The power law repealed: the case for an exponential law of practice

Accounting for speed-accuracy tradeoff in perceptual learning

In the perceptual learning (PL) literature, researchers typically focus on improvements in accuracy, such as d'. In contrast, researchers who investigate the practice of cognitive skills focus on improvements in response times (RT). Here, we argue for the importance of accounting for both accuracy and RT in PL experiments, due to the phenomenon of speed-accuracy tradeoff (SAT): at a given level of discriminability, faster responses tend to produce more errors. A formal model of the decision process, such as the diffusion model, can explain the SAT. In this model, a parameter known as the drift rate represents the perceptual strength of the stimulus, where higher drift rates lead to more accurate and faster responses. We applied the diffusion model to analyze responses from a yes-no coherent motion detection task. The results indicate that observers do not use a fixed threshold for evidence accumulation, so changes in the observed accuracy may not provide the most appropriate estimate of learning. Instead, our results suggest that SAT can be accounted for by a modeling approach, and that drift rates offer a promising index of PL.

Less is more: latent learning is maximized by shorter training sessions in auditory perceptual learning

Background

The time course and outcome of perceptual learning can be affected by the length and distribution of practice, but the training regimen parameters that govern these effects have received little systematic study in the auditory domain. We asked whether there was a minimum requirement on the number of trials within a training session for learning to occur, whether there was a maximum limit beyond which additional trials became ineffective, and whether multiple training sessions provided benefit over a single session.

Methodology/Principal Findings

We investigated the efficacy of different regimens that varied in the distribution of practice across training sessions and in the overall amount of practice received on a frequency discrimination task. While learning was relatively robust to variations in regimen, the group with the shortest training sessions (∼8 min) had significantly faster learning in early stages of training than groups with longer sessions. In later stages, the group with the longest training sessions (>1 hr) showed slower learning than the other groups, suggesting overtraining. Between-session improvements were inversely correlated with performance; they were largest at the start of training and reduced as training progressed. In a second experiment we found no additional longer-term improvement in performance, retention, or transfer of learning for a group that trained over 4 sessions (∼4 hr in total) relative to a group that trained for a single session (∼1 hr). However, the mechanisms of learning differed; the single-session group continued to improve in the days following cessation of training, whereas the multi-session group showed no further improvement once training had ceased.

Conclusions/Significance

Shorter training sessions were advantageous because they allowed for more latent, between-session and post-training learning to emerge. These findings suggest that efficient regimens should use short training sessions, and optimized spacing between sessions.

Task-related versus stimulus-specific practice

When people repeatedly practice the same cognitive task, their response times (RT) invariably decrease. Dutilh, Vandekerckhove, Tuerlinckx, and Wagenmakers (2009) argued that the traditional focus on how mean RT decreases with practice offers limited insight; their diffusion model analysis showed that the effect of practice is multifaceted, involving an increase in rate of information processing, a decrease in response caution, adjusted response bias, and, unexpectedly, a strong decrease in nondecision time. In this study, we aim to further disentangle these effects into stimulus-specific and task-related components. The data of a transfer experiment, in which repeatedly presented sets and new sets of stimuli were alternated, show that the practice effects on both speed of information processing and time needed for peripheral processing are partly task-related and partly stimulus-specific. The effects on response caution and response bias appear to be task-related. This diffusion model decomposition provides a perspective on practice that is more detailed and more informative than the traditional analysis of mean RT.

Training the developing brain: a neurocognitive perspective

Developmental training studies are important to increase our understanding of the potential of the developing brain by providing answers to questions such as: “Which functions can and which functions cannot be improved as a result of practice?,” “Is there a specific period during which training has more impact?,” and “Is it always advantageous to train a particular function?”In addition, neuroimaging methods provide valuable information about the underlying mechanisms that drive cognitive plasticity. In this review, we describe how neuroscientific studies of training effects inform us about the possibilities of the developing brain, pointing out that childhood is a special period during which training may have different effects. We conclude that there is much complexity in interpreting training effects in children. Depending on the type of training and the level of maturation of the individual, training may influence developmental trajectories in different ways. We propose that the immature brain structure might set limits on how much can be achieved with training, but that the immaturity can also have advantages, in terms of flexibility for learning.

