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      Training on an Appetitive (Delay)-Conditioning Task Enhances Oscillatory Waves During Sleep in the Cortical and Amygdalar Network

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          Abstract

          Oscillating waves during sleep play an essential role in memory consolidation. The cortical slow wave activity (SWA) and sigma waves during NREM sleep and theta waves during REM sleep increase after a variety of memory tasks including declarative, procedural and associative learning tasks. These oscillatory waves during sleep help to promote neural dialog between circuitries, which possibly plays a causal role in memory consolidation. However, the role of sleep-associated oscillating waves in a complex appetitive-conditioning paradigm is not clear. The parietal cortex and amygdala are involved in the cognitive evaluation of the environmental stimuli, and appetitive conditioning. Here, we have studied the changes in sleep architecture and oscillatory waves during NREM and REM sleep in the parietal cortices and amygdalar-local field potential (A-LFP) after appetitive-conditioning in the rat. We observed that REM sleep increased significantly after appetitive conditioning, which significantly positively correlated with performance on the appetitive-conditioning task. Further, the cortical SWA (0.1–4.5 Hz), and sigma (12–14.25 Hz) waves during NREM sleep, theta (6–9 Hz) waves during REM sleep, the amygdalar SWA (0.1–3.75 Hz) during NREM sleep and theta (6–8.25 Hz) waves during REM sleep significantly increased after appetitive conditioning. Interestingly, the augmented oscillatory waves significantly positively correlated with the performances on the appetitive-conditioning task. Our results suggest that the augmented REM sleep after conditioning may be required for the consolidation of appetitive-conditioned memory. Further, a significant correlation between augmented power in oscillatory waves during sleep and performance suggesting that these waves may be playing a crucial role in the consolidation of appetitive-conditioned memory.

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          Most cited references57

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          Prefrontal phase locking to hippocampal theta oscillations.

          The interactions between cortical and hippocampal circuits are critical for memory formation, yet their basic organization at the neuronal network level is not well understood. Here, we demonstrate that a significant portion of neurons in the medial prefrontal cortex of freely behaving rats are phase locked to the hippocampal theta rhythm. In addition, we show that prefrontal neurons phase lock best to theta oscillations delayed by approximately 50 ms and confirm this hippocampo-prefrontal directionality and timing at the level of correlations between single cells. Finally, we find that phase locking of prefrontal cells is predicted by the presence of significant correlations with hippocampal cells at positive delays up to 150 ms. The theta-entrained activity across cortico-hippocampal circuits described here may be important for gating information flow and guiding the plastic changes that are believed to underlie the storage of information across these networks.
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            Coordinated interactions between hippocampal ripples and cortical spindles during slow-wave sleep.

            Sleep is characterized by a structured combination of neuronal oscillations. In the hippocampus, slow-wave sleep (SWS) is marked by high-frequency network oscillations (approximately 200 Hz "ripples"), whereas neocortical SWS activity is organized into low-frequency delta (1-4 Hz) and spindle (7-14 Hz) oscillations. While these types of hippocampal and cortical oscillations have been studied extensively in isolation, the relationships between them remain unknown. Here, we demonstrate the existence of temporal correlations between hippocampal ripples and cortical spindles that are also reflected in the correlated activity of single neurons within these brain structures. Spindle-ripple episodes may thus constitute an important mechanism of cortico-hippocampal communication during sleep. This coactivation of hippocampal and neocortical pathways may be important for the process of memory consolidation, during which memories are gradually translated from short-term hippocampal to longer-term neocortical stores.
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              Sleep-dependent learning and memory consolidation.

              While the functions of sleep remain largely unknown, one of the most exciting and contentious hypotheses is that sleep contributes importantly to memory. A large number of studies offer a substantive body of evidence supporting this role of sleep in what is becoming known as sleep-dependent memory processing. This review will provide evidence of sleep-dependent memory consolidation and sleep-dependent brain plasticity and is divided into five sections: (1) an overview of sleep stages, memory categories, and the distinct stages of memory development; (2) a review of the specific relationships between sleep and memory, both in humans and animals; (3) a survey of evidence describing sleep-dependent brain plasticity, including human brain imaging studies as well as animal studies of cellular neurophysiology and molecular biology. We close (4) with a consideration of unanswered questions as well as existing arguments against the role of sleep in learning and memory and (5) a concluding summary.
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                Author and article information

                Contributors
                Journal
                Front Behav Neurosci
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Media S.A.
                1662-5153
                07 November 2018
                2018
                : 12
                : 260
                Affiliations
                [1] 1Department of Biotechnology, School of Engineering and Technology, Sharda University , Greater Noida, India
                [2] 2School of Life Sciences, Jawaharlal Nehru University , New Delhi, India
                Author notes

                Edited by: Valérie Doyère, Centre National de la Recherche Scientifique (CNRS), France

                Reviewed by: Charles-Francois V. Latchoumane, Institute for Basic Science (IBS), South Korea; Antoine Adamantidis, Universität Bern, Switzerland

                Article
                10.3389/fnbeh.2018.00260
                6234907
                30464744
                75920c0c-fabc-47d9-93dd-cb43841a8150
                Copyright © 2018 Tripathi, Taneja and Jha.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 December 2017
                : 15 October 2018
                Page count
                Figures: 9, Tables: 0, Equations: 0, References: 70, Pages: 17, Words: 0
                Funding
                Funded by: Department of Biotechnology, Ministry of Science and Technology 10.13039/501100001409
                Funded by: Department of Science and Technology, Ministry of Science and Technology 10.13039/501100001409
                Categories
                Neuroscience
                Original Research

                Neurosciences
                swa,learning,nrem sleep,rem sleep,sigma waves,theta waves
                Neurosciences
                swa, learning, nrem sleep, rem sleep, sigma waves, theta waves

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