Foundation to Cognitive Psychology.Explained.

An Introduction

 The scientific study of how people perceive, understand, evaluate, and think about the complexities and significance of mind is known as cognitive psychology. Cognitive psychology has always been concerned with evaluating the science of mental life. Cognitive psychology has a significant impact on psychology as a whole, and cognitive science, which is a unified programme for studying the mind, is its more inclusive partner. The mind is a processor that helps us understand and transmit information to others by processing information from our senses. If this processing is prohibited, the data may not be processed in a meaningful manner. For example, in dyslexia, a child may struggle in school due to an impairment in their ability to read English texts fluently, a disorder known as dyslexia. It's a learning disability that prevents you from turning printed characters into useful information. Cognitive psychologists observe behaviours in the lab in order to draw concrete conclusions about hidden mental processes. As a result, the experimental method is central to cognitive psychology. The main goal of cognitive psychology has always been to explain how humans use complex and often mysterious cognitive processes to transform input into thoughts and actions (Eysenck, 2004, Willingham, 2007). As a result, understanding human psychology without focusing on cognitive psychology may be impossible. Cognitive psychology benefited greatly in its research domain from work in the area of artificial intelligence, thanks to the use of computational metaphors. This led to the development of another subject for study, cognitive science, which attempts to integrate a variety of approaches in research on the mind and mental processes. The key turning points in cognitive psychology's development would be extremely useful in comprehending its journey. It would aid in comprehending behaviorism's demise, computer metaphors and information processing, abstract intelligence, and other schools of thought.



It describes how data from the environment is processed through a series of stages or processing systems. When a stimulus is presented, for example, our basic perceptual processes kick in, followed by our attentional processes. Our attentional processes transfer the information that has been the focus of our attention to our short term memory, which is then transferred to our long term memory store (perception, attention and memory). Cognitive psychologists have used this model for decades because it makes sense and is simple to comprehend. Three assumptions of the information processing approach are as follows: • Cognition can be understood by breaking it down into a series of sequential stages using processing systems. • The system modifies the incoming data, resulting in unique processing at each stage. • The goal of this model is to specify the processes and structures. For example, at the perceptual stage, information is coded; at the memory stage, information is recalled, which improves our concept formation, judgement, and so on. Because each component is linked to the next stage, it can be difficult to tell which stage is present at the start. It should be obvious that the initial stage is always incoming data, which is then processed into stages for specific purposes. There is also a significant drawback to this strategy. It has been observed that the individual's past experiences and expectations have a significant impact on processing. As a result, the stimuli intrude on an organism that is either inactive or unprepared to process the incoming data. There are a variety of approaches to investigating cognitive psychology. Traditional methods of obtaining evidence about human cognition are referred to as such. Experimental cognitive psychology, cognitive neuropsychology, and cognitive neurosciences are some of them (which is explained in the next modules). Let's look at the other two, which are as follows:

