200 research outputs found

    Tetrode recording from the hippocampus of behaving mice coupled with four-point-irradiation closed-loop optogenetics: A technique to study the contribution of Hippocampal SWR events to learning

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    With the advent of optogenetics, it became possible to change the activity of a targeted population of neurons in a temporally controlled manner. To combine the advantages of 60-channel in vivo tetrode recording and laser-based optogenetics, we have developed a closed-loop recording system that allows for the actual electrophysiological signal to be used as a trigger for the laser light mediating the optogenetic intervention. We have optimized the weight, size, and shape of the corresponding implant to make it compatible with the size, force, and movements of a behaving mouse, and we have shown that the system can efficiently block sharp wave ripple (SWR) events using those events themselves as a trigger. To demonstrate the full potential of the optogenetic recording system we present a pilot study addressing the contribution of SWR events to learning in a complex behavioral task

    ์ž์œ ๋กญ๊ฒŒ ์›€์ง์ด๋Š” ์ƒ์ฅ์˜ ํ•ด๋งˆ์—์„œ sharp wave-ripple์˜ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ์‹ ํ˜ธ์™€ ์นผ์Š˜ ์‹ ํ˜ธ๋ฅผ ๋™์‹œ์— ๊ธฐ๋กํ•˜๋Š” ๋ฐฉ๋ฒ•๊ณผ ํ™œ์šฉ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜๊ณผํ•™๊ณผ, 2023. 2. ๊น€์ƒ์ •.Various experiences occur in our daily life in diverse context, and among them, some experiences become a life-long memory while some are easily forgotten. Not only encoding of experiences, this phenomenon of memory selection is heavily dependent on the consolidation of memory. In the investigation of long-term memory formation, hippocampal SWR signal and its neuronal contents have been extensively studied using neuronal decoding analysis of electrophysiological signal to recognize SWRs in the neuronal signals. However, as this signal has low spatial resolution and hard to track neurons across time, it has been difficult to analyze the individual contribution of neurons to task-specific SWRs. In