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Friedman, Jason; SKM, Varadhan; Zatsiorsky, Vladimir M.; Latash, Mark L. |
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Title |
The sources of two components of variance: an example of multifinger cyclic force production tasks at different frequencies |
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2009 |
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Experimental Brain Research |
Abbreviated Journal |
Exp Brain Res |
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196 |
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2 |
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263-277 |
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Abstract |
In a multifinger cyclic force production task, the finger force variance measured across trials can be decomposed into two components, one that affects the combined force output (“bad variance”) and one that does not (“good variance”). Previous studies have found similar time patterns of “bad variance” and force rate leading to an approximately linear relationship between them. Based on this finding and a recently developed model of multifinger force production, we expected the “bad variance” during cyclic force production to increase monotonically with the rate of force change, both within a cycle and across trials at different frequencies. Alternatively, “bad variance” could show a dependence on task frequency, not on actual force derivative values. Healthy subjects were required to produce cyclic force patterns to prescribed targets by pressing on unidimensional force sensors, at a frequency set by a metronome. The task was performed with only the index finger, and with all four fingers. In the task with all four fingers, the “good variance” increased approximately linearly with an increase in the force magnitude. The “bad variance” showed within-a-cycle modulation similar to that of the force rate. However, an increase in the frequency did not lead to an increase in the “bad variance” that could be expected based on the natural relationships between action frequency and the rate of force change modulation. The results have been interpreted in the framework of an earlier model of multifinger force production where “bad variance” is a result of variance of the timing parameter. The unexpected lack of modulation of the “bad variance” with frequency suggests a drop in variance of the timing parameter with increased frequency. This mechanism may serve to maintain a constant acceptable level of variance under different conditions. |
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Department of Kinesiology, The Pennsylvania State University, University Park, PA 16802, USA |
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1432-1106 |
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PMID:19468721 |
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Penn State @ write.to.jason @ |
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15 |
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Awasthi, Bhuvanesh; Friedman, Jason; Williams, Mark A |
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Title |
Reach Trajectories Reveal Delayed Processing of Low Spatial Frequency Faces in Developmental Prosopagnosia |
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Journal Article |
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2012 |
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Cognitive Neuroscience |
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3 |
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2 |
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120-130 |
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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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Penn State @ write.to.jason @ |
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27 |
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Friedman, Jason; Flash, Tamar |
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Title |
Task-dependent selection of grasp kinematics and stiffness in human object manipulation |
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2007 |
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Cortex |
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43 |
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3 |
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444-460 |
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Object manipulation with the hand is a complex task. The task has redundancies at many levels, allowing many possibilities for the selection of grasp points, the orientation and posture of the hand, the forces to be applied at each fingertip and the impedance properties of the hand. Despite this inherent complexity, humans perform object manipulation nearly effortlessly. This article presents experimental findings of how humans grasp and manipulate objects, and examines the compatibility of grasps selected for specific tasks. This is accomplished by looking at the velocity transmission and force transmission ellipsoids, which represent the transmission ratios of the corresponding quantity from the joints to the object, as well as the stiffness ellipsoid which represents the directional stiffness of the grasp. These ellipsoids allow visualization of the grasp Jacobian and grasp stiffness matrices. The results show that the orientation of the ellipsoids can be related to salient task requirements. |
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Penn State @ write.to.jason @ |
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14 |
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Friedman, Jason; Brown, Scott; Finkbeiner, Matthew |
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Title |
Linking cognitive and reaching trajectories via intermittent movement control |
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2013 |
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Journal of Mathematical Psychology |
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57 |
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3-4 |
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140-151 |
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Decision making; Diffusion model; Reaction times; Arm movements; Submovements |
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Theories of decision-making have traditionally been constrained by reaction time data. A limitation of reaction time data, particularly for studying the temporal dynamics of cognitive processing, is that they index only the endpoint of the decision making process. Recently, physical reaching trajectories have been used as proxies for underlying mental trajectories through decision space. We suggest that this approach has been oversimplified: while it is possible for the motor control system to access the current state of the evidence accumulation process, this access is intermittent. Instead, we demonstrate how a model of arm movements that assumes intermittent, not continuous, access to the decision process is sufficient to describe the effects of stimulus quality and viewing time in curved reaching movements. |
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70 |
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Friedman, Jason; Flash, Tamar |
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Title |
Trajectory of the index finger during grasping |
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Journal Article |
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Year |
2009 |
Publication |
Experimental Brain Research |
Abbreviated Journal |
Exp Brain Res |
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Volume |
196 |
Issue |
4 |
Pages |
497-509 |
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The trajectory of the index finger during grasping movements was compared to the trajectories predicted by three optimization-based models. The three models consisted of minimizing the integral of the weighted squared joint derivatives along the path (inertia-like cost), minimizing torque change, and minimizing angular jerk. Of the three models, it was observed that the path of the fingertip and the joint trajectories, were best described by the minimum angular jerk model. This model, which does not take into account the dynamics of the finger, performed equally well when the inertia of the finger was altered by adding a 20 g weight to the medial phalange. Thus, for the finger, it appears that trajectories are planned based primarily on kinematic considerations at a joint level. |
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Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel, write.to.jason@gmail.com |
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1432-1106 |
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PMID:19521692 |
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Penn State @ write.to.jason @ |
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17 |
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