Cognitive psychology research

Experimental methods are used to measure the behaviours that cognitive psychology has always been known for. It is possible to explain the cognitive processes involved in human behaviour by measuring their behaviour. A researcher manipulates one of the variables in a true experiment to see how it affects another variable. For example, we'd like to know if background noise has an impact on math problem performance. Two different groups would be randomly assigned to either a no-noise or a with-noise group in this experiment. The first group will be asked to solve math problems in a quiet environment, whereas the second group will be asked to solve problems while hearing a sound, such as a bell, which is referred to as with-noise. The independent variable in this example is the presence or absence of noise. The dependent variable refers to our final outcome measurement. Physiological methods or cognitive neuropsychology Physiological measurements are important in addition to assessing individual behaviour. Brain activity, eye movements, blood pressure, and heart rate, among other bodily systems, are also being used in experiments to better understand cognitive processes. Electroencephalogram (EEG), Neuro-imaging, and brain lesions are some of the methods that can help us understand it. EEG (Electroencephalogram) is a multichannel recording of the brain's continuous electrical activity. It is measured using a multichannel recorder, which aids in the detection of voltage changes caused by large numbers of neurons. On the scalp, a large number of electrodes are placed. The frequency will be determined by the brain's activity, including whether it is awake and alert, relaxed, or in various stages of sleep. The problem with this method is that it doesn't specify where the evoked potentials are generated. Other methods are required for this. When EEG is unable to help specify exact locations, neuroimaging is used. The location of neural activity generated during a cognitive task is measured using neuroimaging. When compared to electrical scalp recordings, there are a variety of techniques that can provide an indirect measure of more localised brain activity. A strong magnetic pulse causes molecules in the brain to move in Magnetic Resonance Imaging (MRI). Radio frequencies are used to detect the motion of these molecules, which are then reconstructed into 3-D images. CT scans have a lower resolution than MRI scans. However, there is no structure-function relationship in it. Positron emission tomography is another method (PET). Increased radio-labeled glucose activity in the brain is scanned in this method while subjects engage in various cognitive processes. The spatial resolution appears to be good, but the temporal resolutions are not. Functional Magnetic Resonance Imaging is the third technique for assessing localised areas (fMRI). It aids in the detection of changes in blood flow to specific areas of the brain when they are active. It gives you a functional and anatomical view of the brain. It is non-invasive and provides better spatial and temporal resolution than a PET scan. Brain lesions are an ancient method of studying the brain's various functions. It aids in the observation of people who have suffered damage to their brain tissue as a result of accidents, strokes, or diseases like Alzheimer's and Parkinson's. Lesions offer a novel approach to studying the brain's cognitive functions. Physicians did not begin to document disorders caused by damage to certain regions of the brain until World War II. Understanding which brain regions are involved in which types of cognitive functions is useful in determining the exact causes of dysfunctions.


Connectitionism is an alternative to more traditional information processing methods. Its goal is to capture the basic cognitive processes as they might be manifested in the brain. Neurons are the basic building blocks of the brain, and they are connected to other neurons in the brain. Models of neural networks as they might exist in the brain are known as connectionist networks. The two basic connectionist ideas are that information can be broken down into basic units or neurons, and that these neurons are connected. They come in a variety of strengths that can be further customised with the units. Only when both neurons fire at the same time can the connection be made. Connectionist models also assume that many connections can be active at the same time. This is an obvious example of parallel processing, as opposed to serial processing, which is limited to only one connection at a time. Parallel distributed processing is another name for the connectionist model (Detailed discussion in memory module).



Over a century ago, cognitive psychology experiments were being conducted. Philosophers were also interested in cognitive processes, but it wasn't until the late nineteenth century that the first attempts to bring cognitive processes into the laboratory were made. This aided in the study of these concepts in the context of scientific thought. In the fields of perception and attention (Wundt, 1874), memory (Ebbinghaus, 1885), and learning (Wundt, 1874), significant breakthroughs were made (Thorndike, 1914). At this time, research was primarily focused on basic cognitive processes, which led to the development of theories and experimental design that we see today. It was discovered that the research conducted at this time could be applied to real-life situations, but this was not the main goal of their research. For example, Ebbinghaus (1885) conducted experiments on spaced learning and massed learning, demonstrating that learning can be improved by providing some rest. It reduces fatigue and improves concentration. This became a widely used strategy for increasing leaning efficiency. Cognitive researchers, on the other hand, were primarily concerned with pure research, and any practical applications were viewed as largely incidental.

This approach to cognitive psychology was challenged by Bartlett (1932), who argued that cognitive researchers should also consider the relevance of the real world. He went on to say that cognitive researchers should use more naturalistic experimental designs and test materials that are based on or even resemble real-life situations. He contributed his thoughts by using pictures and stories in memory research, such as courtroom witness testimony (discussed in later module). As a result, his research has left an indelible mark on the field of cognitive psychology.


