A comparison of methods for the registration of tractographic fibre images

Diffusion tensor imaging (DTI) and tractography have opened up new avenues in neuroscience. As most applications require precise spatial localization of the fibre images, image registration is an important area of research. Registration is usually performed prior to tractography. However more reliable images could be produced if a viable registration can be performed post tractography. This study shows two available techniques for direct registration of fibre images and explores novel adaptations of these. The methods register volume images derived from the fibres, and reapply the transformation from these registrations to the fibre images. The first method is a local affine registration and the second is a global affine registration. The local affine method produced superior results

Quantitative assessment of parenchymal and ventricular readjustment to intracranial pressure relief

A 26-year-old patient underwent endoscopic third ventriculostomy for the treatment of obstructive hydrocephalus. 3D volume data sets were obtained at 3 T before surgery and three times after surgery. Off-line analysis of individual imaging data (initial linear registration, intensity adjustment, and final nonlinear registration of pre- to postoperative MR images) yielded 3D displacement fields representing the postoperative structural brain change. In principle, such an analysis technique can be used in any clinical follow-up for which careful observation of tissue readjustment is of particular importance

Probabilistic tractography in the ventrolateral thalamic nucleus: cerebellar and pallidal connections

The ventrolateral thalamic nucleus (VL), as part of the ‘motor thalamus’, is main relay station of cerebellar and pallidal projections. It comprises anterior (VLa) and posterior (VLpd and VLpv) subnuclei. Though the fibre architecture of cerebellar and pallidal projections to of the VL nucleus has already been focus in a numerous amount of in vitro studies mainly in animals, probabilistic tractography now offers the possibility of an in vivo comparison in healthy humans. In this study we performed a (a) qualitative and (b) quantitative examination of VL-cerebellar and VL-pallidal pathways and compared the probability distributions between both projection fields in the VL after an (I) atlas-based and (II) manual-based segmentation procedure. Both procedures led to high congruent results of cerebellar and pallidal connectivity distributions: the maximum of pallidal projections was located in anterior and medial parts of the VL nucleus, whereas cerebellar connectivity was more located in lateral and posterior parts. The median connectivity for cerebellar connections in both approaches (manual and atlas-based segmentation) was VLa > VLpv > VLpd, whereas the pallidal median connectivity was VLa ~ VLpv > VLpd in the atlas-based approach and VLpv > VLa > VLpd in the manual approach.Peer reviewe

Atypical processing of uncertainty in individuals at risk for psychosis

Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals. Non-medicated CHR individuals (n = 13) and control participants (n = 13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data. Computational modelling of CHR individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning. Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation

Allostatic self-efficacy: a metacognitive theory of dyshomeostasis-induced fatigue and depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future