The efficacy of transcranial current stimulation techniques to modulate resting-state EEG, to affect vigilance and to promote sleepiness

Transcranial Current Stimulations (tCSs) are non-invasive brain stimulation techniques which modulate cortical excitability and spontaneous brain activity by the application of weak electric currents through the scalp, in a safe, economic, and well-tolerated manner. The direction of the cortical effects mainly depend on the polarity and the waveform of the applied current. The aim of the present work is to provide a broad overview of recent studies in which tCS has been applied to modulate sleepiness, sleep, and vigilance, evaluating the efficacy of different stimulation techniques and protocols. In recent years, there has been renewed interest in these stimulations and their ability to affect arousal and sleep dynamics. Furthermore, we critically review works that, by means of stimulating sleep/vigilance patterns, in the sense of enhancing or disrupting them, intended to ameliorate several clinical conditions. The examined literature shows the efficacy of tCSs in modulating sleep and arousal pattern, likely acting on the top-down pathway of sleep regulation. Finally, we discuss the potential application in clinical settings of this neuromodulatory technique as a therapeutic tool for pathological conditions characterized by alterations in sleep and arousal domains and for sleep disorders per se

Relating Alpha Power and Phase to Population Firing and Hemodynamic Activity Using a Thalamo-cortical Neural Mass Model

Oscillations are ubiquitous phenomena in the animal and human brain. Among them, the alpha rhythm in human EEG is one of the most prominent examples. However, its precise mechanisms of generation are still poorly understood. It was mainly this lack of knowledge that motivated a number of simultaneous electroencephalography (EEG) – functional magnetic resonance imaging (fMRI) studies. This approach revealed how oscillatory neuronal signatures such as the alpha rhythm are paralleled by changes of the blood oxygenation level dependent (BOLD) signal. Several such studies revealed a negative correlation between the alpha rhythm and the hemodynamic BOLD signal in visual cortex and a positive correlation in the thalamus. In this study we explore the potential generative mechanisms that lead to those observations. We use a bursting capable Stefanescu-Jirsa 3D (SJ3D) neural-mass model that reproduces a wide repertoire of prominent features of local neuronal-population dynamics. We construct a thalamo-cortical network of coupled SJ3D nodes considering excitatory and inhibitory directed connections. The model suggests that an inverse correlation between cortical multi-unit activity, i.e. the firing of neuronal populations, and narrow band local field potential oscillations in the alpha band underlies the empirically observed negative correlation between alpha-rhythm power and fMRI signal in visual cortex. Furthermore the model suggests that the interplay between tonic and bursting mode in thalamus and cortex is critical for this relation. This demonstrates how biophysically meaningful modelling can generate precise and testable hypotheses about the underpinnings of large-scale neuroimaging signals

Relating Alpha Power and Phase to Population Firing and Hemodynamic Activity Using a Thalamo-cortical Neural Mass Model

International audienceOscillations are ubiquitous phenomena in the animal and human brain. Among them, the alpha rhythm in human EEG is one of the most prominent examples. However, its precise mechanisms of generation are still poorly understood. It was mainly this lack of knowledge that motivated a number of simultaneous electroencephalography (EEG) – functional magnetic resonance imaging (fMRI) studies. This approach revealed how oscillatory neuronal signatures such as the alpha rhythm are paralleled by changes of the blood oxygenation level dependent (BOLD) signal. Several such studies revealed a negative correlation between the alpha rhythm and the hemodynamic BOLD signal in visual cortex and a positive correlation in the thalamus. In this study we explore the potential generative mechanisms that lead to those observations. We use a bursting capable Stefanescu-Jirsa 3D (SJ3D) neural-mass model that reproduces a wide repertoire of prominent features of local neuronal-population dynamics. We construct a thalamo-cortical network of coupled SJ3D nodes considering excitatory and inhibitory directed connections. The model suggests that an inverse correlation between cortical multi-unit activity, i.e. the firing of neuronal populations , and narrow band local field potential oscillations in the alpha band underlies the empirically observed negative correlation between alpha-rhythm power and fMRI signal in visual cortex. Furthermore the model suggests that the interplay between tonic and bursting mode in thalamus and cortex is critical for this relation. This demonstrates how biophysically meaningful modelling can generate precise and testable hypotheses about the underpinnings of large-scale neuroimaging signals

Modeling biophysical and neural circuit bases for core cognitive abilities evident in neuroimaging patterns: hippocampal mismatch, mismatch negativity, repetition positivity, and alpha suppression of distractors

