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,” 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, said 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 Dr. 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 Dr. 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 Dr. 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 Christian Grefkes-Hermann, MD, PhD, director of the department of neurology at 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 Dr. 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 most important factor for functional recovery after a stroke is neuronal reorganization,” said Dr. 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 Dr. 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.