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    ํ•ด๋งˆ ํ•˜์œ„ ์˜์—ญ CA1๊ณผ CA3์˜ ์‹œ๊ฐ ์ž๊ทน ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์žฅ์†Œ ํ‘œ์ƒ ํŒจํ„ด ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋‡Œ์ธ์ง€๊ณผํ•™๊ณผ, 2023. 2. ์ด์ธ์•„.์šฐ๋ฆฌ๊ฐ€ ์ผ์ƒ์—์„œ ๊ฒฝํ—˜ํ•˜๋Š” ์‚ฌ๊ฑด๋“ค์€ ํ•˜๋‚˜์˜ ์Šคํ† ๋ฆฌ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์ผํ™” ๊ธฐ์–ต์œผ๋กœ ํ˜•์„ฑ๋œ๋‹ค. ํ•ด๋งˆ๋Š” ๊ณผ๊ฑฐ์— ๊ฒฝํ—˜ํ•œ ์ผ ๋“ค ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํ˜„์žฌ ๊ฒฝํ—˜ํ•˜๊ณ  ์žˆ๋Š” ์‚ฌ๊ฑด๋“ค์— ๋Œ€ํ•œ ์ผํ™” ๊ธฐ์–ต์„ ์ฒ˜๋ฆฌํ•  ๋•Œ ํ•„์ˆ˜์ ์ธ ๋‡Œ ์˜์—ญ์ด๋ผ๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์„ค์น˜๋ฅ˜์˜ ํ•ด๋งˆ์—์„œ ๊ด€์ฐฐ๋˜๋Š” ์žฅ์†Œ ์„ธํฌ๋Š” ํ•ด๋งˆ๊ฐ€ ๋™๋ฌผ์ด ์ธ์ง€ํ•˜๊ณ  ์žˆ๋Š” ๊ณต๊ฐ„์— ๋Œ€ํ•œ ์ง€๋„๋ฅผ ํ˜•์„ฑํ•˜๋Š” ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ํŠนํžˆ ํŠน์ •ํ•œ ๊ณต๊ฐ„์—์„œ๋งŒ ์„ ๋ณ„์ ์œผ๋กœ ๋ฐœํ™”ํ•˜๋Š” ์žฅ์†Œ ์„ธํฌ๋Š” ํ™˜๊ฒฝ์— ๋ณ€ํ™”๊ฐ€ ์ฃผ์–ด์กŒ์„ ๋•Œ remapping์ด๋ผ๋Š” ํ˜„์ƒ์œผ๋กœ ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”๋ฅผ ๋ฐ˜์˜ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ํ™˜๊ฒฝ์— ๋ณ€ํ™”๊ฐ€ ์žˆ์„ ๋•Œ, ์žฅ์†Œ ์„ธํฌ๊ฐ€ ๋™์ผํ•œ ์œ„์น˜์—์„œ ํ™œ๋™ํ•˜๋ฉฐ ๋ฐœํ™” ๋นˆ๋„๋ฅผ ์กฐ์ •ํ•˜๊ฑฐ๋‚˜ ์ „ํ˜€ ๋‹ค๋ฅธ ์žฅ์†Œ์—์„œ ํ™œ๋™ํ•˜๋Š” ํŒจํ„ด์œผ๋กœ ๊ด€์ฐฐ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์žฅ์†Œ ์„ธํฌ์˜ ๋ณ€ํ™”๋Š” i) ๊ธฐ์กด์˜ ๊ธฐ์–ต์„ ์กฐ๊ธˆ ๋ณ€ํ˜•ํ•˜๊ฑฐ๋‚˜, ii) ์ƒˆ๋กœ์šด ๊ธฐ์–ต์„ ํ˜•์„ฑํ•˜๋Š” ์ผํ™” ๊ธฐ์–ต์˜ ํ˜•ํƒœ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์žฅ์†Œ ์„ธํฌ๊ฐ€ ๋ถˆ๊ทœ์น™์ ์ธ ํŒจํ„ด์œผ๋กœ ๊ณต๊ฐ„์˜ ๋ณ€ํ™”๋ฅผ ํ‘œ์ƒํ•จ์— ๋”ฐ๋ผ ์ด๋“ค์˜ ํ™œ๋™์ด ๊ฐ–๋Š” ์˜๋ฏธ๋Š” ๋ถˆ๋ถ„๋ช…ํ•˜๊ฒŒ ๋‚จ์•„์žˆ๋‹ค. ๋˜ํ•œ ์žฅ์†Œ ์„ธํฌ๊ฐ€ ๋ณตํ•ฉ์ ์ธ ๊ฐ๊ฐ ์ •๋ณด๋“ค์„ ๋ฐ˜์˜ํ•œ๋‹ค๋Š” ํŠน์ง•์€, ์ด๋“ค์ด ์–ด๋–ค ์ธ์ง€์  ์˜๋ฏธ๋ฅผ ๊ฐ€์ง€๋ฉฐ ํ™œ๋™์„ ํ•˜๋Š” ๊ฒƒ์ธ์ง€์— ๋Œ€ํ•œ ๋‚œ์ œ๋ฅผ ๋‚จ๊ฒผ๋‹ค. ๋ณธ์ธ์€ ํ•ด๋งˆ์˜ ์žฅ์†Œ ์„ธํฌ๊ฐ€ ์ผํ™” ๊ธฐ์–ต์— ์–ด๋–ค ๊ธฐ์—ฌ๋ฅผ ํ•  ๊ฒƒ์ธ์ง€, ํŠนํžˆ ๋ณ€ํ™”๋œ ํ™˜๊ฒฝ์—์„œ ๋ฌด์—‡์„ ์ƒˆ๋กœ ๊ธฐ์–ตํ•˜๊ณ  ๊ธฐ์กด์— ์•Œ๊ณ  ์žˆ๋Š” ์ •๋ณด๋Š” ์–ด๋–ป๊ฒŒ ์ฒ˜๋ฆฌํ•  ๊ฒƒ์ธ์ง€ ์—ฐ์‚ฐํ•˜๋Š” ๊ณผ์ •์„ ํ•ด๋งˆ์˜ ํ•˜์œ„ ์˜์—ญ์ธ CA1๊ณผ CA3์—์„œ ๊ฐ๊ฐ ์–ด๋–ป๊ฒŒ ํ‘œ์ƒํ•˜๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด์— ๋Œ€ํ•œ ๋‹ต์„ ์ฐพ๊ธฐ ์œ„ํ•ด ๋ณธ์ธ์€ ๋™๋ฌผ์ด ์ƒํ˜ธ์ž‘์šฉํ•˜๋ฉฐ ๊ฒฝํ—˜ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ€์ƒ ํ˜„์‹ค (VR) ์‹œ์Šคํ…œ์„ ์ œ์ž‘ํ•˜์—ฌ ๊ฐ€์ƒ ํ™˜๊ฒฝ์˜ ์‹œ๊ฐ ์ž๊ทน์„ ์ •๋Ÿ‰์ ์œผ๋กœ ์กฐ์ž‘ํ•˜์˜€๋‹ค. ์ด ๊ณผ์ •์—์„œ ๋ณธ์ธ์€ ๋™๋ฌผ์ด ๊ฒฝํ—˜ํ•˜๋Š” ์‹œ๊ฐ ์ž๊ทน์˜ ๋ณ€ํ™”์™€ (i.e., input) ํ•ด๋งˆ ์žฅ์†Œ์„ธํฌ์˜ ์ „๊ธฐ์  ํ™œ๋™ (i.e., output) ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ์งˆ๋ฌธ์œผ๋กœ๋Š” ๋ณธ์ธ์ด ๊ตฌ์ถ•ํ•œ ๊ฐ€์ƒ ํ˜„์‹ค ์‹œ์Šคํ…œ์—์„œ ์žฅ์†Œ ์„ธํฌ๊ฐ€ ๋ฐœํ˜„๋˜๋Š”์ง€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ๋กœ ๊ธฐ์กด ๋ฌธํ—Œ์—์„œ ๋ณด๊ณ ๋˜์—ˆ๋˜ ๊ฒฐ๊ณผ์™€ ๋น„์Šทํ•œ ์ˆ˜์ค€์˜ ์žฅ์†Œ ์„ธํฌ๋“ค์„ ๊ฒ€์ฆํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ์ธ์ด ๊ตฌ์ถ•ํ•œ ๊ฐ€์ƒ ํ˜„์‹ค ์‹œ์Šคํ…œ์—์„œ ์žฅ์†Œ ์„ธํฌ๊ฐ€ ๊ด€์ฐฐ๋œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•œ ์ดํ›„์—๋Š”, ๊ธฐ์กด ํ™˜๊ฒฝ์— ์ •๋Ÿ‰์ ์ธ ์‹œ๊ฐ์  ๋ณ€ํ™”๋ฅผ ์ฃผ์–ด ์žฅ์†Œ ์„ธํฌ๊ฐ€ ํ•ด๋‹น ๋ณ€ํ™”๋ฅผ ์–ด๋–ป๊ฒŒ ๋ฐ˜์˜ํ•˜๋Š”์ง€ ์งˆ๋ฌธํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ๋กœ, ํ•ด๋งˆ์˜ ํ•˜์œ„ ์˜์—ญ CA1์—์„œ ๊ธฐ์กด ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ํ‘œ์ƒ์„ ์œ ์ง€ํ•˜๋Š” ์ง‘๋‹จ๊ณผ, ํŠน์ • ํ™˜๊ฒฝ์— ๋ณ€ํ™”๊ฐ€ ๊ฐ€ํ•ด์ง„ ์‚ฌ๊ฑด์— ์˜ํ•ด ์ƒˆ๋กœ์šด ํ‘œ์ƒ์„ ์œ ์ง€ํ•˜๋Š” ์ง‘๋‹จ์ด ๋™์‹œ๋‹ค๋ฐœ์ ์œผ๋กœ ๋‚˜๋‰œ๋‹ค๋Š” ํ˜„์ƒ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋ฐ˜๋ฉด, ํ•ด๋งˆ ํ•˜์œ„ ์˜์—ญ์ธ CA3์—์„œ๋Š” ํ™˜๊ฒฝ์— ๋ณ€ํ™”๊ฐ€ ์ด๋ฃจ์–ด์กŒ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋Œ€๋ถ€๋ถ„์˜ ์žฅ์†Œ ์„ธํฌ๋“ค์ด ๊ธฐ์กด ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ํ‘œ์ƒ์„ ์œ ์ง€ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ํ•ด๋งˆ ํ•˜์œ„ ์˜์—ญ์ธ CA3์€ ๊ธฐ์กด์— ์•Œ๊ณ  ์žˆ๋˜ ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ๊ธฐ์–ต์„ ์•ˆ์ •์ ์œผ๋กœ ์œ ์ง€ํ•˜๋Š” ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ˜๋ฉด, ํ•ด๋งˆ ํ•˜์œ„ ์˜์—ญ์ธ CA1์€ ๋ณ€ํ™”ํ•˜๋Š” ํ™˜๊ฒฝ ๋‚ด์—์„œ๋„ ์ด์ „์˜ ๊ธฐ์–ต๊ณผ ์ƒˆ๋กœ์šด ๊ธฐ์–ต์„ ๋…๋ฆฝ์ ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ ์ƒˆ๋กœ์šด ์ •๋ณด๋ฅผ ์œ ์—ฐํ•˜๊ฒŒ ํ•™์Šตํ•˜๋„๋ก ํ•˜๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜๊ณ ์ž ํ•œ๋‹ค.Any events or experiences in the given space and time are stitched together as an episode. The hippocampus has been widely acknowledged for its role in episodic memory for decades. At the same time, the rodent hippocampus exhibits the salient feature where its principal neurons are active in a spatially selective pattern (i.e., place cell). The place cells change their firing patterns as there are changes in the environments. Until now, we have been interpreting these firing changes, also known as "remapping," to have a functional significance in episodic memory by i) slightly modifying the old map to retrieve subtle changes from the previous memory or ii) forming the new map to reflect any major changes. In the real world, place cells receive complex sensory information from multiple sources, including multimodal sensory inputs and idiothetic information, making it even more challenging to interpret place cell activity from the intermingled sensory inputs fed into the hippocampal system. Taking advantage of the virtual reality (VR) system, I investigated how the hippocampal subregions CA1 and CA3 networks reflect environmental change. Thereby, I parametrically manipulated the environment by adding visual noise (i.e., virtual fog) in the VR environment and examined how