Decisions do not occur all at once; rather they are dynamic processes that unfold over time. Unfortunately, it is often difficult to observe and separate the individual processes and their timing with traditional behavioral measures, and too often a complex process is collapsed into a single event. Neuroimaging data offers researchers an opportunity to measure these decision processes, as they are ongoing. Moreover, neuroimaging technologies offer the opportunity for temporal resolution that is not achievable by traditional behavioral measures. This research topic seeks to exploit neuroimaging’s ability to measure multiple signals across multiple time points to better understand the temporal dynamics of decision-making.
This research topic aims to explore the dynamic behavior of neural systems during the decision-making process. The fundamental goal is to characterize different decision processes across time. We seek to understand how a decision process begins, progresses, and ends. We seek to understand to what degree is a given decision process the same regardless of inputs and outcomes and to what degree does the process vary. We seek to understand when and how to neural systems switch from one processing state to another. We seek to delve into the neural algorithms that drive decision-making by characterizing how neural signals change over time and in response to what stimuli.
For this research topic we encourage submissions of a variety of types not limited to:
• Neuroimaging modalities such as EEG, fMRI, eye tracking, galvanic skin response, and others change across time while subjects make decisions.
• Research that characterized the time path of multiple neural signals from the same or different modalities across time.
• Research, which examines the evolution of the engagement of different brain, networks across time.
• Research that uses novel time series or signal processing techniques to examine the dynamic processes of decision-making.
• Research, which examines ongoing information processing within the brain across significant amounts of time.
Decisions do not occur all at once; rather they are dynamic processes that unfold over time. Unfortunately, it is often difficult to observe and separate the individual processes and their timing with traditional behavioral measures, and too often a complex process is collapsed into a single event. Neuroimaging data offers researchers an opportunity to measure these decision processes, as they are ongoing. Moreover, neuroimaging technologies offer the opportunity for temporal resolution that is not achievable by traditional behavioral measures. This research topic seeks to exploit neuroimaging’s ability to measure multiple signals across multiple time points to better understand the temporal dynamics of decision-making.
This research topic aims to explore the dynamic behavior of neural systems during the decision-making process. The fundamental goal is to characterize different decision processes across time. We seek to understand how a decision process begins, progresses, and ends. We seek to understand to what degree is a given decision process the same regardless of inputs and outcomes and to what degree does the process vary. We seek to understand when and how to neural systems switch from one processing state to another. We seek to delve into the neural algorithms that drive decision-making by characterizing how neural signals change over time and in response to what stimuli.
For this research topic we encourage submissions of a variety of types not limited to:
• Neuroimaging modalities such as EEG, fMRI, eye tracking, galvanic skin response, and others change across time while subjects make decisions.
• Research that characterized the time path of multiple neural signals from the same or different modalities across time.
• Research, which examines the evolution of the engagement of different brain, networks across time.
• Research that uses novel time series or signal processing techniques to examine the dynamic processes of decision-making.
• Research, which examines ongoing information processing within the brain across significant amounts of time.