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Temudo A, Albouy G. Using targeted memory reactivation as a tool to provide mechanistic insights into memory consolidation during sleep. Sleep 2024; 47:zsae163. [PMID: 39044535 DOI: 10.1093/sleep/zsae163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Indexed: 07/25/2024] Open
Affiliation(s)
- Ainsley Temudo
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, USA
| | - Geneviève Albouy
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, USA
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2
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Simor P, Bogdány T, Sifuentes-Ortega R, Rovai A, Peigneux P. Lateralized tactile stimulation during NREM sleep globally increases both slow and fast frequency activities. Psychophysiology 2023; 60:e14191. [PMID: 36153813 PMCID: PMC10078489 DOI: 10.1111/psyp.14191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 07/06/2022] [Accepted: 09/06/2022] [Indexed: 01/25/2023]
Abstract
Slow frequency activity during non-rapid eye movement (NREM) sleep emerges from synchronized activity of widely distributed thalamo-cortical and cortico-cortical networks, reflecting homeostatic and restorative properties of sleep. Slow frequency activity exhibits a reactive nature, and can be increased by acoustic stimulation. Although non-invasive brain stimulation is a promising technique in basic and clinical sleep research, sensory stimulation studies focusing on modalities other than the acoustic are scarce. We explored here the potential of lateralized vibro-tactile stimulation (VTS) of the finger to locally modify electroencephalographic activity during nocturnal NREM sleep. Eight seconds-long sequences of vibro-tactile pulses were delivered at a rate of 1 Hz either to the left or to the right index finger, in addition to a sham condition, in fourteen healthy participants. VTS markedly increased slow frequency activity that peaked between 1-4 Hz but extended to higher (~13 Hz) frequencies, with fronto-central dominance. Enhanced slow frequency activity was accompanied by increased (14-22 Hz) fast frequency power peaking over central and posterior locations. VTS increased the amplitude of slow waves, especially during the first 3-4 s of stimulation. Noticeably, we did not observe local-hemispheric effects, that is, VTS resulted in a global cortical response regardless of stimulation laterality. VTS moderately increased slow and fast frequency activities in resting wakefulness, to a much lower extent compared to NREM sleep. The concomitant increase in slow and fast frequency activities in response to VTS indicates an instant homeostatic response coupled with wake-like, high-frequency activity potentially reflecting transient periods of increased environmental processing.
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Affiliation(s)
- Péter Simor
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.,UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN-Center for Research in Cognition and Neurosciences, Brussels, Belgium.,UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Tamás Bogdány
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.,UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN-Center for Research in Cognition and Neurosciences, Brussels, Belgium.,Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Rebeca Sifuentes-Ortega
- UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN-Center for Research in Cognition and Neurosciences, Brussels, Belgium.,UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Antonin Rovai
- UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.,Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium.,Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Philippe Peigneux
- UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN-Center for Research in Cognition and Neurosciences, Brussels, Belgium.,UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
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Miyamoto D. Neural circuit plasticity for complex non-declarative sensorimotor memory consolidation during sleep. Neurosci Res 2022; 189:37-43. [PMID: 36584925 DOI: 10.1016/j.neures.2022.12.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022]
Abstract
Evidence is accumulating that the brain actively consolidates long-term memory during sleep. Motor skill memory is a form of non-declarative procedural memory and can be coordinated with multi-sensory processing such as visual, tactile, and, auditory. Conversely, perception is affected by body movement signal from motor brain regions. Although both cortical and subcortical brain regions are involved in memory consolidation, cerebral cortex activity can be recorded and manipulated noninvasively or minimally invasively in humans and animals. NREM sleep, which is important for non-declarative memory consolidation, is characterized by slow and spindle waves representing thalamo-cortical population activity. In animals, electrophysiological recording, optical imaging, and manipulation approaches have revealed multi-scale cortical dynamics across learning and sleep. In the sleeping cortex, neural activity is affected by prior learning and neural circuits are continually reorganized. Here I outline how sensorimotor coordination is formed through awake learning and subsequent sleep.
