BOLD responses to trigeminal nerve stimulation.

The current study investigates a new model of barrel cortex activation using stimulation of the infraorbital branch of the trigeminal nerve. A robust and reproducible activation of the rat barrel cortex was obtained following trigeminal nerve stimulation. Blood oxygen level-dependent (BOLD) effects were obtained in the primary somatosensory barrel cortex (S1BF), the secondary somatosensory cortex (S2) and the motor cortex. These cortical areas were reached from afferent pathways from the trigeminal ganglion, the trigeminal nuclei and thalamic nuclei from which neurons project their axons upon whisker stimulation. The maximum BOLD responses were obtained for a stimulus frequency of 1 Hz, a stimulus pulse width of 100 μs and for current intensities between 1.5 and 3 mA. The BOLD response was nonlinear as a function of frequency and current intensity. Additionally, modeling BOLD responses in the rat barrel cortex from separate cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO(2)) measurements showed good agreement with the shape and amplitude of measured BOLD responses as a function of stimulus frequency and will potentially allow to identify the sources of BOLD nonlinearities. Activation of the rat barrel cortex using trigeminal nerve stimulation will contribute to the interpretation of the BOLD signals from functional magnetic resonance imaging studies.

Multisensor change detection with nonlinear canonical correlation

The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of such datasets. However, for change detection existing methods are often unable to deal with heterogeneous image sources and very few consider possible nonlinearities in the data. Additionally, the availability of labeled information is very limited in change detection applications. For these reasons, we present the use of a semi-supervised kernel-based feature extraction technique. It incorporates a manifold regularization accounting for the geometric distribution and jointly addressing the small sample problem. An exhaustive example using Landsat 5 data illustrates the potential of the method for multi-sensor change detection.

Population receptive field estimates of human auditory cortex.

Here we describe a method for measuring tonotopic maps and estimating bandwidth for voxels in human primary auditory cortex (PAC) using a modification of the population Receptive Field (pRF) model, developed for retinotopic mapping in visual cortex by Dumoulin and Wandell (2008). The pRF method reliably estimates tonotopic maps in the presence of acoustic scanner noise, and has two advantages over phase-encoding techniques. First, the stimulus design is flexible and need not be a frequency progression, thereby reducing biases due to habituation, expectation, and estimation artifacts, as well as reducing the effects of spatio-temporal BOLD nonlinearities. Second, the pRF method can provide estimates of bandwidth as a function of frequency. We find that bandwidth estimates are narrower for voxels within the PAC than in surrounding auditory responsive regions (non-PAC).