@article {65283, title = {Fundamental law of memory recall.}, journal = {Physical Review Letters}, volume = {124}, year = {2020}, month = {2020 Jan 10}, pages = {018101}, abstract = {

Human memory appears to be fragile and unpredictable. Free recall of random lists of words is a standard paradigm used to probe episodic memory. We proposed an associative search process that can be reduced to a deterministic walk on random graphs defined by the structure of memory representations. The corresponding graph model can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled (R) out of M items in memory: R=sqrt[3πM/2]. This prediction was verified with a specially designed experimental protocol combining large-scale crowd-sourced free recall and recognition experiments with randomly assembled lists of words or common facts. Our results show that human memory can be described by universal laws derived from first principles.

}, issn = {1079-7114}, doi = {10.1103/PhysRevLett.124.018101}, author = {Naim, Michelangelo and Katkov, Mikhail and Romani, Sandro and Tsodyks, Misha} } @article {47382, title = {Practice makes perfect in memory recall.}, journal = {Learning \& Memory (Cold Spring Harbor, N.Y.)}, volume = {23}, year = {2016}, month = {2016 Apr}, pages = {169-73}, abstract = {

A large variability in performance is observed when participants recall briefly presented lists of words. The sources of such variability are not known. Our analysis of a large data set of free recall revealed a small fraction of participants that reached an extremely high performance, including many trials with the recall of complete lists. Moreover, some of them developed a number of consistent input-position-dependent recall strategies, in particular recalling words consecutively ("chaining") or in groups of consecutively presented words ("chunking"). The time course of acquisition and particular choice of positional grouping were variable among participants. Our results show that acquiring positional strategies plays a crucial role in improvement of recall performance.

}, issn = {1549-5485}, doi = {10.1101/lm.041178.115}, author = {Romani, Sandro and Katkov, Mikhail and Tsodyks, Misha} } @article {46283, title = {Effects of long-term representations on free recall of unrelated words.}, journal = {Learning \& Memory}, volume = {22}, year = {2015}, month = {2015 Jan 15}, pages = {101-8}, abstract = {

Human memory stores vast amounts of information. Yet recalling this information is often challenging when specific cues are lacking. Here we consider an associative model of retrieval where each recalled item triggers the recall of the next item based on the similarity between their long-term neuronal representations. The model predicts that different items stored in memory have different probability to be recalled depending on the size of their representation. Moreover, items with high recall probability tend to be recalled earlier and suppress other items. We performed an analysis of a large data set on free recall and found a highly specific pattern of statistical dependencies predicted by the model, in particular negative correlations between the number of words recalled and their average recall probability. Taken together, experimental and modeling results presented here reveal complex interactions between memory items during recall that severely constrain recall capacity.

}, issn = {1549-5485}, doi = {10.1101/lm.035238.114}, author = {Katkov, Mikhail and Romani, Sandro and Tsodyks, Misha} } @article {47240, title = {Neural Network Model of Memory Retrieval.}, journal = {Frontiers in Computational Neuroscience}, volume = {9}, year = {2015}, month = {2015 Dec 17}, pages = {149}, abstract = {

Human memory can store large amount of information. Nevertheless, recalling is often a challenging task. In a classical free recall paradigm, where participants are asked to repeat a briefly presented list of words, people make mistakes for lists as short as 5 words. We present a model for memory retrieval based on a Hopfield neural network where transition between items are determined by similarities in their long-term memory representations. Meanfield analysis of the model reveals stable states of the network corresponding (1) to single memory representations and (2) intersection between memory representations. We show that oscillating feedback inhibition in the presence of noise induces transitions between these states triggering the retrieval of different memories. The network dynamics qualitatively predicts the distribution of time intervals required to recall new memory items observed in experiments. It shows that items having larger number of neurons in their representation are statistically easier to recall and reveals possible bottlenecks in our ability of retrieving memories. Overall, we propose a neural network model of information retrieval broadly compatible with experimental observations and is consistent with our recent graphical model (Romani et al., 2013).

}, issn = {1662-5188}, doi = {10.3389/fncom.2015.00149}, author = {Recanatesi, Stefano and Katkov, Mikhail and Romani, Sandro and Tsodyks, Misha} } @article {46284, title = {Word length effect in free recall of randomly assembled word lists.}, journal = {Frontiers in Computational Neuroscience}, volume = {8}, year = {2014}, month = {2014 Oct 14}, pages = {129}, abstract = {

In serial recall experiments, human subjects are requested to retrieve a list of words in the same order as they were presented. In a classical study, participants were reported to recall more words from study lists composed of short words compared to lists of long words, the word length effect. The world length effect was also observed in free recall experiments, where subjects can retrieve the words in any order. Here we analyzed a large dataset from free recall experiments of unrelated words, where short and long words were randomly mixed, and found a seemingly opposite effect: long words are recalled better than the short ones. We show that our recently proposed mechanism of associative retrieval can explain both these observations. Moreover, the direction of the effect depends solely on the way study lists are composed.

}, issn = {1662-5188}, doi = {10.3389/fncom.2014.00129}, author = {Katkov, Mikhail and Romani, Sandro and Tsodyks, Misha} }