The CRBLM鈥檚 new scientific program focuses on three interdependent research axes: Language and Music in Society; Linguistic and Musical Plasticity; and Language and Music Models.
Society
In the 鈥淟anguage and Music in Society鈥� Research Axis, we make discoveries about the uniquely human capacities of language and music. These include how we harness and coordinate the many interdependent processes and constraints that enable us to realize our communicative goals, both in terms of producing and comprehending language and music.
Our group has world-class expertise in virtually all of the core processes that make communication possible. These include listening, speaking, language processing and comprehension, perception and production of music, motor learning, pragmatics, emotion, expressive dynamics, neurophysiological processing.
Themes:
- Lifespan
- Communication
- Health and wellness
Plasticity
In the 鈥淟inguistic and Musical Plasticity鈥� Axis, we make discoveries about the mechanisms by which the nervous system changes its function and structure based on experience, as it applies to music and language, which are model systems for studying plasticity. Plasticity occurs over different time scales and involves many distinct features, while impacting behavior and cognition in particular ways.
Our team has the expertise and technical tools to probe these processes both in people and in animal models, and across the lifespan. Indeed, mechanisms of plasticity are relevant for many of the phenomena that are at the core of our group鈥檚 interest, including language learning, reading, bilingualism, music performance, motor learning, sensory loss, and rehabilitation.
Themes:
- Learning
- Sensorimotor Interactions
- Physiological听Mechanisms
Modeling
In the 鈥淟anguage and Music Models鈥� Axis, we pioneer and refine advanced mathematical and computational modeling methods that allow researchers to answer scientific questions and to make innovative discoveries that would be challenging using descriptive data alone.
The approaches include statistical modeling innovations for handling complex, multifactorial behavioural and neurophysiological data (e.g., linear mixed effects regression and other advanced statistical techniques), and complex imaging data (e.g., partial least squares, multivoxel pattern analysis, machine learning approaches to neuroimaging); computational modeling of human behavior and interaction (e.g., neural networks, machine learning algorithms); computational linguistics approaches for mining an ever-growing array of linguistic corpora and other relevant sources of 鈥渂ig data鈥�; computational neuroscience methods for modeling the neural bases of behaviour at both a cellular and systems level; and dynamical systems approaches for investigating the oscillatory behaviors found at different time scales in both human behaviour and neural systems.
Themes
- Computational modeling
- Neural modeling
- AI / Machine learning
