Localizing Sites of Activation in Primary Visual Cortex Using Visual-Evoked Potentials and Functional Magnetic Resonance Imaging

Improved method for retinotopy constrained source estimation of visual-evoked responses

Retinotopy constrained source estimation (RCSE) is a method for noninvasively measuring the time courses of activation in early visual areas using magnetoencephalography (MEG) or electroencephalography (EEG). Unlike conventional equivalent current dipole or distributed source models, the use of multiple, retinotopically mapped stimulus locations to simultaneously constrain the solutions allows for the estimation of independent waveforms for visual areas V1, V2, and V3, despite their close proximity to each other. We describe modifications that improve the reliability and efficiency of this method. First, we find that increasing the number and size of visual stimuli results in source estimates that are less susceptible to noise. Second, to create a more accurate forward solution, we have explicitly modeled the cortical point spread of individual visual stimuli. Dipoles are represented as extended patches on the cortical surface, which take into account the estimated receptive field size at each location in V1, V2, and V3 as well as the contributions from contralateral, ipsilateral, dorsal, and ventral portions of the visual areas. Third, we implemented a map fitting procedure to deform a template to match individual subject retinotopic maps derived from functional magnetic resonance imaging (fMRI). This improves the efficiency of the overall method by allowing automated dipole selection, and it makes the results less sensitive to physiological noise in fMRI retinotopy data. Finally, the iteratively reweighted least squares (IRLS) method was used to reduce the contribution from stimulus locations with high residual error for robust estimation of visual evoked responses.

Electrical source dynamics in three functional localizer paradigms

The visual cortex exhibits functional specialization that can be routinely demonstrated using hemodynamic measures like fMRI and PET. To understand the dynamic nature of cortical processes, however, source imaging with a high temporal resolution is necessary. Here, we asked how well distributed EEG source localization (LAURA) identifies functionally specialized visual processes. We tested three stimulus paradigms commonly used in fMRI with the aim to localize striate cortex, motion-sensitive areas, and face-sensitive areas. EEG source localization showed initial activations in striate and extra-striate areas at around 70ms after stimulus onset. These were quickly followed by extensive cortical, as well as subcortical activation. Functional motion and face-selective areas were localized with margins of below 2cm, at around 170 and 150ms, respectively. The results furthermore show for the first time that the C1 component has generators in the insula and frontal eye fields, but also in subcortical areas like the parahippocampus and the thalamus.

Comprehension of degraded speech sounds with m-sequence modulation: an fMRI study

In a recent electroencephalography (EEG) study (Takeichi et al., 2007a), we developed a new technique for assessing speech comprehension using speech degraded by m-sequence modulation and found a correlation peak with a 400-ms delay. This peak depended on the comprehensibility of the modulated speech sounds. Here we report the results of a functional magnetic resonance imaging (fMRI) experiment comparable to our previous EEG experiment. We examined brain areas related to verbal comprehension of the modulated speech sound to examine which neural system processes this modulated speech. A non-integer, alternating-block factorial design was used with 23 Japanese-speaking participants, with time reversal and m-sequence modulation as factors. A main effect of time reversal was found in the left temporal cortex along the superior temporal sulcus (BA21 and BA39), left precentral gyrus (BA6) and right inferior temporal gyrus (BA21). A main effect of modulation was found in the left postcentral gyrus (BA43) and the right medial frontal gyri (BA6) as an increase by modulation and in the left temporal cortex (BA21, 39), parahippocampal gyrus (BA34), posterior cingulate (BA23), caudate and thalamus and right superior temporal gyrus (BA38) as a decrease by modulation. An interaction effect associated specifically with non-modulated speech was found in the left frontal gyrus (BA47), left occipital cortex in the cuneus (BA18), left precuneus (BA7, 31), right precuneus (BA31) and right thalamus (forward>reverse). The other interaction effect associated specifically with modulation of speech sound was found in the inferior frontal gyrus in the opercular area (BA44) (forward>reverse). Estimated scalp projection of the component correlation function (Cao et al., 2002) for the corresponding EEG data (Takeichi et al., 2007a, showed leftward dominance. Hence, activities in the superior temporal sulcus (BA21 and BA39), which are commonly observed for speech processing, as well as left precentral gyrus (BA6) and left inferior frontal gyrus in the opercular area (BA44) is suggested to contribute to the comprehension-related EEG signal.

The folding fingerprint of visual cortex reveals the timing of human V1 and V2

Primate neocortex contains over 30 visual areas. Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics between visual areas. The electroencephalogram (EEG) provides information with high temporal precision, but has had limited success separating out the signals from individual neighboring cortical areas. Consequently, controversies exist over the temporal dynamics across cortical areas. In order to address this problem we developed a new method to identify the sources of the EEG. An individual's unique cortical pattern of sulci and gyri along with a visual area's functional retinotopic layout provides a folding fingerprint that predicts specific scalp topographies for stimuli presented in different parts of the visual field. Using this folding fingerprint with a 96 or 192 location stimulus severely constrains the solution space making it relatively easy to extract the temporal response of multiple visual areas to multiple stimulus locations. The large number of stimuli also provides a means to validate the waveforms by comparing across stimulus sets, an important feature not present in most EEG source identification procedures. Using this method our data reveal that both V1 and V2 waveforms have similar onset latencies, and their temporal dynamics provide new information regarding the response latencies of these areas in humans. Our method enables the previously unattainable separation of EEG responses from neighboring brain areas. While we applied the method to the first two cortical visual areas, V1 and V2, this method is also applicable to somatosensory areas that have defined mappings. This method provides a means to study the rapid information flow in the human brain to reveal top-down and bottom-up cognitive processes.