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Mapping tonotopic organization in human temporal cortex: representational similarity analysis in EMEG source space.

Su L, Zulfiqar I, Jamshed F, Fonteneau E, Marslen-Wilson W - Front Neurosci (2014)

Bottom Line: We then combined a form of multivariate pattern analysis (representational similarity analysis) with a spatiotemporal searchlight approach to successfully decode information about patterns of neuronal frequency preference and selectivity in bilateral superior temporal cortex.Observed frequency preferences in and around Heschl's gyrus matched current proposals for the organization of tonotopic gradients in primary acoustic cortex, while the distribution of narrow frequency selectivity similarly matched results from the fMRI literature.The spatial maps generated by this novel combination of techniques seem comparable to those that have emerged from fMRI or ECOG studies, and a considerable advance over earlier MEG results.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, University of Cambridge Cambridge, UK ; Department of Psychology, University of Cambridge Cambridge, UK.

ABSTRACT
A wide variety of evidence, from neurophysiology, neuroanatomy, and imaging studies in humans and animals, suggests that human auditory cortex is in part tonotopically organized. Here we present a new means of resolving this spatial organization using a combination of non-invasive observables (EEG, MEG, and MRI), model-based estimates of spectrotemporal patterns of neural activation, and multivariate pattern analysis. The method exploits both the fine-grained temporal patterning of auditory cortical responses and the millisecond scale temporal resolution of EEG and MEG. Participants listened to 400 English words while MEG and scalp EEG were measured simultaneously. We estimated the location of cortical sources using the MRI anatomically constrained minimum norm estimate (MNE) procedure. We then combined a form of multivariate pattern analysis (representational similarity analysis) with a spatiotemporal searchlight approach to successfully decode information about patterns of neuronal frequency preference and selectivity in bilateral superior temporal cortex. Observed frequency preferences in and around Heschl's gyrus matched current proposals for the organization of tonotopic gradients in primary acoustic cortex, while the distribution of narrow frequency selectivity similarly matched results from the fMRI literature. The spatial maps generated by this novel combination of techniques seem comparable to those that have emerged from fMRI or ECOG studies, and a considerable advance over earlier MEG results.

No MeSH data available.


Peak frequencies in left and right hemisphere superior temporal cortex derived from ssRSA analysis of EMEG data plotted in logarithmic scale in order to accommodate the full frequency range. Dashed green lines show the outlines of Heschl's gyrus (HG).
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Figure 8: Peak frequencies in left and right hemisphere superior temporal cortex derived from ssRSA analysis of EMEG data plotted in logarithmic scale in order to accommodate the full frequency range. Dashed green lines show the outlines of Heschl's gyrus (HG).

Mentions: In addition, to complement these plots of center frequency preference for each vertex, we also provide plots of the significant peak frequencies observed for the same vertices (see Figure 8). These plots, showing patches of peak frequency extending up to 8000 Hz, show a very similar distribution across superior temporal cortex to the center frequency results in Figure 7. Unsurprisingly, when the Gaussian tuning curve includes responses to lower frequencies, this may shift the center frequency of the Gaussian (see Figure 7) downwards from the peak frequency (Figure 8).


Mapping tonotopic organization in human temporal cortex: representational similarity analysis in EMEG source space.

Su L, Zulfiqar I, Jamshed F, Fonteneau E, Marslen-Wilson W - Front Neurosci (2014)

Peak frequencies in left and right hemisphere superior temporal cortex derived from ssRSA analysis of EMEG data plotted in logarithmic scale in order to accommodate the full frequency range. Dashed green lines show the outlines of Heschl's gyrus (HG).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4228977&req=5

Figure 8: Peak frequencies in left and right hemisphere superior temporal cortex derived from ssRSA analysis of EMEG data plotted in logarithmic scale in order to accommodate the full frequency range. Dashed green lines show the outlines of Heschl's gyrus (HG).
Mentions: In addition, to complement these plots of center frequency preference for each vertex, we also provide plots of the significant peak frequencies observed for the same vertices (see Figure 8). These plots, showing patches of peak frequency extending up to 8000 Hz, show a very similar distribution across superior temporal cortex to the center frequency results in Figure 7. Unsurprisingly, when the Gaussian tuning curve includes responses to lower frequencies, this may shift the center frequency of the Gaussian (see Figure 7) downwards from the peak frequency (Figure 8).

Bottom Line: We then combined a form of multivariate pattern analysis (representational similarity analysis) with a spatiotemporal searchlight approach to successfully decode information about patterns of neuronal frequency preference and selectivity in bilateral superior temporal cortex.Observed frequency preferences in and around Heschl's gyrus matched current proposals for the organization of tonotopic gradients in primary acoustic cortex, while the distribution of narrow frequency selectivity similarly matched results from the fMRI literature.The spatial maps generated by this novel combination of techniques seem comparable to those that have emerged from fMRI or ECOG studies, and a considerable advance over earlier MEG results.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, University of Cambridge Cambridge, UK ; Department of Psychology, University of Cambridge Cambridge, UK.

ABSTRACT
A wide variety of evidence, from neurophysiology, neuroanatomy, and imaging studies in humans and animals, suggests that human auditory cortex is in part tonotopically organized. Here we present a new means of resolving this spatial organization using a combination of non-invasive observables (EEG, MEG, and MRI), model-based estimates of spectrotemporal patterns of neural activation, and multivariate pattern analysis. The method exploits both the fine-grained temporal patterning of auditory cortical responses and the millisecond scale temporal resolution of EEG and MEG. Participants listened to 400 English words while MEG and scalp EEG were measured simultaneously. We estimated the location of cortical sources using the MRI anatomically constrained minimum norm estimate (MNE) procedure. We then combined a form of multivariate pattern analysis (representational similarity analysis) with a spatiotemporal searchlight approach to successfully decode information about patterns of neuronal frequency preference and selectivity in bilateral superior temporal cortex. Observed frequency preferences in and around Heschl's gyrus matched current proposals for the organization of tonotopic gradients in primary acoustic cortex, while the distribution of narrow frequency selectivity similarly matched results from the fMRI literature. The spatial maps generated by this novel combination of techniques seem comparable to those that have emerged from fMRI or ECOG studies, and a considerable advance over earlier MEG results.

No MeSH data available.