Biology subjects

Tsodyks, M.

Publications and source records attributed to Tsodyks, M..

11 recordsLinked to original sources

bioRxiv2024

Random Tree Model of Meaningful Memory

Traditional studies of memory for meaningful narratives focus on specific stories and their semantic structures but do not address common quantitative features of recall across different narratives. We introduce a statistical ensemble of random trees to represent narratives as hierarchies of key points, where each node is a compressed representation of its descendant leaves, which are the original narrative segments. Recall is modeled as constrained by working memory capacity from this hierarchical structure. Our analytical solution aligns with observations from large-scale narrative recall experiments. Specifically, our model explains that (1) average recall length increases sublinearly with narrative length, and (2) individuals summarize increasingly longer narrative segments in each recall sentence. Additionally, the theory predicts that for sufficiently long narratives, a universal, scale-invariant limit emerges, where the fraction of a narrative summarized by a single recall sentence follows a distribution independent of narrative length.

neuroscience↗

bioRxiv2024

Hierarchical Working Memory and a New Magic Number

Working memory often appears to exceed its basic span by organizing items into compact representations called chunks. Chunking can be learned over time for familiar inputs; however, it can also arise spontaneously for novel stimuli. Such on-the-fly structuring is crucial for cognition, yet the underlying neural mechanism remains unclear. Here we introduce a synaptic theory of chunking, in which short-term synaptic plasticity enables the formation of chunk representations in working memory. We show that a specialized population of "chunking neurons" selectively controls groups of stimulus-responsive neurons, akin to gating. As a result, the network maintains and retrieves the stimuli in chunks, thereby exceeding the basic capacity. Moreover, we show that our model can dynamically construct hierarchical representations within working memory through hierarchical chunking. A consequence of this proposed mechanism is a new limit on the number of items that can be stored and subsequently retrieved from working memory, depending only on the basic working memory capacity when chunking is not invoked. Predictions from our model were confirmed by analyzing single-unit responses in epileptic patients and memory experiments with verbal material. Our work provides a novel conceptual and analytical framework for understanding how the brain organizes information in real time.

neuroscience↗

bioRxiv2024

Synaptic Theory of Working Memory for Serial Order

AO_SCPLOWBSTRACTC_SCPLOWPeople effortlessly remember short, but otherwise arbitrary, sequences of familiar stimuli over a brief period of time. This deceptively mundane ability is core for purposeful behavior and cognition. Surprisingly, however, it remains largely unexplained. Here, we propose that both the stimuli and their order of occurrence are encoded by transient synaptic enhancement over multiple time scales. To substantiate this proposal, we extend our previously-proposed synaptic theory of Working Memory (WM) to include synaptic augmentation besides short-term depression and facilitation, consistently with experimental observations. Like facilitation, augmentation builds up with repetitive activation but persists for much longer. We find that the long time scales associated with augmentation naturally lead to the emergence of a "primacy gradient" in the synaptic efficacies that can be used to reconstruct the order of presentation at recall. The novel theory accounts for prominent features of the behavior of humans recalling lists of items, makes testable predictions and, intriguingly, suggests that WM capacity limitations result from a failure in retrieving, rather than storing, information. Taken together, our results advance the understanding of the neuronal mechanisms underpinning the encoding of serial order and offer novel insights into the origin of WM capacity.

neuroscience↗

bioRxiv2023

Using large language models to study human memory for meaningful narratives

One of the most impressive achievements of the AI revolution is the development of large language models that can generate meaningful text and respond to instructions in plain English with no additional training necessary. Here we show that language models can be used as a scientific instrument for studying human memory for meaningful material. We developed a pipeline for designing large scale memory experiments and analyzing the obtained results. We performed online memory experiments with a large number of participants and collected recognition and recall data for narratives of different lengths. We found that both recall and recognition performance scale linearly with narrative length. Furthermore, in order to investigate the role of narrative comprehension in memory, we repeated these experiments using scrambled versions of the presented stories. We found that even though recall performance declined significantly, recognition remained largely unaffected. Interestingly, recalls in this condition seem to follow the original narrative order rather than the scrambled presentation, pointing to a contextual reconstruction of the story in memory.

neuroscience↗

bioRxiv2022

Forgetting Dynamics For Items of Different Categories

AO_SCPLOWBSTRACTC_SCPLOWHow the dynamic evolution of forgetting changes for different materials is unexplored. By using a common experimental paradigm with stimuli of different types, we were able to directly cross-examine the emerging dynamics and we found that even though the presentation sets differ minimally by design, the obtained curves appear to fall on a discrete spectrum. Furthermore, we have previously proposed a model of forgetting based on the notion of retrograde interference with a single integer parameter. All measured curves were compatible with the model with different values of the parameter, hinting to a potential common underlying mechanism of forgetting.

neuroscience↗

bioRxiv2021

Putative role of PV and SOM interneuron subtypes in working memory

Working memory is an essential human trait required for all cognitive activities. Our previous model from Mongillo et al. (1), Mi et al. (2) uses synaptic facilitation to store traces of working memory. Thus memories can be maintained without persistent neural activity. A critical component of this model is a central inhibition which prevents multiple item representations from being active at the same time. We know from experimental studies that multiple genetically-defined interneuron subtypes (e.g. PV, SOM) with different excitability and connectivity properties mediate inhibition in the cortex. The role of these sub-types in working memory however is not known. Here we develop a modified model with these interneuron subtypes, and propose their functional roles in working memory. We make concrete testable predictions about the roles of these groups.