This dissertation develops computational models to address outstanding problems in the domain of expectation-related cognitive processes and their neuroimaging markers in functional MRI or EEG. The new models reveal a way to unite diverse phenomena within a common framework focused on dynamic neural encoding shifts, which can arise from robust interactive effects of M-currents and chloride currents in pyramidal neurons. By specifying efficient, biologically realistic circuits that achieve predictive coding (e.g., Friston, 2005), these models bridge among neuronal biophysics, systems neuroscience, and theories of cognition. Chapter one surveys data types and neural processes to be examined, and outlines the Dynamically Labeled Predictive Coding (DLPC) framework developed during the research. Chapter two models hippocampal prediction and mismatch, using the DLPC framework. Chapter three presents extensions to the model that allow its application for modeling neocortical EEG genesis. Simulations of this extended model illustrate how dynamic encoding shifts can produce Mismatch Negativity (MMN) phenomena, including pharmacological effects on MMN reported for humans or animals. Chapters four and five describe new modeling studies of possible neural bases for alpha-induced information suppression, a phenomenon associated with active ignoring of stimuli. Two models explore the hypothesis that in simple rate-based circuits, information suppression might be a robust effect of neural saturation states arising near peaks of resonant alpha oscillations. A new proposal is also introduced for how the basal ganglia may control onset and offset of alpha-induced information suppression. Although these rate models could reproduce many experimental findings, they fell short of reproducing a key electrophysiological finding: phase-dependent reduction in spiking activity correlated with power in the alpha frequency band. Therefore, chapter five also specifies how a DLPC model, adapted from the neocortical model developed in chapter three, can provide an expectation-based model of alpha-induced information suppression that exhibits phase-dependent spike reduction during alpha-band oscillations. The model thus can explain experimental findings that were not reproduced by the rate models. The final chapter summarizes main theses, results, and basic research implications, then suggests future directions, including expanded models of neocortical mismatch, applications to artificial neural networks, and the introduction of reward circuitry

Generative modelling of the thalamo-cortical circuit mechanisms underlying the neurophysiological effects of ketamine

Cortical recordings of task-induced oscillations following subanaesthetic ketamine administration demonstrate alterations in amplitude, including increases at high-frequencies (gamma) and reductions at low frequencies (theta, alpha). To investigate the population-level interactions underlying these changes, we implemented a thalamo-cortical model (TCM) capable of recapitulating broadband spectral responses. Compared with an existing cortex-only 4-population model, Bayesian Model Selection preferred the TCM. The model was able to accurately and significantly recapitulate ketamine-induced reductions in alpha amplitude and increases in gamma amplitude. Parameter analysis revealed no change in receptor time-constants but significant increases in select synaptic connectivity with ketamine. Significantly increased connections included both AMPA and NMDA mediated connections from layer 2/3 superficial pyramidal cells to inhibitory interneurons and both GABAA and NMDA mediated within-population gain control of layer 5 pyramidal cells. These results support the use of extended generative models for explaining oscillatory data and provide in silico support for ketamine's ability to alter local coupling mediated by NMDA, AMPA and GABA-A

Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex

Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio

Alpha and gamma-band oscillations in MEG-data: networks, function and development