Computer-based learning of spelling skills in children with and without dyslexia

Our spelling training software recodes words into multisensory representations comprising visual and auditory codes. These codes represent information about letters and syllables of a word. An enhanced version, developed for this study, contains an additional phonological code and an improved word selection controller relying on a phoneme-based student model. We investigated the spelling behavior of children by means of learning curves based on log-file data of the previous and the enhanced software version. First, we compared the learning progress of children with dyslexia working either with the previous software (n = 28) or the adapted version (n = 37). Second, we investigated the spelling behavior of children with dyslexia (n = 37) and matched children without dyslexia (n = 25). To gain deeper insight into which factors are relevant for acquiring spelling skills, we analyzed the influence of cognitive abilities, such as attention functions and verbal memory skills, on the learning behavior. All investigations of the learning process are based on learning curve analyses of the collected log-file data. The results evidenced that those children with dyslexia benefit significantly from the additional phonological cue and the corresponding phoneme-based student model. Actually, children with dyslexia improve their spelling skills to the same extent as children without dyslexia and were able to memorize phoneme to grapheme correspondence when given the correct support and adequate training. In addition, children with low attention functions benefit from the structured learning environment. Generally, our data showed that memory sources are supportive cognitive functions for acquiring spelling skills and for using the information cues of a multi-modal learning environment.

Power laws from individual differences in learning and forgetting: mathematical analyses

It has frequently been claimed that learning performance improves with practice according to the so-called “Power Law of Learning.” Similarly, forgetting may follow a power law. It has been shown on the basis of extensive simulations that such power laws may emerge through averaging functions with other, nonpower function shapes. In the present article, we supplement these simulations with a mathematical proof that power functions will indeed emerge as a result of averaging over exponential functions, if the distribution of learning rates follows a gamma distribution, a uniform distribution, or a half-normal function. Through a number of simulations, we further investigate to what extent these findings may affect empirical results in practice.

A spatial explicit strategy reduces error but interferes with sensorimotor adaptation

Although sensorimotor adaptation is typically thought of as an implicit form of learning, it has been shown that participants who gain explicit awareness of the nature of the perturbation during adaptation exhibit more learning than those who do not. With rare exceptions, however, explicit awareness is typically polled at the end of the study. Here, we provided participants with either an explicit spatial strategy or no instructions before learning. Early in learning, explicit instructions greatly reduced movement errors but also resulted in increased trial-to-trial variability and longer reaction times. Late in adaptation, performance was indistinguishable between the explicit and implicit groups, but the mechanisms underlying performance improvements remained fundamentally different, as revealed by catch trials. The progression of implicit recalibration in the explicit group was modulated by the use of an explicit strategy: these participants showed a lower level of recalibration as well as decreased aftereffects. This phenomenon may be due to the reduced magnitude of errors made to the target during adaptation or inhibition of implicit learning mechanisms by explicit processing.

Adaptation to continuous perturbation of balance: progressive reduction of postural muscle activity with invariant or increasing oscillations of the center of mass depending on perturbation frequency and vision conditions

We investigated the adaptation of balancing behavior during a continuous, predictable perturbation of stance consisting of 3-min backward and forward horizontal sinusoidal oscillations of the support base. Two visual conditions (eyes-open, EO; eyes-closed, EC) and two oscillation frequencies (LF, 0.2 Hz; HF, 0.6 Hz) were used. Center of Mass (CoM) and Center of Pressure (CoP) oscillations and EMG of Soleus (Sol) and Tibialis Anterior (TA) were recorded. The time course of each variable was estimated through an exponential model. An adaptation index allowed comparison of the degree of adaptation of different variables. Muscle activity pattern was initially prominent under the more challenging conditions (HF, EC and EO; LF, EC) and diminished progressively to reach a steady state. At HF, the behavior of CoM and CoP was almost invariant. The time-constant of EMG adaptation was shorter for TA than for Sol. With EC, the adaptation index showed a larger decay in the TA than Sol activity at the end of the balancing trial, pointing to a different role of the two muscles in the adaptation process. At LF, CoM and CoP oscillations increased during the balancing trial to match the platform translations. This occurred regardless of the different EMG patterns under EO and EC. Contrary to CoM and CoP, the adaptation of the muscle activities had a similar time-course at both HF and LF, in spite of the two frequencies implying a different number of oscillation cycles. During adaptation, under critical balancing conditions (HF), postural muscle activity is tuned to that sufficient for keeping CoM within narrow limits. On the contrary, at LF, when vision permits, a similar decreasing pattern of muscle activity parallels a progressive increase in CoM oscillation amplitude, and the adaptive balancing behavior shifts from the initially reactive behavior to one of passive riding the platform. Adaptive balance control would rely on on-line computation of risk of falling and sensory inflow, while minimizing balance challenge and muscle effort. The results from this study contribute to the understanding of plasticity of the balance control mechanisms under posture-challenging conditions.