this work, I focused on the investigation of the hippocampal SWRs in spatial aspect not only in temporal aspect, and identification of cellular ensembles consisting of the activity to improve contents of consolidated memory by SWRs. To understand the composition of SWRs and its change by the environment in detail, I divided the research process into two parts. In the first part, to investigate individual hippocampal neuronal activity participating in SWRs activity, I developed a Microdrive array with tetrodes, that combines with UCLA miniscope, a 1-p calcium imaging device. This method enables us to observe SWRs activity not only populational electrophysiological manner, as well as individual cellular activity using calcium indicators from freely behaving animals. The acquired data show that a group of hippocampal neurons was identified to have increased activity on the onset of SWRs, while activities were found to be decreased when SWRs are disrupted. This result implies the potential contribution of individual neuronal activity in the memory consolidation process. In the second part, the calcium transient signals acquired from hippocampal neurons was compared by the environment of the animal. While animals are exploring two different environments, SWRs were detected in real-time and hippocampal neuronal activities were observed simultaneously. From the result, we found that different subsets of neurons are firing during SWRs depending on the environment of the animals, suggesting that SWR signals are collective signals of multiple neurons but their compositions are different by the contents of experience. This result has a potential to improve decoding accuracy when investigating replay contents and neuronal composition. Overall, this thesis covers comprehensive strides from the development of tools to analysis of scientific findings in search of neuronal constitution of memory engraved in the hippocampus.