Die Adoleszenz, d.h. die Reifungsphase des Jugendlichen zum Erwachsenen, stellt einen zentralen Abschnitt in der menschlichen Entwicklung dar, der mit tief greifenden emotionalen und kognitiven Veränderungen verbunden ist. Neure Studien (Bunge et al., 2002; Durston et al., 2002; Casey et al., 2005; Crone et al., 2006; Bunge and Wright, 2007) machen deutlich, dass sich die funktionelle Architektur des Gehirns während der Adoleszenz grundlegend verändert und dass diese Veränderungen mit der Reifung höherer kognitiven Funktionen in der Adoleszenz assoziiert sein könnten. Messungen des Gehirn-Volumens mit Hilfe der Magnet-Resonanz-Tomographie (MRT) zum Beispiel zeigen eine nicht-lineare Reduktion der grauen und eine Zunahme der weißen Substanz während der Adoleszenz (Giedd et al., 1999; Sowell et al., 1999, 2003). Des weiteren treten in dieser Zeit Veränderungen in exzitatorischen und inhibitorischen Neurotransmitter-Systemen auf (Tseng and O’Donnell, 2005; Hashimoto et al., 2009). Zusammen deuten diese Ergebnisse darauf hin, dass während der Adoleszenz ein Umbau der kortikalen Netzwerke stattfindet, der wichtige Konsequenzen für die Reifung neuronaler Oszillationen haben könnte. Im Anschluss an eine Einführung im Kapitel 2, fasst Kapitel 3 der vorliegenden Dissertation die Vorbefunde bezüglich entwicklungsbedingter Veränderungen in der Amplitude, Frequenz und Synchronisation neuronaler Oszillationen zusammen und diskutiert den Zusammenhang zwischen der Entwicklung neuronaler Oszillationen und der Reifung höhere kognitiver Funktionen während der Adoleszenz. Ebenso werden die anatomischen und physiologischen Mechanismen, die diesen Veränderungen möglicherweise zu Grunde liegen könnten, theoretisch vorgestellt. Die in Kapitel 4-6 vorgestellten eigenen empirischen Arbeiten untersuchen neuronale Oszillationen mit Hilfe der Magnetoencephalographie (MEG), um die Frequenzbänder und die funktionellen Netzwerke zu charakterisieren, die mit höheren kognitiven Prozessen und deren Entwicklung in der Adoleszenz assoziiert sind. Hierzu wurden drei Experimente durchgeführt, bei denen MEG-Aktivität während der Bearbeitung einer Arbeitsgedächtnisaufgabe und im Ruhezustand aufgezeichnet wurde. Die Ergebnisse dieser Experimente zeigen, dass Alpha Oszillationen und Gamma-Band Aktivität sowohl task-abhängig als auch im Ruhezustand gemeinsam auftreten. Darüber hinaus ergänzen die vorliegenden Untersuchungen Vorarbeiten, indem sie eine Wechselwirkung zwischen beiden Frequenzbändern aufgezeigt wird, die als ein Mechanismus für das gezielte Weiterleiten von Informationen dienen könnte. Die in Kapitel 6 vorgestellten Entwicklungsdaten weisen weiterhin darauf, dass in der Adoleszenz späte Veränderungen im Alpha und Gamma-Band stattfinden und dass diese Veränderungen involviert sind in die Entwicklung der Arbeitsgedächtnis-Kapazität und die Entwicklung der Fähigkeit, Distraktoren zu inhibieren. Abschliessend werden in Kapitel 7, die in dieser Dissertation vorgestellten Arbeiten, aus einer übergeordneten Perspektive im Gesamtzusammenhang diskutiert

Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation Is State-Dependent

Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1) stimulation enhanced the targeted oscillation power, (2) this enhancement outlasted stimulation, and (3) the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms

Anesthetic action on the transmission delay between cortex and thalamus explains the beta-buzz observed under propofol anesthesia

In recent years, more and more surgeries under general anesthesia have been performed with the assistance of electroencephalogram (EEG) monitors. An increase in anesthetic concentration leads to characteristic changes in the power spectra of the EEG. Although tracking the anesthetic-induced changes in EEG rhythms can be employed to estimate the depth of anesthesia, their precise underlying mechanisms are still unknown. A prominent feature in the EEG of some patients is the emergence of a strong power peak in the β–frequency band, which moves to the α–frequency band while increasing the anesthetic concentration. This feature is called the beta-buzz. In the present study, we use a thalamo-cortical neural population feedback model to reproduce observed characteristic features in frontal EEG power obtained experimentally during propofol general anesthesia, such as this beta-buzz. First, we find that the spectral power peak in the α– and δ–frequency ranges depend on the decay rate constant of excitatory and inhibitory synapses, but the anesthetic action on synapses does not explain the beta-buzz. Moreover, considering the action of propofol on the transmission delay between cortex and thalamus, the model reveals that the beta-buzz may result from a prolongation of the transmission delay by increasing propofol concentration. A corresponding relationship between transmission delay and anesthetic blood concentration is derived. Finally, an analytical stability study demonstrates that increasing propofol concentration moves the systems resting state towards its stability threshold

Shared and unique features of mammalian sleep spindles - insights from new and old animal models.

Sleep spindles are phasic events observed in mammalian non-rapid eye movement sleep. They are relevant today in the study of memory consolidation, sleep quality, mental health and ageing. We argue that our advanced understanding of their mechanisms has not exhausted the utility and need for animal model work. This is both because some topics, like cognitive ageing, have not yet been addressed sufficiently in comparative efforts and because the evolutionary history of this oscillation is still poorly understood. Comparisons across species often are either limited to referencing the classical cat and rodent models, or are over-inclusive, uncritically including reports of sleep spindles in rarely studied animals. In this review, we discuss the emergence of new (dog and sheep) models for sleep spindles and compare the strengths and shortcomings of new and old models based on the three validation criteria for animal models - face, predictive, and construct validity. We conclude that an emphasis on cognitive ageing might dictate the future of comparative sleep spindle studies, a development that is already becoming visible in studies on dogs. Moreover, reconstructing the evolutionary history of sleep spindles will require more stringent criteria for their identification, across more species. In particular, a stronger emphasis on construct and predictive validity can help verify if spindle-like events in other species are actual sleep spindles. Work in accordance with such stricter validation suggests that sleep spindles display more universally shared features, like defining frequency, than previously thought