Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful technique, typically based on the statistical analysis of the magnitude component of the complex time-series. Here, we additionally interrogated the phase data of the fMRI time-series and used quantitative susceptibility mapping (QSM) in order to investigate the potential of functional QSM (fQSM) relative to standard magnitude BOLD fMRI. High spatial resolution data (1 mm isotropic) were acquired every 3 seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B0. Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM time-series and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatiotemporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data. Our results present the potential of fQSM as a quantitative method of mapping BOLD changes. We also critically discuss the technical challenges and issues linked to this intriguing new technique. seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B 0 . Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM timeseries and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatio-temporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data.

SUMMARY In primates, posterior auditory cortical areas are thought to be part of a dorsal auditory pathway that processes spatial information. But how posterior (and other) auditory areas represent acoustic space remains a matter of debate. Here we provide new evidence based on functional magnetic resonance imaging (fMRI) of the macaque indicating that space is predominantly represented by a distributed hemi-field code rather than by a local spatial topography. Hemifield tuning in cortical and subcortical regions emerges from an opponent hemispheric pattern of activation and deactivation that depends on the availability of interaural delay cues. Importantly, these opponent signals allow responses in posterior regions to segregate space similarly to a hemifield code representation. Taken together, our results reconcile seemingly contradictory views by showing that the representation of space follows closely a hemifield code and suggest that enhanced posterior-dorsal spatial specificity in primates might emerge from this form of coding.

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Single voxel magnetic resonance spectroscopy with ultrashort echo time was implemented at 16.4 T to enhance the neurochemical profile of the rat brain in vivo. A TE of 1.7 msec was achieved by sequence optimization and by using short-duration asymmetric pulses. Macromolecular signal components were parameterized individually and included in the quantitative analysis, replacing the use of a metabolite-nulled spectrum. Because of the high spectral dispersion, several signals close to the water line could be detected, and adjacent peaks could be resolved. All 20 metabolites detected in this study were quantified with Cramé r-Rao lower bounds below 20%, implying reliable quantification accuracy. The signal of acetate was detected for the first time in rat brain in vivo with Cramé rRao lower bounds of 16% and a concentration of 0.52 mmol/g. Localized in vivo 1 H NMR spectroscopy provides a unique opportunity for measuring brain metabolite concentrations noninvasively, thus providing neurochemical information of in vivo processes (1). This capability has been shown to benefit from increasing magnetic field strength because of gains in signal-to-noise ratio (SNR) and chemical shift resolution. These advantages were demonstrated by detecting and quantifying 18 metabolites in the rat brain in vivo with an ultrashort echo time stimulated echo acquisition mode (STEAM) sequence at 9.4 T (2). Subsequently, the detection of ascorbate (Asc) was reported with both ultrashort TE STEAM and a J-difference editing technique (3), also at 9.4 T. Recently, several signals adjacent to the water peak, including N-acetylaspartate (NAA) at 4.38 ppm, glycerophosphorylcholine (GPC) at 4.31 ppm, and phosphorylcholine (PCho) at 4.27 ppm, were resolved with narrow RF bandwidths for water suppression, taking advantage of the increased spectral dispersion at 14.1 T (4).The availability of 16.4 T provides the potential of quantifying additional metabolites not detectable at lower field strength. Acetate (Ace), the anion of a shortchain organic acid, is widely recognized to be a substrate for glial cells (5). With in vivo 1 H NMR spectroscopy, the detection of the Ace methyl resonance at 1.9 ppm has not yet been possible due to its low concentration and virtually complete overlap with the methylene resonances of both g-aminobutyric acid (GABA) at 1.889 ppm and N-acetylaspartylglutamate (NAAG) at 1.9 ppm. Detection of Ace has, therefore, been limited to 1 H-[ 13 C]-NMR spectroscopy (6) and high resolution 1 H-NMR on perchloric acid (PCA) extracts of the rat brain (7).Although ultrashort TE makes it possible to obtain valuable metabolite information, it also leads to larger contributions from signals of macromolecules (MM); assessing this component is a critical factor in accurate metabolite quantification. Three different methods have been used to take account of the MM components in short TE in vivo 1 H NMR spectra. The first approach is to acquire an MM spectrum with an inversion-recovery metabolite-nulled measurement and then use this as a basis...