A simple and objective method for reproducible resting state network (RSN) detection in fMRI

Spatial Independent Component Analysis (ICA) decomposes the time by space functional MRI (fMRI) matrix into a set of 1-D basis time courses and their associated 3-D spatial maps that are optimized for mutual independence. When applied to resting state fMRI (rsfMRI), ICA produces several spatial independent components (ICs) that seem to have biological relevance - the so-called resting state networks (RSNs). The ICA problem is well posed when the true data generating process follows a linear mixture of ICs model in terms of the identifiability of the mixing matrix. However, the contrast function used for promoting mutual independence in ICA is dependent on the finite amount of observed data and is potentially non-convex with multiple local minima. Hence, each run of ICA could produce potentially different IC estimates even for the same data. One technique to deal with this run-to-run variability of ICA was proposed by Yang et al. (2008) in their algorithm RAICAR which allows for the selection of only those ICs that have a high run-to-run reproducibility. We propose an enhancement to the original RAICAR algorithm that enables us to assign reproducibility p-values to each IC and allows for an objective assessment of both within subject and across subjects reproducibility. We call the resulting algorithm RAICAR-N (N stands for null hypothesis test), and we have applied it to publicly available human rsfMRI data (http://www.nitrc.org). Our reproducibility analyses indicated that many of the published RSNs in rsfMRI literature are highly reproducible. However, we found several other RSNs that are highly reproducible but not frequently listed in the literature.Comment: 54 pages, 13 figure

SMART: A statistical framework for optimal design matrix generation with application to fMRI

The general linear model (GLM) is a well established tool for analyzing functional magnetic resonance imaging (fMRI) data. Most fMRI analyses via GLM proceed in a massively univariate fashion where the same design matrix is used for analyzing data from each voxel. A major limitation of this approach is the locally varying nature of signals of interest as well as associated confounds. This local variability results in a potentially large bias and uncontrolled increase in variance for the contrast of interest. The main contributions of this paper are two fold (1) We develop a statistical framework called SMART that enables estimation of an optimal design matrix while explicitly controlling the bias variance decomposition over a set of potential design matrices and (2) We develop and validate a numerical algorithm for computing optimal design matrices for general fMRI data sets. The implications of this framework include the ability to match optimally the magnitude of underlying signals to their true magnitudes while also matching the "null" signals to zero size thereby optimizing both the sensitivity and specificity of signal detection. By enabling the capture of multiple profiles of interest using a single contrast (as opposed to an F-test) in a way that optimizes for both bias and variance enables the passing of first level parameter estimates and their variances to the higher level for group analysis which is not possible using F-tests. We demonstrate the application of this approach to in vivo pharmacological fMRI data capturing the acute response to a drug infusion, to task-evoked, block design fMRI and to the estimation of a haemodynamic response function (HRF) response in event-related fMRI. Our framework is quite general and has potentially wide applicability to a variety of disciplines.Comment: 68 pages, 34 figure

Pain Facilitation Brain Regions Activated by Nalbuphine Are Revealed by Pharmacological fMRI

Nalbuphine, an agonist-antagonist kappa-opioid, produces brief analgesia followed by enhanced pain/hyperalgesia in male postsurgical patients. However, it produces profound analgesia without pain enhancement when co-administration with low dose naloxone. To examine the effect of nalbuphine or nalbuphine plus naloxone on activity in brain regions that may explain these differences, we employed pharmacological magnetic resonance imaging (phMRI) in a double blind cross-over study with 13 healthy male volunteers. In separate imaging sessions subjects were administered nalbuphine (5 mg/70 kg) preceded by either saline (Sal-Nalb) or naloxone 0.4 mg (Nalox-Nalb). Blood oxygen level-dependent (BOLD) activation maps followed by contrast and connectivity analyses revealed marked differences. Sal-Nalb produced significantly increased activity in 60 brain regions and decreased activity in 9; in contrast, Nalox-Nalb activated only 14 regions and deactivated only 3. Nalbuphine, like morphine in a previous study, attenuated activity in the inferior orbital cortex, and, like noxious stimulation, increased activity in temporal cortex, insula, pulvinar, caudate, and pons. Co-administration/pretreatment of naloxone selectively blocked activity in pulvinar, pons and posterior insula. Nalbuphine induced functional connectivity between caudate and regions in the frontal, occipital, temporal, insular, middle cingulate cortices, and putamen; naloxone co-admistration reduced all connectivity to non-significant levels, and, like phMRI measures of morphine, increased activation in other areas (e.g., putamen). Naloxone pretreatment to nalbuphine produced changes in brain activity possess characteristics of both analgesia and algesia; naloxone selectively blocks activity in areas associated with algesia. Given these findings, we suggest that nalbuphine interacts with a pain salience system, which can modulate perceived pain intensity

Comparison of evoked vs. spontaneous tics in a patient with trigeminal neuralgia (tic doloureux)