์šฐ๋ฆฌ์˜ ์ผ์ƒ ์ƒํ™œ์—์„œ๋Š” ๋‹ค์–‘ํ•œ ๊ฒฝํ—˜์ด ๋‹ค์–‘ํ•œ ํ™˜๊ฒฝ์—์„œ ์ผ์–ด๋‚œ๋‹ค. ๊ทธ ์ค‘ ์ผ๋ถ€๋Š” ํ‰์ƒ ์ง€์†๋˜๋Š” ๊ฐ•๋ ฌํ•œ ๊ฒฝํ—˜์ด ๋˜๊ธฐ๋„ ํ•˜๊ณ , ๋‹ค๋ฅธ ๊ฒฝํ—˜๋“ค์€ ๊ธฐ์–ต๋„ ๋˜์ง€ ๋ชปํ•˜๊ณ  ์‰ฝ๊ฒŒ ์žŠํ˜€์ง„๋‹ค. ์ด๋Ÿฌํ•œ ๊ธฐ์–ต์˜ ์„ ํƒ์  ์ €์žฅ์—๋Š”, ๊ฒฝํ—˜์˜ ์ž…๋ ฅ ๊ณผ์ •(encoding) ๋ฟ ๋งŒ ์•„๋‹ˆ๋ผ ๊ฒฝํ—˜์˜ ๊ฐ•ํ™” (consolidation) ๊ณผ์ •๋„ ํฐ ์˜ํ–ฅ์„ ๋ผ์นœ๋‹ค. ํ•ด๋งˆ์˜ sharp wave-ripples (SWRs) ์™€ ๊ทธ ๊ตฌ์„ฑ ๋‰ด๋Ÿฐ๋“ค์€ ์žฅ๊ธฐ ๊ธฐ์–ต์˜ ํ˜•์„ฑ ๊ณผ์ •์„ ์—ฐ๊ตฌํ•˜๋Š” ๋ฐ์— ํฐ ๋น„์ค‘์„ ์ฐจ์ง€ํ•ด์™”๋‹ค. ํŠนํžˆ ์ด ๋‰ด๋Ÿฐ์˜ ์‹ ํ˜ธ๋“ค์€ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ๋ฐฉ์‹์œผ๋กœ ๊ธฐ๋ก๋˜๊ณ  ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ด๋Ÿฌํ•œ ์‹ ํ˜ธ๋“ค์€ ๋‰ด๋Ÿฐ์˜ ์œ„์น˜์— ๋Œ€ํ•œ ์ •๋ณด๊ฐ€ ๋ถ€์กฑํ•˜๊ณ  ์žฅ๊ธฐ๊ฐ„์— ๊ฑธ์ณ ๊ฐ™์€ ๋‰ด๋Ÿฐ์„ ์ธ์‹ํ•  ์ˆ˜ ์—†๊ธฐ ๋•Œ๋ฌธ์—, ํŠน์ • ํ™˜๊ฒฝ์—์„œ ์ผ์–ด๋‚˜๋Š” SWRs์ด ์–ด๋– ํ•œ ๋‰ด๋Ÿฐ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด์žˆ๋Š”์ง€ ์—ฐ๊ตฌํ•˜๋Š” ๋ฐ์—๋Š” ์–ด๋ ค์›€์ด ์žˆ์—ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š”, ํ•ด๋งˆ์˜ SWRs์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‰ด๋Ÿฐ๋“ค์„ ์‹œ๊ฐ„์  ์ธก๋ฉด ๋ฟ ๋งŒ ์•„๋‹ˆ๋ผ ๊ณต๊ฐ„์  ์ธก๋ฉด์—์„œ๋„ ๊ด€์ฐฐํ•˜์—ฌ, SWRs๋กœ ์ธํ•ด ๊ฐ•ํ™”๋˜๋Š” ๊ธฐ์–ต์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‰ด๋Ÿฐ๋“ค์„ ์‹๋ณ„ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. SWRs์˜ ๊ตฌ์„ฑ๊ณผ ํ™˜๊ฒฝ์— ๋”ฐ๋ฅธ ๊ตฌ์„ฑ์˜ ๋ณ€ํ™”๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด, ๋ณธ ์—ฐ๊ตฌ๋Š” ์•„๋ž˜์˜ ๋‘ ๋ถ€๋ถ„์œผ๋กœ ๋‚˜๋ˆ„์–ด ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์ฒซ๋ฒˆ์งธ ๋ถ€๋ถ„์—์„œ๋Š” ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ๋ฐฉ๋ฒ•๊ณผ ์นผ์Š˜ ์ด๋ฏธ์ง• ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด, ์ž์œ ๋กญ๊ฒŒ ์›€์ง์ด๋Š” ์ƒ์ฅ์˜ ํ•ด๋งˆ์—์„œ ๋ฐœ์ƒํ•˜๋Š” SWRs์„ ๋‘ ๊ฐ€์ง€ ๋ฐฉ๋ฒ•์œผ๋กœ ๊ธฐ๋กํ•˜๊ณ , ๊ทธ ์‹ ํ˜ธ์— ๋”ฐ๋ผ ๋ณ€ํ™”ํ•˜๋Š” ๋‡Œ์„ธํฌ์˜ ํ™œ๋™์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์‚ด์•„์žˆ๋Š” ๋™๋ฌผ์—์„œ ์‹ค์‹œ๊ฐ„์œผ๋กœ ์ „๊ธฐ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์ดˆ์†Œํ˜• ๊ธฐ๊ตฌ๋ฅผ ๋งŒ๋“ค๊ณ , ์ด๋ฅผ ๋‹จ๊ด‘์ž ์นผ์Š˜ ์ด๋ฏธ์ง• ์žฅ์น˜์™€ ๊ฒฐํ•ฉ์‹œ์ผฐ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฉ์‹์„ ํ†ตํ•ด ํ•ด๋งˆ์˜ SWRs์„ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ๋ฐฉ์‹๊ณผ ์นผ์Š˜ ์‹ ํ˜ธ์˜ ๋‘ ๊ฐ€์ง€ ๋ฐฉ์‹์œผ๋กœ ๊ธฐ๋กํ•˜์˜€๋‹ค. ๊ธฐ๋ก ๊ฒฐ๊ณผ, ํ•ด๋งˆ์˜ ๋‡Œ์„ธํฌ๋“ค์˜ ํ™œ๋™์„ฑ์ด SWRs์ด ์‹œ์ž‘๋จ์— ๋”ฐ๋ผ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋ฐ˜๋ฉด, SWRs์ด ๋ฐฉํ•ด๋œ ๊ฒฝ์šฐ์—๋Š” ํ•ด๋งˆ ๋‡Œ์„ธํฌ์˜ ํ™œ๋™์„ฑ ์ฆ๊ฐ€๊ฐ€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š”, SWRs์„ ๊ตฌ์„ฑํ•˜๋Š” ์„ธํฌ๋“ค์ด ๊ธฐ์–ต ๊ฐ•ํ™” ๊ณผ์ •์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ์Œ์„ ์•”์‹œํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ ๋ถ€๋ถ„์—์„œ๋Š”, ํ•ด๋งˆ ๋‰ด๋Ÿฐ์—์„œ ์–ป์–ด์ง„ ์นผ์Š˜ ์‹ ํ˜ธ๋“ค์„ ๋™๋ฌผ๋“ค์˜ ์‹คํ—˜ ํ™˜๊ฒฝ์— ๋”ฐ๋ผ ๋น„๊ตํ•˜์—ฌ ๋ณด์•˜๋‹ค. ๋™๋ฌผ๋“ค์ด ๋‘ ๊ฐœ์˜ ๋‹ค๋ฅธ ํ™˜๊ฒฝ์„ ๊ฒฝํ—˜ํ•˜๊ณ  ์žˆ๋Š” ๋™์•ˆ, ํ•ด๋งˆ์—์„œ ๋ฐœ์ƒํ•˜๋Š” SWRs ์‹ ํ˜ธ๊ฐ€ ์‹ค์‹œ๊ฐ„์œผ๋กœ ๊ธฐ๋ก๋˜์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ๋™๋ฌผ๋“ค์ด ์ฒ˜ํ•œ ํ™˜๊ฒฝ์— ๋”ฐ๋ผ์„œ, ์„œ๋กœ ๋‹ค๋ฅธ ํ•ด๋งˆ ๋‰ด๋Ÿฐ์œผ๋กœ ๊ตฌ์„ฑ๋œ ๊ทธ๋ฃน๋“ค์ด SWRs์„ ๊ตฌ์„ฑํ•˜๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ์ฆ‰, ํ•ด๋งˆ์˜ SWRs๋“ค์€ ์—ฌ๋Ÿฌ ๋‰ด๋Ÿฐ์˜ ์‹ ํ˜ธ๋“ค๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ์œผ๋‚˜ ๊ทธ ๊ฐ๊ฐ์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‰ด๋Ÿฐ์€ ๊ฒฝํ—˜์˜ ํ™˜๊ฒฝ์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š”, ๊ธฐ์–ต์˜ ์žฌ์ƒ (replay)๊ณผ ๊ทธ ๊ตฌ์„ฑ ๋‰ด๋Ÿฐ์„ ์‹๋ณ„ํ•˜๊ธฐ ์œ„ํ•œ ์‹ ํ˜ธ์˜ ํ•ด๋…(decoding) ๊ณผ์ •์—์„œ์˜ ์ •ํ™•์„ฑ์„ ๋†’์ด๋Š” ๋ฐ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ •๋ฆฌํ•˜๋ฉด, ์ด ๋…ผ๋ฌธ์„ ํ†ตํ•˜์—ฌ, ํ•ด๋งˆ์— ์ €์žฅ๋˜์–ด ์žˆ๋Š” ๊ธฐ์–ต์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‰ด๋Ÿฐ๋“ค์„ ์‹๋ณ„ํ•˜๊ธฐ ์œ„ํ•œ ์‹คํ—˜ ๋„๊ตฌ์˜ ๊ฐœ๋ฐœ๋ถ€ํ„ฐ ๊ทธ ๊ฒฐ๊ณผ ๋ฐœ๊ฒฌํ•œ ๊ณผํ•™์ ์ธ ๋‚ด์šฉ์˜ ๋ถ„์„์— ์ด๋ฅด๊ธฐ๊นŒ์ง€์˜ ๋‹จ๊ณ„๋“ค์„ ํฌ๊ด„์ ์œผ๋กœ ๊ธฐ์ˆ ํ•˜๊ณ  ์†Œ๊ฐœํ•˜๊ณ ์ž ํ•œ๋‹ค.Abstract 4 Table of contents 7 List of figures and tables 8 Chapter 1. Introduction 10 Chapter 2. Simultaneous cellular imaging, electrical recording and stimulation of hippocampal activity in freely behaving mice 39 Summary 39 Introduction 41 Materials and Methods 43 Results 53 Discussion 58 Chapter 3. Simultaneous cellular imaging and electrical recording for dissecting neuronal ensemble activity of SWRs in multiple environments 76 Summary 76 Introduction 77 Materials and Methods 78 Results 79 Discussion 81 Chapter 4. Conclusion and future perspective 88 References 92 ๊ตญ๋ฌธ์š”์•ฝ 113๋ฐ•

