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MSc Cognitive and Computational Neuroscience

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  • Objectives
    This broad-based interdisciplinary course, taught by internationally recognised experts, will provide: A broad and critical understanding of leading-edge cognitive and computational neuroscience and an appreciation of different approaches for understanding brain function. Development of a range of computational and analytic skills relevant to the modelling of brain function. The ability to generate and test specific experimental hypotheses which incorporate constraints derived from psychophysics, cognitive neuroscience, and behavioural studies. Experience of the rich scientific culture provided by a thriving interdisciplinary community that rewards innovation, fosters a sense of community and encourages students to direct their own learning. The MSc includes an extended project giving the opportunity to work closely with individual scientists on topics central to their research. After gaining the MSc you will be well placed to continue research in academia, or in industry in robotics and brain-inspired computation.
  • Entry requirements
    Entry requirements Good Honours degree (2:1 or above) or equivalent qualification in either a life science or mathematical/physical science. If your existing training is in the life sciences then you will be able to take advantage of specially-designed mathematics and programming classes as well as instruction in the relevant applied mathematics integrated into specific modules. If you have a qualification in mathematics, engineering, or the physical sciences, you will benefit from the introductory course in neuroscience that ensures all students have the same foundation in this area. Students who are non-native speakers of English must also demonstrate that their language ability is sufficient before starting the course. We require non-native speakers of English to have achieved at least 6.5 overall in the IELTS with no less than 6 in any one component, or an equivalent English language qualification. Overall suitability will be determined at interview where appropriate.
  • Academic Title
    MSc Cognitive and Computational Neuroscience
  • Course description
    Cognitive and Computational Neuroscience - MSc

    Cognitive and computational neuroscience provide the foundation for understanding the relationship between brain function and the cognitive, perceptual and motor mechanisms which underpin behaviour.

    Specifically, computational neuroscience utilises neuroscientific data to construct rigorous computational models of brain function, whereas cognitive neuroscience relates cognitive and behavioural function to its underlying neural substrate.

    Together, these new and interdependent disciplines provide the foundation for meeting one of the key scientific `Grand Challenges´ of the twenty-first century: elucidating the relationship between brain and behaviour.

    -A broad and critical understanding of leading-edge cognitive and computational neuroscience.

    -Appreciation of different approaches for understanding brain function.

    -Development of a range of computational and analytic skills relevant to the modelling of brain function.

    -The ability to generate and test specific experimental hypotheses which incorporate constraints derived from psychophysics, cognitive neuroscience, and behavioural studies.

    -An appreciation of an academic scientific environment that rewards innovation, fosters a sense of community, and encourages students to direct their own learning.

    At Sheffield we have a strong track record in both computational neuroscience and cognitive neuroscience. Recently, this strength has been consolidated by the creation of the Centre for Signal Processing in Neuroimaging and Systems Neuroscience. Areas of special interest include the neurobiology and cognitive neuroscience of action selection; oculomotor control and the cerebellum; memory and learning; the neural basis of addiction; sensory control of dopamine; the rat somatosensory pathway; automatic and controlled processing.

    Investigative techniques include anatomical tracing, multi-electrode electrophysiology, optical imaging, behavioural observation, computational modelling at several levels of description (from the biophysics of neural membranes to neural populations) and robotics.

    This diverse range of research interests and techniques ensures a vibrant research environment.

    Course content

    Semester 1:
    Fundamentals of Cognitive Neuroscience, Computational Neuroscience 1, Fundamentals of Neuroscience, Mathematical Modelling and Research Skills.

    Semester 2:
    Computational Neuroscience 2, Current Issues in Systems Neuroscience, Current Issues in Cognitive Neuroscience, Brain Imaging.

    Summer:
    Extensive Empirical Project

    Teaching
    -Lectures
    -Seminars
    -Laboratory classes

    Assessment
    -Examinations at the end of semesters 1 and 2
    -Research projec

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