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Project Details
Funding Scheme : General Research Fund
Project Number : 14621119
Project Title(English) : Understanding the neural mechanisms of expert recognition of musical notation and Roman letters 
Project Title(Chinese) : 專家辨認音符和英文字母的神經機制 
Principal Investigator(English) : Prof Wong, Yetta Kwai-Ling  
Principal Investigator(Chinese) :  
Department : Dept of Educational Psychology
Institution : The Chinese University of Hong Kong
E-mail Address : yetta.wong@cuhk.edu.hk 
Tel : 3943 3410 
Co - Investigator(s) :
Dr Tan, Cheng Yong
Panel : Humanities, Social Sciences
Subject Area : Education
Exercise Year : 2019 / 20
Fund Approved : 588,200
Project Status : Completed
Completion Date : 30-6-2022
Project Objectives :
To investigate the early and selective visual processes engaged by expert recognition of musical notation;
To investigate and compare the visual processes engaged by expert recognition of musical notation and Roman letters
Abstract as per original application
(English/Chinese):
Reading is one of the most challenging skills to acquire in education settings. Fluent reading requires excellent visual abilities for processing the visual codes. For example, students devote a lot of effort and time to practice recognizing letters and words during schooling. In musical training, students are trained to efficiently process musical notation for performing, enriching one’s repertoire or for sight-reading. The development of these skills is not trivial, given the considerable individual differences in visual abilities even among expert readers. How do we explain such individual differences? This proposal focuses on how the experts’ brain processes visual codes of reading. While it is widely accepted that object recognition is achieved at later stages of visual processing, recent findings demonstrated that expert recognition of musical notation engages selective brain processes responsible for early visual processing, and these processes may be shared by expert letter recognition. What drives these early selective brain activities, and how do these activities support expert recognition? This proposal aims to understand the source and the functional significance of the early selective neural activities for expert note recognition and letter recognition. Study One will use electroencephalogram (EEG) to test whether the early selective activations for expert note recognition is driven by a type of diagnostic information for identifying musical notation – line junctions. Also, it will use machine learning and neural decoding techniques to identify the time frame when the experts’ brain extracts sufficient information for discriminating between musical notes and other stimuli, and for discriminating between different musical notes. Study Two will examine whether the early selective brain activities are also observed for expert letter recognition. It will systematically compare the source, functional significance and temporal dynamics of the neural mechanisms for expert letter recognition and expert note recognition. This research will have important theoretical impacts. First, it clarifies the conditions under which we will observe exceptional recruitment of early visual processes for object recognition. This will help modify existing theories of object recognition to better characterize the role of early and late visual processing in object recognition. Second, it will help understand one important process of skilled reading - how the brain learns to process the visual codes of reading efficiently. In the long run, it will help psychologists, neuroscientists and educators build a common ground to understand the development of skilled reading, and to formulate effective strategies for learning and teaching of reading skills.
Realisation of objectives: Both objectives are achieved. For the first objective, our findings showed that with perceptual expertise, line junctions are more involved in category selective representation of objects, and are more explicitly represented in later stages of processing to support expert recognition performance. This clarified the early and selective visual processes engaged by expert musical notation recognition. For the 2nd objective, we performed a behavioural study that showed that letters did not show a similar effect of line junction when another potential confound on the images was controlled for. These was in contrast to what’s been observed with expert musical notation recognition, and highlighted how these two domains of expert object recognition differ from each other.
Summary of objectives addressed:
Objectives Addressed Percentage achieved
1.To investigate the early and selective visual processes engaged by expert recognition of musical notation;Yes100%
2.To investigate and compare the visual processes engaged by expert recognition of musical notation and Roman lettersYes100%
Research Outcome
Major findings and research outcome: Our analyses showed separable neural representations of musical notation from pseudo-letter for experts than for novices when line junctions were present and during 180–280 ms after stimulus onset. Also, the decoding accuracy during 320–580ms predicted the behavioral recognition advantage of musical notation when line junctions were present.
Potential for further development of the research
and the proposed course of action:
Our findings clarified how line junctions were represented in expert recognition of musical notation, but it may not be applicable to other domains of visual perceptual expertise. Subsequent experiments are planned to clarify the factors underlying these differences.
Layman's Summary of
Completion Report:
Line junctions are well-known to be important for real-world object recognition, and sensitivity to line junctions is enhanced with perceptual experience with an object category. However, it remains unclear whether and how these very simple visual features are involved in expert object representations at the neural level. Our findings suggest that, with perceptual expertise, line junctions are more involved in the neural representation of objects that are also more specific to the expert object category. Also, they are more explicitly represented in later stages of processing to support expert recognition performance.
Research Output
Peer-reviewed journal publication(s)
arising directly from this research project :
(* denotes the corresponding author)
Year of
Publication
Author(s) Title and Journal/Book Accessible from Institution Repository
2023 Felix Tze-Hei Cho, Cheng Yong Tan, Yetta Kwailing Wong*  Role of line junctions in expert object recognition: The case of musical notation  Yes 
Recognized international conference(s)
in which paper(s) related to this research
project was/were delivered :
Other impact
(e.g. award of patents or prizes,
collaboration with other research institutions,
technology transfer, etc.):

  SCREEN ID: SCRRM00542