Awasthi, B., Friedman, J., & Williams, M. A. (2011). Processing of low spatial frequency faces at periphery in choice reaching tasks. Neuropsychologia, 49(7), 2136–2141.
Abstract: Various aspects of face processing have been associated with distinct ranges of spatial frequencies. Configural processing of faces depends chiefly on low spatial frequency (LSF) information whereas high spatial frequency (HSF) supports feature based processing. However, it has also been argued that face processing has a foveal-bias (HSF channels dominate the fovea). Here we used reach trajectories as a continuous behavioral measure to study perceptual processing of faces. Experimental stimuli were LSF–HSF hybrids of male and female faces superimposed and were presented peripherally and centrally. Subject reached out to touch a specified sex and their movements were recorded. The reaching trajectories reveal that there is less effect of (interference by) LSF faces at fovea as compared to periphery while reaching to HSF targets. These results demonstrate that peripherally presented LSF information, carried chiefly by magnocellular channels, enables efficient processing of faces, possibly via a retinotectal (subcortical) pathway.
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Awasthi, B., Friedman, J., & Williams, M. (2011). Faster, stronger, lateralized: Low spatial frequency information supports face processing. Neuropsychologia, 49(13), 3583–3590.
Abstract: Distinct visual pathways are selectively tuned for processing specific spatial frequencies. Recently, Awasthi, Friedman and Williams (2011) reported fast categorisation of faces at periphery, arguing for primacy of low spatial frequency (LSF) information in face processing. However, previous studies have also documented rapid categorization of places and natural scenes. Here, we tested if the LSF advantage is face specific or also involved in place perception. We used visually guided reaching as a continuous behavioral measure to examine the processing of LSF and high spatial frequency (HSF) hybrids, presented at the periphery. Subjects reached out and touched targets and their movements were recorded. The trajectories revealed that LSF interference was both 95 ms earlier and stronger for faces than places and was lateralized to the left visual field. The early processing of LSF information supports the assumption that faces are prioritised and provides a (neural) framework for such specialised processing.
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Friedman, J., Latash, M. L., & Zatsiorsky, V. M. (2011). Directional variability of the isometric force vector produced by the hand in multi-joint planar tasks. Journal of Motor Behavior, 43(6), 451–463.
Abstract: Numerous studies have examined control of force magnitude, but relatively little research has considered force direction control. In this study, subjects applied isometric forces to a handle and we compared within-trial variability when producing force in different directions. The standard deviation (SD) of the force parallel to the prescribed direction of force production increased linearly with the targeted force level, as did the SD of the force perpendicular to the instructed direction. In contrast, the SD of the angle of force production decreased with increased force level. In the four (of eight) instructed force directions where the endpoint force was generated due to a joint torque in only one joint (either the shoulder or elbow) the principal component axes in force space were well aligned with the prescribed direction of force production. In the other directions, the variance was approximately equal along the two force axes. The variance explained by the first principal component was significantly larger in torque space compared to the force space, and mostly corresponded to positive correlation between the joint torques. Such coordinated changes suggest that the torque variability was mainly due to the variability of the common drive to the muscles serving two joints, although this statement needs to be supported by direct studies of muscle activation in the future.
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Awasthi, B., Friedman, J., & Williams, M. A. (2012). Reach Trajectories Reveal Delayed Processing of Low Spatial Frequency Faces in Developmental Prosopagnosia. Cognitive Neuroscience, 3(2), 120–130.
Abstract: Developmental prosopagnosia (DP) is characterized by a selective deficit in face recognition despite normal cognitive and neurological functioning. Previous research has established configural processing deficits in DP subjects. Low spatial frequency (LSF) information subserves configural face processing. Using hybrid stimuli, here we examined the evolution of perceptual dynamics and integration of LSF information by DP subjects while they pointed to high spatial frequency (HSF) face targets. Permutation analysis revealed a 230-ms delay in LSF processing by DP subjects as compared to controls. This delayed processing is likely to contribute to the difficulties associated with face recognition in DP subjects and is reflective of their alleged reliance on local rather than global features in face perception. These results suggest that quick and efficient processing of LSF information is critical for the development of normal face perception.
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Friedman, J., & Korman, M. (2012). Kinematic Strategies Underlying Improvement in the Acquisition of a Sequential Finger Task with Self-Generated vs. Cued Repetition Training. PLoS One, 7(12), e52063.
Abstract: Many motor skills, such as typing, consist of articulating simple movements into novel sequences that are executed faster and smoother with practice. Dynamics of re-organization of these movement sequences with multi-session training and its dependence on the amount of self-regulation of pace during training is not yet fully understood. In this study, participants practiced a sequence of key presses. Training sessions consisted of either externally (Cued) or self-initiated (Uncued) training. Long-term improvements in performance speed were mainly due to reducing gaps between finger movements in both groups, but Uncued training induced higher gains. The underlying kinematic strategies producing these changes and the representation of the trained sequence differed significantly across subjects, although net gains in speed were similar. The differences in long-term memory due to the type of training and the variation in strategies between subjects, suggest that the different neural mechanisms may subserve the improvements observed in overall performance.
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