--- OA_place: publisher _id: '17346' abstract: - lang: eng text: "Acquiring, retaining, and retrieving information over a wide range of timescales are crucial\r\nfunctions of the brain. The successful processing of memories affects many aspects of our\r\nlives and enables us and many other organisms to operate in a complex environment and\r\nto interact with it. In this context, the hippocampus and functionally connected brain\r\nareas, such as the prefrontal cortex, are central and have been subject to intensive research\r\nin the past decades. Storage of memories is believed to rely on distributed neural activity\r\nwithin these neural circuits. Additionally, neural memory traces of recent experience are\r\nreinstated during periods of rest or sleep. These reactivations are thought to play an\r\noutstanding role in the consolidation of memories and potentially facilitate the transfer of\r\ninformation from the hippocampus to cortical areas for long-term storage and integration\r\ninto existing knowledge.\r\nHowever, there is growing evidence that memory-related neural representations in the\r\nhippocampus are not as stable as initially thought and that they change even in the\r\nabsence of learning. It has been suggested that these changes reflect the accumulation of\r\nexperience, but the influence of interspersed consolidation periods has not been considered.\r\nPrevious studies have analyzed consolidation periods by detecting activity that strongly\r\nresembled neural activity during the acquisition of memory. Besides being often limited\r\nto only non-rapid eye movement (NREM) sleep, the used approaches were not capable of\r\ntracking changes in neural representations over extended temporal periods. More fluid\r\nrepresentations do not only challenge our understanding of how information is stored, but\r\nthey also affect the transfer of information between brain areas during the consolidation\r\nprocess.\r\nFor this thesis, I investigated the evolution of memory-related activity during sleep\r\nperiods expected to be involved in consolidation in the hippocampus and between the\r\nhippocampus and prefrontal cortex. I found that reactivated activity in the hippocampus\r\ngradually transformed during prolonged periods of sleep and inactivity. In the beginning,\r\nneural activity strongly resembled acquisition activity, whereas, with the progression of\r\ntime, it became more similar to the subsequent recall activity. NREM periods drove\r\nthis process, while rapid-eye movement (REM) periods showed a resetting effect. This\r\nreactivation drift was due to firing rate changes of a subset of cells and mirrored the\r\nrepresentational changes from the acquisition to the recall. A stable subset of cells\r\nwithstood the drift and maintained their activity. Therefore, my results indicate that\r\nmemory-related representations undergo spontaneous modifications during consolidation\r\nperiods and that these changes are predictive of representational drift.\r\nFurthermore, I found that the amount of change in the neural activity during subsequent\r\nsleep periods was biased by prior behavioral performance. Observed changes in the\r\nhippocampus and the prefrontal cortex were synchronized and increased after poor\r\nperformance, highlighting a potential role in the exchange of information. Low-variance\r\nvii\r\nperiods with distinct, more stable activity from a subset of cells significantly contributed\r\nto the heightened synchrony between both areas. Hence, interleaved phases of more stable\r\nneural activity could facilitate the information transfer between brain areas.\r\nIn conclusion, my investigations underline the fluidity of memory-related representations\r\nand assign a prominent role to sleep reactivation periods in their evolution. In addition, I\r\nidentified a potential mechanism of stable activity phases that might facilitate the synchronization across hippocampal-prefrontal activity despite ongoing changes. Reconciling\r\nand integrating findings from both spontaneous and behaviorally-related representational\r\nchanges in functionally related brain areas will help to broaden our understanding of how\r\nknowledge is stored, maintained, updated, and transferred between brain areas." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Lars full_name: Bollmann, Lars id: 47AD3038-F248-11E8-B48F-1D18A9856A87 last_name: Bollmann citation: ama: Bollmann L. Stability and change in the memory system during rest. 2024. doi:10.15479/at:ista:17346 apa: Bollmann, L. (2024). Stability and change in the memory system during rest. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:17346 chicago: Bollmann, Lars. “Stability and Change in the Memory System during Rest.” Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:17346. ieee: L. Bollmann, “Stability and change in the memory system during rest,” Institute of Science and Technology Austria, 2024. ista: Bollmann L. 2024. Stability and change in the memory system during rest. Institute of Science and Technology Austria. mla: Bollmann, Lars. Stability and Change in the Memory System during Rest. