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

Neurochemical Pathways That Converge on Thalamic Trigeminovascular Neurons: Potential Substrate for Modulation of Migraine by Sleep, Food Intake, Stress and Anxiety

Dynamic thalamic regulation of sensory signals allows the cortex to adjust better to rapidly changing behavioral, physiological and environmental demands. To fulfill this role, thalamic neurons must themselves be subjected to constantly changing modulatory inputs that originate in multiple neurochemical pathways involved in autonomic, affective and cognitive functions. Our overall goal is to define an anatomical framework for conceptualizing how a ‘decision’ is made on whether a trigeminovascular thalamic neuron fires, for how long, and at what frequency. To begin answering this question, we determine which neuropeptides/neurotransmitters are in a position to modulate thalamic trigeminovascular neurons. Using a combination of in-vivo single-unit recording, juxtacellular labeling with tetramethylrhodamine dextran (TMR) and in-vitro immunohistochemistry, we found that thalamic trigeminovascular neurons were surrounded by high density of axons containing biomarkers of glutamate, GABA, dopamine and serotonin; moderate density of axons containing noradrenaline and histamine; low density of axons containing orexin and melanin concentrating hormone (MCH); but not axons containing CGRP, serotonin 1D receptor, oxytocin or vasopressin. In the context of migraine, the findings suggest that the transmission of headache-related nociceptive signals from the thalamus to the cortex may be modulated by opposing forces (i.e., facilitatory, inhibitory) that are governed by continuous adjustments needed to keep physiological, behavioral, cognitive and emotional homeostasis

Threat Response System: Parallel Brain Processes in Pain vis-à-vis Fear and Anxiety

Pain is essential for avoidance of tissue damage and for promotion of healing. Notwithstanding the survival value, pain brings about emotional suffering reflected in fear and anxiety, which in turn augment pain thus giving rise to a self-sustaining feedforward loop. Given such reciprocal relationships, the present article uses neuroscientific conceptualizations of fear and anxiety as a theoretical framework for hitherto insufficiently understood pathophysiological mechanisms underlying chronic pain. To that end, searches of PubMed-indexed journals were performed using the following Medical Subject Headings’ terms: pain and nociception plus amygdala, anxiety, cognitive, fear, sensory, and unconscious. Recursive sets of scientific and clinical evidence extracted from this literature review were summarized within the following key areas: (1) parallelism between acute pain and fear and between chronic pain and anxiety; (2) all are related to the evasion of sensory-perceived threats and are subserved by subcortical circuits mediating automatic threat-induced physiologic responses and defensive actions in conjunction with higher order corticolimbic networks (e.g., thalamocortical, thalamo-striato-cortical and amygdalo-cortical) generating conscious representations and valuation-based adaptive behaviors; (3) some instances of chronic pain and anxiety conditions are driven by the failure to diminish or block respective nociceptive information or unconscious treats from reaching conscious awareness; and (4) the neural correlates of pain-related conscious states and cognitions may become autonomous (i.e., dissociated) from the subcortical activity/function leading to the eventual chronicity. Identifying relative contributions of the diverse neuroanatomical sources, thus, offers prospects for the development of novel preventive, diagnostic, and therapeutic strategies in chronic pain patients

A Key Role of the Basal Ganglia in Pain and Analgesia - Insights Gained Through Human Functional Imaging

The basal ganglia (BG) are composed of several nuclei involved in neural processing related to the execution of motor, cognitive and emotional activities. Preclinical and clinical data have implicated a role for these structures in pain processing. Recently neuroimaging has added important information on BG activation in conditions of acute pain, chronic pain and as a result of drug effects. Our current understanding of alterations in cortical and sub-cortical regions in pain suggests that the BG are uniquely involved in thalamo-cortico-BG loops to integrate many aspects of pain. These include the integration of motor, emotional, autonomic and cognitive responses to pain

An Approach to Localizing Corneal Pain Representation in Human Primary Somatosensory Cortex

The cornea has been a focus of animal electrophysiological research for decades, but little is known regarding its cortical representation in the human brain. This study attempts to localize the somatotopic representation of the cornea to painful stimuli in human primary somatosensory cortex using functional magnetic resonance imaging (fMRI). In this case study, a subject was imaged at 3T while bright light was presented in a block-design, which either produced pain and blinking (during photophobia) or blinking alone (after recovery from photophobia). Pain and blinking produced precisely localized activations in primary somatosensory cortex and primary motor cortex. These results indicate that noxious stimulation of the cornea can produce somatotopic activation in primary somatosensory cortex. This finding opens future avenues of research to evaluate the relationship between corneal pain and central brain mechanisms relating to the development of chronic pain conditions, such as dry eye-like symptoms

Role of brain imaging in disorders of brain-gut interaction: a Rome Working Team Report.