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bioRxiv2020

Effects of order on episodic memory of event times

Memorizing time of an event may employ two processes (i) encoding of the absolute time of events within an episode, (ii) encoding of its relative order. Here we study interaction between these two processes. We performed experiments in which one or several items were presented, after which participants were asked to report the time of occurrence of items. When a single item was presented, the distribution of reported times was quite wide. When two or three items were presented, the relative order among them strongly affected the reported time of each of them. Bayesian theory that takes into account the memory for the events order is compatible with the experimental data, in particular in terms of the effect of order on absolute time reports. Our results suggest that people do not deduce order from memorized time, instead peoples memory for absolute time of events relies critically on memorized order of the events.

neuroscience↗

bioRxiv2019

Retroactive Interference Model of Power-Law Forgetting

Memory and forgetting constitute two sides of the same coin, and although the first has been rigorously investigated, the latter is often overlooked. A number of experiments under the realm of psychology and experimental neuroscience have described the properties of forgetting in humans and animals, showing that forgetting exhibits a power-law relationship with time. These results indicate a counter-intuitive property of forgetting, namely that old memories are more stable than younger ones. We have devised a phenomenological model that is based on the principle of retroactive interference, such that stronger memories acquired after weaker ones erase the latter. The model has only one free integer parameter and can be solved analytically. Recognition experiments with long streams of words were performed, resulting in a good match to a five-dimensional version of the model.

neuroscience↗

bioRxiv2019

Emergence of hierarchical organization in memory for random material

Structured information is easier to remember and recall than random one. In real life, information exhibits multi-level hierarchical organization, such as clauses, sentences, episodes and narratives in language. Here we show that multi-level grouping emerges even when participants perform memory recall experiments with random sets of words. To quantitatively probe brain mechanisms involved in memory structuring, we consider an experimental protocol where participants perform final free recall (FFR) of several random lists of words each of which was first presented and recalled individually. We observe a hierarchy of grouping organizations of FFR, most notably many participants sequentially recalled relatively long chunks of words from each list before recalling words from another list. More-over, participants who exhibited strongest organization during FFR achieved highest levels of performance. Based on these results, we develop a hierarchical model of memory recall that is broadly compatible with our findings. Our study shows how highly controlled memory experiments with random and meaningless material, when combined with simple models, can be used to quantitatively probe the way meaningful information can efficiently be organized and processed in the brain, so to be easily retrieved. Significance StatementInformation that people communicate to each other is highly structured. For example, a story contains meaningful elements of various degrees of complexity (clauses, sentences, episodes etc). Recalling a story, we are chiefly concerned with these meaningful elements and not its exact wording. Here we show that people introduce structure even when recalling random lists of words, by grouping the words into chunks of various sizes. Doing so improves their performance. The so formed chunks closely correspond in size to story elements described above. This suggests that our memory is trained to create a structure that resembles the one it typically deals with in real life, and that using random material like word lists can be used to quantitatively probe these memory mechanisms.

neuroscience↗

bioRxiv2019

Fundamental Law of Memory Recall

Free recall of random lists of words is a standard paradigm used to probe human 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 is different from the ones considered in the past but still can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled (RC) out of M items in memory: [Formula]. 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 theoretical and experimental results indicate that memory recall operates according to a stereotyped search process common to all people.

neuroscience↗

bioRxiv2016

A theory of working memory without consciousness or sustained activity

Working memory and conscious perception are thought to share similar brain mechanisms, yet recent reports of non-conscious working memory challenge this view. Combining visual masking with magnetoencephalography, we demonstrate the reality of non-conscious working memory and dissect its neural mechanisms. In a spatial delayed-response task, participants reported the location of a subjectively unseen target above chance-level after a long delay. Conscious perception and conscious working memory were characterized by similar signatures: a sustained desynchronization in the alpha/beta band over frontal cortex, and a decodable representation of target location in posterior sensors. During non-conscious working memory, such activity vanished. Our findings contradict models that identify working memory with sustained neural firing, but are compatible with recent proposals of activity-silent working memory. We present a theoretical framework and simulations showing how slowly decaying synaptic changes allow cell assemblies to go dormant during the delay, yet be retrieved above chance-level after several seconds.

neuroscience↗