Summary: Researchers look at evolving epileptic brain networks to obtain a better understanding of brain activity in those with epilepsy.
Source: American Institute of Physics.
University of Bonn researchers are exploring ‘evolving epileptic brain networks’ to gain a better understanding of brain activity in epilepsy patients and the roles played by different regions of the brain.
Epilepsy is a complex neurological disorder that afflicts approximately 50 million people worldwide. Although this disease has been known to exist for centuries, the exact mechanism of its cardinal symptom, the epileptic seizure, remains poorly understood. In fact, roughly 25 percent of epileptic seizures can’t be controlled by any of the therapies available today.
Recent advances have led to a conceptualization of epilepsy as a “network disease” exhibiting connections within the brain. This large-scale epileptic network comprises various areas of the brain involved in normal brain activity during both seizure-free intervals and those involved in so-called pathophysiological activities such as seizures.
Little is known, however, about which specific areas of the brain contribute to a patient’s epileptic network or the roles these different areas play. As a group of researchers in Germany now reports this week in Chaos, one way to get closer to the complex wiring of the human brain is by merging concepts from a timed-based synchronization theory and space-based network theory to construct functional brain networks.
Until now, the “seizure-generating area” of the brain — in which the earliest signs of seizure activity can be observed — was considered the most important of these regions. This finding was based on very limited data and it was unclear whether its importance changes with time.
With this new analytical approach, Professor Klaus Lehnertz, head of the Neurophysics Group in the Department of Epileptology at the University of Bonn, and his group explored the temporal and spatial variability of the importance of the brain’s different regions.
“New developments in network theory are providing powerful tools to construct so-called ‘functional networks’ from observations of brain activities such as the electroencephalogram (EEG), and helping to identify the important nodes and links within such networks,” Lehnertz said.
By associating network nodes with individually sampled brain regions, Lehnertz’s group can define a link between a pair of nodes by assessing the degree of synchrony between neuronal signals from all pairs of nodes; the higher the degree, the stronger the link.
“Applying these analysis concepts to multichannel long-term EEG recordings from 17 epilepsy patients with high temporal resolution allowed us to derive a sequence of functional brain networks spanning several days in duration,” said Christian Geier, a doctoral student working with Lehnertz. “For each network, we assess various aspects of the importance of individual brain regions with different centrality indices that were developed earlier for the social sciences. Then, we explore how the importance of network nodes fluctuates over time.”
The group’s work is particularly significant because they showed for the first time how the importance of individual nodes within functional brain networks fluctuates on timescales spanning tens of seconds up to days. They further showed that these fluctuations can be largely attributed to the normal, daily rhythms of a patient, yet only minimally attributed to phenomena directly related to the disease.
Perhaps their most intriguing finding is that in general, according to Geier, there isn’t a constant importance hierarchy between brain regions.
“Rather, they take turns in importance on various time scales,” Geier said. “And, depending on which aspect of importance is assessed, the seizure-generating area isn’t — as commonly believed — the most important node within a large-scale epileptic network.”
The understandings gained from this research are part of the necessary foundation for developing treatments related to the causes and symptoms of epilepsy.
“When different brain regions assume the highest importance within a functional brain network is the key to improving both prediction and control of epileptic seizures,” Lehnertz said. “In the long run, this improved understanding may enable the development of better treatment options for patients suffering from epilepsy. And understanding the importance of the nodes and links of functional brain networks may also be relevant for other neurological diseases.”
About this neuroscience research article
Source: Julia Majors – American Institute of Physics Image Source: NeuroscienceNews.com image is in the public domain. Original Research: Full open access research for “Long-term variability of importance of brain regions in evolving epileptic brain networks” by Christian Geier and Klaus Lehnertz in Chaos. Published online April 2017 doi:10.1063/1.4979796
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[cbtabs][cbtab title=”MLA”]American Institute of Physics “New Analysis of Brain Network Activity Offers Unique Insight into Epileptic Seizures.” NeuroscienceNews. NeuroscienceNews, 27 April 2017. <https://neurosciencenews.com/brain-network-epilepsy-6529/>.[/cbtab][cbtab title=”APA”]American Institute of Physics (2017, April 27). New Analysis of Brain Network Activity Offers Unique Insight into Epileptic Seizurese. NeuroscienceNew. Retrieved April 27, 2017 from https://neurosciencenews.com/brain-network-epilepsy-6529/[/cbtab][cbtab title=”Chicago”]American Institute of Physics “New Analysis of Brain Network Activity Offers Unique Insight into Epileptic Seizures.” https://neurosciencenews.com/brain-network-epilepsy-6529/ (accessed April 27, 2017).[/cbtab][/cbtabs]
Long-term variability of importance of brain regions in evolving epileptic brain networks
We investigate the temporal and spatial variability of the importance of brain regions in evolving epileptic brain networks. We construct these networks from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients and use centrality indices to assess the importance of brain regions. Time-resolved indications of highest importance fluctuate over time to a greater or lesser extent, however, with some periodic temporal structure that can mostly be attributed to phenomena unrelated to the disease. In contrast, relevant aspects of the epileptic process contribute only marginally. Indications of highest importance also exhibit pronounced alternations between various brain regions that are of relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches. Nonetheless, these findings may guide new developments for individualized diagnosis, treatment, and control.
Epilepsy is now recognized as a network disease, with focal-onset seizures—that appear to originate from a circumscribed region of the brain (the so-called seizure onset zone)—resulting from complex interactions in a large-scale epileptic network, which comprises various brain structures and regions. Concepts and tools from the network theory proved useful in characterizing such networks. Temporal changes of global characteristics of evolving epileptic brain networks not only provide important clues about mechanisms underlying the generation and terminating of seizures but also about how these networks are influenced by various pathophysiologic and physiologic processes, which act on different timescales. Our study aims at shedding more light onto temporal changes of local properties, namely of the importance of brain regions, as this could guide new developments of individualized diagnosis, treatment, and control. To do so, we investigate—in a time-resolved manner— the importance of brain regions constituting the nodes in evolving epileptic brain networks derived from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients. We show that importance of brain regions is highly variable, and daily rhythms can be regarded as a dominating influencing factor.
“Long-term variability of importance of brain regions in evolving epileptic brain networks” by Christian Geier and Klaus Lehnertz in Chaos. Published online April 2017 doi:10.1063/1.4979796