hippocampal place cells in the CA1 and CA3 responded as visual noises were added to the environment in a quantified manner. Prior studies have suggested that CA3 forms a discrete map of the modified environments, presumably by performing either pattern separation or pattern completion. However, place cells in CA1 exhibit less coherent responses to environmental changes compared to CA3. This discrepancy between the CA1 and CA3 subregions is puzzling because CA3 output must pass through the CA1 area before reaching cortical areas. Furthermore, the functional roles of the CA1 in processing the environmental changes still need to be investigated due to the heterogeneous neural outputs with mixed yet conflicting findings. I first questioned whether our VR system reliably induced the place cells from both hippocampal subregions CA1 and CA3. As a result, I observed that the firing properties of hippocampal place cells are equivalent to that reported in the previous studies. Once I confirmed that visual environments in our VR system dominantly controlled the place cells, I examined how place cells in the CA1 and CA3 subregions responded to various levels of changes made to the visual environment. As visual noise was introduced to the familiar environment, I found that place cells in CA1 split simultaneously into two subpopulations: In one, place cells with old maps while changing their firing rate to reflect noise levels (i.e., rate remapping); in another, place cells with new maps to differentiate the dynamically changing environment from an old stable environment (i.e., global remapping). The place cells in CA3 mainly sustained the old map and reflected noise levels by rate remapping. Suppose one considers the rate remapping class of place cells as pattern-completing cells and the global remapping class as pattern-separating cells. In that case, the CA1 can manifest both pattern separation and pattern completion classes of neurons at the environmental change. My dissertation suggests that CA1 can simultaneously form an orthogonal map of the same environment to remember new episodes without interfering with the old memory.Background 1 Anatomical structures of the Hippocampal system and their proposed roles 2 The remapping properties of Hippocampal place cell 7 The usage of the virtual reality (VR) system for rodents in studying the hippocampus 16 Chapter 1. Visual scene stimulus exerts dominant control over the place fields 19 Introduction 20 Materials and methods 22 Results 37 Discussion 53 Chapter 2. The functional role of the CA1 and CA3 in processing the visually modified environment 56 Introduction 57 Materials and methods 59 Results 63 Discussion 94 General Discussion 98 Bibliography 111 ๊ตญ๋ฌธ์ดˆ๋ก 137๋ฐ•

