Jp Maxwell

The theory of reinvestment

This review provides an overview of a diverse, temporally distributed, body of literature regarding the effects of conscious attention to movement. An attempt is made to unite the many different views within the literature through Reinvestment Theory (Masters, 1992; Masters, Polman, & Hammond, 1993), which suggests that relatively automated motor processes can be disrupted if they are run using consciously accessed, task-relevant declarative knowledge to control the mechanics of the movements on-line. Reinvestment Theory argues that the propensity for consciousness to control movements on-line is a function of individual personality differences, specific contexts and a broad range of contingent events that can be psychological, physiological, environmental or even mechanical.

The role of working memory in motor learning and performance

Three experiments explore the role of working memory in motor skill acquisition and performance. Traditional theories postulate that skill acquisition proceeds through stages of knowing, which are initially declarative but later procedural. The reported experiments challenge that view and support an independent, parallel processing model, which predicts that procedural and declarative knowledge can be acquired separately and that the former does not depend on the availability of working memory, whereas, the latter does. The behaviour of these two processes was manipulated by providing or withholding visual (and auditory) appraisal of outcome feedback. Withholding feedback was predicted to inhibit the use of working memory to appraise success and, thus, prevent the formation of declarative knowledge without affecting the accumulation of procedural knowledge. While the first experiment failed to support these predictions, the second and third experiments demonstrated that procedural and declarative knowledge can be acquired independently. It is suggested that the availability of working memory is crucial to motor performance only when the learner has come to rely on its use.

Passing thoughts on the evolutionary stability of implicit motor behaviour: performance retention under physiological fatigue.

Heuristics of evolutionary biology (e.g., survival of the fittest) dictate that phylogenetically older processes are inherently more stable and resilient to disruption than younger processes. On the grounds that non-declarative behaviour emerged long before declarative behaviour, Reber (1992) argues that implicit (non-declarative) learning is supported by neural processes that are evolutionarily older than those supporting explicit learning. Reber suggested that implicit learning thus leads to performance that is more robust than explicit learning. Applying this evolutionary framework to motor performance, we examined whether implicit motor learning, relative to explicit motor learning, conferred motor output that was resilient to physiological fatigue and durable over time. In Part One of the study a fatigued state was induced by a double Wingate Anaerobic test protocol. Fatigue had no affect on performance of participants in the implicit condition; whereas, performance of participants in the explicit condition deteriorated significantly. In Part Two of the study a convenience sample of participants was recalled following a one-year hiatus. In both the implicit and the explicit condition retention of performance was seen and, contrary to the findings in Part One, so was resilience to fatigue. The resilient performance in the explicit condition after one year may have resulted from forgetting (the decay of declarative knowledge) or from consolidation of declarative knowledge as implicit memories. In either case, implicit processes were left to more effectively support motor performance.

Stable implicit motor processes despite aerobic locomotor fatigue

Implicit processes almost certainly preceded explicit processes in our evolutionary history, so they are likely to be more resistant to disruption according to the principles of evolutionary biology [Reber, A. S. (1992). The cognitive unconscious: An evolutionary perspective. Consciousness and Cognition, 1, 93-133.]. Previous work (e.g., [Masters, R. S. W. (1992). Knowledge, (k)nerves and know-how: The role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. British Journal of Psychology, 83, 343-358.]) has shown that implicitly learned motor skills remain stable under psychological pressure and concurrent cognitive demands, and recently [Poolton, J. M., Masters, R. S. W., & Maxwell, J. P. (2007). Passing thoughts on the evolutionary stability of implicit motor behaviour: Performance retention under physiological fatigue. Consciousness and Cognition, 16(2), 456-468.] showed that they also remain stable under conditions of anaerobic fatigue that would have significantly challenged the survival skills of our ancestors. Here we examine the stability of an implicitly learned motor skill under fatigue conditions that primarily tax a different physiological system (the aerobic system), but which have equally strong evolutionary connotations. Participants acquired a throwing task by means of an errorless (implicit) learning method or an errorful (explicit) method. Motor performance in the errorless condition, but not the errorful condition, remained stable following an exhaustive VO2 max. running test. Our findings replicate and extend the work of Poolton et al., providing further support for Rebers evolutionary distinction between implicit and explicit processes.

Neural co-activation as a yardstick of implicit motor learning and the propensity for conscious control of movement.

Two studies examined EEG co-activation (coherence) between the verbal-analytical (T3) and motor planning (Fz) regions during a golf putting task. In Study 1, participants with a strong propensity to consciously monitor and control their movements, determined psychometrically by high scores on a movement specific Reinvestment Scale, displayed more alpha2 T3-Fz co-activation than participants with a weak propensity. In Study 2, participants who practiced a golf putting task implicitly (via an errorless learning protocol) displayed less alpha2 T3-Fz co-activation than those who practiced explicitly (by errorful learning). In addition, explicit but not implicit motor learners displayed more T3-Fz co-activation during golf putting under pressure, implying that verbal-analytical processing of putting movements increased under pressure. These findings provide neuropsychological evidence that supports claims that implicit motor learning can be used to limit movement specific reinvestment.

