Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.

Memory stretches over a lifetime. In controlled laboratory settings, the hippocampus and other medial temporal lobe brain structures have been shown to represent space and time on the scale of meters and seconds. It remains unclear whether the hippocampus also represents space and time over the longer scales necessary for human episodic memory. We recorded neural activity while participants relived their own experiences, cued by photographs taken with a custom lifelogging device. We found that the left anterior hippocampus represents space and time for a month of remembered events occurring over distances of up to 30 km. Although previous studies have identified similar drifts in representational similarity across space or time over the relatively brief time scales (seconds to minutes) that characterize individual episodic memories, our results provide compelling evidence that a similar pattern of spatiotemporal organization also exists for organizing distinct memories that are distant in space and time. These results further support the emerging view that the anterior, as opposed to posterior, hippocampus integrates distinct experiences, thereby providing a scaffold for encoding and retrieval of autobiographical memories on the scale of our lives.hippocampus | representational similarity analysis | lifelogging | episodic memory T he hippocampus plays a critical role in remembering the events of our lives (1). Direct evidence from single-neuron recordings in rats indicates that cells in the hippocampus fire in specific spatial locations (2-6) or at specific times during a temporal delay (7,8). Single-neuron and functional MRI (fMRI) studies in individuals navigating virtual environments have confirmed that cells coding for spatial location are also present in the human hippocampus (9-11). Similarly, place-responsive cell activity recorded in the hippocampus of patients with epilepsy during navigation of a virtual town was shown to reinstate during episodic memory retrieval of the previous virtual navigation (12). Together, these studies provide evidence that the same neurons in the medial temporal lobe (MTL) that are active during an experience also help represent the memory for that experience. These results, however, are limited to simple events in laboratory settings that occur on the scale of minutes and meters, thereby leaving unanswered whether we harness similar mechanisms in more natural settings and over larger temporal and spatial scales.Recent studies have used more naturalistic designs with incidentally acquired memories recorded via lifelogging devices that automatically capture photographs from the participants' lives (13,14). The typical finding is increased hippocampal activation when participants view images from their cameras as opposed to images from other participants' cameras (15-17), and this activation decays over the course of months (14). Still, there is no evidence to date that the hippocampus or other MTL structures actually represent space or time of autobiographical experiences. We a...

This paper reports the results of a study of free association in which participants were asked to produce the first two words to come to mind. The findings were used to estimate the reliability of indices of strength and set size for different types of items and to model free association as a retrieval task. When confined to first responses, reliability was generally high for both indices, particularly for words with smaller sets of associates and stronger primaries. When second responses were included, reliability declined. A second response added new but weak items to the set, and, when the primary associate was not produced on the first opportunity, it tended not to be produced on the second. Relative to when multiple responses are requested, first-response free association provides more reliable indices of the relative strength and set size for a word's strongest associates. A model of free association assuming that a strength distribution underlies each response provided a good fit to the data.Memory tasks and their theoretical implementations model everyday memory tasks. Research on free recall, cued recall, and recognition, as well as work with implicit memory procedures, capture some, ifnot the majority, of the characteristics of the memory requirements needed in interactions with the environment. In this context, it is interesting that a memory task that has been used in research for more than 100 years (Galton, 1880) has not attracted much theoretical attention. We refer to free association, a task that requires participants to produce the first word to come to mind that is related in a specified way to a presented cue (e.g., meaning, rhyme, makes a word). This task is used in everyday activities as a means for "collecting thoughts." For example, when one uses the Yellow Pages, free associating to a needed product or service can be helpful in determining an effective search heading. The same advantage is apparent when attempting to find information on the Internet or just the right word in writing and speech. Similarly, we are often called on to provide information in response to broad and unanticipated questions, such as "Why are you a Democrat?" In such cases, recovering the needed information can be more akin to free association to the question than to directed recall.Free association is a utilitarian production task that has been directed to a variety ofdifferent types of information, such as

A powerful theoretical framework for exploring recognition memory is the global matching framework, in which a cue's memory strength reflects the similarity of the retrieval cues being matched against the contents of memory simultaneously. Contributions at retrieval can be categorized as matches and mismatches to the item and context cues, including the self match (match on item and context), item noise (match on context, mismatch on item), context noise (match on item, mismatch on context), and background noise (mismatch on item and context). We present a model that directly parameterizes the matches and mismatches to the item and context cues, which enables estimation of the magnitude of each interference contribution (item noise, context noise, and background noise). The model was fit within a hierarchical Bayesian framework to 10 recognition memory datasets that use manipulations of strength, list length, list strength, word frequency, study-test delay, and stimulus class in item and associative recognition. Estimates of the model parameters revealed at most a small contribution of item noise that varies by stimulus class, with virtually no item noise for single words and scenes. Despite the unpopularity of background noise in recognition memory models, background noise estimates dominated at retrieval across nearly all stimulus classes with the exception of high frequency words, which exhibited equivalent levels of context noise and background noise. These parameter estimates suggest that the majority of interference in recognition memory stems from experiences acquired before the learning episode.