Predictive processing

Question 1

Prediction error minimization

Answer 1

1. Build model of the world, H, based on sensory input
2. Evaluate H by taking action, thereby getting a new O, using that to update the probability of H
3. Keep taking action to minimise the error on H to build confidence in H
4. If new O indicates that H’ is more probable, abandon H, and evaluate H’ by taking action

Question 2

Bayes rule/inference

Answer 2

P(H│O)=(P(O│H)·P(H))/(P(O))

Question 3

Sensory input

Answer 3

What we perceive (bottom up)

Question 4

Expectation

Answer 4

What we expect to perceive

Question 5

Bottom up processing

Answer 5

An outer stimulus (that often was uninspected) that goes from the senses to the brain

Question 6

Top down processing

Answer 6

The brain expects something

Question 7

Hierarchical processing

Answer 7

There are different layers which become more and more abstract and when we perceive something it starts with the least abstract one (our senses)

Question 8

Likelihood

Answer 8

P(O|H)
The probability of observing something given the hypothesis

Question 9

Binocular rivalry

Answer 9

We can only perceive one thing at a time, so when we see two overlapping images with a face and a house we can only perceive one of them at a time (you can only focus on one thing and the other things will be “blinded out”)
Rivalry is characterized by this very dramatic change in actual visual consciousness

Question 10

Today’s posterior is tomorrows prior

Answer 10

We always update our priors and beliefs

Question 11

Solution to symbol grounding problem

Answer 11

No longer symbols

Question 12

Feedforward error signal

Answer 12

Bottom up processing. When we perceive something unexpected

Question 13

Main assumption of predictive processing

Answer 13

“a […] substantial view based on the rather uncontroversial idea that the brain is involved in information processing, and that information theory is cast in terms of the probability theory from which Bayes’ rule is derived”
The brain is only concerned with minimizing prediction error

Question 14

Normative notion

Answer 14

How it should be and not how it is

Question 15

Díaz-Caneja stimuli

Answer 15

Reveal that we update our prior probability/hypothesis.
In 1928 Emilio Diaz-Caneja (Diaz-Caneja 1928) discovered that if the two images are cut in half and combined such that one eye sees, for example, half a house and half a face, and the other eye sees the other halves of the house and the face, then there is not rivalry between what is presented to each eye, there is instead rivalry between the full, uncut images of the face and the house

Question 16

Active inference

Answer 16

We sample sensory input in the light of the model we hold about the world. We should expect that the brain minimizes prediction error by changing its position in the world and by changing the states of the world, both of which will change its sensory input
Action in this sense of testing perceptual models is therefore a moment of prediction error minimization

Question 17

Perceptual inference

Answer 17

Is done following Bayes’ rule to infer causes of sensory input. Minimization of the variation of the expected prediction error. A matter of selecting and adjusting hypotheses about the world in response to the prediction error they engender

Question 18

External interpretation

Answer 18

Interpretations that come from experience

Question 19

Phenomenology

Answer 19

An approach that concentrates on the study of consciousness and the objects of direct experience.

Question 20

Neuroanthropomorphism

Answer 20

Inappropriately imputing human-like properties to the brain and thereby confusing personal level explanations with subpersonal level explanations

Question 21

Functionalist

Answer 21

Mental states are defined by a functional role that specifies a certain kind of input-output profile, given a certain internal state

Question 22

Causal inference

Answer 22

The process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system

Question 23

Inferential

Answer 23

Characterized by or involving conclusions reached on the basis of evidence and reasoning.

Question 24

Invariant representations

Answer 24

Representations that do not change

Question 25

The perceptual hierarchy

Answer 25

The basic idea for the hierarchy of perceptual inference is that for every level of the hierarchy we probe deeper into the causal structure of the world

Question 26

Empirical Bayes

Answer 26

The prior expectations are pulled down from what has previously been learned best at higher levels of the hierarchy

Question 27

Attention allocation

Answer 27

Updating working memory, and language processing are interdependent cognitive tasks related to the focused direction of limited resources, refreshing and substituting information in the current focus of attention, and receiving/sending verbal communication, respectively

Question 28

Agency

Answer 28

Important, without it we would be stuck at our starting point
To improve our position in the world and that we, of course, use the way we perceive the world to inform and guide agency

Question 29

Perceptual inference

Answer 29

A matter of selecting and adjusting hypotheses about the world in response to the prediction error they engender

Question 30

James-Lange theory

Answer 30

Feeling states arise as responses to states of bodily arousal including rise in heart rate, perspiration, and so on
E.g. “I cry therefore I’m sad”

Question 31

Interoceptive

Answer 31

The feeling of knowing what is happening in your body

Question 32

Introspection

Answer 32

We attend to our own mental states

Question 33

Introspective dissonance

Answer 33

Introspection seems both accessible and certain, and inaccessible and uncertain.

Question 34

Emotion

Answer 34

Perceptual inference on our internal states

Question 35

Privacy of self

Answer 35

Makes my estimate of the state of affairs independent of the estimates of others, meaning that we can use the estimates together socially to make even better estimates

Question 36

The self

Answer 36

A self-model is needed to predict how acting on the world results in new sensory input

Question 37

Best inference

Answer 37

The inference that minimizes prediction error

Question 38

Marginal probability

Answer 38

P(O): The sum of the probabilities of O conditional in all hypotheses