The Experts below are selected from a list of 236940 Experts worldwide ranked by ideXlab platform
Benjamin Becker - One of the best experts on this subject based on the ideXlab platform.
-
putamen volume predicts real time fmri neurofeedback Learning Success across paradigms and neurofeedback target regions
Human Brain Mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M. Kendrick, Klaus Mathiak, H Chen, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real‐time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
Human brain mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real-time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
2020Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Abstract Real-time fMRI guided neurofeedback training has gained increasing interest as a non-invasive brain regulation technique with the potential to normalize functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI datasets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three datasets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning the finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
Zhiying Zhao - One of the best experts on this subject based on the ideXlab platform.
-
putamen volume predicts real time fmri neurofeedback Learning Success across paradigms and neurofeedback target regions
Human Brain Mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M. Kendrick, Klaus Mathiak, H Chen, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real‐time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
Human brain mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real-time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
2020Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Abstract Real-time fMRI guided neurofeedback training has gained increasing interest as a non-invasive brain regulation technique with the potential to normalize functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI datasets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three datasets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning the finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
Michael Hortsch - One of the best experts on this subject based on the ideXlab platform.
-
correlating students educational background study habits and resource usage with Learning Success in medical histology
Anatomical Sciences Education, 2015Co-Authors: Daniel Selvig, Louisa Holaday, Joel Purkiss, Michael HortschAbstract:Histology is a traditional core basic science component of most medical and dental education programs and presents a didactic challenge for many students. Identifying students that are likely to struggle with histology would allow for early intervention to support and encourage their Learning Success. To identify student characteristics that are associated with Learning Success in histology, three first-year medical school classes at the University of Michigan (>440 students) were surveyed about their educational background, attitudes toward Learning histology, and their use of histology Learning strategies and resources. These characteristics were linked with the students' quiz and examination results in histology. Students who reported previous experience in histology or pathology and hold science or biomedical science college degrees usually did well in histology. Learning Success in histology was also positively associated with students' perception that histology is important for their professional career. Other positive indicators were in-person participation in teacher-guided Learning experiences, specifically lecture and laboratory sessions. In contrast, students who relied on watching histology lectures by video rather than going to lectures in-person performed significantly worse. These characteristics and Learning strategies of students who did well in this very visual and challenging study subject should be of help for identifying and advising students early, who might be at risk of failing a histology course or component. Anat Sci Educ 8: 1–11. © 2014 American Association of Anatomists.
-
Correlating students' educational background, study habits, and resource usage with Learning Success in medical histology
Anatomical sciences education, 2014Co-Authors: Daniel Selvig, Louisa Holaday, Joel Purkiss, Michael HortschAbstract:Histology is a traditional core basic science component of most medical and dental education programs and presents a didactic challenge for many students. Identifying students that are likely to struggle with histology would allow for early intervention to support and encourage their Learning Success. To identify student characteristics that are associated with Learning Success in histology, three first-year medical school classes at the University of Michigan (>440 students) were surveyed about their educational background, attitudes toward Learning histology, and their use of histology Learning strategies and resources. These characteristics were linked with the students' quiz and examination results in histology. Students who reported previous experience in histology or pathology and hold science or biomedical science college degrees usually did well in histology. Learning Success in histology was also positively associated with students' perception that histology is important for their professional career. Other positive indicators were in-person participation in teacher-guided Learning experiences, specifically lecture and laboratory sessions. In contrast, students who relied on watching histology lectures by video rather than going to lectures in-person performed significantly worse. These characteristics and Learning strategies of students who did well in this very visual and challenging study subject should be of help for identifying and advising students early, who might be at risk of failing a histology course or component.
Xinqi Zhou - One of the best experts on this subject based on the ideXlab platform.
-
putamen volume predicts real time fmri neurofeedback Learning Success across paradigms and neurofeedback target regions
Human Brain Mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M. Kendrick, Klaus Mathiak, H Chen, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real‐time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
Human brain mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real-time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
2020Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Abstract Real-time fMRI guided neurofeedback training has gained increasing interest as a non-invasive brain regulation technique with the potential to normalize functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI datasets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three datasets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning the finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
Klaus Mathiak - One of the best experts on this subject based on the ideXlab platform.
-
putamen volume predicts real time fmri neurofeedback Learning Success across paradigms and neurofeedback target regions
Human Brain Mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M. Kendrick, Klaus Mathiak, H Chen, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real‐time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
Human brain mapping, 2021Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning this finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
-
Putamen volume predicts real-time fMRI neurofeedback Learning Success across paradigms and neurofeedback target regions
2020Co-Authors: Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, He-sheng Chen, Keith M. Kendrick, Klaus Mathiak, Benjamin BeckerAbstract:Abstract Real-time fMRI guided neurofeedback training has gained increasing interest as a non-invasive brain regulation technique with the potential to normalize functional brain alterations in therapeutic contexts. Individual variations in Learning Success and treatment response have been observed, yet the neural substrates underlying the Learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for Learning Success with pooled data from three real-time fMRI datasets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback Learning Success across the three datasets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with Learning Success independent of specific aspects of the experimental design. Given the role of the putamen in associative Learning the finding may reflect an important role of instrumental Learning processes and brain structural variations in associated brain regions for Successful acquisition of fMRI neurofeedback-guided self-regulation.