A 53-year old woman with tic doloureaux, affecting her right maxillary division of the trigeminal nerve (V2), could elicit shooting pains by slightly tapping her teeth when off medication. The pains, which she normally rated as > 6/10 on a visual analog scale (VAS), were electric shock-like in nature. She had no other spontaneous or ongoing background pain affecting the region. Based on her ability to elicit these tics, functional magnetic resonance imaging (fMRI) was performed while she produced brief shocks every 2 minutes on cue (evoked pain) over a 20 min period. In addition, she had 1–2 spontaneous shocks manifested between these evoked pains over the course of functional image acquisition. Increased fMRI activation for both evoked and spontaneous tics was observed throughout cortical and subcortical structures commonly observed in experimental pain studies with healthy subjects; including the primary somatosensory cortex, insula, anterior cingulate, and thalamus. Spontaneous tics produced more decrease in signals in a number of regions including the posterior cingulate cortex and amygdala, suggesting that regions known to be involved in expectation/anticipation may have been activated for the evoked, but not spontaneous, tics. In this patient there were large increases in activation observed in the frontal regions, including the anterior cingulate cortex and the basal ganglia. Spontaneous tics showed increased activation in classic aversion circuitry that may contribute to increased levels of anxiety. We believe that this is the first report of functional imaging of brain changes in tic-doloureaux

Excitatory neurotransmitters in brain regions in interictal migraine patients

<p>Abstract</p> <p>Objective</p> <p>To examine biochemical differences in the anterior cingulate cortex (ACC) and insula during the interictal phase of migraine patients. We hypothesized that there may be differences in levels of excitatory amino acid neurotransmitters and/or their derivatives in migraine group based on their increased sensitivity to pain.</p> <p>Methods</p> <p>2D <it>J</it>-resolved proton magnetic resonance spectroscopy (¹H-MRS) data were acquired at 4.0 Tesla (T) from the ACC and insula in 10 migraine patients (7 women, 3 men, age 43 ± 11 years) and 8 age gender matched controls (7 women, 3 men, age 41 ± 9 years).</p> <p>Results</p> <p>Standard statistical analyses including analysis of variance (ANOVA) showed no significant metabolite differences between the two subject cohorts in the ACC nor the insula. However, linear discriminant analysis (LDA) introduced a clear separation between subject cohorts based on N-acetyl aspartylglutamate (NAAG) and glutamine (Gln) in the ACC and insula.</p> <p>Conclusion</p> <p>These results are consistent with glutamatergic abnormalities in the ACC and insula in migraine patients during their interictal period compared to healthy controls. An alteration in excitatory amino acid neurotransmitters and their derivatives may be a contributing factor for migraineurs for a decrease in sensitivity for migraine or a consequence of the chronic migraine state. Such findings, if extrapolated to other regions of the brain would offer new opportunities to modulate central system as interictal or preemptive medications in these patients.</p

Migraine attacks the Basal Ganglia

<p>Abstract</p> <p>Background</p> <p>With time, episodes of migraine headache afflict patients with increased frequency, longer duration and more intense pain. While episodic migraine may be defined as 1-14 attacks per month, there are no clear-cut phases defined, and those patients with low frequency may progress to high frequency episodic migraine and the latter may progress into chronic daily headache (> 15 attacks per month). The pathophysiology of this progression is completely unknown. Attempting to unravel this phenomenon, we used high field (human) brain imaging to compare functional responses, functional connectivity and brain morphology in patients whose migraine episodes did not progress (LF) to a matched (gender, age, age of onset and type of medication) group of patients whose migraine episodes progressed (HF).</p> <p>Results</p> <p>In comparison to LF patients, responses to pain in HF patients were significantly lower in the caudate, putamen and pallidum. Paradoxically, associated with these lower responses in HF patients, gray matter volume of the right and left caudate nuclei were significantly larger than in the LF patients. Functional connectivity analysis revealed additional differences between the two groups in regard to response to pain.</p> <p>Conclusions</p> <p>Supported by current understanding of basal ganglia role in pain processing, the findings suggest a significant role of the basal ganglia in the pathophysiology of the episodic migraine.</p

The future of care work: towards a radical politics of care in CSCW research and practice

Computer-Supported Cooperative Work (CSCW) and Human- Computer Interaction (HCI) have long studied how technology can support material and relational aspects of care work, typically in clinical healthcare settings. More recently, we see increasing recognition of care work such as informal healthcare provision, child and elderly care, organizing and advocacy, domestic work, and service work. However, the COVID-19 pandemic has underscored long-present tensions between the deep necessity and simultaneous devaluation of our care infrastructures. This highlights the need to attend to the broader social, political, and economic systems that shape care work and the emerging technologies being used in care work. This leads us to ask several critical questions: What counts as care work and why? How is care work (de)valued, (un)supported, or coerced under capitalism and to what end? What narratives drive the push for technology in care work and whom does it benefit? How does care work resist or build resilience against and within oppressive systems? And how can we as researchers advocate for and with care and caregivers? In this one-day workshop, we will bring together researchers from academia, industry, and community-based organizations to reflect on these questions and extend conversations on the future of technology for care work

Robust Reproducible Resting State Networks in the Awake Rodent Brain

Resting state networks (RSNs) have been studied extensively with functional MRI in humans in health and disease to reflect brain function in the un-stimulated state as well as reveal how the brain is altered with disease. Rodent models of disease have been used comprehensively to understand the biology of the disease as well as in the development of new therapies. RSN reported studies in rodents, however, are few, and most studies are performed with anesthetized rodents that might alter networks and differ from their non-anesthetized state. Acquiring RSN data in the awake rodent avoids the issues of anesthesia effects on brain function. Using high field fMRI we determined RSNs in awake rats using an independent component analysis (ICA) approach, however, ICA analysis can produce a large number of components, some with biological relevance (networks). We further have applied a novel method to determine networks that are robust and reproducible among all the components found with ICA. This analysis indicates that 7 networks are robust and reproducible in the rat and their putative role is discussed