Although orientation columns are less than a millimeter in width, recent neuroimaging studies indicate that viewed orientations can be decoded from cortical activity patterns sampled at relatively coarse resolutions of several millimeters. One proposal is that these differential signals arise from random spatial irregularities in the columnar map. However, direct support for this hypothesis has yet to be obtained. Here, we used high-field, high-resolution functional magnetic resonance imaging (fMRI) and multivariate pattern analysis to determine the spatial scales at which orientation-selective information can be found in the primary visual cortex (V1) of cats and humans. We applied a multiscale pattern analysis approach in which fine-and coarse-scale signals were first removed by ideal spatial lowpass and highpass filters, and the residual activity patterns then analyzed by linear classifiers. Cat visual cortex, imaged at 0.3125 mm resolution, showed a strong orientation signal at the scale of individual columns. Nonetheless, reliable orientation bias could still be found at spatial scales of several millimeters. In the human visual cortex, imaged at 1 mm resolution, a majority of orientation information was found on scales of millimeters, with small contributions from global spatial biases exceeding ϳ1 cm. Our high-resolution imaging results demonstrate a reliable millimeters-scale orientation signal, likely emerging from irregular spatial arrangements of orientation columns and their supporting vasculature. fMRI pattern analysis methods are thus likely to be sensitive to signals originating from other irregular columnar structures elsewhere in the brain.

Activation resembling ocular dominance or orientation columns has been mapped with high-resolution functional magnetic resonance imaging (fMRI). However, the neuronal interpretation of these functional maps is unclear because of the poor sensitivity of fMRI, unknown point spread function (PSF), and lack of comparison with independent techniques. Here we show that cerebral blood volume (CBV)-weighted fMRI with a blood plasma contrast agent (monocrystalline iron oxide nanoparticles), in combination with continuous temporally encoded stimulation, can map columnar neuronal activity in the cat primary visual cortex with high sensitivity, selectivity, and reproducibility. We examined hemodynamic response PSF by comparing these CBV-based signals with oxygen metabolism-based negative blood oxygenation level-dependent signals. A significant positive correlation exists between CBV-and metabolism-based iso-orientation maps, suggesting that the hemodynamic PSF is narrower than intercolumn distances. We also compared CBV-based fMRI with optical intrinsic signal (OIS) imaging, a technique that identifies sites of increased neuronal activity, to investigate neuronal correlation. Iso-orientation maps obtained by fMRI and OIS were well matched, indicating that areas of the highest orientation-selective CBV signals correspond to sites of increased neural activity. Using CBV-based fMRI, we successfully mapped orientation-selective functional architecture in the medial bank of the visual cortex, an area inaccessible to OIS imaging. Thus, we conclude that contrast agent-based fMRI, in combination with continuous temporally encoded stimulation, is a highly sensitive technique capable of mapping neural activity at the resolution of functional columns without depth limitation.

Whether conventional gradient-echo (GE) blood oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is able to map submillimeter-scale functional columns remains debatable mainly because of the spatially nonspecific large vessel contribution, poor sensitivity and reproducibility, and lack of independent evaluation. Furthermore, if the results from optical imaging of intrinsic signals are directly applicable, regions with the highest BOLD signals may indicate neurally inactive domains rather than active columns when multiple columns are activated. To examine these issues, we performed BOLD fMRI at a magnetic field of 9.4 tesla to map orientation-selective columns of isoflurane-anesthetized cats. We could not convincingly map orientation columns using conventional block-design stimulation and differential analysis method because of large fluctuations of signals. However, we successfully obtained GE BOLD iso-orientation maps with high reproducibility (r ϭ 0.74) using temporally encoded continuous cyclic orientation stimulation with Fourier data analysis, which reduces orientation-nonselective signals such as draining artifacts and is less sensitive to signal fluctuations. We further reduced large vessel contribution using the improved spin-echo (SE) BOLD method but with overall decreased sensitivity. Both GE and SE BOLD iso-orientation maps excluding large pial vascular regions were significantly correlated to maps with a known neural interpretation, which were obtained in contrast agent-aided cerebral blood volume fMRI and total hemoglobin-based optical imaging of intrinsic signals at a hemoglobin iso-sbestic point (570 nm). These results suggest that, unlike the expectation from deoxyhemoglobin-based optical imaging studies, the highest BOLD signals are localized to the sites of increased neural activity when column-nonselective signals are suppressed.

Accurate individualized muscle architecture data is crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor magnetic resonance (MR) imaging (DTI) has emerged as a promising method of gathering muscle architecture data in vivo, however its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here we provide a validation of the method of using anatomical MRI and DTI to gather muscle architecture data in vivo, by directly comparing those data obtained from MR scans of 3 human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.