Impact of brain parcellation on prediction performance in models of cognition and demographics.

Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predictive model performance. In this work, structural, functional and combined connectivity were each defined with five different parcellation schemes. The resolution and modality of the parcellation schemes were varied. Each connectivity defined with each parcellation was used to predict individual differences in age, education, sex, executive function, self-regulation, language, encoding and sequence processing. It was found that low-resolution functional parcellation consistently performed above chance at producing generalisable models of both demographics and cognition. However, no single parcellation scheme showed a superior predictive performance across all cognitive domains and demographics. In addition, although parcellation schemes impacted the graph theory measures of each connectivity type (structural, functional and combined), these differences did not account for the out-of-sample predictive performance of the models. Taken together, these findings demonstrate that while high-resolution parcellations may be beneficial for modelling specific individual differences, partial voluming of signals produced by the higher resolution of the parcellation likely disrupts model generalisability.

InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels.

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and γ -aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget .

Reconciling lesions, relapses and smouldering associated worsening: A unifying model for multiple sclerosis pathogenesis.

The failure of relapses and white matter lesions to properly explain long-term disability and progression in multiple sclerosis is compounded by its artificial separation into relapsing remitting, secondary progressive, and primary progressive pigeonholes. The well-known epidemiological disconnection between relapses and long-term disability progression has been rediscovered as "progression independent of relapse activity", i.e. smouldering multiple sclerosis. This smouldering associated worsening proceeds despite early and prolonged use of disease modification therapies, even those that are highly effective at preventing relapses and new/enhancing white matter lesions on MRI. We recognise that smouldering associated worsening and relapse/lesion associated worsening coexist, to varying extents. The extent of cortical demyelination has been shown to correlate significantly with the severity of diffuse injury in normal appearing white matter (post mortem histopathologically (r = 0.55; P = 0.001), and in vivo with MRI (r = -0.6874; P = 0.0006)) and does so independently of white matter lesion burden. Axon loss in the normal appearing white matter explains disability in multiple sclerosis better than focal white matter lesions do. Smouldering associated worsening typically manifests as a length-dependent central axonopathy. We propose a unifying model for multiple sclerosis pathogenesis, wherein accumulation of cortical lesion burden predisposes associated normal appearing white matter to diffuse injury, whilst also intensifying damage within white matter lesions. Our novel two-hit hypothesis implicates cortical disease as a culprit for smouldering multiple sclerosis, abetted by active focal inflammation in the white matter (and vice versa). Substantiation of the two-hit hypothesis would advance the importance of specific therapeutic intervention for (and monitoring of) cortical/meningeal inflammation in people with multiple sclerosis.

Noradrenergic alterations associated with early life stress.

Significant stress in childhood or adolescence is linked to both structural and functional changes in the brain in human and analogous animal models. In addition, neuromodulators, such as noradrenaline (NA), show life-long alterations in response to these early life stressors, which may impact upon the sensitivity and time course of key adrenergic activities, such as rapid autonomic stress responses (the 'fight or flight response'). The locus-coeruleus noradrenergic (LC-NA) network, a key stress-responsive network in the brain, displays numerous changes in response to significant early- life stress. Here, we review the relationship between NA and the neurobiological changes associated with early life stress and set out future lines of research that can illuminate how brain circuits and circulating neurotransmitters adapt in response to childhood stressors.