MEG Data on Audio-Visual Speech Perception with Functional Connectivity

Encompassing magnetoencephalography (MEG) data from human participants listening to speech under varying acoustic signal-to-noise ratios and visual contexts. It was collected to investigate the network mechanisms underlying audio-visual speech perception, focusing on local speech encoding and directed functional connectivity. The data was authored by Bruno L. Giordano and last updated in June 2020.

Use Cases

• Analyze directed functional connectivity between temporal and inferior frontal cortex to predict behavioral benefits from visual speech cues.
• Investigate changes in local speech encoding, measured by entrainment, in premotor and superior frontal cortex during low SNR conditions.
• Model the role of auditory-frontal interactions in visual speech representations using MEG data from varying acoustic SNR levels.
• Examine connectivity along the ventral stream and auditory-premotor axis to understand speech comprehension in multisensory environments.

Strengths

• Data includes MEG recordings, a high-temporal-resolution neuroimaging technique.
• Dataset is associated with a published study investigating specific network mechanisms for speech perception.
• Released under the permissive CC0 1.0 public domain license.

Limitations

• The specific sample size (number of participants or MEG recording sessions) is not provided.
• Data details such as file formats, size, and exact variables (columns) are unknown.
• The data is from 2020 and may not reflect the latest methodologies or findings in the field.

Provenance

Source

Dryad digital repository.

Collection Method

MEG data collected from human participants during audio-visual speech perception experiments.

Freshness

Last updated on 2020-06-30.