    The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

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    After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the insideโ€“outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of โ€œsleep replayโ€ of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata

    Temporal Encoding of Place Sequences by Hippocampal Cell Assemblies

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    SummaryBoth episodic memory and spatial navigation require temporal encoding of the relationships between events or locations. In a linear maze, ordered spatial distances between sequential locations were represented by the temporal relations of hippocampal place cell pairs within cycles of theta oscillation in a compressed manner. Such correlations could arise due to spike โ€œphase precessionโ€ of independent neurons driven by common theta pacemaker or as a result of temporal coordination among specific hippocampal cell assemblies. We found that temporal correlation between place cell pairs was stronger than predicted by a pacemaker drive of independent neurons, indicating a critical role for synaptic interactions and precise timing within and across cell assemblies in place sequence representation. CA1 and CA3 ensembles, identifying spatial locations, were active preferentially on opposite phases of theta cycles. These observations suggest that interleaving CA3 neuronal sequences bind CA1 assemblies representing overlapping past, present, and future locations into single episodes

    ์น˜์ƒํšŒ ์†์ƒ์— ๋”ฐ๋ฅธ CA3 ์žฅ์†Œ์„ธํฌ์˜ ์žฅ๋ฉด์˜์กด์  ๋ฐœํ™”์œจ ๋ณ€์กฐ์˜ ์ €ํ•˜

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋‡Œ์ธ์ง€๊ณผํ•™๊ณผ, 2020. 8. ์ด์ธ์•„.The ability to differentiate similar experiences into discrete events in memory is a fundamental component of the episodic memory. Computational models and experimental evidence have suggested that projections from the dentate gyrus (DG) to CA3 play important roles in representing orthogonal information (i.e., pattern separation) in the hippocampus. However, the effects of eliminating the DG on neural firing patterns in the CA3 have rarely been tested in a goal-directed memory task that requires both the DG and CA3. In this thesis, the simultaneous application of lesion and in-vivo electrophysiology were used to examine the role of the DG inputs to the CA3 as the animal processes scene memory. Selective lesions in the DG were made using colchicine in male Long-Evans rats, and CA3 single units were recorded as the rats performed visual scene memory tasks. The original scenes used in training were modified during testing by blurring to varying degrees, by using visual masks, or by overlaying competing scenes to examine how changes in scenes differentially recruit the DG-CA3 circuits. Compared with controls, the performance of rats with DG lesions was particularly impaired when blurred scenes were used in the task. The firing-rate modulation associated with visual scenes in these rats was significantly reduced in the single units recorded from the CA3 when blurred scenes were presented, largely because DG-deprived CA3 cells did not show stepwise, categorical rate changes across varying degrees of scene ambiguity compared with controls. These findings suggest that the DG plays key roles not only during the acquisition of scene memories but also when modified visual scenes are processed in conjunction with the CA3 by making the CA3 network respond orthogonally to ambiguous scenes.