    Large-scale neural ensemble recording in the brains of freely behaving mice

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    Abstract With the availability of sophisticated genetic techniques, the mouse is a valuable mammalian model to study the molecular and cellular basis of cognitive behaviors. However, the small size of mice makes it difficult for a systematic investigation of activity patterns of neural networks in vivo. Here we report the development and construction of a high-density ensemble recording array with up to 128-recording channels that can be formatted as single electrodes, stereotrodes, or tetrodes. This high-density recording array is capable of recording from hundreds of individual neurons simultaneously in the hippocampus of the freely behaving mice. This large-scale in vivo ensemble recording techniques, once coupled with mouse genetics, should be valuable to the study of complex relationship between the genes, neural network, and cognitive behaviors

    Pitx3Null Mutant (Striatal Dopamine-Deficient) Mice Have Exaggerated Spiny Projection Neuron Responses to l-DOPA and D1 Agonism and Lack Baseline Striatonigral Spiking

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    L-3,4 dihidroxyphenylalanine (l-DOPA) strongly stimulates motor activity in parkinsonian patients and animal models of Parkinson\u27s disease. Severe striatal dopamine (DA) loss characterizes Parkinson\u27s disease and its animal models. Given the canonical rate model of Parkinson\u27s Disease pathophysiology based on differences in DA pharmacology manifesting as electrophysiological differences in striatal projection neuron (SPN) spike rates, SPNs should increase spiking during the motor response to l-DOPA. In fact, stimulating specific subsets of these neurons to spike in freely-moving wild type and parkinsonian animals causes or inhibits motor activity as predicted. However, pharmacological effects of DA deficiency, let alone those of DA replacement, on SPN spiking activity in freely-moving animals are poorly studied and ultimately unknown. Showing the activity of SPNs of both in-/direct pathways may help elucidate mechanisms by which l-DOPA increases motor activity to normal and sometimes abnormal levels; such mechanistic information would advance understanding about how DA is such a potent motor stimulant. To this end, I devised a Top-hat u-array (with microdrive) for recording in the striatum while stimulating the reticulated substantia nigra. Using my micro-array, I tested l-DOPA\u27s acute effect on SPN spiking activity within contexts that varied in DA deficiency according to the Pitx3Null mouse\u27s Parkinson\u27s-like gradient of striatal DA denervation. Evidently, chronic DA denervation renders SPNs hyper-responsive to l-DOPA and a D1 agonist, SKF 81297, as indicated by exaggerated SPN spike rate responses biased by low baselines in Pitx3Null mice compared to wild-type mice. However, this may be a motor network effect on spiking as it was found in both dorsal (DA-denervated) and non-dorsal (having residual DA) Pitx3Null striatal regions. Furthermore, antidromically identifying dorsal SPNs allowed us to putatively distinguish a particularly relevant subset (striatonigral, D1-SPNs or d[irect]SPNs) known to elicit movement; serendipitously we also identified putative fibers of passage that strongly resembled striatal interneurons. D1-SPNs in Pitx3Null animals had baselines about an order of magnitude significantly below those in wild-type, and all increased firing more so in Pitx3Null than wild-type mice after drug injections, which lends some credence to the hypothesis that direct pathway SPNs are hyper-responsive during l-DOPA-induced normal and abnormal motor behavior secondary to DA depletion. Furthermore, they uncover a need to incorporate more neural factors in explaining electrophysiological effects attributable to DA denervation and restoration pharmacology. The latter data (putative fibers) tempt the interpretation that cortical axons of passage are being mistaken for striatal fast-spiking interneurons in the literature more often than not

    Long-Term Neural Recordings Using MEMS Based Movable Microelectrodes in the Brain

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    One of the critical requirements of the emerging class of neural prosthetic devices is to maintain good quality neural recordings over long time periods. We report here a novel MEMS (Micro Electro Mechanical Systems) based technology that can move microelectrodes in the event of deterioration in neural signal to sample a new set of neurons. Microscale electro-thermal actuators are used to controllably move microelectrodes post-implantation in steps of approximately 9 ฮผm. In this study, a total of 12 movable microelectrode chips were individually implanted in adult rats. Two of the twelve movable microelectrode chips were not moved over a period of 3 weeks and were treated as control experiments. During the first 3 weeks of implantation, moving the microelectrodes led to an improvement in the average signal to noise ratio (SNR) from 14.61 ยฑ 5.21โ€‰dB before movement to 18.13 ยฑ 4.99โ€‰dB after movement across all microelectrodes and all days. However, the average root-mean-square values of noise amplitudes were similar at 2.98 ยฑ 1.22 ฮผV and 3.01 ยฑ 1.16 ฮผV before and after microelectrode movement. Beyond 3 weeks, the primary observed failure mode was biological rejection of the PMMA (dental cement) based skull mount resulting in the device loosening and eventually falling from the skull. Additionally, the average SNR for functioning devices beyond 3 weeks was 11.88 ยฑ 2.02โ€‰dB before microelectrode movement and was significantly different (p < 0.01) from the average SNR of 13.34 ยฑ 0.919โ€‰dB after movement. The results of this study demonstrate that MEMS based technologies can move microelectrodes in rodent brains in long-term experiments resulting in improvements in signal quality. Further improvements in packaging and surgical techniques will potentially enable movable microelectrodes to record cortical neuronal activity in chronic experiments

    Extensive Cortical Convergence to Primate Reticulospinal Pathways.

