Brain Stimulation Can Improve Prognosis Following a Stroke and Other Neurological Diseases

Roland Fath

March 28, 2023

HAMBURG, Germany – Around 86 billion nerve cells in our brain work together in complex dynamic networks to control almost every sensorimotor and cognitive process. However, the way in which the information is processed in the different regions of the brain is still unclear. There are already some promising approaches to specifically influence the dynamics of neuronal networks to treat neurological and psychiatric diseases.

One of the main topics at the Congress for Clinical Neuroscience of the German Society for Clinical Neurophysiology and Functional Neuroimaging (DGKN), recently held in Hamburg, Germany, was the dynamics of cerebral networks in sensorimotor and cognitive processes, as well as disruptions to network dynamics in neurological and psychiatric diseases.

"We will be unable to develop innovative therapies for widespread neurological and psychiatric diseases until we understand neuronal functions on every level of complexity," said Prof. Andreas K. Engel, PhD, director of the Institute for Neurophysiology and Pathophysiology at the University Hospital of Hamburg-Eppendorf, president of the DGKN, and congress president, during an online press conference.

Characterizing States of Consciousness

For more than 30 years, it has been known that neuronal signals in the brain are dynamically coupled. Despite intensive research, the functional significance of this coupling on information processing is still largely unknown.

Neuroimaging methods such as electroencephalography (EEG), magnetoencephalography (MEG), structural and functional magnetic resonance imaging (MRI), and electrophysiological examinations were used. Model calculations of the data suggest that dynamic couplings of signals in the cortex play a crucial role in memory performance, thinking processes, and developing perception, among other things.

It has already been shown that the network dynamics of neuronal signals could possibly characterize states of consciousness. Neuronal signals and coupling patterns differ significantly between healthy individuals in a waking state and those who are asleep, under general anesthetic, or in a vegetative state. In Engel's view, it may be possible in the future for machine learning algorithms to be used to classify states of consciousness.

Changes in Brain Activity as a Biomarker?

The differences in the dynamics of neuronal signals between healthy individuals and patients with psychiatric diseases such as schizophrenia appear much more important for clinical practice. "The characteristic changes in brain activity in the primary auditory cortex could be considered a potential biomarker and used to predict the clinical course of psychiatric diseases, such as psychoses," reported Engel.

The gamma-band activity in the auditory cortex could be a potential marker for schizophrenia. According to MEG examinations, the values are decreased both in people at increased risk of psychosis and experiencing first symptoms compared with controls.

Activation or Inhibition of Cerebral Networks as New Therapeutic Approaches

New therapeutic approaches based on the activation or inhibition of cerebral networks are currently areas of intensive research. Close interdisciplinary collaboration between basic science researchers and clinicians is necessary, stressed Engel. The use of noninvasive brain stimulation is already within reach for the neurorehabilitation of stroke patients. "I am optimistic that in a few years brain stimulation will be established as an integral element of stroke therapy," said Prof. Christian Grefkes-Hermann, MD, PhD, director of the Department of Neurology at the University Hospital of Frankfurt and first vice president of the DGKN.

Despite great advances in acute stroke therapy, many patients must endure permanent deficits in their everyday life, he said. According to Grefkes-Hermann, rehabilitation procedures often have a dissatisfactory effect, and results greatly vary. He hopes that in the future it may be possible to personalize therapy by using network patterns, thereby improving results.

The aim is to reorganize areas of the brain in which the network activity has been disrupted following a stroke using targeted transcranial magnetic stimulation (TMS). "The most important factor for functional recovery after a stroke is neuronal reorganization," said Grefkes-Hermann. With the new methods of neurorehabilitation, network-connectivity disruptions, which are associated with motor function deficits, are first visualized using functional MRI (fMRI).

The imaging or the EEG makes visible the area of the brain that may benefit most from neurostimulation. Subsequently, nerve cells in this region may be precisely stimulated with TMS. Because the healthy hemisphere of the brain is usually overactive after a stroke, there are simultaneous attempts to inhibit the contralesional motor cortex.

Initial results are hopeful. In the initial period after a stroke, TMS can be used in some patients to correct pathological connectivities and thereby improve motor deficits, reported Grefkes-Hermann. The fMRI pattern can also be used to predict recovery and intervention effects on an individual basis. A phase 3 trial is currently underway of 150 patients who have had a stroke and aims to study the efficacy of the new procedure.

Combined TMS and EEG

With the combination of TMS and the simultaneous measurement of EEG activity, a further development of fMRI connectivity analyses is currently being tested. Grefkes-Hermann believes that this procedure, which is more cost-effective, has higher temporal resolution, and can be used directly at the bedside, has more potential for personalized therapy planning in clinical practice.

The TMS-EEG procedure also makes it possible to predict the risk of post-stroke delirium, which affects around 30% of stroke patients and greatly worsens the outcome, underlined Prof. Ulf Ziemann, MD, medical director of the Department of Neurology at Tübingen University Hospital. In a study of 33 patients with acute stroke, the onset of post-stroke delirium could be predicted with a high degree of accuracy by using the TMS-EEG procedure no later than 48 hours after the event.

Other promising, noninvasive methods for neuron activation mentioned by Ziemann include transcranial focused ultrasound stimulation (tFUS) with low intensity, which is being studied for chronic pain, dementia, epilepsy, traumatic brain injury, and depression, as well as transcranial pulse stimulation (TPS), which is also based on ultrasound. In a pilot study of 35 patients with Alzheimer's disease, use of TPS within 3 months had positive effects on cognition. However, the study was not controlled and therefore further assessments are needed.

Custom Deep Brain Stimulation

For deep brain stimulation (DBS), an established therapy for Parkinson's disease and other movement disorders, the aim is individualized, symptom-related network stimulation, reported Prof. Andrea Kühn, MD, head of the Movement Disorders and Neuromodulation Section in the Department of Neurology of the Charité University Hospital Berlin.

At the panregional collaborative research center ReTune, which has been supported for 4 years now by €10 million from the German Research Foundation (DFG), imaging and computer-assisted programming algorithms are being developed for DBS. They will greatly simplify the time-consuming standard procedure for the best possible setting of the stimulation parameters, which requires a hospital stay of several days.

A randomized crossover study of 35 patients with Parkinson's disease proved the equivalence of the fast, algorithm-assisted DBS for the control of motor symptoms compared with standard procedures.

The new methods have the potential to considerably improve the outcome of patients with neurological and psychiatric diseases, according to scientists. However, the positive data must still be validated in further studies.

This article was translated from Medscape's German edition.

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