Model discrimination through adaptive experimentation

An ideal experiment is one in which data collection is efficient and the results are maximally informative. This standard can be difficult to achieve because of uncertainties about the consequences of design decisions. We demonstrate the success of a Bayesian adaptive method (adaptive design optimization, ADO) in optimizing design decisions when comparing models of the time course of forgetting. Across a series of testing stages, ADO intelligently adapts the retention interval in order to maximally discriminate power and exponential models. Compared with two different control (non-adaptive) methods, ADO distinguishes the models decisively, with the results unambiguously favoring the power model. Analyses suggest that ADO's success is due in part to its flexibility in adjusting to individual differences. This implementation of ADO serves as an important first step in assessing its applicability and usefulness to psychology.

Objective assessment of operator performance during ultrasound-guided procedures

PURPOSE

Simulation permits objective assessment of operator performance in a controlled and safe environment. Image-guided procedures often require accurate needle placement, and we designed a system to monitor how ultrasound guidance is used to monitor needle advancement toward a target. The results were correlated with other estimates of operator skill.

METHODS

The simulator consisted of a tissue phantom, ultrasound unit, and electromagnetic tracking system. Operators were asked to guide a needle toward a visible point target. Performance was video-recorded and synchronized with the electromagnetic tracking data. A series of algorithms based on motor control theory and human information processing were used to convert raw tracking data into different performance indices. Scoring algorithms converted the tracking data into efficiency, quality, task difficulty, and targeting scores that were aggregated to create performance indices. After initial feasibility testing, a standardized assessment was developed. Operators (N = 12) with a broad spectrum of skill and experience were enrolled and tested. Overall scores were based on performance during ten simulated procedures. Prior clinical experience was used to independently estimate operator skill.

RESULTS

When summed, the performance indices correlated well with estimated skill. Operators with minimal or no prior experience scored markedly lower than experienced operators. The overall score tended to increase according to operator's clinical experience. Operator experience was linked to decreased variation in multiple aspects of performance. The aggregated results of multiple trials provided the best correlation between estimated skill and performance. A metric for the operator's ability to maintain the needle aimed at the target discriminated between operators with different levels of experience.

CONCLUSIONS

This study used a highly focused task model, standardized assessment, and objective data analysis to assess performance during simulated ultrasound-guided needle placement. The performance indices were closely related to operator experience.

Naturalistic approaches to sensorimotor control

Human sensorimotor control has been predominantly studied using fixed tasks performed under laboratory conditions. This approach has greatly advanced our understanding of the mechanisms that integrate sensory information and generate motor commands during voluntary movement. However, experimental tasks necessarily restrict the range of behaviors that are studied. Moreover, the processes studied in the laboratory may not be the same processes that subjects call upon during their everyday lives. Naturalistic approaches thus provide an important adjunct to traditional laboratory-based studies. For example, wearable self-contained tracking systems can allow subjects to be monitored outside the laboratory, where they engage spontaneously in natural everyday behavior. Similarly, advances in virtual reality technology allow laboratory-based tasks to be made more naturalistic. Here, we review naturalistic approaches, including perspectives from psychology and visual neuroscience, as well as studies and technological advances in the field of sensorimotor control.

