The dynamics of memory context dependent updating No charge femdom chat
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).Bottom: CMR2 simulations capture the release from PI pattern. CMR2 simulations of hit and false alarm rates in recognition. As predicted by CMR2, recognition false alarm rates correlate with free recall intrusion rates.We investigate the neurophysiology of episodic memory with electrocorticographic (ECo G) and single neuron recordings from neurosurgical patients who have had electrodes surgically implanted on the cortical surface of the brain or in the medial temporal lobes (including hippocampus) as part of the clinical process of localizing seizure foci.Specifically, recency effects appear because the context at the time of the memory test is most similar to the context associated with recent items.When an item is retrieved at test, it reinstates the context active when that item was studied.By analyzing the dynamics of the recall process one can quantify the way in which people transition from one recalled word to the next (see Fig. Furthermore, by studying the electrophysiology of the brain while engaged in memory tasks, we can find, for example, regions that show increased or decreased activity when a word is successfully encoded (i.e., later recalled) versus when it is not successfully encoded, known as the subsequent memory effect (see Fig. Two of our ongoing, large-scale data collection projects are the Penn Electrophysiology of Encoding and Retrieval Study (PEERS), a multi-session experiment with young and older adults combining free recall and scalp EEG (a book of these results can be found here); and an effort to collect electrophysiological data on patients with intractable epilepsy (undergoing monitoring with intracranial electrodes at partnering local hospitals) while they participate in a variety of memory and decision-making tasks.To explain the processes underlying encoding, organization and retrieval of episodic memories, Kahana and colleagues (notably Marc Howard, Sean Polyn, Per Sederberg, and Lynn Lohnas) have developed a class of retrieved-context models.
The temporal context model (TCM; Howard and Kahana, 2002) was introduced to explain recency and contiguity effects in free recall.
Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. An associative weight matrix (MFC) allows each item to update a context representation that contains the item and source features of recently studied items.
MATLAB scripts to run the CMR2 model can be downloaded here. During study, the features of each item are associated with coactive context elements. This curve shows the probability of making a recall to serial position i lag immediately following recall of serial position i—that is, the conditional-response probability (CRP) as a function of lag. Participants studied lists of three items, each drawn from the same semantic category.
The Computational Memory Lab uses mathematical modeling and computational techniques to study human memory.
We apply these quantitative methods both to data from laboratory studies of human memory and from electrophysiological studies involving direct human brain recordings in neurosurgical patients.
Participants were instructed to memorize the object images.