Information flow between resting state networks

The resting brain dynamics self-organizes into a finite number of correlated patterns known as resting state networks (RSNs). It is well known that techniques like independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method to compute the information flow (IF) between different RSNs from resting state magnetic resonance imaging. After haemodynamic response function blind deconvolution of all voxel signals, and under the hypothesis that RSNs define regions of interest, our method first uses principal component analysis to reduce dimensionality in each RSN to next compute IF (estimated here in terms of Transfer Entropy) between the different RSNs by systematically increasing k (the number of principal components used in the calculation). When k = 1, this method is equivalent to computing IF using the average of all voxel activities in each RSN. For k greater than one our method calculates the k-multivariate IF between the different RSNs. We find that the average IF among RSNs is dimension-dependent, increasing from k =1 (i.e., the average voxels activity) up to a maximum occurring at k =5 to finally decay to zero for k greater than 10. This suggests that a small number of components (close to 5) is sufficient to describe the IF pattern between RSNs. Our method - addressing differences in IF between RSNs for any generic data - can be used for group comparison in health or disease. To illustrate this, we have calculated the interRSNs IF in a dataset of Alzheimer's Disease (AD) to find that the most significant differences between AD and controls occurred for k =2, in addition to AD showing increased IF w.r.t. controls.Comment: 47 pages, 5 figures, 4 tables, 3 supplementary figures. Accepted for publication in Brain Connectivity in its current for

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

Getting the best outcomes from epilepsy surgery.

Neurosurgery is an underutilized treatment that can potentially cure drug-refractory epilepsy. Careful, multidisciplinary presurgical evaluation is vital for selecting patients and to ensure optimal outcomes. Advances in neuroimaging have improved diagnosis and guided surgical intervention. Invasive electroencephalography allows the evaluation of complex patients who would otherwise not be candidates for neurosurgery. We review the current state of the assessment and selection of patients and consider established and novel surgical procedures and associated outcome data. We aim to dispel myths that may inhibit physicians from referring and patients from considering neurosurgical intervention for drug-refractory focal epilepsies. Ann Neurol 2018;83:676-690

Structural and functional differences in medial prefrontal cortex underlie distractibility and suppression deficits in ageing.

Older adults experience deficits in working memory (WM) that are acutely exacerbated by the presence of distracting information. Human neurophysiological studies have revealed that these changes are accompanied by a diminished ability to suppress visual cortical activity associated with task-irrelevant information. Although this is often attributed to deficits in top-down control from a prefrontal cortical source, this has not yet been directly demonstrated. Here we evaluate the neural basis of distraction's negative impact on WM and the impairment in neural suppression in older adults by performing structural and functional MRIs while older participants engage in tasks that require remembering relevant visual stimuli in the context of overlapping irrelevant stimuli. Analysis supports both an age-related distraction effect and neural suppression deficit, and extends our understanding by revealing an alteration in functional connectivity between visual cortices and a region in the default network, the medial prefrontal cortex (mPFC). Moreover, within the older population, the magnitude of WM distractibility and neural suppression are both associated with individual differences in cortical volume and activity of the mPFC, as well as its associated white-matter tracts

A novel receive-only liquid nitrogen (LN2)-cooled RF coil for high-resolution in vivo imaging on a 3-Tesla whole-body scanner

The design and operation of a receive-only liquid nitrogen (LN2)-cooled coil and cryostat suitable for medical imaging on a 3-T whole-body magnetic resonance scanner is presented. The coil size, optimized for murine imaging, was determined by using electromagnetic (EM) simulations. This process is therefore easier and more cost effective than building a range of coils. A nonmagnetic cryostat suitable for small-animal imaging was developed having good vacuum and cryogenic temperature performance. The LN2-cooled probe had an active detuning circuit allowing the use with the scanner's built-in body coil. External tuning and matching was adopted to allow for changes to the coil due to temperature and loading. The performance of the probe was evaluated by comparison of signal-to-noise ratio (SNR) with the same radio-frequency RF) coil operating at room temperature (RT). The performance of the RF coil at RT was also benchmarked against a commercial surface coil with a similar dimension to ensure a fair SNR comparison. The cryogenic coil achieved a 1.6- to twofold SNR gain for several different medical imaging applications: For mouse-brain imaging, a 100-mu m resolution was achieved in an imaging time of 3.5 min with an SNR of 25-40, revealing fine anatomical details unseen at lower resolutions for the same time. For heavier loading conditions, such as imaging of the hind legs and liver, the SNR enhancement was slightly reduced to 1.6-fold. The observed SNR was in good agreement with the expected SNR gain correlated with the loaded-quality factor of RF coils from the EM simulations. With the aid of this end-user-friendly and economically attractive cryogenic RF coil, the enhanced SNR available can be used to improve resolution or reduce the duration of individual scans in a number of biomedical applications

