A persistent problem in neuroscientific research, particularly neuroimaging techniques such as fMRI and ERPs, is the intrinsically low signal-to-noise ratio in the data generated with such apparati. The conventional solution has been to average data across many participants to allow statistical identification of the signal with sufficient power. Although this strategy has produced useful results, it is not without problems including a downplaying (or ignoring) of potentially important idiosyncratic differences in the subjects exposed to the experimental conditions.
Over the last five decades, a tradition of research known as the Experimental Analysis of Behavior has developed a robust set of experimental procedures and designs to study the behavior of individual subjects. These designs measure the behavior of an individual subject across many experimental sessions and, if applied to neuroimaging research, may allow increasing the signal-to-noise ratio while overcoming potential pitfalls due to averaging across participants. In addition, the experimental designs allow each individual subject to serve as his/her own control, thereby helping to ease the challenges involved in interpreting differences across subjects. Finally, the emphasis on individual changes in behavior leads the experimenter to fine-tune experimental procedures to best isolate the relationship between behavior and the variables of which it is a function.
The purpose of this Research Topic is to explore the utility of this research methodology on understanding issues relevant to neuroscientists with a wide variety of research interests. In particular, the Research Topic seeks to provide a forum for the description of innovative research focused on the behavior of single subjects and for a theoretical debate about the potential utility of a focus on individual data in neuroscience.
Relevant topics include (but are not limited to): empirical reports focused on analyses of individual results using neuroimaging (fMRI, PET, ERPs, MEG) or other technologies (e.g., TMS) as well as technical and theoretical manuscripts about research methodology in neuroscience.
A persistent problem in neuroscientific research, particularly neuroimaging techniques such as fMRI and ERPs, is the intrinsically low signal-to-noise ratio in the data generated with such apparati. The conventional solution has been to average data across many participants to allow statistical identification of the signal with sufficient power. Although this strategy has produced useful results, it is not without problems including a downplaying (or ignoring) of potentially important idiosyncratic differences in the subjects exposed to the experimental conditions.
Over the last five decades, a tradition of research known as the Experimental Analysis of Behavior has developed a robust set of experimental procedures and designs to study the behavior of individual subjects. These designs measure the behavior of an individual subject across many experimental sessions and, if applied to neuroimaging research, may allow increasing the signal-to-noise ratio while overcoming potential pitfalls due to averaging across participants. In addition, the experimental designs allow each individual subject to serve as his/her own control, thereby helping to ease the challenges involved in interpreting differences across subjects. Finally, the emphasis on individual changes in behavior leads the experimenter to fine-tune experimental procedures to best isolate the relationship between behavior and the variables of which it is a function.
The purpose of this Research Topic is to explore the utility of this research methodology on understanding issues relevant to neuroscientists with a wide variety of research interests. In particular, the Research Topic seeks to provide a forum for the description of innovative research focused on the behavior of single subjects and for a theoretical debate about the potential utility of a focus on individual data in neuroscience.
Relevant topics include (but are not limited to): empirical reports focused on analyses of individual results using neuroimaging (fMRI, PET, ERPs, MEG) or other technologies (e.g., TMS) as well as technical and theoretical manuscripts about research methodology in neuroscience.
