Engram (neuropsychology) Engrams are a means by which memory traces are stored[1] as biophysical or biochemical changes in the brain (and other neural tissue) in response to external stimuli.
They are also sometimes thought of as a neural network or fragment of memory, sometimes using a hologram analogy to describe its action in light of results showing that memory appears not to be localized in the brain. The existence of engrams is posited by some scientific theories to explain the persistence of memory and how memories are stored in the brain.
The existence of neurologically defined engrams is not significantly disputed, though their exact mechanism and location has been a focus of persistent research for many decades. The term engram was coined by the little-known but influential memory researcher Richard Semon. Karl S. In Lashley's experiments (1929, 1950), rats were trained to run a maze. Later, Richard F. One region that Thompson's group studied was the lateral interpositus nucleus (LIP). Hebbian theory. Hebbian theory is a theory in neuroscience which proposes an explanation for the adaptation of neurons in the brain during the learning process.
It describes a basic mechanism for synaptic plasticity, where an increase in synaptic efficacy arises from the presynaptic cell's repeated and persistent stimulation of the postsynaptic cell. Introduced by Donald Hebb in his 1949 book The Organization of Behavior,[1] the theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows: "Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability.… When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.
Hebbian engrams and cell assembly theory[edit] Stigmergy. Stigmergy is a mechanism of indirect coordination between agents or actions.[1] The principle is that the trace left in the environment by an action stimulates the performance of a next action, by the same or a different agent.
In that way, subsequent actions tend to reinforce and build on each other, leading to the spontaneous emergence of coherent, apparently systematic activity. Stigmergy is a form of self-organization. It produces complex, seemingly intelligent structures, without need for any planning, control, or even direct communication between the agents. As such it supports efficient collaboration between extremely simple agents, who lack any memory, intelligence or even individual awareness of each other.[1] History[edit] Swarm intelligence. Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial.
The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.[1] The application of swarm principles to robots is called swarm robotics, while 'swarm intelligence' refers to the more general set of algorithms. 'Swarm prediction' has been used in the context of forecasting problems.
Example algorithms[edit] Particle swarm optimization[edit] Ant colony optimization[edit] Artificial bee colony algorithm[edit] Artificial bee colony algorithm (ABC) is a meta-heuristic algorithm introduced by Karaboga in 2005,[5] and simulates the foraging behaviour of honey bees. Bacterial colony optimization[edit] Differential evolution[edit] Differential evolution is similar to genetic algorithm and pattern search. Hebbian theory. Long-term potentiation.
Long-term potentiation (LTP) is a persistent increase in synaptic strength following high-frequency stimulation of a chemical synapse.
Studies of LTP are often carried out in slices of the hippocampus, an important organ for learning and memory. In such studies, electrical recordings are made from cells and plotted in a graph such as this one. This graph compares the response to stimuli in synapses that have undergone LTP versus synapses that have not undergone LTP. Synapses that have undergone LTP tend to have stronger electrical responses to stimuli than other synapses. The term long-term potentiation comes from the fact that this increase in synaptic strength, or potentiation, lasts a very long time compared to other processes that affect synaptic strength.[1]