Imaging of the living human brain is a powerful tool to probe the interactions between brain, gut and microbiome in health and in disorders of brain-gut interactions, in particular IBS. While altered signals from the viscera contribute to clinical symptoms, the brain integrates these interoceptive signals with emotional, cognitive and memory related inputs in a non-linear fashion to produce symptoms. Tremendous progress has occurred in the development of new imaging techniques that look at structural, functional and metabolic properties of brain regions and networks. Standardisation in image acquisition and advances in computational approaches has made it possible to study large data sets of imaging studies, identify network properties and integrate them with non-imaging data. These approaches are beginning to generate brain signatures in IBS that share some features with those obtained in other often overlapping chronic pain disorders such as urological pelvic pain syndromes and vulvodynia, suggesting shared mechanisms. Despite this progress, the identification of preclinical vulnerability factors and outcome predictors has been slow. To overcome current obstacles, the creation of consortia and the generation of standardised multisite repositories for brain imaging and metadata from multisite studies are required

Altered Hypothalamic Functional Connectivity with Autonomic Circuits and the Locus Coeruleus in Migraine

The hypothalamus has been implicated in migraine based on the manifestation of autonomic symptoms with the disease, as well as neuroimaging evidence of hypothalamic activation during attacks. Our objective was to determine functional connectivity (FC) changes between the hypothalamus and the rest of the brain in migraine patients vs. control subjects. This study uses fMRI (functional magnetic resonance imaging) to acquire resting state scans in 12 interictal migraine patients and 12 healthy matched controls. Hypothalamic connectivity seeds were anatomically defined based on high-resolution structural scans, and FC was assessed in the resting state scans. Migraine patients had increased hypothalamic FC with a number of brain regions involved in regulation of autonomic functions, including the locus coeruleus, caudate, parahippocampal gyrus, cerebellum, and the temporal pole. Stronger functional connections between the hypothalamus and brain areas that regulate sympathetic and parasympathetic functions may explain some of the hypothalamic-mediated autonomic symptoms that accompany or precede migraine attacks

Diffuse Optical Tomography Activation in the Somatosensory Cortex: Specific Activation by Painful vs. Non-Painful Thermal Stimuli

Background: Pain is difficult to assess due to the subjective nature of self-reporting. The lack of objective measures of pain has hampered the development of new treatments as well as the evaluation of current ones. Functional MRI studies of pain have begun to delineate potential brain response signatures that could be used as objective read-outs of pain. Using Diffuse Optical Tomography (DOT), we have shown in the past a distinct DOT signal over the somatosensory cortex to a noxious heat stimulus that could be distinguished from the signal elicited by innocuous mechanical stimuli. Here we further our findings by studying the response to thermal innocuous and noxious stimuli. Methodology/Principal Findings: Innocuous and noxious thermal stimuli were applied to the skin of the face of the first division (ophthalmic) of the trigeminal nerve in healthy volunteers (N = 6). Stimuli temperatures were adjusted for each subject to evoke warm (equivalent to a 3/10) and painful hot (7/10) sensations in a verbal rating scale (0/10 = no/max pain). A set of 26 stimuli (5 sec each) was applied for each temperature with inter-stimulus intervals varied between 8 and 15 sec using a Peltier thermode. A DOT system was used to capture cortical responses on both sides of the head over the primary somatosensory cortical region (S1). For the innocuous stimuli, group results indicated mainly activation on the contralateral side with a weak ipsilateral response. For the noxious stimuli, bilateral activation was observed with comparable amplitudes on both sides. Furthermore, noxious stimuli produced a temporal biphasic response while innocuous stimuli produced a monophasic response. Conclusions/Significance: These results are in accordance with fMRI and our other DOT studies of innocuous mechanical and noxious heat stimuli. The data indicate the differentiation of DOT cortical responses for pain vs. innocuous stimuli that may be useful in assessing objectively acute pain