Christoph Zrenner

Order-Based Representation in Random Networks of Cortical Neurons

The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

Neuronal Response Clamp

Responses of individual neurons to ongoing input are highly variable, reflecting complex threshold dynamics. Experimental access to this threshold dynamics is required in order to fully characterize neuronal input–output relationships. The challenge is practically intractable using present day experimental paradigms due to the cumulative, non-linear interactions involved. Here we introduce the Neuronal Response Clamp, a closed-loop technique enabling control over the instantaneous response probability of the neuron. The potential of the technique is demonstrated by showing direct access to threshold dynamics of cortical neuron in vitro using extracellular recording and stimulation, over timescales ranging from seconds to many hours. Moreover, the method allowed us to expose the sensitivity of threshold dynamics to spontaneous input from the network in which the neuron is embedded. The Response-Clamp technique follows the rationale of the voltage-clamp and dynamic-clamp approaches, extending it to the neurons spiking behavior. The general framework offered here is applicable in the study of other neural systems, beyond the single neuron level.

Closed-Loop Neuroscience and Non-Invasive Brain Stimulation: A Tale of Two Loops

Closed-loop neuroscience is receiving increasing attention with recent technological advances that enable complex feedback loops to be implemented with millisecond resolution on commodity hardware. We summarize emerging conceptual and methodological frameworks that are available to experimenters investigating a “brain in the loop” using non-invasive brain stimulation and briefly review the experimental and therapeutic implications. We take the view that closed-loop neuroscience in fact deals with two conceptually quite different loops: a “brain-state dynamics” loop, used to couple with and modulate the trajectory of neuronal activity patterns, and a “task dynamics” loop, that is the bidirectional motor-sensory interaction between brain and (simulated) environment, and which enables goal-directed behavioral tasks to be incorporated. Both loops need to be considered and combined to realize the full experimental and therapeutic potential of closed-loop neuroscience.

A generic framework for real-time multi-channel neuronal signal analysis, telemetry control, and sub-millisecond latency feedback generation.

Distinct modules of the neural circuitry interact with each other and (through the motor-sensory loop) with the environment, forming a complex dynamic system. Neuro-prosthetic devices seeking to modulate or restore CNS function need to interact with the information flow at the level of neural modules electrically, bi-directionally and in real-time. A set of freely available generic tools is presented that allow computationally demanding multi-channel short-latency bi-directional interactions to be realized in in vivo and in vitro preparations using standard PC data acquisition and processing hardware and software (Mathworks Matlab and Simulink). A commercially available 60-channel extracellular multi-electrode recording and stimulation set-up connected to an ex vivo developing cortical neuronal culture is used as a model system to validate the method. We demonstrate how complex high-bandwidth (>10 MBit/s) neural recording data can be analyzed in real-time while simultaneously generating specific complex electrical stimulation feedback with deterministically timed responses at sub-millisecond resolution.

Modeling TMS-induced I-waves in human motor cortex

Despite many years of research, it is still unknown how exactly transcranial magnetic stimulation activates cortical circuits. A recent computational model by Rusu et al. (2014) has attempted to shed light on potential underlying mechanisms and has successfully explained key experimental findings on I-wave physiology. Here, we critically discuss this model, point out some of its shortcomings, and suggest a number of extensions that may be necessary for it to capture additional existing and emerging data on the physiology of I-waves.

Therapeutischer Einsatz von Closed-loop-Hirnstimulation

The therapeutic application of brain stimulation is still limited to relatively few indications and small groups of patients due to variable efficacy. Individualization of stimulation parameters by employing a closed-loop system, i.e. synchronization of stimulation with endogenous brain activity with millisecond precision, has the potential to significantly improve the therapeutic efficacy when compared to open-loop systems. In this article the theoretical and experimental results are reviewed including first clinical trials that support the superiority of closed-loop brain stimulation, fundamental aspects in the development of closed loop methods are discussed and clinical studies which could quantify an increase in effectiveness are summarized. A significant increase in the indications for therapeutic applications of closed-loop systems is to be expected in the near future.ZusammenfassungDer therapeutische Einsatz von Hirnstimulation blieb bisher, bedingt durch eine hohe Variabilität der Wirksamkeit, auf wenige Indikationen und kleine Patientengruppen limitiert. Eine Individualisierung der Stimulationsparameter innerhalb eines Closed-loop-Systems, welches die Stimulation mit einer Auflösung von wenigen Millisekunden mit der Hirnaktivität synchronisiert, hat das Potenzial, die therapeutische Effektivität gegenüber traditionellen Open-loop-Ansätzen relevant zu erhöhen. In diesem Beitrag werden theoretische und experimentelle Ergebnisse vorgestellt, die für einen Closed-loop-Ansatz sprechen, und es werden grundlegende Aspekte bei der Entwicklung einer Closed-loop-Methode diskutiert sowie klinische Arbeiten, welche eine Effektivitätssteigerung quantifizieren konnten, kurz zusammengefasst. Eine deutliche Ausweitung der Indikationen einer therapeutischen Hirnstimulation in der klinischen Praxis ist mit der zukünftigen weiteren Entwicklung von Closed-loop-Methoden zu erwarten.SummaryThe therapeutic application of brain stimulation is still limited to relatively few indications and small groups of patients due to variable efficacy. Individualization of stimulation parameters by employing a closed-loop system, i.e. synchronization of stimulation with endogenous brain activity with millisecond precision, has the potential to significantly improve the therapeutic efficacy when compared to open-loop systems. In this article the theoretical and experimental results are reviewed including first clinical trials that support the superiority of closed-loop brain stimulation, fundamental aspects in the development of closed loop methods are discussed and clinical studies which could quantify an increase in effectiveness are summarized. A significant increase in the indications for therapeutic applications of closed-loop systems is to be expected in the near future.