ํŠน์ • ํ™˜๊ฒฝ์— ์ ํ•ฉํ•œ ํ–‰๋™์„ ํ•˜๊ธฐ ์œ„ํ•ด ์šฐ๋ฆฌ๋Š” ๊ณผ๊ฑฐ์— ๊ทธ ํ™˜๊ฒฝ์—์„œ ์–ด๋– ํ•œ ๊ฒฝํ—˜์„ ํ•˜์˜€๋Š”์ง€ ๋ฐ˜์ถ”ํ•œ๋‹ค. ํ•ด๋งˆ๋Š” ์ด์™€ ๊ฐ™์ด ๊ณผ๊ฑฐ์— ๊ฒฝํ—˜ํ•œ ์‚ฌ๊ฑด ๋“ฑ์— ๋Œ€ํ•œ ์ผํ™” ๊ธฐ์–ต์„ ์ฒ˜๋ฆฌํ•  ๋•Œ ์ค‘์š”ํ•œ ๋‡Œ ์˜์—ญ์ด๋ผ๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ํ•ญ์ƒ ๋ณ€ํ™”ํ•˜๋Š” ํ™˜๊ฒฝ ์†์—์„œ ๋งค๋ฒˆ ๊ณผ๊ฑฐ์™€ ๋™์ผํ•œ ์ž๊ทน์„ ๊ฒฝํ—˜ํ•˜๊ธด ์–ด๋ ต๋‹ค. ๋”ฐ๋ผ์„œ, ์ผํ™” ๊ธฐ์–ต์˜ ์ฒ˜๋ฆฌ์—๋Š” ์„œ๋กœ ์œ ์‚ฌํ•˜์ง€๋งŒ ๋‹ค๋ฅธ ์ƒํ™ฉ์„ ๊ตฌ๋ถ„ํ•˜๋Š” ๊ณผ์ •์ด ํ•„์š”ํ•˜๋‹ค. ํ•ด๋งˆ์˜ ํ•˜์œ„ ์˜์—ญ์ธ ์น˜์ƒํšŒ๋Š” ์„œ๋กœ ์œ ์‚ฌํ•œ ์ž๊ทน์„ ๋ถ„๋ฆฌํ•˜์—ฌ ์ €์žฅํ•˜๊ธฐ ์œ„ํ•ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ์œผ๋‚˜, ๋‹จ์œ„์‹ ๊ฒฝ์„ธํฌ ์ˆ˜์ค€์˜ ์ •๋ณด์ฒ˜๋ฆฌ ๊ธฐ์ „์€ ์•„์ง ์•Œ๋ ค์ง„ ๋ฐ” ์—†๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ตœ๊ทผ ์ผํ™” ๊ธฐ์–ต์˜ ์ €์žฅ๊ณผ ์ธ์ถœ ๊ณผ์ •์ด ์‹œ๊ฐ์ ์œผ๋กœ ๋“ค์–ด์˜ค๋Š” ์žฅ๋ฉด์— ๋Œ€ํ•œ ์ฒ˜๋ฆฌ์™€ ๋ฐ€์ ‘ํ•œ ์—ฐ๊ด€์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๋Š” ์ฃผ์žฅ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ, ์œ ์‚ฌํ•œ ์žฅ๋ฉด ์ž๊ทน๋“ค์ด ํ•ด๋งˆ์—์„œ ์ฒ˜๋ฆฌ๋˜๋Š” ๊ธฐ์ „์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์ฝœ์น˜์‹ ์„ ์‚ฌ์šฉํ•œ ์ฅ์˜ ์น˜์ƒํšŒ์˜ ์†์ƒ์ด ์‹œ๊ฐ ์žฅ๋ฉด ๊ธฐ์–ต ๊ณผ์ œ์˜ ์ˆ˜ํ–‰์„ ์ €ํ•ดํ•˜๋Š”์ง€ ๊ทธ ํ–‰๋™์  ์˜ํ–ฅ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์น˜์ƒํšŒ๋กœ๋ถ€ํ„ฐ ์ •๋ณด๋ฅผ ๋ฐ›๋Š” CA3์˜์—ญ์˜ ๋‹จ์œ„์‹ ๊ฒฝ์„ธํฌ์˜ ํ™œ๋™ ์ „์œ„๊ฐ€ ์–ด๋– ํ•œ ๋ฐฉ์‹์œผ๋กœ ์žฅ๋ฉด ์ž๊ทน์„ ํ‘œ์ƒํ•˜๊ณ , ๊ธฐ์กด์— ํ•™์Šตํ–ˆ๋˜ ์žฅ๋ฉด ์ž๊ทน์ด ๋ณ€ํ˜•๋˜์—ˆ์„ ๋•Œ๋Š” ์–ด๋–ป๊ฒŒ ํ‘œ์ƒํ•˜๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ๊ทธ ํ‘œ์ƒ ๋ฐฉ์‹๋“ค์ด ์น˜์ƒํšŒ์˜ ์†์ƒ ์—ฌ๋ถ€์— ๋”ฐ๋ผ ์–ด๋–ป๊ฒŒ ์˜ํ–ฅ์„ ๋ฐ›๋Š”์ง€ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ๊ฒ€์ฆ์„ ์‹œ๋„ํ•˜์˜€๋‹ค. ํ†ต์ œ ์ง‘๋‹จ์— ๋น„ํ•ด ์น˜์ƒํšŒ ์†์ƒ ์ง‘๋‹จ์€ ๊ธฐ์กด์— ํ•™์Šตํ•˜์˜€๋˜ ์žฅ๋ฉด ์ž๊ทน์ด ํ๋ฆฟํ•˜๊ฒŒ ์ œ์‹œ๋  ๋•Œ์—๋งŒ ๋‚ฎ์€ ๊ณผ์ œ ์ˆ˜ํ–‰๋ฅ ์„ ๋ณด์˜€๋‹ค. ๋™์‹œ์— ์น˜์ƒํšŒ๊ฐ€ ์†์ƒ๋œ ์ฅ๋“ค์˜ CA3 ๋‹จ์œ„์‹ ๊ฒฝ์„ธํฌ์˜ ์‹œ๊ฐ ์žฅ๋ฉด ๊ด€๋ จ ๋ฐœํ™”์œจ ๋ณ€์กฐ๊ฐ€ ํ๋ฆฟํ•œ ์žฅ๋ฉด ์ž๊ทน์ด ์ œ์‹œ๋˜์—ˆ์„ ๋•Œ ํ˜„์ €ํ•˜๊ฒŒ ๊ฐ์†Œํ•˜์˜€๋‹ค. ์ด๋Š” ์น˜์ƒํšŒ๊ฐ€ ์†์ƒ๋œ ์ฅ์˜ CA3 ๋‹จ์œ„์‹ ๊ฒฝ์„ธํฌ๊ฐ€ ํ†ต์ œ ์ง‘๋‹จ์— ๋น„ํ•ด ํ๋ฆฟํ•œ ์žฅ๋ฉด ์ž๊ทน์˜ ๋ชจํ˜ธ์„ฑ์˜ ์ •๋„์— ๋”ฐ๋ฅธ ๋ฒ”์ฃผ์  ๋ณ€ํ™”๋ฅผ ๋ณด์—ฌ์ฃผ์ง€ ์•Š์•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์น˜์ƒํšŒ๊ฐ€ CA3 ์˜์—ญ์ด ์• ๋งคํ•œ ์žฅ๋ฉด์— ์ง๊ต์ ์œผ๋กœ ๋ฐ˜์‘ํ•˜๊ฒŒ ํ•จ์œผ๋กœ์จ ์žฅ๋ฉด ๊ธฐ์–ต์„ ์ €์žฅํ•˜๋Š” ๊ณผ์ •๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, CA3์™€ ํ•จ๊ป˜ ์ˆ˜์ •๋œ ์‹œ๊ฐ ์žฅ๋ฉด์ด ์ฒ˜๋ฆฌ๋  ๋•Œ์—๋„ ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๊ทœ๋ช…ํ•˜์˜€๋‹ค.Chapter 1. Recognition of ambiguous visual scenes following the lesion of the dentate gyrus 12 Introduction 13 Materials and methods 14 Results 26 Discussion 33 Chapter 2. Impaired pattern separation in scene-dependent rate modulation in CA3 single units following the lesion of the dentate gyrus 36 Introduction 37 Materials and methods 38 Results 49 Discussion 75 General Discussion 77 Bibliography 85 Acknowledgement (๊ฐ์‚ฌ์˜ ๋ง) 97 ๊ตญ๋ฌธ์ดˆ๋ก 98Docto

