L1 - Intro to vision: defining the problem Flashcards

1
Q

Is vision simple?

A
  • Similar to a camera
  • Straightforward
  • BUT when college students were asked to recreate this with AI, there was no model that matched to the biological vision.
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2
Q

What is deep learning?

A
  • Modern machine vision
  • Very powerful but easy to fool
  • Work in very different ways to how the human works
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3
Q

How is vision deceptively simple?

A
  • e.g Computer won against the best chess player of the time
  • Computers are nowhere nearly as good as humans in detecting vision
  • Vision = complex
  • Visual brain = large proportion is dedicated to processing visual info
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4
Q

How do camera record?

A
  • Light enters from object onto lens which is reflected onto the sensors
  • Only when the red light is persistent, even if not relevant
  • Records light intensity
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5
Q

The visual system is not a camera?

A
  • Purpose of camera is to record local light intensities
  • Purpose of perception is to generate meaningful and adaptive representations, especially if there are explicit aspects of the environment
  • Meaningful and adaptive representations encode specific aspects of the world to help guide behaviour.
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6
Q

What is the Craik O’Brien Corn street Effect?

A
  • Same colour in different places
  • But makes you feel like two diff colours depending on what surrounds it
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7
Q

What are optics and inverse optics?

A
  • Through the eyes, an object is projected onto the retina = form an image (optics)
  • Visual system tries to infer which object is out there from the image on the retina
  • Often using this process for vision is ambiguous so we use prior knowledge or assumptions to help
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8
Q

What is the information processing paradigm?

A
  • Input (stimulus) –> brain/mind - info processing –> Output (perception)
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9
Q

How is vision science transdisciplinary?

A
  • Derived concepts from psych, neuro
  • Level of analysis = from neurons to percepts
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10
Q

What is Psychophysics?

A
  • Tries to determine the relationship between stimulus and perception quantitively
  • Psychophysicists measure thresholds and limits of the perceptual system
  • Studies perception at the level of the whole organism
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11
Q

What are the types of measures for threshold?

A
  • Absolute: smallest amount of stimulation that can be reliability detected
  • Difference: smallest difference between two stimuli that can be reliably detected
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12
Q

How to measure absolute threshold (contrast)?

A
  • 2-alternative-forced-choice task
  • Show ppts 2 different stimuli, one containing stimulus (stripey patterns) and one is grey and plain
  • Reduce the contrast of the stripey pattern where ppt is JUST able to see the difference between blocks
  • RESULTS: there is no hard threshold for a certain amount of stimulus to be seen BUT there is a soft threshold, some ppt will never be able to see it so will guess, and others will see it always, some trials they will see and others they will not
  • ABSOLUTE: what level will they identify at e.g when are they 75% sure, stimulus intensity for a ppt to recognise it
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13
Q

How to measure difference threshold?

A
  • Use the 2-alternative-forced-choice task
  • Both have a stripey pattern, one is the reference/standard and you have a comparison
  • Ref = fixed stim intensity
  • Ask which one has a higher contrast
  • Change the contrast until ppt is just able to see the difference between the two
  • Also known as the just noticeable difference
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14
Q

What is the Weber Fraction?

A
  • The ratio between JND and reference intensity is constant
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15
Q

What is electrophysiology?

A
  • Neurones communicate via action potentials
  • Microelectrode located near & neuron is able to pick up this activity
  • Provides info about processing in individual neurones or a small number of neurons
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16
Q

What are neuroimaging techniques?

A
  • Pick up consequences of electrical signals in the brain without the need for direct access
  • Provide info about processing in brain at the level of whole brain areas
  • EEG/MEG: Good temporal res, bad spatial res
  • fMRI: good spatial res, bad temporal res
17
Q

What are computational methods?

A
  • Build mathematical models of info processing at diff levels
  • Provide very precise explanations of biological vision
  • Important implications for machine vision
18
Q

Neuropsychology and Neuropsychiatry?

A
  • Studying individuals with brain lesions or neurological/psychiatric conditions
  • Important for understanding healthy vision
  • Treatment and interventions