Alpha-Synchronized Stimulation of the Dorsolateral Prefrontal Cortex (DLPFC) in Major Depression: A Proof-of-Principle EEG-TMS Study

High-frequency repetitive transcranial magnetic stimulation (rTMS) of the left dorsolateral prefrontal cortex (DLPFC) shows therapeutic potential in pharmaco-resistant patients with major depression. However, clinical efficacy is limited by high inter-individual variability and low response rates. One possible strategy to improve the effect size and consistency may be brain state dependent brain stimulation, i.e. coupling of TMS pulses to the endogenous brain states as reflected by the instantaneous oscillatory brain activity. Here we present findings from a proof-of-principle study of alpha-oscillation synchronized brain stimulation of the frontal cortex in patients with major depression (BOSSFRONT). Repetitive stimulation consistently on the negative peak of ongoing alpha activity in left DLPFC, but not brain state independent intermittent theta-burst stimulation (iTBS), resulted in suppression of resting-state alpha activity in left DLPFC and an increase in TMS-induced beta activity. Findings show that alpha-synchronized rTMS of left DLPFC is both feasible and safe, and suggest that it interferes with frontal brain networks important in the pathophysiology of major depression.

μ-rhythm extracted with personalized EEG filters correlates with corticospinal excitability in real-time phase-triggered EEG-TMS

Ongoing brain activity has been implicated in the modulation of cortical excitability. The combination of electroencephalography (EEG) and transcranial magnetic stimulation (TMS) in a real-time triggered setup is a novel method for testing hypotheses about the relationship between spontaneous neuronal oscillations, cortical excitability, and synaptic plasticity. For this method, a reliable real-time extraction of the neuronal signal of interest from scalp EEG with high signal-to-noise ratio (SNR) is of crucial importance. Here we compare individually tailored spatial filters as computed by spatial-spectral decomposition (SSD), which maximizes SNR in a frequency band of interest, against established local C3-centered Laplacian filters for the extraction of the sensorimotor μ-rhythm. Single-pulse TMS over the left primary motor cortex was synchronized with the surface positive or negative peak of the respective extracted signal, and motor evoked potentials (MEP) were recorded with electromyography (EMG) of a contralateral hand muscle. Both extraction methods led to a comparable degree of MEP amplitude modulation by phase of the sensorimotor μ-rhythm at the time of stimulation. This could be relevant for targeting other brain regions with no working benchmark such as the local C3-centered Laplacian filter, as sufficient SNR is an important prerequisite for reliable real-time single-trial detection of EEG features.

Brain-State Dependent Stimulation in Human Motor Cortex for Plasticity Induction Using EEG-TMS

Non-invasive motor cortex stimulation may result in long-term potentiation (LTP)-like plasticity of corticospinal excitability, and this may be useful to support neurorehabilitation after lesion, such as in stroke. However, the reported plasticity effects show large interindividual variability, and even intraindividual reliability is moderate at best. One possible strategy to improve size effect and consistency is to couple pulsed transcranial magnetic stimulation (TMS) to the endogenous brain state. We show here that instantaneous brain states measured with EEG have significant impact on TMS-induced corticospinal excitability. Consistent stimulation on the negative peak of the ongoing µ-rhythm results in LTP-like plasticity in 21/23 subjects, while stimulation at the positive peak had no effect. Findings raise the intriguing possibility that real-time information of instantaneous brain state can be utilized to control efficacy of plasticity induction in humans, and this may be utilized in clinical settings to support therapeutic reorganization of brain networks.

PB13. Is 0.9 Hz rTMS-induced LTD-like corticospinal plasticity dependent on μ-rhythm phase during the intervention?

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive method to stimulate the human brain. It is capable of inducing plasticity and altering the state of the brain. The method is widely used by clinicians and neuroscientists alike and has increasing experimental, diagnostic and therapeutic applications. Yet so far, it often suffers from a considerable variability and low effect size. Low-frequency rTMS of the primary motor cortex at near 1 Hz (0.9 Hz) induced long-term depression (LTD)-like effects on corticospinal excitability (Chen et al., 1997). It was recently demonstrated that corticospinal excitability as well as induction of long-term potentiation (LTP)-like plasticity effects depend on the phase of the 8–12 Hz alpha oscillation of the somatosensory cortex ( μ -alpha oscillation) at the time of stimulation. LTP-like corticospinal plasticity resulted from real-time EEG-triggered 100 Hz burst rTMS during the negative but not positive peak of the μ -alpha oscillation (Zrenner et al., under revision). Since LTD-like plasticity of near 1 Hz rTMS was examined in random phase (‘open loop’) rTMS protocols only so far, it is unknown, whether the observed effect is dependent on a phase of the μ -alpha oscillation and by which phase it might be controlled. Here we address this question using a real-time EEG-triggered TMS set-up. Motor evoked potentials (MEPs) are recorded from right hand muscles before and after a phase-triggered 15-min 0.9 Hz rTMS intervention in a double-blind randomized cross-over design: Each subject will undergo three phase conditions in the 0.9 Hz intervention: (1) random phase stimulation, (2) stimulation triggered by the EEG positive peak and (3) stimulation triggered by the negative peak of the ongoing μ -rhythm. The results of this study will show whether μ -oscillation phase modules LTD-like corticospinal excitability induced by rTMS near 1 Hz. They will have substantial implications for understanding the neurophysiology underlying plasticity induction and for the development of personalized EEG-triggered stimulation protocols. The project is currently ongoing. The results will be presented at the conference.