How the brain receives external information, performs decision making, and responds to the decision is largely affected by the ongoing and constant fluctuations of brain state. Understanding the mechanisms of brain state transition and how they are controlled is important to interpret how the nervous system operates, both normally in health and abnormally in disease. Cognitive control is a neural control process that encompasses a diverse range of functions involved in flexibly coordinating information to achieve internal goals in a changing environment. Such control processes include the ability to link multiple sources of information to solve problems, selective retrieval of information from memory, inhibition of inappropriate behavioral responses, and active selection and maintenance of behaviorally relevant information online. Motor control involves interaction between several motor-related regions to respond to different movement states such as perception, motor planning or execution. It is also critical to analyze the changes in motor-related regions according to movement states to elucidate the brain motor control mechanism, which has not been fully investigated yet.
In the last decade, human neuroimaging studies have suggested that these complex control functions are supported by anatomically distributed brain networks that share information via coordinated activity called functional connectivity. Alterations in human brain networks has contributed to the cognitive control impairment in diseases such as Depression and Dementia. In the case of Parkinson’s disease (PD), movement slowness can be explained by a disruption of the neural control network that determine normal movement speed. Although recent studies have proposed various analytical pipelines to explore the underlying neural control mechanisms based on different neuroimaging modalities in health and disease, the solutions are still limited and lack precise interpretation in a “control” perspective. More recently, brain controllability analysis has been proposed to specifically identify the underlying neural control patterns related to different neuropsychological processes and alterations caused by diseases, and has been employed to explore the cognitive control alteration in diseases such as Alzheimer’s Disease (AD), Mild cognitive impairment (MCI) and Depression, and motor control deficits in Stroke, providing a new insight into the investigation of neural control mechanism of the brain. Meanwhile, it has been employed to determine the optimal stimulation targets to optimize neuromodulation protocol for treating various neuropsychiatric disorders.
The scope of this Topic focuses on developments and findings that provide further insight into the novel methodology for neural control analysis and investigations on neural control patterns in both normal and abnormal populations, using different brain imaging techniques.
We welcome contributions that address, but are not limited to, the following themes:
(1) Novel analytical methods and algorithms to explore the underlying neural control mechanisms.
(2) Investigation of neural control mechanism using different neuroimaging modalities, including, but not limited to, EEG, ECog, LFP, fMRI, fNIRS, Calcium Imaging, Spike trains.
(3) Exploration of the neural control mechanism such as cognitive control and motor control related to different neuropsychological processes such as intelligence, executive functions, attention, memory, language, perception, sensorimotor functions, mood state, and emotion.
(4) Characterization of the neural control pattern alteration caused by various neuropsychiatric disorders, including, but not limited to, Depression, Anxiety, Dementia (such as AD and MCI), Stroke, PD, Seizures, Schizophrenia, Bipolar disorder (BD), and Addictions.
(5) Relationship between the underlying neural control patterns and neuromodulation.
(6) Review of recent developments in neural control investigations.
How the brain receives external information, performs decision making, and responds to the decision is largely affected by the ongoing and constant fluctuations of brain state. Understanding the mechanisms of brain state transition and how they are controlled is important to interpret how the nervous system operates, both normally in health and abnormally in disease. Cognitive control is a neural control process that encompasses a diverse range of functions involved in flexibly coordinating information to achieve internal goals in a changing environment. Such control processes include the ability to link multiple sources of information to solve problems, selective retrieval of information from memory, inhibition of inappropriate behavioral responses, and active selection and maintenance of behaviorally relevant information online. Motor control involves interaction between several motor-related regions to respond to different movement states such as perception, motor planning or execution. It is also critical to analyze the changes in motor-related regions according to movement states to elucidate the brain motor control mechanism, which has not been fully investigated yet.
In the last decade, human neuroimaging studies have suggested that these complex control functions are supported by anatomically distributed brain networks that share information via coordinated activity called functional connectivity. Alterations in human brain networks has contributed to the cognitive control impairment in diseases such as Depression and Dementia. In the case of Parkinson’s disease (PD), movement slowness can be explained by a disruption of the neural control network that determine normal movement speed. Although recent studies have proposed various analytical pipelines to explore the underlying neural control mechanisms based on different neuroimaging modalities in health and disease, the solutions are still limited and lack precise interpretation in a “control” perspective. More recently, brain controllability analysis has been proposed to specifically identify the underlying neural control patterns related to different neuropsychological processes and alterations caused by diseases, and has been employed to explore the cognitive control alteration in diseases such as Alzheimer’s Disease (AD), Mild cognitive impairment (MCI) and Depression, and motor control deficits in Stroke, providing a new insight into the investigation of neural control mechanism of the brain. Meanwhile, it has been employed to determine the optimal stimulation targets to optimize neuromodulation protocol for treating various neuropsychiatric disorders.
The scope of this Topic focuses on developments and findings that provide further insight into the novel methodology for neural control analysis and investigations on neural control patterns in both normal and abnormal populations, using different brain imaging techniques.
We welcome contributions that address, but are not limited to, the following themes:
(1) Novel analytical methods and algorithms to explore the underlying neural control mechanisms.
(2) Investigation of neural control mechanism using different neuroimaging modalities, including, but not limited to, EEG, ECog, LFP, fMRI, fNIRS, Calcium Imaging, Spike trains.
(3) Exploration of the neural control mechanism such as cognitive control and motor control related to different neuropsychological processes such as intelligence, executive functions, attention, memory, language, perception, sensorimotor functions, mood state, and emotion.
(4) Characterization of the neural control pattern alteration caused by various neuropsychiatric disorders, including, but not limited to, Depression, Anxiety, Dementia (such as AD and MCI), Stroke, PD, Seizures, Schizophrenia, Bipolar disorder (BD), and Addictions.
(5) Relationship between the underlying neural control patterns and neuromodulation.
(6) Review of recent developments in neural control investigations.