Editing Atkinson–Shiffrin memory model (section)

==Search of associative memory (SAM)==
Due to the above and other criticism through the 1970s, the original model underwent many revisions to account for phenomena it could not explain. The "search of associative memory" (SAM) model is the culmination of that work. The SAM model uses a two-phase memory system: short- and long-term stores. Unlike the original Atkinson–Shiffrin model, there is no sensory store in the SAM model.<ref name=RaaijmakersShiffrin1981 />

===Short-term store===
Short-term store takes on the form of a buffer, which has a limited capacity. The model assumes a buffer rehearsal system in which the buffer has a size, ''r''. Items enter the short-term store and accompany other items that are already present in the buffer, until size ''r'' has been reached. Once the buffer is at full capacity,  when new items enter, they replace an item, ''r'', which already exists in the buffer. A probability of 1/''r'' determines which already existing item will be replaced from the buffer.<ref name=RaaijmakersShiffrin1981 /> In general, items that have been in the buffer for longer are more likely to be replaced by new items.<ref name=PhillipsShiffrinAtkinson1967 />

===Long-term store===
The long-term store is responsible for storing relationships between different items and of items to their contexts. Context information refers to the situational and temporal factors present at the time when an item is in the short-term store, such as emotional feelings or environmental details. The amount of item-context information which is transferred to the long-term store is proportional to the amount of time that the item remains in the short-term store. On the other hand, the strength of the item-item associations is proportional to the amount of time that two items simultaneously existed in the short-term store.<ref name=RaaijmakersShiffrin1981 />

===Retrieval from long-term store===
[[File:Retrieval in SAM.png|thumb|Simplified diagram of the steps involved in retrieving an item from the long-term store under the SAM model. Simplification of the diagram found in Raaijmakers & Shiffrin, 1981.<ref name=RaaijmakersShiffrin1981 />]]
It is best to show how items are recalled from the long-term store using an example. Assume a participant has just studied a list of word pairs and is now being tested on his memory of those pairs. If the prior list contained, ''blanket – ocean'', the test would be to recall ''ocean'' when prompted with ''blanket – ?''.

Memories stored in long-term store are retrieved through a logical process involving the assembly of cues, sampling, recovery, and evaluation of recovery. According to the model, when an item needs to be recalled from memory the individual assembles the various cues for the item in the short-term store. In this case, the cues would be any cues surrounding the pair ''blanket – ocean'', like the words that preceded and followed it, what the participant was feeling at the time, how far into the list the words were, etc.

Using these cues the individual determines which area of the long-term store to search and then samples any items with associations to the cues. This search is automatic and unconscious, which is how the authors would explain how an answer "pops" into one's head. The items which are eventually recovered, or recalled, are those with the strongest associations to the cue item, here ''blanket''. Once an item has been recovered it is evaluated, here the participant would decide whether ''blanket – [recovered word]'' matches ''blanket – ocean''. If there is a match, or if the participant believes there is a match, the recovered word is output. Otherwise the search starts from the beginning using different cues or weighting cues differently if possible.<ref name=RaaijmakersShiffrin1981 />

===Recency effects===
The usefulness of the SAM model and in particular its model of the short-term store is often demonstrated by its application to the recency effect in free recall. When serial-position curves are applied to SAM, a strong recency effect is observed, but this effect is strongly diminished when a distractor, usually arithmetic, is placed in between study and test trials. The recency effect occurs because items at the end of the test list are likely to still be present in short-term store and therefore retrieved first. However, when new information is processed, this item enters the short-term store and displaces other information from it. When a distracting task is given after the presentation of all items, information from this task displaces the last items from short-term store, resulting in a substantial reduction of recency.<ref name=RaaijmakersShiffrin1981 />

===Problems for the SAM model===
The SAM model faces serious problems in accounting for long-term recency data<ref name=BjorkWhitten1974 /> and long-range contiguity data.<ref name=HowardKahana1999 /> While both of these effects are observed, the short-term store cannot account for the effects. Since a distracting task after the presentation of word pairs or large interpresentation intervals filled with distractors would be expected to displace the last few studied items from the short-term store, recency effects are still observed. According to the rules of the short-term store, recency and contiguity effects should be eliminated with these distractors as the most recently studied items would no longer be present in the short-term memory. Currently, the SAM model competes with single-store free recall models of memory, such as the Temporal Context Model.<ref name=HowardKahana2002/> 

Additionally, the original model assumes that the only significant associations between items are those formed during the study portion of an experiment. In other words, it does not account for the effects of prior knowledge about to-be-studied items. A more recent extension of the model incorporates various features which allow the model to account for memory store for the effects of prior semantic knowledge and prior episodic knowledge. The extension proposes a store for preexisting semantic associations; a contextual drift mechanism allowing for decontextualisation of knowledge, e.g. if you first learned a banana was a fruit because you put it in the same class as apple, you do not always have to think of apples to know bananas are fruits; a memory search mechanism that uses both episodic and semantic associations, as opposed to a unitary mechanism; and a large lexicon including both words from prior lists and unpresented words.<ref name=SirotinKimballKahana2005 />