Biology subjects

Katkov, M.

Publications and source records attributed to Katkov, M..

8 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↗

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↗

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

Age-Related Changes in Neural Networks Supporting Complex Visual and Social Processing in Adolescence

Despite our differences, there is much about the natural visual world that almost all observers apparently perceive in common. This coherence across observers is evidenced by the finding that, across adults, approximately 30% of the brain is activated in a consistent fashion in response to viewing naturalistic input. The critical question addressed here is how does this consistency emerge and is this pattern of coherence apparent from early in development or does it evolve with time and/or experience? We focused our investigation at a key developmental juncture that might bridge the child and adult patterns, namely, the period of adolescence. We acquired fMRI BOLD data evoked by an 11-minute age-appropriate movie in younger (age 9-14 years) and older adolescents (age 15-19 years) and in adults. Using an intra-subject correlation approach, we characterized the consistency of the neural response within-individual (across two separate runs of the movie), and then, using an inter-subject correlation approach, evaluated the similarity of the response profile within individuals of the same age group and between age-groups. In primary sensory areas (A1+, V1) the response profiles in both groups of adolescents were highly similar to those of the adults, suggesting that these areas are functionally mature at earlier stages of the development. In contrast, some other regions exhibited higher within-age correlations in the adolescent groups than in the adult group. Last, we evaluated the brain responses across the whole cortex and identified the different patterns of maturation as reflected in different inter-subject correlations across the age groups. Together, these findings provide a fine-grained characterization of functional neural development. The approach offers the potential for careful tracking of the development of widespread cortical networks that support the emerging stereotypical responses to naturalistic visual and social stimuli and has important implications for future studies of cortical development.

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↗