TY - JOUR
T1 - Gender-dependent changes in time production following quadrato motor training in dyslexic and normal readers
AU - Ben-Soussan, Tal Dotan
AU - Glicksohn, Joseph
N1 - Publisher Copyright:
© 2018 Ben-Soussan and Glicksohn.
PY - 2018/8/29
Y1 - 2018/8/29
N2 - Time estimation is an important component of the ability to organize and plan sequences of actions as well as cognitive functions, both of which are known to be altered in dyslexia. While attention deficits are accompanied by short Time Productions (TPs), expert meditators have been reported to produce longer durations, and this seems to be related to their increased attentional resources. In the current study, we examined the effects of a month of Quadrato Motor Training (QMT), which is a structured sensorimotor training program that involves sequencing of motor responses based on verbal commands, on TP using a pre-post design. QMT has previously been found to enhance attention and EEG oscillatory activity, especially within the alpha range. For the current study, 29 adult Hebrew readers were recruited, of whom 10 dyslexic participants performed the QMT. The normal readers were randomly assigned to QMT (n = 9) or Verbal Training (VT, identical cognitive training with no overt motor component, and only verbal response, n = 10). Our results demonstrate that in contrast to the controls, longer TP in females was found following 1 month of intensive QMT in the dyslexic group, while the opposite trend occurred in control females. We suggest that this longer TP in the female dyslexics is related to their enhanced attention resulting from QMT. The current findings suggest that the combination of motor and mindful training, embedded in QMT, has a differential effect depending on gender and whether one is dyslexic or not. These results have implications for educational and contemplative neuroscience, emphasizing the connection between specifically-structured motor training, time estimation and attention.
AB - Time estimation is an important component of the ability to organize and plan sequences of actions as well as cognitive functions, both of which are known to be altered in dyslexia. While attention deficits are accompanied by short Time Productions (TPs), expert meditators have been reported to produce longer durations, and this seems to be related to their increased attentional resources. In the current study, we examined the effects of a month of Quadrato Motor Training (QMT), which is a structured sensorimotor training program that involves sequencing of motor responses based on verbal commands, on TP using a pre-post design. QMT has previously been found to enhance attention and EEG oscillatory activity, especially within the alpha range. For the current study, 29 adult Hebrew readers were recruited, of whom 10 dyslexic participants performed the QMT. The normal readers were randomly assigned to QMT (n = 9) or Verbal Training (VT, identical cognitive training with no overt motor component, and only verbal response, n = 10). Our results demonstrate that in contrast to the controls, longer TP in females was found following 1 month of intensive QMT in the dyslexic group, while the opposite trend occurred in control females. We suggest that this longer TP in the female dyslexics is related to their enhanced attention resulting from QMT. The current findings suggest that the combination of motor and mindful training, embedded in QMT, has a differential effect depending on gender and whether one is dyslexic or not. These results have implications for educational and contemplative neuroscience, emphasizing the connection between specifically-structured motor training, time estimation and attention.
KW - Dyslexia
KW - Gender difference
KW - Quadrato motor training
KW - Time and motion studies
KW - Time production
UR - http://www.scopus.com/inward/record.url?scp=85053422890&partnerID=8YFLogxK
U2 - 10.3389/fncom.2018.00071
DO - 10.3389/fncom.2018.00071
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C2 - 30210326
AN - SCOPUS:85053422890
SN - 1662-5188
VL - 12
JO - Frontiers in Computational Neuroscience
JF - Frontiers in Computational Neuroscience
M1 - 71
ER -