Nonlinear System Identification of Neural Systems from Neurophysiological Signals

The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a small amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention

Infraslow fluctuations and respiration are driving cortical neurophysiological oscillations during sleep

Abstract. Recently sleep has been linked to increased brain clearance through perivascular spaces from blood-brain barrier (BBB) externa limitans, facilitated by physiological pulsations such as cardiovascular and respiratory pulsations. Infraslow fluctuations (ISFs) characterize both fMRI BOLD signals and scalp EEG potentials. They are associated with both permeability fluctuations of BBB and the amplitude dynamics of faster (> 1Hz) neuronal oscillations. ISF together with respiration are though to synchronize with neural rhythms, however the directionality of these interactions has not been studied before. I used non-invasive measures which are necessary not to interfere the pressure sensitive CSF convection and BBB permeability combined with directional metrics to fully evaluate these relationships. I recorded full-band resting state EEG (fbEEG) during wakefulness and sleep and investigated whether recently shown increased brain clearance during sleep is followed by increased drive of neural amplitudes by the ISF and respiration phases. I show that ISF power increases during non-REM sleep, possibly reflecting altered BBB status. Furthermore, I show that ISF and respiration phase-amplitude couple and predict neuronal brain rhythms seen especially during sleep. These results pave the way for understanding the mechanisms how neuronal activity is modulated by the slow oscillations in human brain during wakefulness and sleep

Methods for analysis of brain connectivity : An IFCN-sponsored review

The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. (C) 2019 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology.Peer reviewe

Probing Binding Interactions of Cytisine Derivatives to the α4β2 Nicotinic Acetylcholine Receptor

Nicotinic acetylcholine receptors (nAChRs) are crucial for communication between synapses in the central nervous system. As such, they are also implicated in several neuropsychiatric and addictive diseases. Cytisine is a partial agonist of some nAChRs and has been used for smoking cessation. Previous studies have established a binding model for several agonists to several nAChR subtypes. Here, we evaluate the extent to which this model applies to cytisine at the α4β2 nAChR, which is a subtype that is known to play a prominent role in nicotine addiction. Along with the commonly seen cation−π interaction and two hydrogen bonds, we find that cytisine makes a second cation−π interaction at the agonist binding site. We also evaluated a series of C(10)-substituted cytisine derivatives, using two-electrode voltage-clamp electrophysiology and noncanonical amino acid mutagenesis. Double-mutant cycle analyses revealed that C(10) substitution generally strengthens the newly established second cation−π interaction, while it weakens the hydrogen bond typically seen to LeuE in the complementary subunit. The results suggest a model for how cytisine derivatives substituted at C(10) (as well as C(9)/C(10)) adjust their binding orientation, in response to pyridone ring substitution

Evolution of Charge-Lattice Dynamics across the Kuramoto Synchronization Phase Diagram of Quantum Tunneling Polarons in Cuprate Superconductors

Because of its sensitivity to the instantaneous structure factor, S(Q,t = 0), Extended X-ray Absorption Fine Structure (EXAFS) is a powerful tool for probing the dynamic structure of condensed matter systems in which the charge and lattice dynamics are coupled. When applied to hole-doped cuprate superconductors, EXAFS has revealed the presence of internal quantum tunneling polarons (IQTPs). An IQTP arises in EXAFS as a two-site distribution for certain Cu–O pairs, which is also duplicated in inelastic scattering but not observed in standard diffraction measurements. The Cu–Sr pair distribution has been found to be highly anharmonic and strongly correlated to both the IQTPs and to superconductivity, as, for example, in YSr2Cu2.75Mo0.25O7.54(Tc=84 K). In order to describe such nontrivial, anharmonic charge-lattice dynamics, we have proposed a model Hamiltonian for a prototype six-atom cluster, in which two Cu-apical-O IQTPs are charge-transfer bridged through Cu atoms by an O atom in the CuO2 plane and are anharmonically coupled via a Sr atom. By applying an exact diagonalization procedure to this cluster, we have verified that our model indeed produces an intricate interplay between charge and lattice dynamics. Then, by using the Kuramoto model for the synchronization of coupled quantum oscillators, we have found a first-order phase transition for the IQTPs into a synchronized, phase-locked phase. Most importantly, we have shown that this transition results specifically from the anharmonicity. Finally, we have provided a phase diagram showing the onset of the phase-locking of IQTPs as a function of the charge-lattice and anharmonic couplings in our model. We have found that the charge, initially confined to the apical oxygens, is partially pumped into the CuO2 plane in the synchronized phase, which suggests a possible connection between the synchronized dynamic structure and high-temperature superconductivity (HTSC) in doped cuprates