Vascular imprints of neuronal activity: Relationships between the dynamics of cortical blood flow, oxygenation, and volume changes following sensory stimulation

Modern functional neuroimaging methods, such as positron-emission tomography (PET), optical imaging of intrinsic signals, and functional MRI (fMRI) utilize activity-dependent hemodynamic changes to obtain indirect maps of the evoked electrical activity in the brain. Whereas PET and flow-sensitive MRI map cerebral blood flow (CBF) changes, optical imaging and blood oxygenation level-dependent MRI map areas with changes in the concentration of deoxygenated hemoglobin (HbR). However, the relationship between CBF and HbR during functional activation has never been tested experimentally. Therefore, we investigated this relationship by using imaging spectroscopy and laser-Doppler flowmetry techniques, simultaneously, in the visual cortex of anesthetized cats during sensory stimulation. We found that the earliest microcirculatory change was indeed an increase in HbR, whereas the CBF increase lagged by more than a second after the increase in HbR. The increased HbR was accompanied by a simultaneous increase in total hemoglobin concentration (Hbt), presumably reflecting an early blood volume increase. We found that the CBF changes lagged after Hbt changes by 1 to 2 sec throughout the response. These results support the notion of active neurovascular regulation of blood volume in the capillary bed and the existence of a delayed, passive process of capillary filling.

The vibrational energy flow transition in organic molecules: Theory meets experiment

Most large dynamical systems are thought to have ergodic dynamics, whereas small systems may not have free interchange of energy between degrees of freedom. This assumption is made in many areas of chemistry and physics, ranging from nuclei to reacting molecules and on to quantum dots. We examine the transition to facile vibrational energy flow in a large set of organic molecules as molecular size is increased. Both analytical and computational results based on local random matrix models describe the transition to unrestricted vibrational energy flow in these molecules. In particular, the models connect the number of states participating in intramolecular energy flow to simple molecular properties such as the molecular size and the distribution of vibrational frequencies. The transition itself is governed by a local anharmonic coupling strength and a local state density. The theoretical results for the transition characteristics compare well with those implied by experimental measurements using IR fluorescence spectroscopy of dilution factors reported by Stewart and McDonald [Stewart, G. M. & McDonald, J. D. (1983) J. Chem. Phys. 78, 3907–3915].

Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex

Cortical blood flow at the level of individual capillaries and the coupling of neuronal activity to flow in capillaries are fundamental aspects of homeostasis in the normal and the diseased brain. To probe the dynamics of blood flow at this level, we used two-photon laser scanning microscopy to image the motion of red blood cells (RBCs) in individual capillaries that lie as far as 600 μm below the pia mater of primary somatosensory cortex in rat; this depth encompassed the cortical layers with the highest density of neurons and capillaries. We observed that the flow was quite variable and exhibited temporal fluctuations around 0.1 Hz, as well as prolonged stalls and occasional reversals of direction. On average, the speed and flux (cells per unit time) of RBCs covaried linearly at low values of flux, with a linear density of ≈70 cells per mm, followed by a tendency for the speed to plateau at high values of flux. Thus, both the average velocity and density of RBCs are greater at high values of flux than at low values. Time-locked changes in flow, localized to the appropriate anatomical region of somatosensory cortex, were observed in response to stimulation of either multiple vibrissae or the hindlimb. Although we were able to detect stimulus-induced changes in the flux and speed of RBCs in some single trials, the amplitude of the stimulus-evoked changes in flow were largely masked by basal fluctuations. On average, the flux and the speed of RBCs increased transiently on stimulation, although the linear density of RBCs decreased slightly. These findings are consistent with a stimulus-induced decrease in capillary resistance to flow.

Simple mechanochemistry describes the dynamics of kinesin molecules

Recently, Block and coworkers [Visscher, K., Schnitzer, M. J., & Block, S. M. (1999) Nature (London) 400, 184–189 and Schnitzer, M. J., Visscher, K. & Block, S. M. (2000) Nat. Cell Biol. 2, 718–723] have reported extensive observations of individual kinesin molecules moving along microtubules in vitro under controlled loads, F = 1 to 8 pN, with [ATP] = 1 μM to 2 mM. Their measurements of velocity, V, randomness, r, stalling force, and mean run length, L, reveal a need for improved theoretical understanding. We show, presenting explicit formulae that provide a quantitative basis for comparing distinct molecular motors, that their data are satisfactorily described by simple, discrete-state, sequential stochastic models. The simplest (N = 2)-state model with fixed load-distribution factors and kinetic rate constants concordant with stopped-flow experiments, accounts for the global (V, F, L, [ATP]) interdependence and, further, matches relative acceleration observed under assisting loads. The randomness, r(F,[ATP]), is accounted for by a waiting-time distribution, ψ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}{\mathrm{_{1}^{+}}}\end{equation*}\end{document}(t), [for the transition(s) following ATP binding] with a width parameter ν ≡ 〈t〉2/〈(Δt)2〉≃2.5, indicative of a dispersive stroke of mechanicity ≃0.6 or of a few (≳ν − 1) further, kinetically coupled states: indeed, N = 4 (but not N = 3) models do well. The analysis reveals: (i) a substep of d0 = 1.8–2.1 nm on ATP binding (consistent with structurally based suggestions); (ii) comparable load dependence for ATP binding and unbinding; (iii) a strong load dependence for reverse hydrolysis and subsequent reverse rates; and (iv) a large (≳50-fold) increase in detachment rate, with a marked load dependence, following ATP binding.

Dynamics of maize endosperm development and DNA endoreduplication.

Endosperm development in Zea mays is characterized by a period of intense mitotic activity followed by a period in which mitosis is essentially eliminated and the cell cycle becomes one of alternating S and G phases, leading to endoreduplication of the nuclear DNA. The endosperm represents a significant contribution to the grain yield of maize; thus, methods that facilitate the study of cellular kinetics may be useful in discerning cellular and molecular components of grain yield. Two mathematical models have been developed to describe the kinetics of endosperm growth. The first describes the kinetics of mitosis during endosperm development; the second describes the kinetics of DNA endoreduplication during endosperm development. The mitotic model is a modification of standard growth curves. The endoreduplication model is composed of six differential equations that represent the progression of nuclei from one DNA content to another during the endoreduplication process. Total nuclei number per endosperm and the number of 3C, 6C, 12C, 24C, 48C, and 96C nuclei per endosperm (C is the haploid DNA content per nucleus) for inbred W64A from 8 to 18 days after pollination were determined by flow cytometry. The results indicate that the change in number of nuclei expressed as a function of the number of days after pollination is the same from one yearly crop to another. These data were used in the model to determine the endosperm growth rate, the maximum nuclei number per endosperm, and transition rates from one C value to the next higher C value. The kinetics of endosperm development are reasonably well represented by the models. Thus, the models provide a means to quantify the complex pattern of endosperm development.