    Mechanisms of memory consolidation : Analyzing the coordinated activity of concept neurons in the human medial temporal lobe during waking and sleep

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    The aim of this thesis is to investigate the role of human concept neurons in memory consolidation during sleep. Memory consolidation is a process by which memories initially dependent on the hippocampus are transferred to cortical areas, thereby gradually becoming independent of the hippocampus. Theories of memory consolidation posit that memory traces encoding autobiographic episodes are rapidly formed in the hippocampus during waking, and reactivated during subsequent slow-wave sleep to be transformed into a long-lasting form. Concept neurons in the human medial temporal lobe are neurons tuned to semantic concepts in a selective, sparse, and invariant manner. These neurons respond to pictures or written and spoken words representing their preferred concept (for example, a person, an animal, an object), regardless of physical stimulus properties. Concept neurons have been speculated to be building blocks for episodic memory. We used whole-night recordings from concept neurons in the medial temporal lobe of epilepsy patients implanted with depth electrodes for presurgical monitoring to test the hypothesis that the coordinated activity of concept neurons during sleep is a neurophysiological correlate of memory consolidation in humans. To conduct this study, we developed software methods for artifact removal and spike sorting of long-term recordings from single neurons. In an evaluation on both simulated model data and visual stimulus presentation experiments, our software outperformed previous methods. Starting from the conceptual analogy between rodent place cells and human concept neurons, we developed an episodic memory task in which participants learned a story eliciting sequential activity in concept neurons. We found that concept neurons preserved their semantic tuning across whole-night recordings. Hippocampal concept neurons had, on average, lower firing rates during rapid-eye-movement (REM) sleep than during waking. During slow-wave sleep, firing rates did not significantly differ from waking. The activity of concept neurons increased during ripples in the local field potential. Furthermore, concept neurons whose preferred stimuli participated in the memorized story were conjointly reactivated after learning, most pronouncedly during slow-wave sleep. Cross-correlations of concept neurons were most asymmetric during slow-wave sleep. Cross-correlation peak times were often in the range believed to be relevant for spike-timing-dependent plasticity. However, time lags of peak cross-correlations did not correlate with the positional order of stimuli in the memorized story. Our findings support the hypothesis that concept neurons rapidly encode a memory trace during learning, and that the reactivation of the same neurons during subsequent slow-wave sleep and ripples contributes to the consolidation of the memory episode. However, the consolidation of the temporal order of events in humans appears to differ from what rodent research suggests.Mechanismen der Gedรคchtniskonsolidierung : Analyse der Aktivitรคt von Konzeptzellen im menschlichen Schlรคfenlappen wรคhrend Wachheit und Schlaf In dieser Arbeit wird die Rolle von Konzeptzellen ("concept neurons") im Gehirn des Menschen bei der Gedรคchtniskonsolidierung im Schlaf untersucht. Gedรคchtniskonsolidierung ist ein Prozess, durch den Gedรคchtnisinhalte, die zunรคchst vom Hippokampus abhรคngen, in die GroรŸhirnrinde