From Intention to Input: Motor Cognition, Motor Performance, and the Control of Technology

Fundamental knowledge of motor cognition is an important component in a human factors repertoire, and this chapter serves as a guide to the history, theory, and application of motor cognition research.“From intention to input” captures the scope of this chapter in that cognitive theories of motor control, neural control of movement, and the effects of feedback on movement are all discussed. The chapter progresses from an overview and history of motor cognition theories down to the neural basis for movement, then to an application of these theories via the study of specific actions. From there, rooted in the scientist-practitioner paradigm of human factors, the chapter covers applied considerations for designing control tasks and their associated inputs, taking into account individual differences in motor cognition and control and identifying critical issues in designing for input. General, applied guidelines are provided for use with current and future systems that have a motor cognition component.

Effect of D-amphetamine on inhibition and motor planning as a function of baseline performance

RATIONALE

Baseline performance has been reported to predict dopamine (DA) effects on working memory, following an inverted-U pattern. This pattern may hold true for other executive functions that are DA-sensitive.

OBJECTIVES

The objective of this study is to investigate the effect of D: -amphetamine, an indirect DA agonist, on two other putatively DA-sensitive executive functions, inhibition and motor planning, as a function of baseline performance.

METHODS

Participants with no prior stimulant exposure participated in a double-blind crossover study of a single dose of 0.3 mg/kg, p.o. of D: -amphetamine and placebo. Participants were divided into high and low groups, based on their performance on the antisaccade and predictive saccade tasks on the baseline day. Executive functions, mood states, heart rate and blood pressure were assessed before (T0) and after drug administration, at 1.5 (T1), 2.5 (T2) and 3.5 h (T3) post-drug.

RESULTS

Antisaccade errors decreased with D: -amphetamine irrespective of baseline performance (p = 0.025). For antisaccade latency, participants who generated short-latency antisaccades at baseline had longer latencies on D: -amphetamine than placebo, while those with long-latency antisaccades at baseline had shorter latencies on D: -amphetamine than placebo (drug x group, p = 0.04). D: -amphetamine did not affect motor planning. Ratings of mood improved on D: -amphetamine (p < 0.001). Magnitude of D: -amphetamine-induced changes in elation was related to baseline reaction time variability.

CONCLUSIONS

D: -amphetamine reduced antisaccade error rates in healthy controls, replicating and extending findings with DA agonists in clinical populations. D: -amphetamine had baseline-dependent effects on antisaccade latency, consistent with an inverted-U relationship between performance and DA activity.

A crossed random effects diffusion model for speeded semantic categorization decisions

Choice reaction times (RTs) are often used as a proxy measure of typicality in semantic categorization studies. However, other item properties have been linked to choice RTs as well. We apply a tailored process model of choice RT to a speeded semantic categorization task in order to deconfound different sources of variability in RT. Our model is based on a diffusion model of choice RT, extended to include crossed random effects (of items and participants). This model retains the interesting process interpretation of the diffusion model's parameters, but it can be applied to choice RTs even in the case where there are few or no repeated measurements of each participant-item combination. Different aspects of the response process are then linked to different types of item properties. A typicality measure turns out to predict the rate of information uptake, while a lexicographic measure predicts the stimulus encoding time. Accessibility measures cannot reliably predict any component of the decision process.

A diffusion model decomposition of the practice effect

When people repeatedly perform the same cognitive task, their mean response times (RTs) invariably decrease. The mathematical function that best describes this decrease has been the subject of intense debate. Here, we seek a deeper understanding of the practice effect by simultaneously taking into account the changes in accuracy and in RT distributions with practice, both for correct and error responses. To this end, we used the Ratcliff diffusion model, a successful model of two-choice RTs that decomposes the effect of practice into its constituent psychological processes. Analyses of data from a 10,000-trial lexical decision task demonstrate that practice not only affects the speed of information processing, but also response caution, response bias, and peripheral processing time. We conclude that the practice effect consists of multiple subcomponents, and that it may be hazardous to abstract the interactive combination of these subcomponents in terms of a single output measure such as mean RT for correct responses. Supplemental materials may be downloaded from http://pbr.psychonomic-journals.org/content/supplemental.

How much practice is needed to produce perceptual learning?