Reinvestment and Falls in Community-Dwelling Older Adults

Background. Falls are common in older adults and have many adverse consequences. In an attempt to prevent further incidents, elder fallers may consciously monitor and control their movements. Ironically, conscious movement control may be one factor that contributes to disruption of automaticity of walking, increasing the likelihood of subsequent falls. Objective. The Movement Specific Reinvestment Scale (MSRS), which aims to measure the propensity for movement-related self-consciousness and for conscious processing of movement, was used to try to discriminate elder fallers from non-fallers. Methods. Fifty-two volunteer older adults, aged 65 or above, participated. In addition to the 10-item MSRS, participants completed the Mini-Mental State Examination questionnaire, Timed “Up & Go” test, and Four Word Short-Term Memory test. Demographics including age, gender, and history of falling were collected. Results. Elder fallers scored significantly higher than non-fallers on both the movement self-consciousness and conscious motor processing components of the MSRS. Logistic regression revealed a significant association between the MSRS (conscious motor processing component) and “faller or non-faller” status. Conclusions. Elder fallers may have a higher propensity to consciously control their movements. The MSRS shows potential as a clinical tool with which to predict falls in the elderly, as well as to gain insight into the perception of safety during walking in any impaired patient.

Performance Breakdown in Sport: The Roles of Reinvestment and Verbal Knowledge.

ptimal performance is the goal of all athletes, particularly when rewards are high. In pressure situ-ations, many athletes perform suboptimally despite ahigh motivation to succeed (Baumeister & Showers,1986). The phenomenon of paradoxical performancebreakdown has been observed under pressure (Bau-meister, 1984; Beilock & Carr, 2001), during competition(Baumeister, 1984; Seta, Paulus, & Risner, 1977), and inthe presence of an audience (Baumeister, 1982, 1984;Schlenker, 1980) or evaluative others (Martens LGray, 2004; Lewis & Linder, 1997).Gray (2004), for example, found that expertise inbaseball batting was associated with poor awareness ofonline movement kinematics (see also Beilock & Carr,2001). Attending to movement dynamics degraded bat-ting performance among expert batters. Gray alsofound that performance pressure tended to increaseskill-focused attention, supporting the idea that devot-ing attentional resources to normally automatic pro-cesses may mediate choking in sport. In a series ofpapers demonstrating a benefit of focusing externallyon movement outcome rather than internally on move-ment dynamics, Wulf and colleagues reported on theimportance of attentional focus (e.g., McNevin, Shea, W Shea & Wulf, 1999; Wulf, McNevin, & Shea,2001). McNevin et al

Probing the allocation of attention in implicit (motor) learning

Abstract We investigated the attention demands associated with implicit and explicit (motor) learning and performance using a probe reaction time paradigm. Two groups of participants learned a golf putting task over eight blocks of 50 trials performed from different distances. One group (errorless learning) began putting from the shortest distance (25 cm) and moved progressively back to the furthest distance (200 cm). A second group (errorful learning) began putting from the furthest distance (200 cm) and moved progressively closer (25 cm). Retention tests were used to assess learning in the two conditions, followed by transfer tests in which participants used either an unusual putter or a very unusual putter. Transfer to the unusual putters had an equivalent effect on the performance of both errorless and errorful learners, but probe reaction times were unaffected in the errorless learners, suggesting that execution of their movements was associated with reduced attention demands. Reducing errors during initial learning trials may encourage an implicit mode of learning and lower the demand for cognitive resources in subsequent performance.

EEG activity during the verbal-cognitive stage of motor skill acquisition

This study examined changes in EEG activity associated with motor performance during the verbal-cognitive stage of skill learning. Participants (n=14) were required to practice a sequential finger tapping task. EEG activity was recorded both before and after short-term practice, during finger tapping and during two control conditions. EEG power (Fz, Cz, Pz, T3, T4) and coherence (T3-Fz, T4-Fz, Fz-Cz, Fz-Pz) were computed for the theta (4-8 Hz), slow alpha (8-10 Hz), fast alpha (10-12 Hz), slow beta (12-20 Hz), and fast beta (20-28 Hz) bandwidths. Changes in motor performance were rapid during the very early stages of practice and then slowed in accord with the law of practice. These changes were accompanied by increases of theta power at Fz and beta coherence at T4-Fz, suggesting that progression through the verbal-cognitive stage of a sequential finger tapping task is accompanied by more narrowed attention and improved mapping between the stimuli and the finger movements.

Rules for reinvestment

In response to further validation of the Reinvestment Scale by Chell, Graydon, Crowley, and Child, a structural equation model was formulated to clarify the relationship between the predisposition for conscious control of an otherwise automatic motor skill (reinvestment), verbal knowledge, and performance degradation under pressure. The model implies that the more task-relevant movement knowledge the performer holds, the stronger the propensity to reinvest.