Related Experiment Video
Updated: Jan 22, 2026
08:49
Transduction and Expansion of Primary T Cells in Nine Days with Maintenance of Central Memory Phenotype
Published on: March 18, 2020
11.6K
Convergence on collective memories: Central speakers and distributed remembering
Jeremy K Yamashiro1, William Hirst2
1Department of Psychological and Brain Sciences.
Journal of Experimental Psychology. General
|July 19, 2019
Summary
Central speakers can shape collective memory by influencing what groups remember and forget. Ingroup relationships amplify this effect, while outgroup relationships diminish it, impacting shared memory formation.
Area of Science:
- Social Psychology
- Cognitive Psychology
- Collective Memory Studies
Background:
- Collective memory research examines how public figures influence group recall.
- Sociocognitive processes are key to understanding how memory is reshaped.
Purpose of the Study:
- To investigate how Central Speakers induce memory effects in listeners.
- To examine the role of communication and group membership in moderating these effects.
Main Methods:
- Two experiments were conducted to assess memory influence.
- Methods included inducing socially shared retrieval-induced forgetting (SSRIF) and examining serial transmission chains.
- Listener's relational motives and perceived group membership were operationalized.
Main Results:
- Central Speakers induced SSRIF and shared practice effects.
- Communicational remembering amplified memory inaccessibility for unmentioned items.
- Perceived group membership moderated these effects: ingroup amplified, outgroup attenuated.
Conclusions:
- Central Speakers significantly influence collective memory through sociocognitive processes.
- Communication dynamics and social identity play crucial roles in memory transmission and modification.
- Understanding these mechanisms is vital for analyzing public discourse and memory formation.
Related Concept Videos
01:54Convergent Evolution
31.5K
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
31.5K
01:17Region of Convergence
895
The z-transform is a powerful mathematical tool used in the analysis of discrete-time signals and systems. It is a crucial tool in the analysis of discrete-time systems, but its convergence is limited to specific values of the complex variable z. This range of values, known as the Region of Convergence (ROC), is fundamental in determining the behavior and stability of a system or signal. The ROC defines the region in the complex plane where the z-transform converges, which can take various...
895
02:16Measures of Central Tendency
20.2K
The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...
20.2K
01:21Convergence of Fourier Series
384
The Fourier series is a powerful mathematical tool for representing periodic signals as an infinite sum of complex exponentials. In practice, this infinite series is truncated to a finite number of terms, yielding a partial sum. This truncation makes the approximation of the signal feasible but introduces certain challenges, particularly near discontinuities, known as the Gibbs phenomenon.
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
384
01:25The Central Dogma
139.0K
Overview
139.0K
01:20Region of Convergence of Laplace Tarnsform
1.1K
The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This...
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This...
1.1K