World War 2 ushered in the modern era of cognitive psychology. The war resulted in significant technological changes as well as extraordinary human efforts to adapt to these changes. As a result of the introduction of new or advanced equipment, it has become increasingly important to understand the capabilities and limitations of human operators. During this time, a new goal arose to assess human performance and attention, which led to the development of artificial intelligence.

Donald Broadbent, a British psychologist who was a pilot trainer during the war and thus had firsthand experience of the cognitive problems faced by most pilots at the time, was referred to as a pioneer of a new wave of applied research. Broadbent (1958) became more interested in studying the human brain's ability to process information. Humans' abilities to deal with two or more competing perceptual inputs at the same time were given special attention. To delve deeper into this, he devised a method for determining the fundamental limitation of human attention, and he was able to apply his findings to aiding the pilots' performance. The year 1956 was a watershed moment in the history of cognitive psychology. According to Anderson (1995), cognitive psychology first emerged between 1950 and 1970, spanning two decades. Chomsky founded the field of artificial intelligence in 1956. Both cognitive psychology and cognitive science were born in this year. Cognitive Psychology is the title of his book. The "Father of Cognitive Psychology," as Neisser is known, was a pioneer in the field of cognitive psychology. Neisser defined cognition as "all processes by which sensory input is transformed, reduced, elaborated, stored, recovered, and used; it is concerned with these processes even when they operate in the absence of relevant stimulation, as in images and hallucinations." It is clear that all psychological phenomena are related to cognitive aspects.


From the 1930s to the 1960s, the work of Pavlov, Skinner, and Watson contributed significantly to the growth of this field. Watson focused more on observable behaviour and was eager to move psychological research from the laboratory to the real world. He disliked the approach of introspection and functionalist approach and recommended that thoughts and feelings be dropped from the study of psychology because they are not directly observed.


Structuralism was based on the method of introspection, which was initiated by Wundt and developed by Titchener, and was aimed at describing the elemental components of consciousness such as sensation, images, and feelings. According to this school of thought, consciousness was considered to be the proper subject matter of psychology.


Functionalism was a philosophy that opposed the prevailing structuralism of psychology in the late 19th century. One of the most prominent proponents of functionalism was Thorndike, who is best known for his puzzle box. He was considered to study the primary issues of functionalism. This school of thought also focused on observable events rather than unobservable events (such as what goes on in someone's mind).


Many changes in human psychology were brought about by World War II, which inspired dissatisfaction with the behavioristic approach, as there was a need to solve the problems faced by the military on a practical basis. It was seen that many of the problems were of a cognitive nature, such as fatigue, demands of constant vigilance, and so on.


The remarkable increase in research in the area of cognition has been credited to the twentieth-century psychology revolution (Baars, 1986; Gardner, 1985; Matlin, 1989), which led to the development of digital computers, which provided psychologists with both a plausible metaphor (the mind as a computational system) and an innovative method for investigating the mind (Baars, 1986; Gardner, 1985; Matlin, 1989).

Artificial intelligence

Machines or programmes that use intelligence to solve complex problems in the same way that humans do are known as artificial intelligence. Examples include computers performing medical diagnoses, flying jet planes, and playing chess. Artificial intelligence in essence entails creating programmes and devices that are efficient, flexible, and learn through experience, though they may not be as similar in approach as human consciousness.

Al research has two main goals (Winston, 1984): the first is to make computers more useful to people, and the second is to investigate the principles that make intelligence possible. To put it another way, Al researchers with the first goal tend to be interested in developing intelligent machines, whereas those with the latter goal seek to create intelligent machines.


• The information processing model has dominated cognitive psychology, where cognition can only be understood by breaking it down into a series of sequential stages using processing systems, which can then be further investigated using experimental methods and neuropsychological methods.


  1. It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with primary consciousness will probably have to come first.

    The thing I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990's and 2000's. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I've encountered is anywhere near as convincing.

    I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there's lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.

    My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar's lab at UC Irvine, possibly. Dr. Edelman's roadmap to a conscious machine is at

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