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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.


The  distribution of maximum beta parameters from 1000 permutations. The threshold for the top 5% is at 0.0029, shown as the red line.
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Figure 5: The distribution of maximum beta parameters from 1000 permutations. The threshold for the top 5% is at 0.0029, shown as the red line.

Mentions: After permuting the condition labels in our data RDMs 1000 times, we obtain a distribution of the maximal beta parameters (see Figure 5). This distribution is skewed toward zero and has a long tail toward the positive end. This distribution reflects the fact that when we randomly permute the condition labels, thereby disassociating the EMEG data of each word from their spectral characteristics, most of the model RDMs fail to explain much of the variance in the permuted data RDMs, resulting in beta values close to zero. This in fact is what the hypothesis is assuming. Thus, values above zero reflect false positives and p = 0.05 corresponds to the threshold of beta values at 0.0029, which selects the top 5% of the distribution.


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)

The  distribution of maximum beta parameters from 1000 permutations. The threshold for the top 5% is at 0.0029, shown as the red line.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 5: The distribution of maximum beta parameters from 1000 permutations. The threshold for the top 5% is at 0.0029, shown as the red line.
Mentions: After permuting the condition labels in our data RDMs 1000 times, we obtain a distribution of the maximal beta parameters (see Figure 5). This distribution is skewed toward zero and has a long tail toward the positive end. This distribution reflects the fact that when we randomly permute the condition labels, thereby disassociating the EMEG data of each word from their spectral characteristics, most of the model RDMs fail to explain much of the variance in the permuted data RDMs, resulting in beta values close to zero. This in fact is what the hypothesis is assuming. Thus, values above zero reflect false positives and p = 0.05 corresponds to the threshold of beta values at 0.0029, which selects the top 5% of the distribution.

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.