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Related Concept Videos

Cognitivism01:17

Cognitivism

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Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process...
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Introduction to Cognitive Psychology01:20

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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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The human brain, a complex organ, is functionally divided into two cerebral hemispheres—left and right. These hemispheres are interconnected by a structure of paramount importance, the corpus callosum. This substantial bundle of neural fibers is not just a bridge between the hemispheres but a crucial element for the brain's comprehensive functioning. It enables efficient communication between the two hemispheres, allowing each side of the brain to control and receive sensory and motor...
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Cognitive Learning01:21

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
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Organization of the Brain01:30

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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
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Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
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Related Experiment Video

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Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
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Human Cognitive Neuroscience as It Is Taught.

Olaf Hauk1

  • 1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.

Frontiers in Psychology
|December 17, 2020
PubMed
Summary

Junior cognitive neuroscience researchers need better data analysis training. An online survey revealed skill gaps in areas like signal analysis and linear algebra, highlighting a demand for targeted educational programs.

Area of Science:

  • Cognitive Neuroscience
  • Scientific Computing
  • Data Analysis

Background:

  • Cognitive neuroscience utilizes complex data analysis, requiring diverse skills from researchers in psychology, engineering, and medicine.
  • Interdisciplinary backgrounds present challenges in acquiring scientific computing and data analysis skills.
  • Effective communication is hindered by varying knowledge and skill sets among researchers.

Purpose of the Study:

  • To assess the current methods skills of junior researchers in cognitive neuroscience.
  • To identify specific areas where skills acquisition is needed.
  • To provide an empirical basis for developing targeted training programs.

Main Methods:

  • An online survey was administered to 307 cognitive neuroscience students and post-doctoral researchers.
Keywords:
EEGMEGcomputational modelingfMRIneuroimagingskillssurveytraining

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  • Multiple-choice questions assessed fundamental neuroimaging data analysis concepts (signal analysis, linear algebra, statistics).
  • Performance was analyzed based on undergraduate degree, researcher status, gender, and self-rated expertise.
  • Main Results:

    • Overall accuracy was 72%, with 'Methods' graduates (87%) outperforming 'Biology' (73%) and 'Psychology' (66%) graduates.
    • Accuracy improved from undergraduate (59%) to PhD (74%) levels but plateaued at the post-doctoral level (74%).
    • Significant performance differences were observed in signal analysis and linear algebra, crucial for neuroimaging.

    Conclusions:

    • Junior cognitive neuroscience researchers demonstrate a need for improved methods skills, particularly in signal analysis and linear algebra.
    • Researchers are aware of their skill gaps and express a strong demand for additional, skills-oriented training.
    • The findings support the development of bespoke training programs to enhance data analysis capabilities in the field.