We examined the amount of practice needed to improve performance on 10-AFC face- and texture identification tasks. On Day 1, subjects were grouped by amount of practice: a control group had 0 trials of practice, and several experimental groups had practice that ranged from 1 to 40 trials per condition. On Day 2, all groups performed 40 trials per condition of the trained task. The effect of practice was estimated by comparing performance across groups on Day 2. In both tasks, increasing practice was associated with greater learning, but surprisingly small amounts of practice were required to improve performance. In the face identification task, for example, only one trial per condition on Day 1 was required to increase performance relative to the control group at the start of testing on Day 2. In the texture identification task, five trials per condition on Day 1 were required to increase performance relative to the control group. In both tasks, the advantage associated with small amounts of practice declined during the Day 2 session due to larger within-session learning in the control group. Sleep had little to no effect on learning; performance depended primarily on the amount of preceding practice.

Adaptation and learning: characteristic time scales of performance dynamics

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning.

Statistics of natural movements are reflected in motor errors

Humans use their arms to engage in a wide variety of motor tasks during everyday life. However, little is known about the statistics of these natural arm movements. Studies of the sensory system have shown that the statistics of sensory inputs are key to determining sensory processing. We hypothesized that the statistics of natural everyday movements may, in a similar way, influence motor performance as measured in laboratory-based tasks. We developed a portable motion-tracking system that could be worn by subjects as they went about their daily routine outside of a laboratory setting. We found that the well-documented symmetry bias is reflected in the relative incidence of movements made during everyday tasks. Specifically, symmetric and antisymmetric movements are predominant at low frequencies, whereas only symmetric movements are predominant at high frequencies. Moreover, the statistics of natural movements, that is, their relative incidence, correlated with subjects' performance on a laboratory-based phase-tracking task. These results provide a link between natural movement statistics and motor performance and confirm that the symmetry bias documented in laboratory studies is a natural feature of human movement.

Skill acquisition while operating in-vehicle information systems: interface design determines the level of safety-relevant distractions

OBJECTIVE

This study tested whether the ease of learning to use human-machine interfaces of in-vehicle information systems (IVIS) can be assessed at standstill.

BACKGROUND

Assessing the attentional demand of IVIS should include an evaluation of ease of learning, because the use of IVIS at low skill levels may create safety-relevant distractions.

METHOD

Skill acquisition in operating IVIS was quantified by fitting the power law of practice to training data sets collected in a driving study and at standstill. Participants practiced manual destination entry with two route guidance systems differing in cognitive demand. In Experiment 1, a sample of middle-aged participants was trained while steering routes of varying driving demands. In Experiment 2, another sample of middle-aged participants was trained at standstill.

RESULTS

In Experiment 1, display glance times were less affected by driving demands than by total task times and decreased at slightly higher speed-up rates (0.02 higher on average) than task times collected at standstill in Experiment 2. The system interface that minimized cognitive demand was operated more quickly and was easier to learn. Its system delays increased static task times, which still predicted 58% of variance in display glance times compared with even 76% for the second system.

CONCLUSION

The ease of learning to use an IVIS interface and the decrease in attentional demand with training can be assessed at standstill.

APPLICATION

Fitting the power law of practice to static task times yields parameters that predict display glance times while driving, which makes it possible to compare interfaces with regard to ease of learning.

„Do it again and again. And again?”

Zusammenfassung. Die wiederholte Bearbeitung eines identisch oder parallel konstruierten kognitiven Fähigkeitstests führt in der Regel zu einer deutlich verbesserten Leistung. Zunächst wird ein Überblick zur bestehenden empirischen Befundlage zu Testwiederholungseffekten sowie zu möglichen Verursachungen gegeben. Als kognitionspsychologischer Anknüpfungspunkt dient hierbei Ackermans (1988) Theorie zum Fertigkeitserwerb. Danach wird in der vorgestellten Studie am Beispiel eines Tests zum räumlichen Vorstellungsvermögen (Relative Position, REP) die Auswirkung von Testwiederholungseffekten auf die Testleistung der Probanden sowie die Testreliabilität und -validität untersucht. 156 Bewerber in einem Auswahlprogramm für Nachwuchsflugzeugführer bearbeiteten insgesamt zehnmal hintereinander das jeweils fünfminütige Testverfahren. Nach der fünften Testdurchführung weisen die erzielten Zuwächse keine praktische Bedeutsamkeit mehr auf. Reliabilität und Validität des Tests werden durch die Übung nicht beeinträchtigt, sondern scheinen eher noch anzusteigen. Konsequenzen für die diagnostische Anwendung werden diskutiert.

