The Blue-Collar Brain

Self Cite

Recent research has provided evidence for scalingrelations in eye-movement fluctuations, but not much is known about what these scaling relations imply about cognition or eye-movement control. Generally, scaling relations in behavioral and neurophysiological data have been interpreted as an indicator for the coordination of neurophysiological and cognitive processes. In this study, we investigated the effect of predictability in timing and gaze-direction on eye-movement fluctuations. Participants performed a simple eye-movement task, in which a visual cue prompted their gaze to different locations on a spatial layout, and the predictability about temporal and directional aspects of the cue were manipulated. The results showed that scaling exponents in eye-movements decreased with predictability and were related to the participants' perceived effort during the task. In relation to past research, these findings suggest that scaling exponents reflect a relative demand for voluntary control during task performance.

Section: Discussionmentioning

confidence: 99%

Cue predictability changes scaling in eye-movement fluctuations

Wallot

Coey

Richardson

2015

Self Cite

“…The present findings, however, showed that practicing isometric force control under specific constraints (i.e., selective scaling of visual feedback information) enhanced the learned adaptability of force output structure. It is not clear whether a slow-to-fast (Haken, 1983;Van Orden et al, 2012) or fast-to-slow direction occurred in terms of learning to use the multiple time scales of force control but the findings clearly demonstrate that the selective visual scaling of shorter time scales of visual information altered the interaction between multiple time scale processes of force control and led to a different time scale of learning (change over time).…”

Section: Informational Constraints and Transfermentioning

confidence: 89%

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking

King

Newell

2015

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4)(5)(6)(7)(8) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.Keywords Motorlearning . Time scales . Visualinformation . Isometric force When learning a novel motor skill, an individual has access to multiple sources of information derived from different modalities (e.g., vision, touch, and audition) to facilitate a change in motor performance as a function of practice. In addition to these inherent perceptual sources, augment information can be provided in the practice environment to guide performance toward the task goal. Two of the most effective categories of augmented information that enhance learning and performance are information about (a) the to-beproduced movement that is provided in advance of a trial (such as in instructions and demonstrations) and (b) feedback about the movement and its outcome of the just completed trial (Bilodeau & Bilodeau, 1961;Hodges & Franks, 2004;Kernodle & Carlton, 1992;Newell, 1996;Newell, Morris, & Scully, 1985). A core issue in motor learning is the effect of informational constraints on the learning, retention, and transfer of motor skills. The manipulation of different informational constraints present during acquisition includes the structure of the practice environment (e.g., variability of practice and contextual interference) as well augmented information (i.e., instructions, concurrent, and feedback) provided to the learner.The manipulation of different forms of informational constraints on motor learning relates to varying theoretical interpretation. Traditional viewpoints posited that augmented information, such as knowledge of results or knowledge of performance, acts to strengthen the respective memory trace for action (Schmidt, 1975). However, performance degrades when the learner (a) becomes dependent on the augmented feedback (Armstrong, 1970) or (b) is unable to process inherent feedback relative to augmented information (Swinnen, Schmidt, Nicholson, & Shapiro, 1990). Contemporary approaches related to the ...

“…In other words, this theory states that these dynamic patterns reflect the functional organization of the system producing the behavior. Proponents of this perspective also commonly argue that behavior is Bsoft-molded,^meaning that the functional organization of the system is flexible and can change to meet task demands (Kello & Van Orden, 2009;Van Orden, 2010;Van Orden, Hollis, & Wallot 2012). Thus, the results of the current experiment extend this line of research from the nomothetic perspective as a demonstration that the processes underlying the finger tapping behavior are reorganized as required by changes in task constraints and suggesting that the fractal scaling in some way reflects these functional organizations.…”

Section: Resultsmentioning

confidence: 99%

The complexities of keeping the beat: dynamical structure in the nested behaviors of finger tapping

Coey

Hassebrock

Kloos

et al. 2015

Recent research on fractal scaling in simple human behaviors (e.g., reaction time tasks) has demonstrated that different aspects of the performance (e.g., key presses and key releases) all reveal pink noise signals but yet are uncorrelated with one another in time. These studies have suggested that the independence of these signals might be due to the functional independence of these different sub-actions, given the task constraints. The current experiments investigated whether under a different set of constraints (e.g., finger tapping with and without a metronome) nested sub-actions might show interrelated dynamics, and whether manipulations affecting the fractal scaling of one also might have consequences for the scaling of others. Experiment 1 revealed that the inter-tap intervals and key-press durations of participants' tapping behavior were dynamically related to one another and that the fractal scaling of both changed in the switch from selfpaced to metronome-paced tapping. Consistent with past research, the inter-tap intervals changed toward an antipersistent, blue noise pattern of variation, but the keypress durations became even more persistent. Experiment 2 revealed that this pattern of results could be altered by asking participants to attempt to hold the key down for the entire length of the metronome tone. Specifically, the key-press duration of participants in the Bhold^group became less persistent in the switch across task conditions. Collectively, the results of these experiments suggest that fractal scaling reliably reflects the functional relationships of the processes underlying task performance. Keywords Fractal scaling . Long-range correlation . Finger tappingThere is growing appreciation within the fields of psychology and cognitive science that human behavior is inherently complex. Although there is not yet a consensus scientific definition (Delignières & Marmelat, 2012;Gell-Mann, 1995; Goldberger, Peng, & Lipsitz, 2002;Kelty-Stephen & Dixon, 2012;Kloos & Van Orden, 2010;Mainzer, 2005), Bcomplexity^here is intended to mean not only that behavior involves Ba lot of parts^(neurons, muscles, and bones within an actor, the behavior of other actors, the perpetually changing state of the environment) but also that these parts are interdependently coupled via nonlinear and sometimes nonobvious interactions. Understanding such complexity is no easy task, especially given that even the simplest of behaviors can reveal a surprising degree of complexity.Consider the task of rhythmically tapping one's finger. Although this is a relatively common and easily performed human behavior, scientific investigation has found that this simple act is supported and influenced by a range of complex, interdependent processes. Indeed, a vast literature on Bsensorimotor synchronization^has shown that the ability of humans to time their actions to other events depends on a host of neural