxels. Left hemisphere shown on left of image