Neurophysiology and Information

Transcription

1 Neurophysiology and Information Christopher Fiorillo BiS 527, Spring , Part 10: Perception Reading: Students should visit some websites where they can experience and learn about illusions. Addresses are given in later slides.

2 Inference, Perception, and Attention Conscious perception appears to correspond to the information of neurons at the top of the cortical hierarchy Structures such as prefrontal cortex and hippocampus The process of top-down selective attention influences the information that is processed Bottom-up inputs that are the most relevant to reward and the least predictable are selectively processed by higher levels Perception corresponds to the information of highlevel neurons about the state of the world (their best guess )

3 Bayes s Theorem Posterior distribution = prior X likelihood Best guess = combination of prior knowledge with current sensory evidence Information can be separated in various ways prior knowledge, current visual evidence, current auditory evidence, etc. Examples: The aperture problem McGurk Effect Sensorimotor task P(B AC) P(A BC) = P(A C) x P(B C)

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6 Illusions and Perceptual Ambiguity Many illusions are the result of rational inference The sensory evidence coming into the brain is ambiguous There are many possible interpretations of what is the true state of the world. To guess, the brain combines prior information with new sensory information Prior information is already in the brain as the result of learning about patterns in the sensory world Some patterns are common, and these are the patterns that the brain expects to see Illusions occur when sensory patterns are unusual (in a statistical sense). The rational, best guess is that the pattern is similar to the pattens that have been experienced in the past (based on the prior information). But in some rare circumstances, our best guess is wrong, and we experience an illusion. The critical point is that when we experience an illusion, we are doing the best we possibly can with our limited information. Our brains are working perfectly.

7 The Aperture Problem The direction of motion of a large object is ambiguous when viewed in a small region of space (an aperture ) Given the current sensory evidence, motion could be in any direction over a range of 180 degrees What is the relevant prior information (what are the most common patterns in the world)? There is more likely to be one object moving with one velocity rather than multiple objects moving with multiple velocities. Objects tend to move slower rather than faster. A Detailed Study Weiss, Simoncelli, and Adelson. Motion illusions as optimal percepts. Nature Neuroscience 2002

8 Bayesian Integration in Sensorimotor Learning Kording and Wolpert, Nature 2004 As in studies of visual illusions, this study provided evidence of Bayesian integration In the case of visual illusions, the prior information comes from a lifetime of experience with the visual world. Prior information is not controlled by the experimenters In this experiment, they manipulated a frequency distribution, and they showed that subjects were able to learn about that distribution and use that knowledge as their prior in Bayesian integration.

9 An Audiovisual Illusion The McGurk Effect When we watch someone speak, our perception of their words depends on both auditory and visual information What we hear depends on both auditory and visual inputs (as well as prior information) Conscious perception corresponds to high-level multisensory neurons, not low-level monosensory neurons

10 Perceptual Bistability These images exhibit perceptual bistability There are two ways in which they are perceived, and they alternate There are numerous objects that are consistent with these images. The sensory evidence is ambiguous. The brain guesses that one of two objects is the most probable given knowledge of objects in the real world. Perception corresponds to the best guess. For example, the lower image is seen as a 3-D cube, rather than as an unusual combination of 2-D lines There are higher neurons for faces and vases and cubes of various orientations, but not for objects that have not been learned through experience. Usually, the perceived object changes every few seconds. This is probably because of adaptation in high level neurons. Over time, the perceived object becomes more predictable, and the activity of neurons that represent that object decreases. Then the other object is perceived.

11 Binocular Rivalry When different images are presented to the two eyes, one image is seen (usually for a few seconds), and then the other One does not see a superposition (mixture) of the two, or an average To observe rivalry, view the images from a short distance, but allow your eyes to relax as though you are looking at something far away Rivalry demonstrates that some of the information that is present at low levels of the visual system is suppressed and does not advance to the high levels Since the two images are not compatible with one another, the high levels see only one or the other This is a rational inference When the two images differ quantitatively rather than qualitatively, then one observes an average of the two The alternation could be explained by adaptation of neurons at higher levels of cortex Rivalry is not seen at all in LGN. It is weakly present in neurons of striate cortex, and becomes stronger at higher levels. It is essentially complete in IT cortex.

12 Consciousness The neural basis of consciousness is not agreed upon But it is agreed upon that consciousness corresponds to a relatively small number of high level neurons, presumably in cerebral cortex. It does not correspond to low-level cortical neurons (like V1) Consciousness cannot be observed. Thus, knowledge of consciousness is based largely upon introspection Therefore, I should speak about my consciousness Since there is no entity that integrates more information than a single neuron, I am convinced that consciousness corresponds to just one neuron I am just one high-level neuron. However, it is reasonable to think that each of the neuron s in my brain, and the world, could be conscious. The fact that consciousness can shift from one object to another is explained by top-down reward signals that select bottom-up inputs and mediate selective attention (as discussed in later)