Modulating pathological oscillations by rhythmic non-invasive brain stimulation-a therapeutic concept?

Aberrant oscillatory activity in neurofibromatosis type 1: an EEG study of resting state and working memory

BACKGROUND

Neurofibromatosis type 1 (NF1) is a genetic neurodevelopmental disorder commonly associated with impaired cognitive function. Despite the well-explored functional roles of neural oscillations in neurotypical populations, only a limited number of studies have investigated oscillatory activity in the NF1 population.

METHODS

We compared oscillatory spectral power and theta phase coherence in a paediatric sample with NF1 (N = 16; mean age: 13.03 years; female: n = 7) to an age/sex-matched typically developing control group (N = 16; mean age: 13.34 years; female: n = 7) using electroencephalography measured during rest and during working memory task performance.

RESULTS

Relative to typically developing children, the NF1 group displayed higher resting state slow wave power and a lower peak alpha frequency. Moreover, higher theta power and frontoparietal theta phase coherence were observed in the NF1 group during working memory task performance, but these differences disappeared when controlling for baseline (resting state) activity.

CONCLUSIONS

Overall, results suggest that NF1 is characterised by aberrant resting state oscillatory activity that may contribute towards the cognitive impairments experienced in this population.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03310996 (first posted: October 16, 2017).

Resting-state EEG and MEG biomarkers of pathological fatigue - A transdiagnostic systematic review

Fatigue is a highly prevalent and disabling symptom of many disorders and syndromes, resulting from different pathomechanisms. However, whether and how different mechanisms converge and result in similar symptomatology is only partially understood, and transdiagnostic biomarkers that could further the diagnosis and treatment of fatigue are lacking. We, therefore, performed a transdiagnostic systematic review (PROSPERO: CRD42022330113) of quantitative resting-state electroencephalography (EEG) and magnetoencephalography (MEG) studies in adult patients suffering from pathological fatigue in different disorders. Studies investigating fatigue in healthy participants were excluded. The risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semi-quantitative data synthesis was conducted using modified albatross plots. After searching MEDLINE, Web of Science Core Collection, and EMBASE, 26 studies were included. Cross-sectional studies revealed increased brain activity at theta frequencies and decreased activity at alpha frequencies as potential diagnostic biomarkers. However, the risk of bias was high in many studies and domains. Together, this transdiagnostic systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of pathological fatigue. Beyond, this review might help to guide future M/EEG studies on the development of fatigue biomarkers.

Personalized repetitive transcranial magnetic stimulation (prtms®) for post-traumatic stress disorder (ptsd) in military combat veterans

Emerging data suggest that post-traumatic stress disorder (PTSD) arises from disrupted brain default mode network (DMN) activity manifested by dysregulated encephalogram (EEG) alpha oscillations. Hence, we pursued the treatment of combat veterans with PTSD (n = 185) using an expanded form of repetitive transcranial magnetic stimulation (rTMS) termed personalized-rTMS (PrTMS). In this treatment methodology spectral EEG based guidance is used to iteratively optimize symptom resolution via (1) stimulation of multiple motor sensory and frontal cortical sites at reduced power, and (2) adjustments of cortical treatment loci and stimulus frequency during treatment progression based on a proprietary frequency algorithm (PeakLogic, Inc. San Diego) identifying stimulation frequency in the DMN elements of the alpha oscillatory band. Following 4 - 6 weeks of PrTMS® therapy in addition to routine PTSD therapy, veterans exhibited significant clinical improvement accompanied by increased cortical alpha center frequency and alpha oscillatory synchronization. Full resolution of PTSD symptoms was attained in over 50% of patients. These data support DMN involvement in PTSD pathophysiology and suggest a role in therapeutic outcomes. Prospective, sham controlled PrTMS® trials may be warranted to validate our clinical findings and to examine the contribution of DMN targeting for novel preventive, diagnostic, and therapeutic strategies tailored to the unique needs of individual patients with both combat and non-combat PTSD.

Driving Oscillatory Dynamics: Neuromodulation for Recovery After Stroke

Stroke is a leading cause of death and disability worldwide, with limited treatments being available. However, advances in optic methods in neuroscience are providing new insights into the damaged brain and potential avenues for recovery. Direct brain stimulation has revealed close associations between mental states and neuroprotective processes in health and disease, and activity-dependent calcium indicators are being used to decode brain dynamics to understand the mechanisms underlying these associations. Evoked neural oscillations have recently shown the ability to restore and maintain intrinsic homeostatic processes in the brain and could be rapidly deployed during emergency care or shortly after admission into the clinic, making them a promising, non-invasive therapeutic option. We present an overview of the most relevant descriptions of brain injury after stroke, with a focus on disruptions to neural oscillations. We discuss the optical technologies that are currently used and lay out a roadmap for future studies needed to inform the next generation of strategies to promote functional recovery after stroke.

