Functional fixation refers to the tendency to view the functions or uses we assign to objects as fixed or stable so that we do not see the properties of the stimulus that might be useful in problem-solving. Functional fixation occurs when top-down processing is over-activated because we depend too much on our previous concepts, expectations, and memories. Thus, one perceives an object in terms of its most general use. Because objects in the world have a fixed function, a strategy of using one tool for one task and another for another is usually appropriate. Therefore, functional fixation is a basic mistake made in the cognitive process and is often the result of a fundamentally rational strategy.
We use problem-solving when we want to reach a particular goal, but we often don’t immediately figure out the proper path to the goal. For problem-solving, we can think about the four main aspects: problem understanding, problem-solving strategies, factors that influence problem-solving, and creativity. Factors affecting problem-solving include bottom-up and bottom-up processing, which are important for effective problem-solving. Upstream processing emphasizes information about stimuli registered in sensory receptors. Top-down processing, on the other hand, emphasizes concepts, expectations, and memories from past experiences. Experts make good use of well-developed top-down processing techniques. They take full advantage of their accumulated concepts, expectations, and knowledge. However, excessive use of top-down processing sometimes hinders effective problem solving, such as functional fixation and set-of-mind.

We rely too much on previous concepts, expectations, and memories when solving problems. Functional fixation means that we tend to view the functions or uses we assign to objects as fixed or stable. Thus, we do not see the properties of the stimulus that might be useful in problem-solving. That is, functional fixation arises because of the tendency to perceive an object in terms of its most general use.
For example, a person may be moving boxes in an apartment, and he may feel uncomfortable because there is no foot to secure the door, but he may not realize that one of the boxes can be used for that same purpose. Similarly, many people don’t realize that a coin or a blade can be used as a screwdriver in an emergency. As such, functional fixation reflects perceptual rigidity.
The basic mistakes made in cognitive processes are often the result of very rational strategies. Normally, objects in the world have a fixed function. We use a screwdriver to tighten the screws, and we use coins to buy something. In general, a strategy of using one tool for one task and another for another task is appropriate. Each tool is designed specifically for its unique task. But when we rigidly apply such strategies, functional fixation occurs. For example, without a driver, you don’t realize that a coin can take over its function. Similarly, it is generally a wise strategy to use the knowledge you have learned while solving previous problems to solve your current dilemma.
The purpose of the hammer is a tool used to drive nails, but it can also be used as a hammer to put the paper on top so that it does not fly off. To break free from functional fixation like this, we need to increase the flexibility of our thinking.

Reference

https://psu.instructure.com/courses/2130474/modules/items/33027172

At any given moment in real life, the senses are poured out. What will happen to all this coming in? Most of the information leaves your sensory memory within seconds. But the information you pay attention to goes from your sensory memory to your short-term memory. Short-term memory can be thought of as a link between our fast-changing sensory memory and our longer-lasting, long-term memory.
How long information stays in short-term memory depends on how you handle it.
If you don’t do anything with the information, only about 20 seconds will remain in your short-term memory. However, if the information is rehearsed, the information from which the information was rehearsed will be retained in short-term memory for a relatively long time.
This is called maintenance rehearsal.
Maintenance demonstration? It is simply a repetition of information mechanically in order to retain it in short-term memory. There is a limit to the amount of information that can be retained in short-term memory. George Miller discovered that 7 (+B-2) bottles could be stored in short-term memory as blue. A chunk is a meaningful unit of information.
To see how chunking information into 7 or fewer units can be an effective means of using short-term memory, try to memorize the following list of numbers – 19761814164314751203 If you are chunking numbers, you’re probably 1976.1814.1643.1475.1203 You will be able to remember everyone.

Long-term memory is a permanent repository of experiences, knowledge, and skills. Items in long-term memory can be short or can last a lifetime. One way to move information from long-term memory is an elaborative rehearsal, which organizes data and associates it with information in long-term memory that you already have. There are two types of long-term memory: procedural memory and declarative memory. Procedural memory is concerned with remembering how to do things, such as tying shoes, swimming, or riding a bike.
Declarative memory is where explicit information is stored. Sometimes this is called real memory. There are two types of declarative memory: semantic memory and episodic memory. Semantic memory is concerned with remembering general knowledge, especially the meanings and concepts of words. Episodic memory is the memory of a specific event or anecdote that has been personally experienced.

In general, the encoding of linguistic data in short-term memory is different from long-term memory.
The encoding of verbal material into short-term memory tends to be phonological or auditory rather than visual. For example, from short-term memory, when asked to recall letters, they tend to confuse them with sound letters like D and T rather than letters that look like D and O. Conversely, long-term memory items are likely to be encoded based on meaning. This claim was supported by the study of semantic priming.
In general, in a semantic task study, the subject must decide whether the stimulus is a word or not. In a classical experiment, subjects are presented with pairs of semantically related words, some of which are unrelated. The subject’s task is to press a button if two words are real words and not press a button if both words are not. This reaction time is faster if the two words are semantically related.

