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Simo Vanni

Publications and source records attributed to Simo Vanni.

4 recordsLinked to original sources

Central luminance flicker can activate peripheral retinotopic representation.

We aimed to study cortical responses to uniform luminance stimulus in different conditions. We stimulated the central visual field with luminance flicker and reversal of checkerboard pattern contrast and mapped the visual field representation up to 50 degrees of eccentricity. Our results show spreading of cortical BOLD responses when visual stimulus contains mean luminance change in dark surround and no spreading when the stimulus surround has bright illumination. No cortical region was more sensitive to luminance flicker than to pattern reversal during both stimulation setups. We suggest that the spread of luminance responses in retinotopic cortical areas results from intraocular scattering of light. Light scattered inside the eye spreads visual stimulation on the retina, and the contrast of the scattered light is strongest when the surround of the stimulus is dark. The stray light is potential and often neglected source of an artefact in visual experiments, and the responses due to stray light can erroneously be interpreted as indicators for local cortical sensitivity to luminance.

Adult↗

A new method to identify multiple sources of oscillatory activity from magnetoencephalographic data.

Identifying the sources of oscillatory activity in the human brain is a challenging problem in current magnetoencephalography (MEG) and electroencephalography (EEG) research. The fluctuations in phase and amplitude of cortical oscillations preclude signal averaging over successive sections of the data without a priori assumptions. In addition, several sources at different locations often produce oscillatory activity at similar frequencies. For example, spontaneous oscillatory activity in the 8- to 13-Hz band is produced simultaneously at least in the posterior parts of the brain and bilaterally in the sensorimotor cortices. The previous approaches of identifying sources of oscillatory activity by dipole modeling of bandpass filtered data are quite laborious and require that multiple criteria are defined by an experienced user. In this work we introduce a convenient method for source localization using minimum current estimates in the frequency domain. Individual current estimates are calculated for the Fourier transforms of successive sections of continuous data. These current estimates are then averaged. The algorithm was tested on simulated and measured MEG data and compared with conventional dipole modeling. The main advantage of the proposed method is that it provides an efficient approach for simultaneous estimation of multiple sources of oscillatory activity in the same frequency band.

Algorithms↗

Comparison of minimum current estimate and dipole modeling in the analysis of simulated activity in the human visual cortices.

Magnetoencephalographic(MEG) data are typically interpreted using source models because of the nonunique inverse problem. Although single current dipoles, adequately representing local active areas, can be identified accurately, multiple and overlapping sources form a challenge for MEG modeling. We tested the performances of multidipole modeling and minimum current estimate (MCE) in the analysis of complicated source configurations. Simulated current sources were placed to physiologically meaningful areas of the human visual cortices. Ten volunteers from the laboratory staff analyzed four different simulations with both dipole modeling and MCE without prior information of the sources. In general, the same sources were found using both modeling methods. The subjects tended to report more false sources with MCE than with dipole model, in part due to their inexperience with the method. Dipole model was more accurate than MCE both in time and space for nonsimultaneous sources but both methods performed similarly when sources overlapped in time. For all source configurations, considerably smaller source amplitudes were reported with MCE than with dipole model.

Computer Simulation↗