Journal of Cerebral Blood Flow and Metabolism 

About: Journal of Cerebral Blood Flow and Metabolism is an academic journal published by Nature Portfolio. The journal publishes majorly in the area(s): Cerebral blood flow & Ischemia. It has an ISSN identifier of 0271-678X. Over the lifetime, 7361 publications have been published receiving 512687 citations. The journal is also known as: Journal of cerebral blood flow and metabolism.

Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data:

Abstract: A theoretical model of blood-brain exchange is developed and a procedure is derived that can be used for graphing multiple-time tissue uptake data and determining whether a unidirectional transfer process was dominant during part or all of the experimental period. If the graph indicates unidirectionality of uptake, then an influx constant (Ki) can be calculated. The model is general, assumes linear transfer kinetics, and consists of a blood-plasma compartment, a reversible tissue region with an arbitrary number of compartments, and one or more irreversible tissue regions. The solution of the equations for this model shows that a graph of the ratio of the total tissue solute concentration at the times of sampling to the plasma concentration at the respective times (Cp) versus the ratio of the arterial plasma concentration-time integral to Cp should be drawn. If the data are consistent with this model, then this graph will yield a curve that eventually becomes linear, with a slope of Ki and an ordinate intercept less than or equal to the vascular plus steady-state space of the reversible tissue region.

An Energy Budget for Signaling in the Grey Matter of the Brain

Abstract: Anatomic and physiologic data are used to analyze the energy expenditure on different components of excitatory signaling in the grey matter of rodent brain. Action potentials and postsynaptic effects of glutamate are predicted to consume much of the energy (47% and 34%, respectively), with the resting potential consuming a smaller amount (13%), and glutamate recycling using only 3%. Energy usage depends strongly on action potential rate--an increase in activity of 1 action potential/cortical neuron/s will raise oxygen consumption by 145 mL/100 g grey matter/h. The energy expended on signaling is a large fraction of the total energy used by the brain; this favors the use of energy efficient neural codes and wiring patterns. Our estimates of energy usage predict the use of distributed codes, with

A three-dimensional statistical analysis for CBF activation studies in human brain.

Abstract: Many studies of brain function with positron emission tomography (PET) involve the interpretation of a subtracted PET image, usually the difference between two images under baseline and stimulation conditions. The purpose of these studies is to see which areas of the brain are activated by the stimulation condition. In many cognitive studies, the activation is so slight that the experiment must be repeated on several subjects and the subtracted images are averaged to improve the signal-to-noise ratio. The averaged image is then standardized to have unit variance and then searched for local maxima. The main problem facing investigators is which of these local maxima are statistically significant. We describe a simple method for determining an approximate p value for the global maximum based on the theory of Gaussian random fields. The p value is proportional to the volume searched divided by the product of the full widths at half-maximum of the image reconstruction process or number of resolution elements....

Animal Research: Reporting in vivo Experiments—The ARRIVE Guidelines:

Abstract: The following guidelines are excerpted (as permitted under the Creative Commons Attribution License (CCAL), with the knowledge and approval of PLoS Biology and the authors) from Kilkenny et al (2010). ​ Table

Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets

Abstract: The distributed brain systems associated with performance of a verbal fluency task were identified in a nondirected correlational analysis of neurophysiological data obtained with positron tomography. This analysis used a recursive principal-component analysis developed specifically for large data sets. This analysis is interpreted in terms of functional connectivity, defined as the temporal correlation of a neurophysiological index measured in different brain areas. The results suggest that the variance in neurophysiological measurements, introduced experimentally, was accounted for by two independent principal components. The first, and considerably larger, highlighted an intentional brain system seen in previous studies of verbal fluency. The second identified a distributed brain system including the anterior cingulate and Wernicke's area that reflected monotonic time effects. We propose that this system has an attentional bias.