Interactions between Core and Matrix Thalamocortical Projections in Human Sleep Spindle Synchronization

Abstract

Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas.

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

“…We found that the cortical network alone generated slow oscillation activity that was similar to recordings in vitro in cortical slices and isolated cortical slabs (Sanchez-Vives and McCormick, 2000;Timofeev et al, 2000). Thus, thalamic network was necessary to obtain in vivolike pattern of slow oscillation and to ensure that the synaptic reorganization described in this study occurs in the presence of the synchronized effect of matrix thalamic projections (Bonjean et al, 2012;Lemieux et al, 2014).…”

“…Experimental studies (SanchezVives and McCormick, 2000;Chauvette et al, 2010) revealed that Up states of the slow oscillations are more often initiated in layer V neurons. In our model, higher probability of Up-state initiation in layer V ( Fig.…”

“…In the model, spontaneous spike-independent minis mediated transitions from silence to active cortical states Chauvette et al, 2010), and thus any network site could potentially initiate an Up state (Fig. 3A, top and top middle).…”

Manipulating sleep spindles – expanding views on sleep, memory, and disease

“…The reasons for this complex topographic distribution are currently debated and include aspects of neocortical propagation and resonance, different contribution of thalamic nuclei and focal versus distributed TC projections from first-and higher-order thalamic nuclei [56] and the possibility of several spindle-generating loci [5]. Importantly, the local character of spindles is consistent with the observation of learning-induced local regulation of sleep waves [57], and, thus, represents a strong argument for a role of spindles in sleep-dependent memory consolidation.…”

Sleep spindles are locally modulated by training on a brain–computer interface

“…Nishida and Walker (17) showed that following procedural task learning, spindles were increased in the learning hemisphere with respect to the nonlearning hemisphere. More recently there has been a report that spindles recorded by magnetoencephalography, in contrast to those recorded by EEG, arise from multiple asynchronous generators (18), a result which may be explained by the interaction of core and matrix thalmocortical projections (19). The globally synchronous nature of spindles was further challenged by Nir et al (20) who used depth electrodes implanted in medial brain areas to show that the majority of sleep spindles are not synchronous across the brain but rather localized to a single brain area.…”