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  Manda Fischer
  M.A. Candidate Psychology, Graduate Student
University of Toronto
(Present)
   
  BSc., Psychology  
 
McGill University (2018)
 
   
  Emails:
  manda.fischer@mail.utoronto.ca
   
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RESEARCH BACKGROUND
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My background is in psychoacoustics and auditory cognitive neuroscience. Specifically, I have looked at the role of timbre and attention in the perceptual organization of sound (auditory scene analysis) and have examined the neural encoding and cross-modal plasticity of audio-motor sequences in music learning.

In my work, I have often drawn from the elegant parallels and fascinating contrasts between visual and auditory modalities. The elaborate synthesis of information between these two exemplifies the multidimensionality of human experience.

I would like to further explore sensory processing in relation to processing that is driven by cognition and to investigate this interconnectedness from multiple angles, using a diverse set of techniques.

 
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CURRENT RESEARCH: Memory and Auditory Attention
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I am working now on the interaction between memory and auditory attention. In particular, I am looking both at how unsupervised learning and implicit memory can bias auditory spatial attention in complex scenes and how these effects appear in different populations, for example, in older adults with mild cognitive impairment MCI) and in congenitally blind individuals. In addition to sensory information, what other information do we use when immersed in a complex auditory environment? How do implicit and explicit memory affect the associations we make, which in turn affects how we orient ourselves in an acoustic environment? In studying these underlying processes, I wish to uncover more about how listeners perceive and experience complex sound scenes.

Memory serves as a compelling new angle from which to examine perception and cognition, with its broad reaches and its vital role in the functions of many different domains, including auditory processing. I intend to take a dynamic approach and explore the paths on which these processes intersect. This area of research is fascinating, and constantly pushes me to see the complexity of things.

My work is co-supervised by Dr. Morris Moscovitch and Dr. Claude Alain.

 
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RELEVANT EXPERIENCE:
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2018: Undergraduate Student Research Award (NSERC); MVPA analyses of audio-motor sequences; supervised by Dr. Robert Zatorre; McGill University & Montreal Neurological Institute

 

2017-2018: Honours Psychology; Timbre and auditory salience in orchestral stratification; supervised by Dr. Stephen McAdams; McGill University & Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT)

 

2017: Undergraduate Student Research Award (NSERC); Timbre and perceptual segregation - acoustic analyses and hierarchical modelling; supervised by Dr. Stephen McAdams; McGill University & CIRMMT

 

2016-2017: Honours Psychology; Timbre and perceptual segregation; supervised by Dr. Stephen McAdams; McGill University & CIRMMT

 
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JOURNAL PUBLICATIONS: Manuscripts in Preparation
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Fischer, M., Guastavino, C., McAdams, S. (in prep). The role of timbre in orchestral stratification: Examining the complex intersection between auditory perception, attention, and art.

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Fischer, M., McAdams, S. (in prep). The effect of orchestral timbre on the degree of perceptual segregation of complex acoustic scenes.

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CONFERENCE POSTERS
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Fischer, M., Soden, K., & McAdams, S. (2017). Orchestral timbre in segregation: Understanding the link between auditory perception and human expression. Poster presented at the Faculty of Science Undergraduate Research Conference, McGill University.

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ACADEMIC AWARDS
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2018: Faculty of Arts and Science Admissions Award

2018: Suppléments aux bourses de 1er cycle en milieu académique du CRSNG (FRQNT)

2018: Undergraduate Student Research Award (NSERC)

2017: Celia Hendler Scholarship in Psychology

2017: Suppléments aux bourses de 1er cycle en milieu académique du CRSNG (FRQNT)

2017: Undergraduate Student Research Award (NSERC)

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TEACHING EXPERIENCE
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Teaching Assistant (University of Toronto) PSY 201: Statistics Part I

 
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TECHNICAL SKILLS
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Data analysis and coding:
•           Python; MATLAB; SAS; SPSS; LISP
•           Bash (OS X); FSL; AFNI
Other software: Bibliographic database (EndNote); digital audio workstation and MIDI sequencer software (Logic Pro X); vector graphics editing software (Adobe Illustrator); Excel; Word; PowerPoint

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