Inflammation causes mood changes through alterations in subgenual cingulate activity and mesolimbic connectivity

BACKGROUND: Inflammatory cytokines are implicated in the pathophysiology of depression. In rodents, systemically administered inflammatory cytokines induce depression-like behavior. Similarly in humans, therapeutic interferon-alpha induces clinical depression in a third of patients. Conversely, patients with depression also show elevated pro-inflammatory cytokines. OBJECTIVES: To determine the neural mechanisms underlying inflammation-associated mood change and modulatory effects on circuits involved in mood homeostasis and affective processing. METHODS: In a double-blind, randomized crossover study, 16 healthy male volunteers received typhoid vaccination or saline (placebo) injection in two experimental sessions. Mood questionnaires were completed at baseline and at 2 and 3 hours. Two hours after injection, participants performed an implicit emotional face perception task during functional magnetic resonance imaging. Analyses focused on neurobiological correlates of inflammation-associated mood change and affective processing within regions responsive to emotional expressions and implicated in the etiology of depression. RESULTS: Typhoid but not placebo injection produced an inflammatory response indexed by increased circulating interleukin-6 and significant mood reduction at 3 hours. Inflammation-associated mood deterioration correlated with enhanced activity within subgenual anterior cingulate cortex (sACC) (a region implicated in the etiology of depression) during emotional face processing. Furthermore, inflammation-associated mood change reduced connectivity of sACC to amygdala, medial prefrontal cortex, nucleus accumbens, and superior temporal sulcus, which was modulated by peripheral interleukin-6. CONCLUSIONS: Inflammation-associated mood deterioration is reflected in changes in sACC activity and functional connectivity during evoked responses to emotional stimuli. Peripheral cytokine

Why I tense up when you watch me: inferior parietal cortex mediates an audience’s influence on motor performance

The presence of an evaluative audience can alter skilled motor performance through changes in force output. To investigate how this is mediated within the brain, we emulated real-time social monitoring of participants’ performance of a fine grip task during functional magnetic resonance neuroimaging. We observed an increase in force output during social evaluation that was accompanied by focal reductions in activity within bilateral inferior parietal cortex. Moreover, deactivation of the left inferior parietal cortex predicted both inter- and intra-individual differences in socially-induced change in grip force. Social evaluation also enhanced activation within the posterior superior temporal sulcus, which conveys visual information about others’ actions to the inferior parietal cortex. Interestingly, functional connectivity between these two regions was attenuated by social evaluation. Our data suggest that social evaluation can vary force output through the altered engagement of inferior parietal cortex; a region implicated in sensorimotor integration necessary for object manipulation, and a component of the action-observation network which integrates and facilitates performance of observed actions. Social-evaluative situations may induce high-level representational incoherence between one’s own intentioned action and the perceived intention of others which, by uncoupling the dynamics of sensorimotor facilitation, could ultimately perturbe motor output

Succeeding in deactivating: associations of hair zinc levels with functional and structural neural mechanisms

Zinc is a biologically essential element and involved in a wide range of cellular processes. Here, we investigated the associations of zinc levels in hair with brain activity during the n-back working memory task using functional magnetic resonance imaging, fractional anisotropy (FA) of diffusion tensor imaging, and cognitive differences in a study cohort of 924 healthy young adults. Our findings showed that greater hair zinc levels were associated with lower brain activity during working memory in extensive areas in the default mode network (i.e., greater task-induced deactivation) as well as greater FA in white matter areas near the hippocampus and posterior limbs of the internal capsule. These findings advance previous non-neuroimaging findings of zinc’s associations with excitability, excitability-associated disorders, and myelination