A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

/pdf/a-default-mode-of-brain-function-zwenkbmjw7.pdf

A default mode of brain function.

A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g. single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement, and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices, which characterize the information carried by a given representation in a brain or model. We propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing representational dissimilarity matrices. We demonstrate RSA by relating representations of visual objects as measured with fMRI to computational models spanning a wide range of complexities. We argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.

https://www.mrc-cbu.cam.ac.uk/wp-content/uploads/2013/01/kriegeskorte_RSA_frontiersSN20081.pdf

Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

The prevalence and cost of chronic pain is a major physical and mental health care problem in the United States today. As a result, there has been a recent explosion of research on chronic pain, with significant advances in better understanding its etiology, assessment, and treatment. The purpose of the present article is to provide a review of the most noteworthy developments in the field. The biopsychosocial model is now widely accepted as the most heuristic approach to chronic pain. With this model in mind, a review of the basic neuroscience processes of pain (the bio part of biopsychosocial), as well as the psychosocial factors, is presented. This spans research on how psychological and social factors can interact with brain processes to influence health and illness as well as on the development of new technologies, such as brain imaging, that provide new insights into brain-pain mechanisms.

/pdf/the-biopsychosocial-approach-to-chronic-pain-scientific-1047fjbjjh.pdf

The Biopsychosocial Approach to Chronic Pain: Scientific Advances and Future Directions

The brain's default mode network consists of discrete, bilateral and symmetrical cortical areas, in the medial and lateral parietal, medial prefrontal, and medial and lateral temporal cortices of the human, nonhuman primate, cat, and rodent brains. Its discovery was an unexpected consequence of brain-imaging studies first performed with positron emission tomography in which various novel, attention-demanding, and non-self-referential tasks were compared with quiet repose either with eyes closed or with simple visual fixation. The default mode network consistently decreases its activity when compared with activity during these relaxed nontask states. The discovery of the default mode network reignited a longstanding interest in the significance of the brain's ongoing or intrinsic activity. Presently, studies of the brain's intrinsic activity, popularly referred to as resting-state studies, have come to play a major role in studies of the human brain in health and disease. The brain's default mode network plays a central role in this work.

The Brain's Default Mode Network

The structural and functional integrity of the brain depends on the delicate balance between substrate delivery through blood flow and energy demands imposed by neural activity. Complex cerebrovascular control mechanisms ensure that active brain regions receive an adequate amount of blood, but the nature of these mechanisms remains elusive. Recent findings implicate perivascular neurons, gliovascular interactions and intramural vascular signalling in the control of the cerebral microcirculation. Neurons, astrocytes and vascular cells seem to constitute a functional unit, the primary purpose of which is to maintain the homeostasis of the brain's microenvironment. Alterations of these vascular regulatory mechanisms lead to brain dysfunction and disease. The emerging view is that cerebrovascular dysregulation is a feature not only of cerebrovascular pathologies, such as stroke, but also of neurodegenerative conditions, such as Alzheimer's disease.

Neurovascular regulation in the normal brain and in Alzheimer's disease.

Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level. This blood oxygenation level-dependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulin-induced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can be used to provide in vivo real-time maps of blood oxygenation in the brain under normal physiological conditions. BOLD contrast adds an additional feature to magnetic resonance imaging and complements other techniques that are attempting to provide positron emission tomography-like measurements related to regional neural activity.

https://www.pnas.org/content/pnas/87/24/9868.full.pdf

T M Lee

Papers

Brain magnetic resonance imaging with contrast dependent on blood oxygenation