Comparing time-accuracy curves: beyond goodness-of-fit measures

The speed-accuracy trade-off (SAT) is a ubiquitous phenomenon in experimental psychology. One popular strategy for controlling SAT is to use the response signal paradigm. This paradigm produces time-accuracy curves (or SAT functions), which can be compared across different experimental conditions. The typical approach to analyzing time-accuracy curves involves the comparison of goodness-of-fit measures (e.g., adjusted-R2), as well as interpretation of point estimates. In this article, we examine the implications of this approach and discuss a number of alternative methods that have been successfully applied in the cognitive modeling literature. These methods include model selection criteria (the Akaike information criterion and the Bayesian information criterion) and interval estimation procedures (bootstrap and Bayesian). We demonstrate the utility of these methods with a hypothetical data set.

Task precision at transfer determines specificity of perceptual learning

Perceptual learning, the improvement in performance with practice, reflects plasticity in the adult visual system. We challenge a standard claim that specificity of perceptual learning depends on task difficulty during training, instead showing that specificity, or conversely transfer, is primarily controlled by the precision demands (i.e., orientation difference) of the transfer task. Thus, for an orientation discrimination task, transfer of performance improvement is observed in low-precision transfer tasks, while specificity of performance improvement is observed in high-precision transfer tasks, regardless of the precision of initial training. The nature of specificity places important constraints on mechanisms of transfer in visual learning. These results contribute to understanding generalization of practiced improvements that may be key to the development of expertise and for applications in remediation.

A hierarchical approach for fitting curves to response time measurements

Understanding how response time (RT) changes with manipulations has been critical in distinguishing among theories in cognition. It is well known that aggregating data distorts functional relationships (e.g., Estes, 1956). Less well appreciated is a second pitfall: Minimizing squared errors (i.e., OLS regression) also distorts estimated functional forms with RT data. We discuss three properties of RT that should be modeled for accurate analysis and, on the basis of these three properties, provide a hierarchical Weibull regression model for regressing RT onto covariates. Hierarchical regression model analysis of lexical decision task data reveals that RT decreases as a power function of word frequency with the scale of RT decreasing 11% for every doubling of word frequency. A detailed discussion of the model and analysis techniques are presented as archived materials and may be downloaded from www.psychonomic.org/archive.

Assessing individual differences in categorical data

In cognitive modeling, data are often categorical observations taken over participants and items. Usually subsets of these observations are pooled and analyzed by a cognitive model assuming the category counts come from a multinomial distribution with the same model parameters underlying all observations. It is well known that if there are individual differences in participants and/or items, a model analysis of the pooled data may be quite misleading, and in such cases it may be appropriate to augment the cognitive model with parametric random effects assumptions. On the other hand, if random effects are incorporated into a cognitive model that is not needed, the resulting model may be more flexible than the multinomial model that assumes no heterogeneity, and this may lead to overfitting. This article presents Monte Carlo statistical tests for directly detecting individual participant and/or item heterogeneity that depend only on the data structure itself. These tests are based on the fact that heterogeneity in participants and/or items results in overdispersion of certain category count statistics. It is argued that the methods developed in the article should be applied to any set of participant x item categorical data prior to cognitive model-based analyses.

Evidence for criterion shifts in visual perceptual learning: data and implications

Work on visual perceptual learning for contrast detection has shown that reliable decreases in detection thresholds are accompanied by reliable increases in false alarm rates (Wenger & Rasche, 2006). The present study assesses the robustness and replicability of these changes, demonstrating that they are independent of a variety of task demands (i.e., the specific method used for perceptual practice and threshold estimation) and the presence or absence of trial-by-trial feedback and that the source of the increases can be found in shifts in changes in sensitivity and in bias for detection, identification, or both. Although the increase in false alarm rates suggests a strategic shift in response criteria for detection, we demonstrate that there are multiple potential explanations, including explanations that do not require strategic shifts on the part of the observer. The empirical evidence and analysis of alternative explanations reinforce the inference that visual perceptual learning may involve more than changes in perceptual sensitivity and that cortical circuits beyond the primary visual areas may be involved.

