Semantic memory refers to general world knowledge that humans have accumulated throughout their lives. This general knowledge (word meanings, concepts, facts, and ideas) is intertwined in experience and dependent on culture. New concepts are learned by applying knowledge learned from things in the past.
Semantic memory is distinct from episodic memory—the memory of experiences and specific events that occur in one's life that can be recreated at any given point. For instance, semantic memory might contain information about what a cat is, whereas episodic memory might contain a specific memory of stroking a particular cat.
Semantic memory and episodic memory are both types of explicit memory (or declarative memory), or memory of facts or events that can be consciously recalled and "declared". The counterpart to declarative or explicit memory is implicit memory (also known as nondeclarative memory).
The idea of semantic memory was first introduced following a conference in 1972 between Endel Tulving and W. Donaldson on the role of organization in human memory. Tulving constructed a proposal to distinguish between episodic memory and what he termed semantic memory. He was mainly influenced by the ideas of Reiff and Scheers, who in 1959 made the distinction between two primary forms of memory. One form was entitled remembrances, and the other memoria. The remembrance concept dealt with memories that contained experiences of an autobiographic index, whereas the memoria concept dealt with memories that did not reference experiences having an autobiographic index. Semantic memory reflects the knowledge of the world, and the term general knowledge is often used. It holds generic information that is more than likely acquired across various contexts and is used across different situations. According to Madigan in his book titled Memory, semantic memory is the sum of all knowledge one has obtained—vocabulary, understanding of math, or all the facts one knows.
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Multiprocessors are a core component in all types of computing infrastructure, from phones to datacenters. This course will build on the prerequisites of processor design and concurrency to introduce
L'objectif de ce cours est d'introduire les étudiants à la pensée algorithmique, de les familiariser avec les fondamentaux de l'Informatique et de développer une première compétence en programmation (
In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ
Memory is the faculty of the mind by which data or information is encoded, stored, and retrieved when needed. It is the retention of information over time for the purpose of influencing future action. If past events could not be remembered, it would be impossible for language, relationships, or personal identity to develop. Memory loss is usually described as forgetfulness or amnesia. Memory is often understood as an informational processing system with explicit and implicit functioning that is made up of a sensory processor, short-term (or working) memory, and long-term memory.
In mammalian brain anatomy, the prefrontal cortex (PFC) covers the front part of the frontal lobe of the cerebral cortex. The PFC contains the Brodmann areas BA8, BA9, BA10, BA11, BA12, BA13, BA14, BA24, BA25, BA32, BA44, BA45, BA46, and BA47. The basic activity of this brain region is considered to be orchestration of thoughts and actions in accordance with internal goals. Many authors have indicated an integral link between a person's will to live, personality, and the functions of the prefrontal cortex.
The temporal lobe is one of the four major lobes of the cerebral cortex in the brain of mammals. The temporal lobe is located beneath the lateral fissure on both cerebral hemispheres of the mammalian brain. The temporal lobe is involved in processing sensory input into derived meanings for the appropriate retention of visual memory, language comprehension, and emotion association. Temporal refers to the head's temples. The temporal lobe consists of structures that are vital for declarative or long-term memory.
This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.
This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.
Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.
Explores visibility in concurrency, memory models, shared memory, and hardware optimizations.
Delves into memory integration, priming, and transfer of learning concepts.
How the 'what', 'where', and 'when' of past experiences are stored in episodic memories and retrieved for suitable decisions remains unclear. In an effort to address these questions, the authors present computational models of neural networks that behave l ...
This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a graph of textual snippets from review text, where the edges are defined by sem ...
Comprehensive memory safety validation identifies the memory objects whose accesses provably comply with all classes of memory safety, protecting them from memory errors elsewhere at low overhead. We assess the breadth and depth of comprehensive memory saf ...