Publications by authors named "Srinath Ambati"

The muscarinic-cholinergic system is involved in the pathophysiology of bipolar disorder (BD), and contributes to attention and the top-down and bottom-up cognitive and affective mechanisms of emotional processing, functionally altered in BD. Emotion processing can be assessed by the ability to inhibit a response when the content of the image is emotional. Impaired regulatory capacity of cholinergic neurotransmission conferred by reduced M-autoreceptor availability is hypothesized to play a role in elevated salience of negative emotional distractors in euthymic BD relative to individuals with no history of mood instability.

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Background: Graph theory applied to brain networks is an emerging approach to understanding the brain's topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear.

Methods: We examined the role of anatomical network connectivity derived from T1- and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38).

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Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach.

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Manual tracing of magnetic resonance imaging (MRI) represents the gold standard for segmentation in clinical neuropsychiatric research studies, however automated approaches are increasingly used due to its time limitations. The accuracy of segmentation techniques for subcortical structures has not been systematically investigated in large samples. We compared the accuracy of fully automated [(i) model-based: FSL-FIRST; (ii) patch-based: volBrain], semi-automated (FreeSurfer) and stereological (Measure®) segmentation techniques with manual tracing (ITK-SNAP) for delineating volumes of the caudate (easy-to-segment) and the hippocampus (difficult-to-segment).

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Previous structural magnetic resonance imaging (S-MRI) studies of bipolar disorder have reported variable morphological changes in subcortical brain structures and ventricles. This study aimed to establish trait-related subcortical volumetric and shape abnormalities in a large, homogeneous sample of prospectively confirmed euthymic bipolar I disorder (BD-I) patients (n=60), compared with healthy volunteers (n=60). Participants were individually matched for age and gender.

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First episode psychosis (FEP) has been associated with structural brain changes, largely identified by volumetric analyses. Advances in neuroimaging processing have made it possible to measure geometric properties that may identify subtle structural changes not appreciated by a measure of volume alone. In this study we adopt complementary methods of assessing the structural integrity of grey matter in FEP patients and assess whether these relate to patient clinical and functional outcome at 3 year follow-up.

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