รผbertragen werden. Dadurch reduziert sich im Laufe der Zeit die Abhรคngigkeit der Gedรคchtnisinhalte vom Hippokampus. In der Theorie der Gedรคchtniskonsolidierung wird angenommen, dass wรคhrend wachem Erleben sehr schnell Gedรคchtnisspuren im Hippokampus entstehen, welche im darauffolgenden Tiefschlaf reaktiviert werden, um so eine langfristig stabile Gedรคchtnisspur zu erzeugen. Konzeptzellen im Schlรคfenlappen des Menschen sind Nervenzellen, die auf den semantischen Inhalt eines Stimulus selektiv und semantisch invariant reagieren. Konzeptzellen antworten auf Abbildungen ihres prรคferierten Konzepts (zum Beispiel einer Person, eines Tieres oder eines Objekts) oder auf geschriebene und gesprochene Wรถrter, die das gleiche Konzept darstellen, unabhรคngig von den speziellen Eigenschaften des Stimulus, wie zum Beispiel BildgrรถรŸe oder -farbe. Auf jedes Konzept reagiert dabei nur ein sehr kleiner Teil dieser Zellen. Man vermutet, dass Konzeptzellen Bausteine des episodischen Gedรคchtnisses sind. Die vorliegende Studie nutzt Aufzeichnungen der Aktivitรคt einzelner Konzeptzellen wรคhrend ganzer Nรคchte, um zu untersuchen, inwiefern die koordinierte Aktivitรคt von Konzeptzellen im Schlaf ein neurophysiologisches Korrelat der Gedรคchtniskonsolidierung darstellt. Die Teilnehmer der Studie waren Epilepsiepatienten, in deren mediale Schlรคfenlappen aus klinischen Grรผnden Tiefenelektroden zur Anfallsaufzeichnung implantiert worden waren. Zur Analyse der Daten wurde zunรคchst eine Software entwickelt, die eine Artefaktbereinigung und das Spike-Sorting von neuronalen Langzeitaufzeichnungen leistet. Diese Software zeigte deutliche Vorteile gegenรผber vorhandenen Methoden, und zwar sowohl in Tests mit simulierten Modelldatensรคtzen als auch im Falle tatsรคchlicher Aufzeichnungen (hier Experimente, in denen visuelle Stimuli auf einem Laptop dargestellt wurden). Ausgehend von einer Analogie zwischen Ortszellen ("place cells") bei Nagetieren und Konzeptzellen bei Menschen wurde ein Experiment entwickelt, das episodisches Gedรคchtnis operationalisierte. Darin lernten die Teilnehmer eine kurze Geschichte auswendig, was sequentielle Aktivitรคt von Konzeptzellen auslรถste. Konzeptzellen zeigten ein stabiles Antwortverhalten: am Abend und nรคchsten Morgen antworteten sie auf die gleichen Stimuli. Konzeptzellen im Hippokampus hatten im Mittel im Rapid-Eye-Movement-Schlaf (REM-Schlaf) niedrigere Feuerraten als wรคhrend Wachheit. Im Tiefschlaf unterschieden sich die Feuerraten nicht signifikant von Wachheit. Die Aktivitรคt der Konzeptzellen war wรคhrend "ripples" im lokalen Feldpotential erhรถht, und Konzeptzellen, deren prรคferierte Stimuli in der erinnerten Geschichte auftauchten, feuerten im darauffolgenden Schlaf gemeinsam, ein Effekt, der im Tiefschlaf besonders ausgeprรคgt war. Die Kreuzkorrelationen von Konzeptzellen waren im Tiefschlaf asymmetrischer als wรคhrend Wachheit und REM-Schlaf, und die typischen Zeitabstรคnde des Feuerns von Konzeptzellen lagen in einem Bereich, der als relevant fรผr "spike-timing-dependent plasticity" gilt. Die Zeitabstรคnde waren jedoch nicht mit dem Abstand der prรคferierten Stimuli in der erinnerten Geschichte korreliert. Diese Befunde stรผtzen die Theorie, dass die Aktivitรคt von Konzeptzellen wรคhrend des Lernens instantan eine Gedรคchtnisspur erzeugt, und dass die Reaktivierung der gleichen Nervenzellen im Tiefschlaf nach dem Lernen zur Konsolidierung der Gedรคchtnisinhalte beitrรคgt. Die zeitliche Reihenfolge von Ereignissen wird offenbar im menschlichen Gehirn nicht auf die Weise konsolidiert, die sich aus der Forschung an Nagetieren nahelegte