Crossmodal Pattern Discrimination in Humans and Robots: A Visuo-Tactile Case Study

The quality of crossmodal perception hinges on two factors: The accuracy of the independent unimodal perception and the ability to integrate information from different sensory systems. In humans, the ability for cognitively demanding crossmodal perception diminishes from young to old age. Here, we propose a new approach to research to which degree the different factors contribute to crossmodal processing and the age-related decline by replicating a medical study on visuo-tactile crossmodal pattern discrimination utilizing state-of-the-art tactile sensing technology and artificial neural networks (ANN). We implemented two ANN models to specifically focus on the relevance of early integration of sensory information during the crossmodal processing stream as a mechanism proposed for efficient processing in the human brain. Applying an adaptive staircase procedure, we approached comparable unimodal classification performance for both modalities in the human participants as well as the ANN. This allowed us to compare crossmodal performance between and within the systems, independent of the underlying unimodal processes. Our data show that unimodal classification accuracies of the tactile sensing technology are comparable to humans. For crossmodal discrimination of the ANN the integration of high-level unimodal features on earlier stages of the crossmodal processing stream shows higher accuracies compared to the late integration of independent unimodal classifications. In comparison to humans, the ANN show higher accuracies than older participants in the unimodal as well as the crossmodal condition, but lower accuracies than younger participants in the crossmodal task. Taken together, we can show that state-of-the-art tactile sensing technology is able to perform a complex tactile recognition task at levels comparable to humans. For crossmodal processing, human inspired early sensory integration seems to improve the performance of artificial neural networks. Still, younger participants seem to employ more efficient crossmodal integration mechanisms than modeled in the proposed ANN. Our work demonstrates how collaborative research in neuroscience and embodied artificial neurocognitive models can help to derive models to inform the design of future neurocomputational architectures.

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics

OBJECTIVE

Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulation interacts with endogenous neural activity as a function of the brain state and target.

APPROACH

To address this critical issue, we applied periodic stimulation to a unified biophysical thalamic network model that generates multiple distinct oscillations, and examined thoroughly the impact of rhythmic stimulation on different oscillatory states.

MAIN RESULTS

We found that rhythmic perturbation induces four basic response mechanisms: entrainment, acceleration, resonance and suppression. Importantly, the appearance and expression of these mechanisms depend highly on the intrinsic cellular dynamics in each state. Specifically, the low-threshold bursting of thalamocortical cells (TCs) in delta (δ) oscillation renders the network relatively insensitive to entrainment; the high-threshold bursting of TCs in alpha (α) oscillation leads to widespread oscillation suppression while the tonic spiking of TC cells in gamma (γ) oscillation results in prominent entrainment and resonance. In addition, we observed entrainment discontinuity during α oscillation that is mediated by firing pattern switching of high-threshold bursting TC cells. Furthermore, we demonstrate that direct excitatory stimulation of the lateral geniculate nucleus (LGN) entrains thalamic oscillations via an asymmetric Arnold tongue that favors higher frequency entrainment and resonance, while stimulation of the inhibitory circuit, the reticular nucleus, induces much weaker and more symmetric entrainment and resonance. These results support the notion that rhythmic stimulation engages brain oscillations in a state- and target-dependent manner.

SIGNIFICANCE

Overall, our study provides, for the first time, insights into how the biophysics of thalamic oscillations guide the emergence of complex, state-dependent mechanisms of target engagement, which can be leveraged for the future rational design of novel therapeutic stimulation modalities.

Modulating functional connectivity after stroke with neurofeedback: Effect on motor deficits in a controlled cross-over study

Synchronization of neural activity as measured with functional connectivity (FC) is increasingly used to study the neural basis of brain disease and to develop new treatment targets. However, solid evidence for a causal role of FC in disease and therapy is lacking. Here, we manipulated FC of the ipsilesional primary motor cortex in ten chronic human stroke patients through brain-computer interface technology with visual neurofeedback. We conducted a double-blind controlled crossover study to test whether manipulation of FC through neurofeedback had a behavioral effect on motor performance. Patients succeeded in increasing FC in the motor cortex. This led to improvement in motor function that was significantly greater than during neurofeedback training of a control brain area and proportional to the degree of FC enhancement. This result provides evidence that FC has a causal role in neurological function and that it can be effectively targeted with therapy.

•

Stroke patients participated in clinical trial on neurofeedback of functional connectivity.

•

Patients learned to enhance synchrony of neural activity in their motor cortex.

•

This led to reduced motor impairment.

•

Evidence for a causal role of neural synchrony in neurological deficits and recovery.

The therapeutic use of non-invasive brain stimulation in multiple sclerosis - a review

BACKGROUND

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system and a leading cause of disability in young adults. Many disabling symptoms in MS, such as spasticity, pain, depression and cognitive deficits are not fully controlled by drug treatment. Non-invasive brain stimulation (NIBS) techniques can be used as tools for modulating altered cortical excitability and plasticity MS patients, providing an improvement in disabling symptoms affecting such patients.

OBJECTIVE

This review reported and summarized some of the most interesting and promising recent achievements regarding the therapeutic use of NIBS in MS patients.

