A Distributed Representation of Temporal Context Export

@article{howardKahana02, abstract = {The principles of recency and contiguity are two cornerstones of the theoretical and empirical analysis of human memory. Recency has been alternatively explained by mechanisms of decay, displacement, and retroactive interference. Another account of recency is based on the idea of variable context (Estes, 1955; Mensink \& Raaijmakers, 1989). Such notions are typically cast in terms of a randomly fluctuating population of elements reflective of subtle changes in the environment or in the subjects' mental state. This random context view has recently been incorporated into distributed and neural network memory models (Murdock, 1997; Murdock, Smith, \& Bai, 2001). Here we propose an alternative model. Rather than being driven by random fluctuations, this formulation, the temporal context model (TCM), uses retrieval of prior contextual states to drive contextual drift. In TCM, retrieved context is an inherently asymmetric retrieval cue. This allows the model to provide a principled explanation of the widespread advantage for forward recalls in free and serial recall. Modeling data from single-trial free recall, we demonstrate that TCM can simultaneously explain recency and contiguity effects across time scales.}, author = {Howard, M. W. and Kahana, M. J.}, citeulike-article-id = {5936603}, citeulike-linkout-0 = {http://dx.doi.org/10.1006/jmps.2001.1388}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0022-2496(01)91388-4}, doi = {10.1006/jmps.2001.1388}, issn = {00222496}, journal = {Journal of Mathematical Psychology}, keywords = {context, distributed, language}, month = {June}, number = {3}, pages = {269--299}, posted-at = {2009-10-13 14:58:43}, priority = {2}, title = {A Distributed Representation of Temporal Context}, url = {http://dx.doi.org/10.1006/jmps.2001.1388}, volume = {46}, year = {2002} }

TY - JOUR ID - howardKahana02 L3 - citeulike-article-id:5936603 N2 - The principles of recency and contiguity are two cornerstones of the theoretical and empirical analysis of human memory. Recency has been alternatively explained by mechanisms of decay, displacement, and retroactive interference. Another account of recency is based on the idea of variable context (Estes, 1955; Mensink & Raaijmakers, 1989). Such notions are typically cast in terms of a randomly fluctuating population of elements reflective of subtle changes in the environment or in the subjects' mental state. This random context view has recently been incorporated into distributed and neural network memory models (Murdock, 1997; Murdock, Smith, & Bai, 2001). Here we propose an alternative model. Rather than being driven by random fluctuations, this formulation, the temporal context model (TCM), uses retrieval of prior contextual states to drive contextual drift. In TCM, retrieved context is an inherently asymmetric retrieval cue. This allows the model to provide a principled explanation of the widespread advantage for forward recalls in free and serial recall. Modeling data from single-trial free recall, we demonstrate that TCM can simultaneously explain recency and contiguity effects across time scales. IS - 3 JF - Journal of Mathematical Psychology SN - 00222496 EP - 299 TI - A Distributed Representation of Temporal Context VL - 46 SP - 269 KW - context KW - distributed KW - language AU - Howard, MW AU - Kahana, MJ PY - 2002/06// UR - http://dx.doi.org/10.1006/jmps.2001.1388 ER -