Listening to the room: disrupting activity of dorsolateral prefrontal cortex impairs learning of room acoustics in human listeners. Data
Navigating complex sensory environments is critical to survival, and brain mechanisms have evolved to cope with the wide range of surroundings we encounter each day. In echoic spaces, for example, listeners place more emphasis on early-arriving sound energy to determine the location of a sound source, suppressing potentially spurious localisation cues conveyed in later-arriving sound energy reflected from walls and other hard surfaces. Nevertheless, reverberant sound energy is highly informative about those spaces per se, including their dimensions, construction, and the number of potential sources, and human listeners show improved speech understanding when re-encountering known, compared to new, reverberant environments. To determine how listeners learn the statistical properties of acoustic spaces, we assessed their ability to perceive speech in a range of noisy and reverberant rooms. We mimicked the acoustic characteristics of real rooms using an array of loudspeakers positioned within an anechoic chamber and assessed listeners’ performance in a speech-in-noise task using sentences from the Coordinate Response Measure (CRM) corpus—“Ready ‘call sign’ go to |Color| |Number| now.” Listeners were also exposed to repetitive transcranial stimulation to disrupt the dorsolateral prefrontal cortex activity, a region believed to play a role in statistical learning. Our data suggest listeners rapidly adapt to statistical characteristics of an acoustic environment to improve speech understanding. This ability is impaired when repetitive transcranial magnetic stimulation is applied bilaterally to the dorsolateral prefrontal cortex. The data demonstrate that speech understanding in noise is best when exposed to a room with reverberant characteristics common to human-built environments, with performance declining for higher and lower reverberation times, including fully anechoic (non-reverberant) environments. Our findings provide compelling evidence for a reverberation “sweet spot” and the presence of brain mechanisms that might have evolved to cope with the acoustic characteristics of listening environments encountered every day.
The data was collected in the Australian Hearing Hub (Anechoic Chamber), Sydney Australia between 2018-2021. This is a mainly psychoacoustics experiment based on room acoustics learning where some of the participants were exposed to transcranial magnetic stimulation manipulations to modulate the learning of room acoustics. This study was approved by the Human Research Ethics Committee of Macquarie University (ref: 5201833344874). Each participant signed a written informed consent form and was given a small financial remuneration for their time.
Funding
Australian Research Council DP180102524 and FL 160100108
History
Research Project URL
Research Project ID
Pure Project ID : 179652587Q/A Log
- Institutional review completed
- FAIR assessment completed
FAIR Self Assessment Summary
This text has been generated from a tool that has been adapted from the ARDC FAIR Assessment Tool Findable -------- Does the dataset have any identifiers assigned? Global Is the dataset identifier included in all metadata records/files describing the data? No How is the data described with metadata? Comprehensively (see suggestion) using a recognised formal machine-readable metadata schema What type of repository or registry is the metadata record in? Data is in one place but discoverable through several registries Accessible ---------- How accessible is the data? Publicly accessible Is the data available online without requiring specialised protocols or tools once access has been approved? Standard web service API (e.g. OGC) Will the metadata record be available even if the data is no longer available? Yes Interoperable ------------- What (file) format(s) is the data available in? In a structured, open standard, machine-readable format What best describes the types of vocabularies/ontologies/tagging schemas used to define the data elements? Standardised vocabularies/ontologies/schema without global identifiers How is the metadata linked to other data and metadata (to enhance context and clearly indicate relationships)? Metadata is represented in a machine readable format, e.g. in a linked data format such as Resource Description Framework (RDF). Reusable -------- Which of the following best describes the license/usage rights attached to the data? Standard machine-readable license (e.g. Creative Commons) How much provenance information has been captured to facilitate data reuse? Fully recorded in a machine-readable formatFAIR Self Assessment Rating
- 5 Stars
Data Sensitivity
- General