Psychology

PSYC2071 Perception and Cognition, Term 3 2022
Mid-Term Exam Revision Sheet
Below are the key terms associated with each lecture and the associated learning outcomes that you can use to guide your preparation for the
mid-term exam on Weeks 1-5 material.
Week 1.1 Understanding perception and cognition (Erin Goddard)
You should be able to:
Define the stages of perceptual processing: transduction; neural coding; percept
Identify inputs and outputs for different perceptual and cognitive processes
Understand that measuring ‘information’ requires that the dimension of interest is clearly defined
Understand the central ideas of signal detection theory: detecting signals in a noise, dissociating sensitivity and criterion
Describe what is meant by the 4 main characteristics of perception: Cognitive impenetrability; early development; emergent properties; lack of detail
Week 1.2 Early visual processing and visual system overview (Erin Goddard)
You should be able to:
Define terminology for describing visual information: visual angle, contrast, spatial frequency and temporal frequency
Describe the differences between
• Rod and cone photoreceptors
• Central and peripheral vision
• Parvocellular and magnocellular pathways
Understand the relationships between convergence, acuity, sensitivity and receptive field size
Week 2.1 Parallel pathways in visual cortex: Motion processing (Erin Goddard)
You should be able to:
Identify the main organisation principles of V1: retinotopic organisation; cortical magnification; orientation tuning
Identify the broad differences between the ventral and dorsal processing streams: what vs where, what vs how, vision for perception vs vision for action
List some ways motion information is useful for visual perception
Understand how is motion defined, and read a space-time plots
Give reasons why MT is considered a specialised neural region for motion processing: e.g. akinetopsia
Define the aperture problem in motion perception
Understand why self-motion and eye-movements need to be discounted, and how the brain’s solution is pre-emptive
Week 2.2 Parallel pathways in visual cortex: Colour processing (Erin Goddard)
You should be able to:
Identify ways that colour vision is useful: e.g. scene segmentation (objects, shadows); signalling surface properties (edibility; emotion, health)
Understand how our photoreceptors and the retinal neural ‘software’ determine the:
• Range of visible light
• Dimensionality of our colour vision
• Opponent nature of colour vision
Describe why V4 and the ventral visual stream are important for colour vision: e.g. cerebral achromatopsia; ventral visual regions that are strongly
responsive to colour and linked to memory areas
Describe how perceived colour is affected by memory: images with highly diagnostic colours need a small amount of their opponent colour to appear
achromatic
Define ‘colour constancy’ (layers of colour: reflectance; illumination, filters) and some of the image cues thought to play a role (e.g. average colour, specular
highlights, interreflections, luminance/hue correlations)
Week 3.1 From Neural Code to Object Recognition: Mid-level vision (Branka Spehar)
You should be able to:
• Understand the parallel and hierarchical organisation of the visual system (numerous functionally specialised but segregated processing channels
increasing in processing complexity; for example, rods-cones; magno-parvo pathways; modules in IT);
• Understand why this leads to the binding problem (illusory conjunctions);
Describe the organisation of the Inferotemporal (IT) cortex and be familiar with its processing modules: face (FFA); place (PPA); body (EBA); object areas
Describe and differentiate between visual agnosias: Apperceptive agnosia, associative agnosia, prosopagnosia, integrative agnosia
Discuss the potential neural codes for object recognition: 1) Specificity coding (the Grandmother cell) vs Population (distributed/combination) coding
Describe and differentiate between template and structural description models of object recognition
Describe and illustrate the main challenges in object recognition: viewpoint differences (canonical vs non-canonical); clutter; occlusion, camouflage
Define Mid-level vison and its component processes of image (region) segmentation and grouping; appreciate the importance of image discontinuities (for
example, points of high concavity) in these processes.
Week 3.2 Perceptual organisation (Branka Spehar)
You should be able to:
Describe Gestalt psychology and its signature phenomena: Configural superiority effect; Global superiority effects (Navon figures)
Define perceptual organisation and be familiar with different perceptual grouping principles and figure-ground assignment principles
Understand which region is more likely to be perceived as a figure and the concept of border ownership
Recognize neural signatures of figure-ground perception and perceptual grouping: grouping-based contextual modulation in V1; illusory contour coding in
V2; border ownership coding in V2; feedforward, horizontal and feedback connections
Understand the principles of contour completion based on collinearity and good continuation; the principle of contour relatability in boundary completion
of occluded and camouflaged objects
Define the Simplicity (Pragnanz) principle, accidental vs generic views, and whether the prior knowledge play a decisive role in these phenomena.
Week 4.1 High-level visual processing (David White)
You should be familiar with the following concepts:
High vs low-level vision: Tuning to object properties vs mapping of spatial patterns of stimulation (retinotopy)
Domain specificity: modularity of mind; Fodor’s distinction between central (domain general) vs module-based (domain-specific) processing
Is face perception special? Developmental studies; acquired prosopagnosia; object agnosia; double dissociation
Farah’s (1991) work on the co-occurrence of visual agnosia; degrees of holistic vs part-based processing
Neural models of face processing: Separate processing streams for identity (FFA) and expression processing (pSTS)
Bruce & Young’s (1986) Cognitive model of face processing
Individual differences in face processing: are they gradual rather than sharp; what is their link to more general differences in object and scene processing;
Week 4.2. Computational models of face processing (David White)
You should be familiar with the following concepts:
Face-space; the other race effect/bias; Principal Component Analysis (PCA) as a computational implementation of face space;
PCA: a dimensionality reduction toolbox; a metaphor for High-level vision in the ventral stream; face recognition ability is poor; potential as common
representation for emotion and identity processing;
Deep neural networks (DNNs): highly accurate face recognition;
Unsupervised vs supervised learning; feedforward vs back-propagation;
DNNs model of the important aspects of visual processing: retinotopy at early levels; high-level representations tuned to functional specialisations (faces).
Week 5.1. The science of perceptual expertise (Alice Towler)
You should be able to:
Define expertise and recognise examples of people along the novice to expert continuum
Describe mental representations and why/how they differ between experts and novices
Describe the characteristics of expertise (organised knowledge, processing strategies etc.), including experimental evidence that illustrates each.
Explain the role of innate talent and prodigies in the development of expertise
Describe the components of purposeful and deliberate practice, and how they support the development of expertise
Week 5.2 Perceptual expertise in professional context (Alice Towler)
You should be able to:
Describe the evidence assessing the expertise of wine tasters, and the reasons why they don’t have expertise
Describe the evidence assessing the expertise of medical practitioners, and how it relates to the science of expertise (characteristics and development)
Describe the evidence assessing the expertise of forensic scientists, how it relates to the science of expertise (characteristics and development), and how
definitions of ‘superior performance’ may differ between forensic scientists and psychologists
Understand how signal detection theory can be applied in medicine and forensic science