The statistical determinants of adaptation rate in human reaching

Rapid reaching to a target is generally accurate but also contains random and systematic error. Random errors result from noise in visual measurement, motor planning, and reach execution. Systematic error results from systematic changes in the mapping between the visual estimate of target location and the motor command necessary to reach the target (e.g., new spectacles, muscular fatigue). Humans maintain accurate reaching by recalibrating the visuomotor system, but no widely accepted computational model of the process exists. Given certain boundary conditions, a statistically optimal solution is a Kalman filter. We compared human to Kalman filter behavior to determine how humans take into account the statistical properties of errors and the reliability with which those errors can be measured. For most conditions, human and Kalman filter behavior was similar: Increasing measurement uncertainty caused similar decreases in recalibration rate; directionally asymmetric uncertainty caused different rates in different directions; more variation in systematic error increased recalibration rate. However, behavior differed in one respect: Inserting random error by perturbing feedback position causes slower adaptation in Kalman filters but had no effect in humans. This difference may be due to how biological systems remain responsive to changes in environmental statistics. We discuss the implications of this work.

Strategy transitions during cognitive skill learning in younger and older adults: effects of interitem confusability

Groups of young and old adults were trained for four sessions on a set of 24 alphabet-arithmetic problems. Problem sets were either highly confusable or highly distinct. Power-function and mixture-model fits to the means and standard deviations of the acquisition data, resolved at the participant problem level, were compared. "Shallow" power functions signaled that a problem was computed throughout training; "humped" mixture functions signaled a shift from slow computed solutions to fast retrieved solutions. Not surprisingly, shifts to retrieval occurred later for confusable problems, but there were also fewer shifts in that condition. Failures to shift, even after extended practice, suggest that retrieving problem solutions is an elective strategy, and not an automatic concomitant of skill training. Participants can be viewed as choosing between strategies that trade off benefits in speed against costs in accuracy. Older adults showed few retrieval solutions in either condition, perhaps because of their emphasis on accuracy.

Impulsive decision-making: Learning to gamble wisely?

A decade ago, Bechara et al. [Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7-15] published a paper in Cognition, introducing a Gambling Task which was designed to mimic everyday decision-making. Since then, the task has been computerized, its decision-making components have been scrutinized, and it has been employed in various patient groups, such as pathological gamblers, substance abusers, and so forth. Time and again it has been shown that while normal controls perform well on the task, it is the various target populations under scrutiny who exhibit poor performance. Yet, as we show in this paper, a total of 46% of normal individuals exhibited poor performance on the task, indicating a lack of learning. We argue that while so much importance has been placed on contrasting patients with controls, perhaps the real emphasis should lie in distinguishing among different individual profiles of performance on the task, irrespective of clinical classification. Our basic recommendation is to look at the individual data, pool when you can, and only then to contrast groups.

Multivariate neurocognitive and emotional profile of a mannosidosis murine model for therapy assessment

alpha-Mannosidosis is a lysosomal storage disorder caused by lysosomal alpha-mannosidase (LAMAN) deficiency that leads to neurocognitive dysfunctions, psychotic symptoms and emotional changes in human patients. A murine mannosidosis model, LAMAN-deficient mice, was examined on a behavioral task battery that included test for neuromotor, exploratory and neurocognitive (spatial learning and memory) abilities, and multivariate statistical analyses were used to identify behavioral and neurocognitive domains that are most heavily affected by LAMAN deficiency. In addition, we further investigated synaptic plasticity recordings on hippocampal slices that may relate to these behavioral alterations. Correlation analysis revealed significant intra- and intertask correlations and factor analysis that included all 21 behavioral variables identified three main factors (exploration/emotionality, locomotion and learning/memory abilities). Significant correlations were observed between genotype, and factor 1 (exploration/emotionality) and factor 3 (learning/memory abilities). Discriminant function analysis showed that "path length in the open field test" and "time spent in the target quadrant during the water maze probe trial" were the most decisive variables to distinguish between the genotypes. We therefore suggest that these variables would be especially important in forthcoming therapy assessment experiments using this murine mannosidosis model. LAMAN-deficient mice displayed severe changes in synaptic plasticity, which may have contributed to the neurocognitive impairments observed. The present report further shows that targeted deletion of the LAMAN gene in mice mimics many aspects of human alpha-mannosidosis, and these data provide a basis for future therapeutic experiments.