    Hippocampal Replay of Extended Experience

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    During pauses in exploration, ensembles of place cells in the rat hippocampus re-express firing sequences corresponding to recent spatial experience. Such โ€œreplayโ€ co-occurs with ripple events: short-lasting (โˆผ50โ€“120 ms), high-frequency (โˆผ200 Hz) oscillations that are associated with increased hippocampal-cortical communication. In previous studies, rats exploring small environments showed replay anchored to the rat's current location and compressed in time into a single ripple event. Here, we show, using a neural decoding approach, that firing sequences corresponding to long runs through a large environment are replayed with high fidelity and that such replay can begin at remote locations on the track. Extended replay proceeds at a characteristic virtual speed of โˆผ8 m/s and remains coherent across trains of ripple events. These results suggest that extended replay is composed of chains of shorter subsequences, which may reflect a strategy for the storage and flexible expression of memories of prolonged experience.Massachusetts Institute of Technology. Department of Brain and Cognitive Science (Singleton Fellowship)National Institutes of Health (U.S.) (grant MH061976

    Replay of memories of extended behavior in the rat hippocampus

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.Cataloged from PDF version of thesis.Includes bibliographical references.The hippocampus is a highly conserved structure in the medial temporal lobe of the brain that is known to be critical for spatial learning in rodents, and spatial and episodic memory in humans. During pauses in exploration, ensembles of place cells in the rat hippocampus re-express firing sequences corresponding to recent spatial experience. Such 'replay' co-occurs with ripple events: short-lasting (~50-120 ms), high frequency (-200 Hz) oscillations that are associated with increased hippocampal-cortical communication. In previous studies, rats explored small environments, and replay was found to be anchored to the rat's current location, and compressed in time such that replay of the complete environment occurred during a single ripple event. In this thesis, we develop a probabilistic neural decoding approach that allows us to show that firing sequences corresponding to long runs through a large environment are replayed with high fidelity (in both forward and reverse order). We show that such replay can begin at remote locations on the track, and proceeds at a characteristic virtual speed of -8 m/s. Replay remains coherent across trains of sharp wave-ripple events. These results suggest that extended replay is composed of chains of shorter subsequences, which may reflect a strategy for the storage and flexible expression of memories of prolonged experience. We discuss the evidence for the operation of similar mechanisms in humans.by Thomas James Davidson.Ph.D

    IST Austria Thesis

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    The hippocampus is a key brain region for memory and notably for spatial memory, and is needed for both spatial working and reference memories. Hippocampal place cells selectively discharge in specific locations of the environment to form mnemonic represen tations of space. Several behavioral protocols have been designed to test spatial memory which requires the experimental subject to utilize working memory and reference memory. However, less is known about how these memory traces are presented in the hippo campus, especially considering tasks that require both spatial working and long -term reference memory demand. The aim of my thesis was to elucidate how spatial working memory, reference memory, and the combination of both are represented in the hippocampus. In this thesis, using a radial eight -arm maze, I examined how the combined demand on these memories influenced place cell assemblies while reference memories were partially updated by changing some of the reward- arms. This was contrasted with task varian ts requiring working or reference memories only. Reference memory update led to gradual place field shifts towards the rewards on the switched arms. Cells developed enhanced firing in passes between newly -rewarded arms as compared to those containing an unchanged reward. The working memory task did not show such gradual changes. Place assemblies on occasions replayed trajectories of the maze; at decision points the next arm choice was preferentially replayed in tasks needing reference memory while in the pure working memory task the previously visited arm was replayed. Hence trajectory replay only reflected the decision of the animal in tasks needing reference memory update. At the reward locations, in all three tasks outbound trajectories of the current arm were preferentially replayed, showing the animalsโ€™ next path to the center. At reward locations trajectories were replayed preferentially in reverse temporal order. Moreover, in the center reverse replay was seen in the working memory task but in the other tasks forward replay was seen. Hence, the direction of reactivation was determined by the goal locations so that part of the trajectory which was closer to the goal was reactivated later in an HSE while places further away from the goal were reactivated earlier. Altogether my work demonstrated that reference memory update triggers several levels of reorganization of the hippocampal cognitive map which are not seen in simpler working memory demand s. Moreover, hippocampus is likely to be involved in spatial decisions through reactivating planned trajectories when reference memory recall is required for such a decision

    Execution of new trajectories towards a stable goal without a functional hippocampus

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    The hippocampus is a critical component of a mammalian spatial navigation system, with the firing sequences of hippocampal place cells during sleep or immobility constituting a โ€œreplayโ€ of an animal's past trajectories. A novel spatial navigation task recently revealed that such โ€œreplayโ€ sequences of place fields can also prospectively map onto imminent new paths to a goal that occupies a stable location during each session. It was hypothesized that such โ€œprospective replayโ€ sequences may play a causal role in goal-directed navigation. In the present study, we query this putative causal role in finding only minimal effects of muscimol-induced inactivation of the dorsal and intermediate hippocampus on the same spatial navigation task. The concentration of muscimol used demonstrably inhibited hippocampal cell firing in vivo and caused a severe deficit in a hippocampal-dependent โ€œepisodic-likeโ€ spatial memory task in a watermaze. These findings call into question whether โ€œprospective replayโ€ of an imminent and direct path is actually necessary for its execution in certain navigational tasks.Aarhus Institute of Advanced Studies, AarhusUniversitet, Grant/Award Number: 754513;ICT-FET (European Commission), Grant/AwardNumber: 600725; Lundbeckfonden,Grant/Award Number: DANDRITE-R248-2016-2518; Novo Nordisk Fonden,Grant/Award Number: NNF17OC0026774;Wellcome Trust, Grant/Award Numbers:206491, 207481/Z/17/Z; European Molecular Biology Organization, Grant/Award Number:EMBOALTF382-2017Peer reviewe

    A Review of Findings from Neuroscience and Cognitive Psychology as Possible Inspiration for the Path to Artificial General Intelligence

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    This review aims to contribute to the quest for artificial general intelligence by examining neuroscience and cognitive psychology methods for potential inspiration. Despite the impressive advancements achieved by deep learning models in various domains, they still have shortcomings in abstract reasoning and causal understanding. Such capabilities should be ultimately integrated into artificial intelligence systems in order to surpass data-driven limitations and support decision making in a way more similar to human intelligence. This work is a vertical review that attempts a wide-ranging exploration of brain function, spanning from lower-level biological neurons, spiking neural networks, and neuronal ensembles to higher-level concepts such as brain anatomy, vector symbolic architectures, cognitive and categorization models, and cognitive architectures. The hope is that these concepts may offer insights for solutions in artificial general intelligence.Comment: 143 pages, 49 figures, 244 reference
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