References:

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The Psychology of Learning and Motivation: Advances in Research and Theory (Vol. 2). New York: Academic Press.

Tulving, E., Schacter, D. L., & Stark, H. (1982년). Priming effects in word-fragment completion are independent of recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 336-342.

https://psu.instructure.com/courses/2130474/modules/items/33027112

Cognitive neuroscience is a field that studies all mental functions related to neural processes and is a field that seeks to understand the relationship between the brain and the mind by considering various conceptual views. Cognitive neuroscientists seek to understand human cognitive functions based on the idea that human information processing processes will be similar to computer information processing processes (Banich, 2008). Cognitive neuroscientists want to reveal the structure and function of the nervous system that operates in the cognitive process by studying what neurobiological reactions occur in which part of the brain when given a specific stimulus and what behavioral reactions appear externally.

In the field of cognitive neuroscience, researchers are interested in how humans’ overall cognitive processes such as attention, consciousness, decision making, learning, memory, language, social cognition, and emotion are performed in the brain.

1. Attention

In attention-related experiments, participants observe brain mechanisms when they are asked to pay attention to only one of the various stimuli presented. Studies have shown that top-down attention is associated with the left frontal lobe, and bottom-up attention is associated with sensory or parietal areas (Hoppinger, Buoncore, & Mangun, 2000). Experiments using accompanying simulation tasks (flanker tasks) found that the brain regions involved in enforcement (or intentional) attention was frontal and parietal regions (Fan et al., 2005).

  2. Emotion

For the emotional brain region, Damagio et al., 2000 discovered nerve maps related to fear, happiness, sadness, and anger using positron emission imaging. It has also been reported that the amygdala is associated with fear (Vuilleumier et al., 2001). Recently, many brain area studies related to emotional regulation have been conducted (Banks, Eddy, Angstadt, Nathan, & Phan, 2007; Goldin, Mcrae, Ramel, & Gross, 2008).

  3. language

With the development of brain imaging techniques, evidence has been reported for Broca’s area of the left hemisphere, the Wernicke’s area, and the court fibers involved in language (Parker et al., 2005). In addition, brain areas related to language areas are expanding and subdivided through various studies.

Magnetic resonance imaging, MRI is also sensitive to small changes in the biological structure of the brain by exploring the density of hydrogen atoms and interactions with surrounding fibers in the electromagnetic field of the brain. When a person’s head is placed in a cylindrical device in which a magnetic field is emitted and radio waves are projected, the rotational axis of atoms in the body aligned in a specific direction within a high magnetic field falls and occurs in unison due to the impact of the radio wave. At this time, a change in the magnetic field is formed, which is detected using detectors surrounding the skull. When the computer detects the detected change and configures the result as a three-dimensional image, an image of a brain fragment can be obtained.

According to the article, Using data from the National Institutes of Health’s Adolescent Brain Cognitive Development (ABCD) Study, which started in 2015 and will follow about 12,000 9- to 11-year-olds for a decade, the researchers first looked at gray matter volume in the brain. They found that compared to typically developing children, those with disruptive behavior disorders had a less gray matter in the amygdala and hippocampus, areas associated with processing emotion and forming memories. The work, which Waller and Hawes published in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, suggests that early behavior problems do show up in the brain, often regardless of the presence or absence of CU traits.

Among other aspects, future work will analyze what’s happening in the brain when losses occur—the yellow square in the monetary-incentive experiment. It’s all intending to understand whether what’s seen in the brain at age nine or 10 indicates the potential for risky behaviors down the line. Ultimately, the researchers say, it will help to develop novel treatments for conduct problems informed by what’s known about brain function and structure in these disorders.

References

Brain scans of 9-to 11-year-olds offer clues about aggressive, antisocial behavior https://medicalxpress.com/news/2020-08-brain-scans-year-olds-clues.html

Banks, S. J., Eddy, K. T., Angstadt, M., Nathan, P. J., & Phan, K. L. (2007). Amygdala – frontal connectivity during emotion regulation. Social Cognitive and Affective Neuroscience, 2(4), 303-312.

Cloutier, J., Gabrieli, J. D., O’Young, D., & Ambady, N. (2011). An fMRI study of violations of social expectations: when people are not who we expect them to be. NeuroImage, 57(2), 583-588.

Goldin, P. R., Mcrae, K., Ramel, W., & Gross, J. J. (2008). The neural bases of emotion regulation: reappraisal and suppression of negative emotion. Biological Psychiatry, 63(6), 577-586.

Hopfinger, J. B., Buonocore, M. H., & Mangun, G. R. (2000). The neural mechanisms of top-down attentional control. Natute Neuroscience, 3(3), 284-291.