About this Research Topic
The process of modifying neural activity, known as neuromodulation, has been instrumental in addressing both the treatment of brain disorders and the pursuit of scientific inquiry. Deep brain stimulation (DBS), in particular, has proven to be a clinical asset to an estimated 150,000 individuals. As our comprehension of the effects of neuromodulation on the brain continues to develop, there is a shift in focus. Rather than concentrating solely on the localized effects at the site of stimulation, there is an emerging interest in the broader implications for distant brain regions that are interconnected with the stimulated area. This approach promises to offer a more holistic understanding of how neuromodulation can influence the brain's complex network with a spectrum of symptoms that involve disruptions in mood, cognition and motor function.
In recent years, “connectomic neuromodulation” was proposed as a novel concept in this area, which provides numerous opportunities to better understand and predict clinical outcomes, personalize neuromodulation therapy, and integrate findings across neuromodulation targets and modalities. Every opportunity provides a testable hypothesis for improving neuromodulation therapy. For instance, “connectomic neuromodulation” enables us to identify the DBS downregulated circuits that led to symptom improvements — which represent the dysfunctional ones that had caused the symptoms in the first place (also named as dysfunctome). We believe the development of these novel methods would allow big success in clarifying the principles that underlie the effects of neuromodulation for psychoneurological diseases.
This Research Topic aims to explore novel brain network analytical methods to comprehensively evaluate the brain connectomic changes after neuromodulation intervention (e.g., DBS, sEEG, rTMS, rDCS, VNS). Using diffusion/functional MRI or EEG techniques, we focus on pinpointing and quantifying the brain network signature corresponding to neuromodulation, and its relationship with symptom improvement. Interdisciplinary research regarding dysfunctome and cross-disorder designs are highly encouraged.
We welcome research articles and review articles on the following topics among others:
• Using connectomics to explain and predict clinical improvement in neurological or psychological disorders, including Parkinson’s disease, autism, bipolar affective disorders, major depression, drug addiction, etc.
• Linking different neuromodulation targets to the same network or identifying symptom specific networks.
• Discovery of brain networks that lead to neuromodulation side-effects.
• Connectomics guiding DBS programming and neurosurgery.
• Mapping the dysfunctome across multiple brain disorders for targeted brain circuit therapy
• Bridging invasive and noninvasive brain neuromodulation in sharing neural circuits or networks.
In recent years, “connectomic neuromodulation” was proposed as a novel concept in this area, which provides numerous opportunities to better understand and predict clinical outcomes, personalize neuromodulation therapy, and integrate findings across neuromodulation targets and modalities. Every opportunity provides a testable hypothesis for improving neuromodulation therapy. For instance, “connectomic neuromodulation” enables us to identify the DBS downregulated circuits that led to symptom improvements — which represent the dysfunctional ones that had caused the symptoms in the first place (also named as dysfunctome). We believe the development of these novel methods would allow big success in clarifying the principles that underlie the effects of neuromodulation for psychoneurological diseases.
This Research Topic aims to explore novel brain network analytical methods to comprehensively evaluate the brain connectomic changes after neuromodulation intervention (e.g., DBS, sEEG, rTMS, rDCS, VNS). Using diffusion/functional MRI or EEG techniques, we focus on pinpointing and quantifying the brain network signature corresponding to neuromodulation, and its relationship with symptom improvement. Interdisciplinary research regarding dysfunctome and cross-disorder designs are highly encouraged.
We welcome research articles and review articles on the following topics among others:
• Using connectomics to explain and predict clinical improvement in neurological or psychological disorders, including Parkinson’s disease, autism, bipolar affective disorders, major depression, drug addiction, etc.
• Linking different neuromodulation targets to the same network or identifying symptom specific networks.
• Discovery of brain networks that lead to neuromodulation side-effects.
• Connectomics guiding DBS programming and neurosurgery.
• Mapping the dysfunctome across multiple brain disorders for targeted brain circuit therapy
• Bridging invasive and noninvasive brain neuromodulation in sharing neural circuits or networks.
Keywords: connectomic neuromodulation, dysfunctome, circuit therapy, disconnection, symptom specific networks
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
