scholarly journals Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Lyle Muller ◽  
Giovanni Piantoni ◽  
Dominik Koller ◽  
Sydney S Cash ◽  
Eric Halgren ◽  
...  
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Neural Mechanism ◽  
Sleep Spindles ◽  
Sleep Spindle ◽  
Spike Time ◽  
Temporal Precision ◽  
Global Patterns ◽  
Spike Time Dependent Plasticity ◽  
Large Scale Networks

During sleep, the thalamus generates a characteristic pattern of transient, 11-15 Hz sleep spindle oscillations, which synchronize the cortex through large-scale thalamocortical loops. Spindles have been increasingly demonstrated to be critical for sleep-dependent consolidation of memory, but the specific neural mechanism for this process remains unclear. We show here that cortical spindles are spatiotemporally organized into circular wave-like patterns, organizing neuronal activity over tens of milliseconds, within the timescale for storing memories in large-scale networks across the cortex via spike-time dependent plasticity. These circular patterns repeat over hours of sleep with millisecond temporal precision, allowing reinforcement of the activity patterns through hundreds of reverberations. These results provide a novel mechanistic account for how global sleep oscillations and synaptic plasticity could strengthen networks distributed across the cortex to store coherent and integrated memories.

scholarly journals Sleep Spindles: Mechanisms and Functions

2020 ◽  
Vol 100 (2) ◽  
pp. 805-868 ◽  
Author(s):  
Laura M. J. Fernandez ◽  
Anita Lüthi
Keyword(s):  
Cognitive Abilities ◽  
Large Scale ◽  
Physiological State ◽  
Mammalian Brain ◽  
Sleep Spindles ◽  
Cognitive Profiles ◽  
Sleep Spindle ◽  
Discrete Events ◽  
Continuous Power ◽  
Electroencephalogram Eeg

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

scholarly journals The effect of spike time dependent plasticity on activity patterns in the basal ganglia

2011 ◽  
Vol 12 (S1) ◽  
Author(s):  
Marcel AJ Lourens ◽  
Jasmine A Nirody ◽  
Hil GE Meijer ◽  
Tjitske Heida ◽  
Stephan A van Gils
Keyword(s):  
Basal Ganglia ◽  
Activity Patterns ◽  
Time Dependent ◽  
Spike Time ◽  
Dependent Plasticity ◽  
Spike Time Dependent Plasticity

scholarly journals Discovering precise temporal patterns in large-scale neural recordings through robust and interpretable time warping

2019 ◽  
Author(s):  
Alex H. Williams ◽  
Ben Poole ◽  
Niru Maheswaranathan ◽  
Ashesh K. Dhawale ◽  
Tucker Fisher ◽  
...  
Keyword(s):  
Large Scale ◽  
General Purpose ◽  
Spike Time ◽  
Time Warping ◽  
Motor Sequence ◽  
Temporal Precision ◽  
Neural Recordings ◽  
Sequence Production ◽  
Time Patterns

AbstractThough the temporal precision of neural computation has been studied intensively, a data-driven determination of this precision remains a fundamental challenge. Reproducible spike time patterns may be obscured on single trials by uncontrolled temporal variability in behavior and cognition, or may not even be time locked to measurable signatures in either behavior or local field potentials (LFP). To overcome these challenges, we describe a general-purpose time warping framework that reveals precise spike-time patterns in an unsupervised manner, even when spiking is decoupled from behavior or is temporally stretched across single trials. We demonstrate this method across diverse systems: cued reaching in nonhuman primates, motor sequence production in rats, and olfaction in mice. This approach flexibly uncovers diverse dynamical firing patterns, including pulsatile responses to behavioral events, LFP-aligned oscillatory spiking, and even unanticipated patterns, like 7 Hz oscillations in rat motor cortex that are not time-locked to measured behaviors or LFP.

scholarly journals Capturing the spatiotemporal dynamics of task-initiated thoughts with combined EEG and fMRI

2018 ◽  
Author(s):  
Lucie Bréchet ◽  
Denis Brunet ◽  
Gwénaël Birot ◽  
Rolf Gruetter ◽  
Christoph M. Michel ◽  
...  
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Mental Arithmetic ◽  
Brain Activity ◽  
Activity Patterns ◽  
Mental States ◽  
Spatiotemporal Dynamics ◽  
Source Analysis ◽  
Eeg Source Analysis ◽  
Large Scale Networks

AbstractWhen at rest, our mind wanders from thought to thought in distinct mental states. Despite the marked importance of ongoing mental processes, it is challenging to capture and relate these states to specific cognitive contents. In this work, we employed ultra-high field functional magnetic resonance imaging (fMRI) and high-density electroencephalography (EEG) to study the ongoing thoughts of participants instructed to retrieve self-relevant past episodes for periods of 20s. These task-initiated, participant-driven activity patterns were compared to a distinct condition where participants performed serial mental arithmetic operations, thereby shifting from self-related to self-unrelated thoughts. BOLD activity mapping revealed selective activity changes in temporal, parietal and occipital areas (“posterior hot zone”), evincing their role in integrating the re-experienced past events into conscious representations during memory retrieval. Functional connectivity analysis showed that these regions were organized in two major subparts of the default mode network, previously associated to “scene-reconstruction” and “self-experience” subsystems. EEG microstate analysis allowed studying these participant-driven thoughts in the millisecond range by determining the temporal dynamics of brief periods of stable scalp potential fields. This analysis revealed selective modulation of occurrence and duration of specific microstates in both conditions. EEG source analysis revealed similar spatial distributions between the sources of these microstates and the regions identified with fMRI. These findings support growing evidence that specific fMRI networks can be captured with EEG as repeatedly occurring, integrated brief periods of synchronized neuronal activity, lasting only fractions of seconds.SignificanceWe investigated the spatiotemporal dynamics of large-scale brain networks related to specific conscious thoughts. We demonstrate here that instructing participants to direct their thoughts to either episodic autobiographic memory or to mental arithmetic modulates distinct networks both in terms of highly spatially-specific BOLD signal oscillations as well as fast sub-second dynamics of EEG microstates. The combined findings from the two modalities evince a clear link between hemodynamic and electrophysiological signatures of spontaneous brain activity by the occurrence of thoughts that last for fractions of seconds, repeatedly appearing over time as integrated coherent activities of specific large-scale networks.

scholarly journals Sleep spindle refractoriness segregates periods of memory reactivation

2017 ◽  
Author(s):  
James W. Antony ◽  
Luis Piloto ◽  
Margaret Wang ◽  
Paula Pacheco ◽  
Kenneth A. Norman ◽  
...  
Keyword(s):  
Refractory Period ◽  
Functional Role ◽  
Neural Mechanism ◽  
Initial Study ◽  
Sleep Spindles ◽  
Sleep Spindle ◽  
Memory Reactivation ◽  
The Stability

AbstractThe stability of long-term memories is enhanced by reactivation during sleep. Correlative evidence has linked memory reactivation with thalamocortical sleep spindles, although their functional role is poorly understood. Our initial study replicated this correlation but also demonstrated a novel rhythmicity to spindles, such that spindles are less likely to occur immediately following other spindles. We leveraged this rhythmicity to test the role of spindles in memory by using real-time spindle tracking to present cues inside versus outside the presumptive refractory period; as predicted, cues presented outside the refractory period led to better memory. Our findings reveal a previously undescribed neural mechanism whereby spindles segment sleep into two distinct substates: prime opportunities for reactivation and gaps that segregate reactivation events.One Sentence SummaryThe characteristic timing of sleep spindles regulates when memories can be reactivated during sleep.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

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