Synaptic and non-synaptic propagation of slow waves and their modulation by endogenous electric fields

Abstract

The cerebral cortex is organized in complex circuits of neurons strongly interconnected in a conductive medium. During deep sleep stage, this neuronal connectivity generates recurrent synchronized synaptic activity leading to transition states where periods of activity are interspersed with periods of silence. This stereotyped pattern of alternate states is manifested as slow oscillations (SO), <1 Hz rhythm that dominates the cortical network during slow wave sleep (Steriade et al., 1993) becoming important for memory consolidation (Marshall et al., 2006), plasticity (Reig et al., 2006; Reig and Sanchez-Vives, 2007) and metabolic homeostasis (Xie et al., 2013). The spatiotemporal dynamic of the SO is more complex than the simultaneous activation of neurons in a local network. The SO travels with a pattern of propagation in the cortical network, with a preference in the anterior to posterior direction (Massimini et al., 2004; Ruiz-Mejias et al., 2011). This oscillatory rhythm generates extracellular fields that are prominent enough to be measured extracellularly on the conductive medium (local field potentials, LFP) or even from the skull surface (electroencephalograms, EEG). Many excellent studies have raised awareness of the mechanisms involved in these extracellular signals generated by neuronal populations (Kajikawa and Schroeder, 2011; Buzsáki et al., 2012; Herreras, 2016; Telen´ czuk et al., 2017). Moreover, in the last years it has been proved how the electric fields (EFs) generated by neuronal activity, in turn, induce changes in such activity of neurons (Fröhlich and McCormick, 2010; Anastassiou et al., 2011). In other words, the electric environment generated by neuronal activity has a feedback effect on the synaptic activity. In this thesis, we explore how the synaptic and non-synaptic components modulate each other during the propagation of SO. For this purpose, we describe the propagation pattern of SO across the cerebral cortex, and we investigate the endogenous EFs

generated by slow waves dissecting it from the synaptic components to further investigate the modulation that they may induce on the cortical SO. The main methods used during this doctoral thesis consisted of an in vitro preparation of cortical brain slices from ferrets. This preparation is well known for eliciting robust spontaneous SO similar to the ones observed during slow-wave sleep. SO were recorded with a 16-channel array. In order to separate the synaptic from the EF (non-synaptic) activity, a complete cut of the slice perpendicular to white matter was performed. The two sides of the slice remained tightly in contact, without discontinuity between them thanks to the interface chamber used. The results exposed within this thesis unravel that slow waves are not local events, they propagate along the cortical network. The propagation of SO within the cortex is largely influenced by the structure of the cortical tissue. Also, an intermediate excitability level leads to the highest spatiotemporal regularity. In addition, slow waves generate EFs which travel independently of synaptic transmission within the cortical tissue, suggesting that cortical rhythms emerge from interconnected networks and might be influenced by the EFs generated by these networks. Moreover, these EFs travel with damping at a slow propagation speed, similar to the synaptic propagation velocities, rather than instantaneous as volume conduction, suggesting that neural tissue is non-homogeneous. Finally, endogenous fields modulate the SO frequency of a synaptically disconnected network, suggesting that non-synaptic mechanisms may be able to couple populations of neurons. Such coupling may affect information processing in the cortex and synaptic plasticity; thus, the ability of EFs to modulate neuronal timing might be explored as a promising therapeutical intervention to restore abnormal spike timing that characterize many neurobiological disorders..

References Costas A Anastassiou, Rodrigo Perin, Henry Markram, and Christof Koch. Ephaptic coupling of cortical neurons. Nature neuroscience, 14(2):217–223, 2011. György Buzsáki, Costas A Anastassiou, and Christof Koch. The origin of extracellular fields and currents - eeg, ecog, lfp and spikes. Nature reviews neuroscience, 13(6): 407–420, 2012.

Flavio Fröhlich and David A McCormick. Endogenous electric fields may guide neocortical network activity. Neuron, 67(1):129–143, 2010. Oscar Herreras. Local field potentials: Myths and misunderstandings. Frontiers in Neural Circuits, 10, 2016. Yoshinao Kajikawa and Charles E Schroeder. How local is the local field potential? Neuron, 72(5):847–858, 2011.

Lisa Marshall, Halla Helgadóttir, Matthias Mölle, and Jan Born. Boosting slow oscillations during sleep potentiates memory. Nature, 444(7119):610–613, 2006. Marcello Massimini, Reto Huber, Fabio Ferrarelli, Sean Hill, and Giulio Tononi. The sleep slow oscillation as a traveling wave. Journal of Neuroscience, 24(31):6862–6870, 2004. Ramon Reig and Maria V Sanchez-Vives. Synaptic transmission and plasticity in an active cortical network. PLoS One, 2(8):e670, 2007. Ramon Reig, Roberto Gallego, Lionel G Nowak, and Maria V Sanchez-Vives. Impact of cortical network activity on short-term synaptic depression. Cerebral Cortex, 16(5): 688–695, 2006. Marcel Ruiz-Mejias, Laura Ciria-Suarez, Maurizio Mattia, and Maria V Sanchez-Vives. Slow and fast rhythms generated in the cerebral cortex of the anesthetized mouse. Journal of neurophysiology, 106(6):2910–2921, 2011. Mircea Steriade, A Nunez, and F Amzica. A novel slow ( <1 hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. Journal of neuroscience, 13(8):3252–3265, 1993. Bartosz Telen´ czuk, Nima Dehghani, Michel Le Van Quyen, Sydney S Cash, Eric Halgren, Nicholas G Hatsopoulos, and Alain Destexhe. Local field potentials primarily reflect inhibitory neuron activity in human and monkey cortex. Scientific Reports, 7:40211, 2017. Lulu Xie, Hongyi Kang, Qiwu Xu, Michael J Chen, Yonghong Liao, Meenakshisundaram Thiyagarajan, John OâA˘ Z´ Donnell, Daniel J Christensen, Charles Nicholson, Jeffrey J Iliff, et al. Sleep drives metabolite clearance from the adult brain. science, 342(6156): 373–377, 2013.