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Affiliation(s)
- Daisuke Miyamoto
- Laboratory for Sleeping-Brain Dynamics, Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan; Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan.
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Ruch S, Schmidig FJ, Knüsel L, Henke K. Closed-loop modulation of local slow oscillations in human NREM sleep. Neuroimage 2022; 264:119682. [PMID: 36240988 DOI: 10.1016/j.neuroimage.2022.119682] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 10/10/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022] Open
Abstract
Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep's recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. When compared to a more conventional, single-channel-based approach, TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.
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Affiliation(s)
- Simon Ruch
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University Hospital and University of Tuebingen, Otfried-Müller-Str. 45, Tübingen 72076, Germany; Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland.
| | - Flavio Jean Schmidig
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Leona Knüsel
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Katharina Henke
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
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Veldman MP, Dolfen N, Gann MA, Van Roy A, Peeters R, King BR, Albouy G. Somatosensory targeted memory reactivation enhances motor performance via hippocampal-mediated plasticity. Cereb Cortex 2022; 33:3734-3749. [PMID: 35972408 DOI: 10.1093/cercor/bhac304] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 11/14/2022] Open
Abstract
Increasing evidence suggests that reactivation of newly acquired memory traces during postlearning wakefulness plays an important role in memory consolidation. Here, we sought to boost the reactivation of a motor memory trace during postlearning wakefulness (quiet rest) immediately following learning using somatosensory targeted memory reactivation (TMR). Using functional magnetic resonance imaging, we examined the neural correlates of the reactivation process as well as the effect of the TMR intervention on brain responses elicited by task practice on 24 healthy young adults. Behavioral data of the post-TMR retest session showed a faster learning rate for the motor sequence that was reactivated as compared to the not-reactivated sequence. Brain imaging data revealed that motor, parietal, frontal, and cerebellar brain regions, which were recruited during initial motor learning, were specifically reactivated during the TMR episode and that hippocampo-frontal connectivity was modulated by the reactivation process. Importantly, the TMR-induced behavioral advantage was paralleled by dynamical changes in hippocampal activity and hippocampo-motor connectivity during task practice. Altogether, the present results suggest that somatosensory TMR during postlearning quiet rest can enhance motor performance via the modulation of hippocampo-cortical responses.
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Affiliation(s)
- Menno P Veldman
- KU Leuven, Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, Leuven 3001, Belgium.,Leuven Brain Institute (LBI), KU Leuven, Leuven 3001, Belgium
| | - Nina Dolfen
- KU Leuven, Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, Leuven 3001, Belgium.,Leuven Brain Institute (LBI), KU Leuven, Leuven 3001, Belgium
| | - Mareike A Gann
- KU Leuven, Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, Leuven 3001, Belgium.,Leuven Brain Institute (LBI), KU Leuven, Leuven 3001, Belgium
| | - Anke Van Roy
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT 84112, United States
| | - Ronald Peeters
- Department of Radiology, University Hospitals Leuven, Leuven 3000, Belgium.,Department of Imaging and Pathology, Biomedical Sciences Group, Leuven 3000, Belgium
| | - Bradley R King
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT 84112, United States
| | - Geneviève Albouy
- KU Leuven, Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, Leuven 3001, Belgium.,Leuven Brain Institute (LBI), KU Leuven, Leuven 3001, Belgium.,Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT 84112, United States
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Gann MA, King BR, Dolfen N, Veldman MP, Davare M, Swinnen SP, Mantini D, Robertson EM, Albouy G. Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus. Sci Rep 2021; 11:20572. [PMID: 34663890 PMCID: PMC8523553 DOI: 10.1038/s41598-021-99926-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/24/2021] [Indexed: 11/09/2022] Open
Abstract
Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.
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Affiliation(s)
- Mareike A Gann
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Bradley R King
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, 84112, USA
| | - Nina Dolfen
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Menno P Veldman
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Marco Davare
- Department of Clinical Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UB8 3PN, UK
| | - Stephan P Swinnen
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Dante Mantini
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, 30126, Venice, Italy
| | - Edwin M Robertson
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
| | - Geneviève Albouy
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium.
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium.
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, 84112, USA.
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