Cognitive neuroimaging studies typically require fast whole brain image acquisition with maximal sensitivity to small BOLD signal changes. To increase the sensitivity, higher field strengths are often employed, since they provide an increased image signal-to-noise ratio (SNR). However, as image SNR increases, the relative contribution of physiological noise to the total time series noise will be greater compared to that from thermal noise. At 7 T, we studied how the physiological noise contribution can be best reduced for EPI time series acquired at three different spatial resolutions (1.1 mm × 1.1 mm × 1.8 mm, 2 mm × 2 mm × 2 mm and 3 mm × 3 mm × 3 mm). Applying optimal physiological noise correction methods improved temporal SNR (tSNR) and increased the numbers of significantly activated voxels in fMRI visual activation studies for all sets of acquisition parameters. The most dramatic results were achieved for the lowest spatial resolution, an acquisition parameter combination commonly used in cognitive neuroimaging which requires high functional sensitivity and temporal resolution (i.e. 3 mm isotropic resolution and whole brain image repetition time of 2 s). For this data, physiological noise models based on cardio-respiratory information improved tSNR by approximately 25% in the visual cortex and 35% sub-cortically. When the time series were additionally corrected for the residual effects of head motion after retrospective realignment, the tSNR was increased by around 58% in the visual cortex and 71% sub-cortically, exceeding tSNR ~ 140. In conclusion, optimal physiological noise correction at 7 T increases tSNR significantly, resulting in the highest tSNR per unit time published so far. This tSNR improvement translates into a significant increase in BOLD sensitivity, facilitating the study of even subtle BOLD responses.

In-vivo whole brain mapping of the radio frequency transmit field B1 + is a key aspect of recent method developments in ultra high field MRI. We present an optimized method for fast and robust in-vivo whole-brain B1 + mapping at 7T. The method is based on the acquisition of stimulated and spin echo 3D EPI images and was originally developed at 3T. We further optimized the method for use at 7T. Our optimization significantly improved the robustness of the method against large B1 + deviations and off-resonance effects present at 7T. The mean accuracy and precision of the optimized method across the brain was high with a bias less than 2.6 percent unit (p.u.) and random error less than 0.7 p.u. respectively.

LCModel and AMARES, two widely used quantitation tools for magnetic resonance spectroscopy (MRS) data, were employed to analyze simulated spectra similar to those typically obtained at short echo times (TEs) in the human brain at 1.5 T. The study focused mainly on the influence of signal-to-noise ratios (SNRs) and different linewidths on the accuracy and precision of the quantification results, and their effectiveness in accounting for the broad signal contribution of macromolecules and lipids (often called the baseline in in vivo MRS). When applied in their standard configuration (i.e., fitting a spline as a baseline for LCModel, and weighting the first data points for AMARES), both methods performed comparably but with their own characteristics. LCModel and AMARES quantitation benefited considerably from the incorporation of baseline information into the prior knowledge. However, the more accurate quantitation of the sum of glutamate and glutamine (Glx) favored the use of LCModel. Metabolite-to-creatine ratios estimated by LCModel with extended prior knowledge are more accurate than absolute concentrations, and are nearly independent of SNR and line broadening. In clinical magnetic resonance spectroscopy (MRS) of the brain, short echo times (TEs) are employed to optimize the signal-to-noise ratio (SNR), reduce signal attenuation due to transverse relaxation and scalar coupling, and enable the quantification of more than the three dominant singlet resonances (i.e., N-acetylaspartate (NAA), creatine (Cr), and choline (Cho)). Generally, it is difficult to quantify short-TE spectra because of the overlapping metabolite signals and the contribution of macromolecule and lipid components. In addition to software of MR tomographs and various in-house developments at research sites (1-3), two sophisticated and well documented software packages are widely used: LCModel (4) and Magnetic Resonance User Interface (MRUI) (5). These software packages are used worldwide by many groups not only because of their availability and performance, but also because they provide results with a broader basis of comparability. The commercially available software package LCModel (6) fits spectra in the frequency domain using a basis set of spectra of in vitro metabolite solutions acquired under conditions identical to those under which in vivo data are acquired. AMARES (7), which is part of the MRUI package (5), has the advantage of being free of charge to nonprofit organizations. This advanced quantitation toolbox analyzes spectra in the time domain utilizing a priori information that can be introduced flexibly. LCModel employs a "black box" approach, and thus requires less user interaction than AMARES.For application purposes, however, it is important to determine how quantitation depends on linewidth and SNR, and how the two methods handle the broad macromolecular and lipid signal contributions. Of course, the best way to account for macromolecular signal contribution is to acquire the macromolecular spectrum by inversion recovery (8) ...

~u t h o r for correspondence, facsimile: +30 314 2 1122.Abstract. Measurements of time-resolved fluorescence decay, laser-flash-induced absorption changes in the UV and at 820 nm and of the relative fluorescence quantum yield in different preparations (thylakoids, photosystem 11 (PSII) membrane fragments and PSII core complexes) from spinach led to a number of conclusions. (I) Light is transformed into Gibbs energy with trapping times of 250 ps and 130 ps in open reaction centres of PSII membrane fragments and PSII core complexes, respectively. Assuming rapid Boltzmann distribution of excitation energy and taking into account the antenna properties (size and spectral distribution), the molecular rate constant of primary charge separation is estimated to be about (3 ps)-'. (2) The electron transfer from Pheo-to Q, is characterised by a rate constant of (300 p -' . (3) The Q i reoxidation kinetics are significantly retarded in D20 suspensions. These HID isotope effects are interpreted as to reflect hydrogen-bond dependent changes in the protein dynamics that are relevant to electron transfer. (4) In PSII reaction centres closed for photochemical trapping the yield of a primary radical pair with lifetimes exceeding 1 ns is comparatively small (c 30%) at room temperature. Short illumination in the presence of Na2S204 changes the radical pair dynamics. (5) Photoinhibition under aerobic conditions impairs the primary charge separation and leads to formation of quencher(s) of excitation energy.

Photoinhibition was analyzed in O2-evolving and in Tris-treated PS II membrane fragments by measuring flash-induced absorption changes at 830 nm reflecting the transient P680(+) formation and oxygen evolution. Irradiation by visible light affects the PS II electron transfer at two different sites: a) photoinhibition of site I eliminates the capability to perform a 'stable' charge separation between P680(+) and QA (-) within the reaction center (RC) and b) photoinhibition of site II blocks the electron transfer from YZ to P680(+). The quantum yield of site I photoinhibition (2-3×10(-7) inhibited RC/quantum) is independent of the functional integrity of the water oxidizing system. In contrast, the quantum yield of photoinhibition at site II depends strongly on the oxygen evolution capacity. In O2-evolving samples, the quantum yield of site II photoinhibition is about 10(-7) inhibited RC/quantum. After selective elimination of the O2-evolving capacity by Tris-treatment, the quantum yield of photoinhibition at site II depends on the light intensity. At low intensity (<3 W/m(2)), the quantum yield is 10(-4) inhibited RC/quantum (about 1000 times higher than in oxygen evolving samples). Based on these results it is inferred that the dominating deleterious effect of photoinhibition cannot be ascribed to an unique target site or a single mechanism because it depends on different experimental conditions (e.g., light intensity) and the functional status of the PS II complex.