Human Prediction About Life

Humans make predictions of themselves and their surroundings, helping them to make sense of incoming data rapidly and reliably. We examine the broad concepts that arise from recent empirical studies on how expectations influence the neuronal computations that underpin processing of information and perception, explaining how expectations affect vision, as well as the brain origins and targets of expectation, and we look at how empirical evidence informs and constrains theoretical computational models of perception. As several specific examples of such effect show, anticipation may alter perception in a variety of ways. When sensory information is noisy, ambiguous, or weak, anticipation can influence perception, altering not just how well but also what is perceived. When the contrast of the dots or the coherence of motion direction in the cloud is poor, for example, the direction in which a cloud of dots is observed to move might be influenced by an implicit anticipation of the most likely direction. Similarly, when the input is ambiguous, people’s perceptions might be substantially influenced by their expectations. Participants were more likely to identify totally ambiguously moving dots as traveling in the direction corresponding with the glasses they wore after learning to link a certain set of coloured eyeglasses with either leftward or rightward moving dots.

Expectation bias can also emerge in a much more indirect way. A recent study found that modifying participants’ expectancies by exposing them to lines moving slow or fast, made them more likely to perceive perpendicular or oblique movement, respectively. Expectations, on the other hand, are less likely to distort the contents of perception when stimuli are clear or when expectations are severely wrong (seeing a face while anticipating a house). In such cases, the impacts of expectations are more modest and frequently limited to perceptual efficiency, resulting in stimuli being recognized more quickly and correctly when properly expected, compared to when they are not. In general, the proportional influence of expectancies vs sensory information on perception is determined by their respective dependability. Observers depend on past knowledge mostly when predictions are unclear and stimuli are accurate, while they rely on information the most when expectations are weak and stimuli are reliable. This type of uncertainty weighting is compatible with computer models that represent perception as inference.

Our past knowledge, which can be gained via a wealth of experience, has a significant influence on how we see the world; For example, in Figure A, because light normally originates from above, we see forms with shaping at the top (bottom) as concave (convex). Perception can also be influenced by knowledge of the present (high-level) situation. In Figure B, for example, we plainly see a street scene with a car and a pedestrian. However, in this case, the ‘vehicle’ and ‘pedestrian’ are two identical hazy forms that differ only in their orientation and placement in the scene context. In other words, the forms themselves have no information that identifies them as a car or a person, but it is the context of the street scene that causes us to see them as such. On extremely short durations, prior experience can also influence perception. Looking at Figure C; the top picture looks to be a nonsensical arrangement of black and white pieces. However, after seeing the greyscale version of the image once, your perception of the black and white image changes abruptly and powerfully. (PAPER DE LANGE)

Studies that looked at the influences of predictions on perception usually compare expected stimuli versus unexpected stimuli and what is generally found is a benefit for expected stimuli; for example, expected stimuli are faster to getting access to consciousness: Conscious contents, according to one understanding, emerge when predictive models are validated by matched sensory information. On the other hand, conscious contents emerge when unexpected occurrences contradict present perceptual assumptions. Finally, the cognitive impenetrability account holds that such higher-level elements have no effect on conscious experience. Pinto et al. (2015) discovered that anticipated stimuli enter consciousness faster than neutral or surprising stimuli in four tests. These effects are challenging to explain in terms of response priming, pre-existing stimulus connections, or attentional mechanisms causing asynchronous temporal order judgements; and their findings also imply that when bottom-up information is uncertain, top-down expectations play a bigger role, which is consistent with predictive processing models of perception, supporting the concept that conscious access is dependent on the verification of perceptual expectations. (PAPER PINTO 2015); Expected stimuli are also better at discriminating them and are perceived with better clarity.

Research questions
Can we replicate the classic findings showing that expectations have an effect on visual perception?
Do expectations only influence perception when stimuli need to be processed rapidly but not when are processed for longer?

The idea is that expectations are especially useful to rapidly make sense of incoming information but maybe they’re not needed that much when you have more time for progressing and it might be why we do not see an effect in these cases.

Every trial started with a word, end this word was then followed by one of these shapes. The word acted as a cue which in deduced an expectation about the upcoming shape. The idea is if you read the word circle you expect to see the circle shape. It is because throughout life you have learnt to associate the word circle with the circle shape. In addition, the relationship within the word circle and its shape it is also maintained throughout the experiment because on the majority of trials the word circle is followed by the circle shape on 72% of trials. The other two shapes, the triangle and the square were less likely to follow the word circle and here we have divided them into two levels of expectedness: unexpected and highly unexpected. The square is more unexpected then the triangle because eat only follows the word circle 4% of the time while the triangle 24%. And Another thing that was manipulated was when participants could respond they could either respond immediately or after a short delay. The idea is that if they had to give the response immediately the input had to be processed rapidly whereas when the response was delayed there was more time for processing. in both cases participants could respond as soon as the question mark appeared on the screen but we manipulated when these question marks occurred. In a both the immediate and delayed response conditions the trial starts with a fixation cross and the word cue; in the immediate response condition, the shape and the question marks appeared on the screen together so participants could give their responses immediately. In the delayed response condition, the stimuli are first presented for 200ms on own and only then the question mark appeared on the screen

Do you need help with this assignment or any other? We got you! Place your order and leave the rest to our experts.

Quality Guaranteed

Any Deadline

No Plagiarism