Parallel processing (psychology)

In psychology, parallel processing is the ability of the brain to simultaneously process incoming stimuli of differing quality. Parallel processing is associated with the visual system in that the brain divides what it sees into four components: color, motion, shape, and depth. These are individually analyzed and then compared to stored memories, which helps the brain identify what you are viewing. The brain then combines all of these into the field of view that is then seen and comprehended. This is a continual and seamless operation. For example, if one is standing between two different groups of people who are simultaneously carrying on two different conversations, one may be able to pick up only some information of both conversations at the same time. Parallel processing has been linked, by some experimental psychologists, to the stroop effect (resulting from the stroop test where there is a mismatch between the name of a color and the color that the word is written in). In the stroop effect, an inability to attend to all stimuli is seen through people's selective attention.

Background

In 1990, American Psychologist David Rumelhart proposed the model of parallel distributed processing (PDP) in hopes of studying neural processes through computer simulations. According to Rumelhart, the PDP model represents information processing as interactions between elements called units, with the interactions being either excitatory or inhibitory in nature. Parallel Distributed Processing Models are neurally inspired, emulating the organisational structure of nervous systems of living organisms. A general mathematical framework is provided for them.

Parallel processing models assume that information is represented in the brain using patterns of activation. Information processing encompasses the interactions of neuron-like units linked by synapse-like connections. These can be either excitatory or inhibitory. Every individual unit's activation level is updated using a function of connection strengths and activation level of other units. A set of response units is activated by the propagation of activation patterns. The connection weights are eventually adjusted using learning.

Serial vs parallel processing

In contrast to parallel processing, serial processing involves sequential processing of information, without any overlap of processing times. The distinction between these two processing models is most observed during visual stimuli is targeted and processed (also called visual search).

Visual search

In case of serial processing, the elements are searched one after the other in a serial order to find the target. When the target is found, the search terminates. Alternatively, it continues to the end to ensure that the target is not present. This results in reduced accuracy and increased time for displays with more objects.

On the other hand, in the case of parallel processing, all objects are processed simultaneously but the completion times may vary. This may or may not reduce the accuracy, but the time courses are similar irrespective of the size of the display.

However, there are concerns about the efficiency of parallel processing models in case of complex tasks which are discussed ahead in this article.

Aspects of a parallel distributed processing model

There are eight major aspects of a parallel distributed processing model: This means that at any given point, there is a possibility that any of the possible set of input patterns is impinging on the input units. Animals with wider-set eyes have a harder time establishing depth, such as horses and cows. A special depth test was used on infants, named The Visual Cliff. This test consisted of a table, half coated in a checkerboard pattern, and the other half a clear plexiglass sheet, revealing a second checkerboard platform about a foot below. Although the plexiglass was safe to climb on, the infants refused to cross over due to the perception of a visual cliff. This test proved that most infants already have a good sense of depth. This phenomenon is similar to how adults perceive heights.

Certain cues help establish depth perception. Binocular cues are made by humans' two eyes, which are subconsciously compared to calculate distance. This idea of two separate images is used by 3-D and VR filmmakers to give two dimensional footage the element of depth. Monocular cues can be used by a single eye with hints from the environment. These hints include relative height, relative size, linear perspective, lights and shadows, and relative motion.

These limits to attentional resources sometimes lead to serial bottlenecks in parallel processing, meaning that parallel processing is obstructed by serial processing in between. However, there is evidence for coexistence of serial and parallel processes.

Feature integration theory

The feature integration theory by Anne Treisman is one of the theories that integrates serial and parallel processing while taking into account attentional resources. It consists of two stages-

Detection of features- This stage occurs instantaneously and uses parallel processing. In this step, all the basic features of a display are picked up simultaneously, even if attention is being paid to a specific object.
Integration of features- This step is more time-consuming and uses serial processing. It leads to the perception of whole objects and patterns.