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    Early evolution of the motor cortex included development of connections to brainstem reticulospinal neurons; these projections persist in primates. In this study, we examined the organization of corticoreticular connections in five macaque monkeys (one male) using both intracellular and extracellular recordings from reticular formation neurons, including identified reticulospinal cells. Synaptic responses to stimulation of different parts of primary motor cortex (M1) and supplementary motor area (SMA) bilaterally were assessed. Widespread short latency excitation, compatible with monosynaptic transmission over fast-conducting pathways, was observed, as well as longer latency responses likely reflecting a mixture of slower monosynaptic and oligosynaptic pathways. There was a high degree of convergence: 56% of reticulospinal cells with input from M1 received projections from M1 in both hemispheres; for SMA, the equivalent figure was even higher (70%). Of reticulospinal neurons with input from the cortex, 78% received projections from both M1 and SMA (regardless of hemisphere); 83% of reticulospinal cells with input from M1 received projections from more than one of the tested M1 sites. This convergence at the single cell level allows reticulospinal neurons to integrate information from across the motor areas of the cortex, taking account of the bilateral motor context. Reticulospinal connections are known to strengthen following damage to the corticospinal tract, such as after stroke, partially contributing to functional recovery. Extensive corticoreticular convergence provides redundancy of control, which may allow the cortex to continue to exploit this descending pathway even after damage to one area.SIGNIFICANCE STATEMENT The reticulospinal tract (RST) provides a parallel pathway for motor control in primates, alongside the more sophisticated corticospinal system. We found extensive convergent inputs to primate reticulospinal cells from primary and supplementary motor cortex bilaterally. These redundant connections could maintain transmission of voluntary commands to the spinal cord after damage (e.g., after stroke or spinal cord injury), possibly assisting recovery of function

    Theta Rhythmic Clock-Like Activity of Single Units in the Mouse Hippocampus

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    Theta rhythmic clock-like activity was observed in a small group of hippocampal CA1 neurons in freely behaving mice. These neurons were only persistently activated during theta states of waking exploration and rapid eye movement sleep, but were almost silent during the non-theta state of slow-wave sleep. Interestingly, these cells displayed a theta clock-like simple-spike firing pattern, and were capable of firing one spike per theta cycle during theta states. This is the first report of a unique class of hippocampal neurons with a clock-like firing pattern at the theta rhythm. We speculate that these cells may act as a temporal reference to participate in the theta-related temporal coding in the hippocampus. SIGNIFICANCE STATEMENT Theta oscillations, as the predominant rhythms in the hippocampus during waking exploration and rapid eye movement sleep, may be critical for temporal coding/decoding of neuronal information, and theta-phase precession in hippocampal place cells is one of the best demonstrations of such temporal coding. Here, we show that a unique small class of hippocampal CA1 neurons fired with a theta rhythmic clock-like firing pattern during theta states. These firing characteristics support the notion that these neurons may play a critical role in theta-related temporal coding in the hippocampus

    Wireless Simultaneous Stimulation-and-Recording Device (SRD) to Train Cortical Circuits in Rat Somatosensory Cortex

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    The primary goal of this project is to develop a wireless system for simultaneous recording-and-stimulation (SRD) to deliver low amplitude current pulses to the primary somatosensory cortex (SI) of rats to activate and enhance an interhemispheric cortical pathway. Despite the existence of an interhemispheric connection between similar forelimb representations of SI cortices, forelimb cortical neurons respond only to input from the contralateral (opposite side) forelimb and not to input from the ipsilateral (same side) forelimb. Given the existence of this interhemispheric pathway we have been able to strengthen/enhance the pathway through chronic intracortical microstimulation (ICMS) in previous acute experiments of anesthetized rats. In these acute experiments strengthening the interhemispheric pathway also brings about functional reorganization whereby cortical neurons in forelimb cortex respond to new input from the ipsilateral forelimb. Having the ability to modify cortical circuitry will have important applications in stroke patients and could serve to rescue and/or enhance responsiveness in surviving cells around the stroke region. Also, the ability to induce functional reorganization within the deafferented cortical map, which follows limb amputation, will also provide a vehicle for modulating maladaptive cortical reorganization often associated with phantom limb pain leading to reduced pain. In order to increase our understanding of the observed functional reorganization and enhanced pathway, we need to be able to test these observations in awake and behaving animals and eventually study how these changes persist over a prolonged period of time. To accomplish this a system was needed to allow simultaneous recording and stimulation in awake rats. However, no such commercial or research system exists that meets all requirements for such an experiment. In this project we describe the (1) system design, (2) system testing, (3) system evaluation, and (4) system implementation of a wireless simultaneous stimulation-and-recording device (SRD) to be used to modulate cortical circuits in an awake rodent animal model
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