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Neural origins of illusory biases in perception and short term memories

Humans generally have a distorted perception of the world, often classified as illusory biases. Here we want to discover the neural origins of such illusory biases in our perception of the world

Keywords: Neuroscience, ETH, MSc thesis, BSc thesis, internship, decision making, models, perception, memory, cognition, human behavior, biology, EEG, fMRI, brain stimulation, Matlab, R, machine learning, data analysis

  • The ability to make judgments and decisions is a core aspect of behavior in humans and other animals. However, variable decisions and biased judgments are a hallmark of behavior across several perceptual and subjective evaluation modalities, which are often preserved across species. Critically, systematic judgment biases are often posited to deterministic heuristic functions and their associated variability is blamed to unspecific forms of noise in the nervous system, which apparently corrupt ideal behavior. In this study we will use a combination of novel behavioral tasks (together with peripheral measurements such as Eye Tracking), computational models, brain imaging and non-invasive brain stimulation to demonstrate that illusory biases in our perception of the world and short term memory storage of information can be explained via mechanistic models that take into account the limited-capacity nature of biological systems.

    The ability to make judgments and decisions is a core aspect of behavior in humans and other animals. However, variable decisions and biased judgments are a hallmark of behavior across several perceptual and subjective evaluation modalities, which are often preserved across species. Critically, systematic judgment biases are often posited to deterministic heuristic functions and their associated variability is blamed to unspecific forms of noise in the nervous system, which apparently corrupt ideal behavior. In this study we will use a combination of novel behavioral tasks (together with peripheral measurements such as Eye Tracking), computational models, brain imaging and non-invasive brain stimulation to demonstrate that illusory biases in our perception of the world and short term memory storage of information can be explained via mechanistic models that take into account the limited-capacity nature of biological systems.

  • This project is suitable for a BSc or MSc thesis or semester project. The student will focus on the following tasks: piloting data collection involving healthy volunteers data analysis statistical analysis writing-up report R or Matlab experience is desirable. The student will gain in-depth knowledge in the field of human cognition and neuroscience, and will have the opportunity to develop their problem-solving and quantitative skills. The kind involvement of in the project is flexible and depends on the interests and skills of the student

    This project is suitable for a BSc or MSc thesis or semester project. The student will focus on the following tasks:
    piloting
    data collection involving healthy volunteers
    data analysis
    statistical analysis
    writing-up report

    R or Matlab experience is desirable.

    The student will gain in-depth knowledge in the field of human cognition and neuroscience, and will have the opportunity to develop their problem-solving and quantitative skills.

    The kind involvement of in the project is flexible and depends on the interests and skills of the student

  • Joseph Heng, PhD Candidate: joseph.heng@hest.ethz.ch Rafael Polania, PI: rafael.polania@hest.ethz.ch Location Decision Neuroscience Lab (ETHZ)

    Joseph Heng, PhD Candidate: joseph.heng@hest.ethz.ch
    Rafael Polania, PI: rafael.polania@hest.ethz.ch

    Location
    Decision Neuroscience Lab (ETHZ)

Calendar

Earliest start2018-09-03
Latest end2022-08-01

Location

Decision Neuroscience Lab (ETHZ)

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Internship

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Bachelor Thesis

Master Thesis

ETH Organization's Labels (ETHZ)

Topics

  • Medical and Health Sciences
  • Information, Computing and Communication Sciences
  • Engineering and Technology
  • Economics
  • Biology
  • Behavioural and Cognitive Sciences
  • Physics
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