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17346. short: L. Bollmann, Stability and Change in the Memory System during Rest, Institute of Science and Technology Austria, 2024. corr_author: '1' date_created: 2024-07-29T15:08:42Z date_published: 2024-07-31T00:00:00Z date_updated: 2026-04-07T13:21:20Z day: '31' ddc: - '573' degree_awarded: PhD department: - _id: GradSch - _id: JoCs doi: 10.15479/at:ista:17346 file: - access_level: open_access checksum: 12c76297cc27449da80c60d79127770d content_type: application/pdf creator: lbollman date_created: 2024-07-31T18:37:19Z date_updated: 2025-01-31T23:30:03Z embargo: 2025-01-31 file_id: '17359' file_name: PhD_Thesis_Lars_Bollmann.pdf file_size: 12920169 relation: main_file - access_level: closed checksum: 19a0265079dec8038830ad6e35c5106e content_type: application/zip creator: lbollman date_created: 2024-07-31T18:38:39Z date_updated: 2025-01-31T23:30:03Z embargo_to: open_access file_id: '17360' file_name: Latex_source.zip file_size: 27568807 relation: source_file file_date_updated: 2025-01-31T23:30:03Z has_accepted_license: '1' keyword: - Memory - Hippocampus - Consolidation language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: '103' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria status: public supervisor: - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 title: Stability and change in the memory system during rest type: dissertation user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd year: '2024' ... --- _id: '10004' abstract: - lang: eng text: 'Markov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors. Given an MDP and rewards on states, a classical optimization criterion is the maximal expected total reward where the MDP stops after T steps, which can be computed by a simple dynamic programming algorithm. We consider a natural generalization of the problem where the stopping times can be chosen according to a probability distribution, such that the expected stopping time is T, to optimize the expected total reward. Quite surprisingly we establish inter-reducibility of the expected stopping-time problem for Markov chains with the Positivity problem (which is related to the well-known Skolem problem), for which establishing either decidability or undecidability would be a major breakthrough. Given the hardness of the exact problem, we consider the approximate version of the problem: we show that it can be solved in exponential time for Markov chains and in exponential space for MDPs.' acknowledgement: We are grateful to the anonymous reviewers of LICS 2021 and of a previous version of this paper for insightful comments that helped improving the presentation. This research was partially supported by the grant ERC CoG 863818 (ForM-SMArt). article_processing_charge: No arxiv: 1 author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Laurent full_name: Doyen, Laurent last_name: Doyen citation: ama: 'Chatterjee K, Doyen L. Stochastic processes with expected stopping time. In: Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. IEEE; 2021:1-13. doi:10.1109/LICS52264.2021.9470595' apa: 'Chatterjee, K., & Doyen, L. (2021). Stochastic processes with expected stopping time. In Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science (pp. 1–13). Rome, Italy: IEEE. https://doi.org/10.1109/LICS52264.2021.9470595' chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” In Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, 1–13. IEEE, 2021. https://doi.org/10.1109/LICS52264.2021.9470595. ieee: K. Chatterjee and L. Doyen, “Stochastic processes with expected stopping time,” in Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Rome, Italy, 2021, pp. 1–13. ista: 'Chatterjee K, Doyen L. 2021. Stochastic processes with expected stopping time. Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. LICS: Logic in Computer Science, 1–13.' mla: Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, IEEE, 2021, pp. 1–13, doi:10.1109/LICS52264.2021.9470595. short: K. Chatterjee, L. Doyen, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, IEEE, 2021, pp. 1–13. conference: end_date: 2021-07-02 location: Rome, Italy name: 'LICS: Logic in Computer Science' start_date: 2021-06-29 date_created: 2021-09-12T22:01:25Z date_published: 2021-07-07T00:00:00Z date_updated: 2026-08-12T06:39:27Z day: '07' department: - _id: KrCh doi: 10.1109/LICS52264.2021.9470595 ec_funded: 1 external_id: arxiv: - '2104.07278' isi: - '000947350400036' isi: 1 keyword: - Computer science - Heuristic algorithms - Memory management - Automata - Markov processes - Probability distribution - Complexity theory language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2104.07278 month: '07' oa: 1 oa_version: Preprint page: 1-13 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science publication_identifier: eisbn: - 978-1-6654-4895-6 isbn: - 978-1-6654-4896-3 issn: - 1043-6871 publication_status: published publisher: IEEE quality_controlled: '1' related_material: record: - id: '18630' relation: later_version status: public scopus_import: '1' status: public title: Stochastic processes with expected stopping time type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ...