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  Manda Fischer
  Ph.D. Candidate Psychology, Graduate Student
University of Toronto (Present)
 
 
 

M.A. Psychology Cognitive Science
University of Toronto (2019)

 

Honours B.Sc. Psychology Cognitive Science
McGill University (2018)

 
  D.E.C. Honours Health Sciences
Vanier College, Montréal, QC (2015)
   
   
   
  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. Specifically, I am interested both in how everyday auditory experience and implicit memory can bias spatial attention in complex scenes and in 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:
-2018 - present  
2018 - present

Graduate student researcher, University of Toronto

Thesis: Does incidental auditory learning facilitate memory-guided attention? A behavioural and electroencephalogram (EEG) study
Supervisors: Dr. Morris Moscovitch and Dr. Claude Alain

  • Researched the neural correlates of memory-biased attention in hearing. Designed experiments and was responsible for each step of the research process, including training of research assistants. Presented findings at 3 conferences; awarded The Ebbinghaus Award for Best Talk. Submitted paper to peer-reviewed journal.
2016 - 2018 Honours psychology research projects, McGill University
  • Thesis 1: The role of timbre in auditory stream segregation: Investigating the critical link between auditory perception and human expression
    Supervisor: Dr. Stephen McAdams
  • Thesis 2: Timbre saliency and stratification in orchestral musical
    excerpts

    Supervisor: Dr. Stephen McAdams
Summer 2018 Undergraduate Student Research Award (NSERC), McGill University
  • Project 1: Neural encoding of audio-motor sequences in music
    learning using machine learning multi-pattern voxel analysis

    Supervisor: Dr. Robert Zatorre
  • roject 2: Publication preparation; continuation of analysis (previous two theses)
    Supervisor: Dr. Stephen McAdams
Summer 2017

Undergraduate Student Research Award (NSERC), McGill University

Project: Perceptual segregation in orchestral musical excerpts
Supervisor: Dr. Stephen McAdams

 
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JOURNAL PUBLICATIONS/MANUSCRIPTS IN PREPARATION
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  1. Fischer, M., Moscovitch, M., & Alain, C. (2019). Everyday incidental auditory learning and memory-guided attention: A behavioural and electroencephalogram (EEG) study. Journal of Experimental Psychology: Human Perception and Performance. Manuscript submitted.
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  1. Fischer, M., Moscovitch, M., & Alain, C. (2019). Memory-guided attention in hearing and vision: A systematic review and meta-analysis. WIREs Cognitive Science. Invited manuscript registered.
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  1. Fischer, M., Soden, K.,  Thoret, E., Montrey, M., & McAdams, S. (in prep). The role of timbre in perceptual segregation in orchestral music. Music Perception. Manuscript in preparation.
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  1. Fischer, M., Guastavino, C., McAdams, S. The role of timbre in orchestral stratification: Examining the complex intersection of auditory perception, attention, and art. Manuscript in preparation.
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CONFERENCE POSTERS & TALKS
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Talks

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Fischer, M., Moscovitch, M., & Alain, C. (2019). Incidental Auditory Learning and Memory-guided Attention: A Behavioural and Electroencephalogram (EEG) Study. Presentation for the Auditory Perception, Cognition, & Action Meeting (APCAM).

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Fischer, M., Soden, K., Thoret, E., Montrey, M., & McAdams, S. (August 2019). The role of timbre in perceptual segregation in orchestral music. Invited presentation for the Symposium on Interdisciplinary Studies in Orchestration and Timbre: The ACTOR Project at the Society of Music Perception and Cognition (SMPC) 2019, New York, NY.

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Fischer, M., Moscovitch, M., & Alain, C. (May 2019). Does everyday auditory experience facilitate memory-guided attention? Nominated talk at Toronto Area Memory Group (TAMEG), Toronto.

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Fischer, M., Moscovitch, M., & Alain, C. (February 2019). Does everyday auditory experience facilitate memory-guided attention? Invited presentation at the Graduate Speaker Series, University of Toronto.

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Posters

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

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AWARDS
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2019: Finkler Graduate Student Fellowship, Rotman Research Institute at Baycrest

2019: Toronto Area Memory Group (TAMeG) Award for Best Presentation

2019-2020: The Collaborative Research and Training Experience (NSERC)

2019-2020: Canada Graduate Scholarships-Master's Program (NSERC) (Award declined)

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)

2017-2018: Celia Hendler Scholarship in Psychology

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

2017: Undergraduate Student Research Award (NSERC)

2016-2018: Dean’s Honour List (top 10%), McGill University

2013-2015: Dean’s Honour Roll (top 10%); Honour List (85-89% average), Vanier College

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TEACHING EXPERIENCE
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Guest Lecturer: University of Toronto
PSY493 Cognitive Neuroscience (April 2019)

Teaching Assistantship: University of Toronto
PSY203H (Psychological Research) (Fall 2019)
PSY201F (Statistics I) (Summer 2019)
PSY230S (Personality Psychology) (Winter 2019)
PSY201F (Statistics I) (Fall 2018)

 
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TECHNICAL SKILLS
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Foundations in computer science and programming

  • Am familiar with fundamentals of programming and have hands-on experience using LISP. Designed, implemented, and reported computational models in psychology.

Hardware and brain imaging experience

  • EEG experimentation and analyses: Used 76-channel system and audiometer to conduct experiments. Coded scripts in Neurobehavioral Systems Presentation and Matlab. Used BESA Research and BESA Statistics to preprocess, analyze and visualize data.
  • fMRI analyses and visualization: Preprocessed fMRI data and applied machine learning multi-pattern voxel analysis techniques to audio-motor cello training data set, using Python, IPython (Jupyter notebook), SSH, Bash (OSX), FSLeyes, and AFNI.

Statistical/modelling tools

  • Wrote scripts in Statistical Analysis Software (SAS) to create hierarchical linear models, combining behavioural, acoustic, and musical score-based data.
  • Performed meta-analysis, using GingerALE, on a set of fMRI studies.
  • Have used R for statistical analysis and visualization (GPA 4.0).

Acoustic analyses and sound editing

  • Implemented Matlab’s Timbre Toolbox to extract audio attributes from musical signals. Used digital audio workstation and MIDI sequencer software (Logic Pro X) to edit and render sound stimuli.

Operating systems:  Windows and Mac

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