METHODS

We reviewed the clinical application of transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), emphasizing their effect on clinical symptoms and signs that are commonly involved in MS patients. In addition, we shortly described new NIBS protocols, such as transcranial alternating current stimulation and transcranial focused ultrasound stimulation as potential and innovative therapeutic options to be applied in future studies in MS patients.

RESULTS

We reviewed twenty-one studies covering six main clinical domains. Most of such studies focused on fatigues (33.3%), motor performance (19%) and spasticity (19%), sparse results were about pain (9.5%), cognitive abilities (9.5%), sensory deficit (4.8%) and bladder function (4.8%). The most promising results have been published for the improvement of motor (i.e. hand dexterity) and cognitive performances (i.e. attention and working memory) by applying rTMS or tDCS alone or in association with motor/cognitive training, for pain's treatment by using tDCS.

CONCLUSION

There are still no official recommendations for the therapeutic use of tDCS or rTMS in MS. The huge inter-individual variability of NIBS efficacy is still a big challenge which needs to be solved. However, well-designed studies, deeper knowledge about pathomechanisms underlying MS, and the combination of such techniques with motor and cognitive rehabilitation might results in higher effectiveness of NIBS.

Brain oscillations reveal impaired novelty detection from early stages of Parkinson's disease

The identification of reliable biomarkers for early diagnosis and progression tracking of neurodegenerative diseases has become an important objective in clinical neuroscience in the last years. The P3a event-related potential, considered as the neurophysiological hallmark of novelty detection, has been shown to be reduced in Parkinson's disease (PD) and proposed as a sensitive measure for illness duration and severity. Our aim for this study was to explore for the first time whether impaired novelty detection could be observed through phase- and time-locked brain oscillatory activity at early PD. Twenty-seven patients with idiopathic PD at early stages (disease duration <5 years and Hoehn and Yahr stage <3) were included. A healthy control group (n = 24) was included as well. All participants performed an auditory involuntary attention task including frequent and deviant tones while a digital EEG was obtained. A neuropsychological battery was administered as well. Time-frequency representations of power and phase-locked oscillations and P3a amplitudes were compared between groups. We found a significant reduction of power and phase locking of slow oscillations (3-7 Hz) for deviant tones in the PD group compared to controls in the P3a time range (300-550 ms). Also, reduced modulation of late induced (not phase locked) alpha-beta oscillations (400-650 ms, 8-25 Hz) was observed in the PD group after deviant tones onset. The P3a amplitude was predicted by years of evolution in the PD group. Finally, while phase-locked slow oscillations were associated with task behavioral distraction effects, induced alpha-beta activity was related to cognitive flexibility performance. Our results show that novelty detection impairment can be identified in neurophysiological terms from very early stages of PD, and such impairment increases linearly as the disease progresses. Also, induced alpha-beta oscillations underlying novelty detection are related to executive functioning.

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation

The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh) and norepinephrine (NE) and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations) that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.

Computational modeling has served as an important tool to understand the cellular and circuit mechanisms of thalamocortical oscillations. However, most of the existing thalamic models focus on only one particular oscillatory pattern such as alpha or spindle oscillations. Thus, it remains unclear whether the same thalamic circuitry on its own could generate all major oscillatory patterns and if so what mechanisms underlie the transition among these distinct states. Here we present a unified model of the thalamus that is capable of independently generating multiple distinct oscillations corresponding to different physiological conditions. We then mapped out the different thalamic oscillations by varying the ACh/NE modulatory level and input level systematically. Our simulation results offer a mechanistic understanding of thalamic oscillations and support the long standing notion of a thalamic “pacemaker”. It also suggests that pathological oscillations associated with neurological and psychiatric disorders may stem from malfunction of the thalamic circuitry.

[The importance of neuronal networks for motor rehabilitation after a stroke]

Every year in Europe 1.5 million patients suffer a new stroke. Despite the further developments in acute therapy with nationwide stroke units, thrombolysis, thrombectomy and post-acute neurorehabilitation, only a small proportion of patients recover to a satisfactory degree allowing them to return to their normal social and professional life. This makes stroke the main cause of long-term disability with a corresponding impact on patient lives, socioeconomics and the healthcare system. Thus, the concepts of neurorehabilitation have to be extended to enhance the effects of rehabilitative treatment strategies. To achieve this, an understanding of the prediction of the course of recovery, the mechanisms underlying functional recovery and factors influencing recovery have to be enhanced for the development towards patient-tailored precision medicine approaches. A central point towards this is the understanding of stroke as a disease, which not only influences the damaged area but also the associated network. This is crucial for the understanding of the stroke-induced deficits, for prediction of recovery and options for interventional treatment strategies, which can target different areas in this network (e.g. primary motor cortex and secondary motor regions) based on individual factors of the patient. The present article discusses the importance of network alterations for motor neurorehabilitation after a stroke and which novel options, concepts and consequences could arise from this for neurorehabilitation.

Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation

Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson's disease (PD), Alzheimer's disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets.