Memory stability
Stability of memory is a long-term memory variable that determines how long a memory can last if not retrieved. Stability determines the probability of forgetting in unit time (the higher the stability, the less the probability). For the exact formula, see: Forgetting curve.
Stability (S) and Retrievability (R) are part of the Two component model of long-term memory. At each review, stability increases along the stabilization curve (see: Stabilization).
Stability slows down encoding of new memories in the affected system of synapses. This slow down prevents memory interference, which is the prime cause of forgetting. This property can be used by the brain to optimize memory storage. Similarly, it can be used in artificial neural networks to prevent catastrophic forgetting.
In SuperMemo, stability is expressed as the period of time in which 10% of memories are likely to be forgotten.
See also:
- Two components of memory
- Two component model of long-term memory
- Two component model of memory stability
- Search for a universal memory formula
This glossary entry is used to explain SuperMemo, a pioneer of spaced repetition software since 1987
Figure: Changes in memory status over time for an exemplary piece of knowledge. The horizontal axis represents time spanning the entire repetition history. The top panel shows retrievability (tenth power, R10, for easier analysis). Retrievability grid in gray is labelled by R=99%, R=98%, etc. The middle panel displays optimum intervals in navy. Repetition dates are marked by blue vertical lines and labelled in aqua. The end of the optimum interval where R crosses 90% line is marked by red vertical lines (only if intervals are longer than optimum intervals). The bottom panel visualizes stability (presented as
ln(S)/ln(days)for easier analysis). The graph shows that retrievability drops fast (exponentially) after early repetitions when stability is low, however, it only drops from 100% to 94% in long 10 years after the 7th review. All values are derived from an actual repetition history and the three component model of memory.
Figure: Uncertain course of the stabilization of complex memories. The picture shows a hypothetical course of stabilization, forgetting, generalization, and interference on the example of a single dendritic input pattern of a single concept cell. The neuron, dendrites and dendritic filipodia are shown in orange. The picture does not show the conversion of filopodia into dendritic spines whose morphology changes over time with stabilization. The squares represent synapses involved in the recognition of the input pattern. Each square shows the status of the synapse in terms of the two component model of long-term memory. The intensity of red represents retrievability. The size of the blue area represents stability. After memorizing a complex memory pattern, the concept cell is able to recognize the pattern upon receiving a summation of signals from the red squares representing a new memory of high retrievability and very low stability. Each time the cell is re-activated, active inputs will undergo stabilization, which is represented by the increase in the blue area in the input square. Each time a signal does not arrive at an input while the concept cell is active, its stability will drop (generalization). Each time a source axon is active and the target neuron fails to fire, the stability will drop as well (competitive interference). Due to the uneven input of signal patterns to the concept cell, some synapses will be stabilized, while others will be lost. Forgetting occurs when a synapse loses its stability and its retrievability and when the relevant dendritic spine is retracted. Generalization occurs when the same concept cell can be re-activated using a smaller, but a more stable input pattern. Retroactive interference occurs when a new input pattern contributes to forgetting some of the redundant inputs necessary for the recognition of the old input pattern. Stabilization of the old patterns results in the reduced mobility of filopodia, which prevents the takeover of a concept by new patterns (proactive interference). At the every end of the process, a stable and a well-generalized input pattern is necessary and sufficient to activate the concept cell. The same cell can respond to different patterns as long as they are consistently stabilized. In spaced repetition, poor choice of knowledge representation will lead to poor reproducibility of the activation pattern, unequal stabilization of synapses, and forgetting. Forgetting of an item will occur when the input pattern is unable to activate sufficiently many synapses and thus unable to reactivate the concept cell. At repetition, depending on the context and the train of thought, an item may be retrieved or forgotten. The outcome of the repetition is uncertain