The dynamics of memory context dependent updating
These models assume that the input to the memory system itself produces contextual drift, and that the current state of context is used to retrieve items from memory.
Consistent with experimental data, TCM and its variants also predict that recency and contiguity effects are approximately time-scale invariant (Sederberg, Howard, and Kahana, 2008).
Polyn, Norman, and Kahana (2009) developed the Context Maintenance and Retrieval model (CMR), which is a generalized version of TCM that accounts for the influence of non-temporal associations (e.g., semantic knowledge) on recall dynamics.
MATLAB scripts to run the CMR model can be downloaded here.
In CMR2, memory accumulates across multiple experimental lists, and temporal context is used both to focus retrieval on a target list and to censor retrieved information when its match to the current context indicates that it was learned in a non-target list.
The model simultaneously accounts for a wide range of intralist and interlist phenomena, including the pattern of prior-list intrusions observed in free recall, build-up of and release from proactive interference, and the ability to selectively target retrieval of items on specific prior lists (Jang & Huber, 2008; Shiffrin, 1970).