Mechanisms and neural basis of object and pattern recognition: a study with chess experts

How Time Pressure Modulates Individual Differences in the Functional Connectivity of Chunk Memory in Chess Games

Previous studies on the chess game demonstrated that chess experts strongly rely on the activation of memory chunks to manifest accurate decision-making. Although the chunk memory might be affected by temporal constraints, it is unclear why the performance of chess experts is not significantly dropped under time pressure. In this study, our objective is to examine the variations in cognitive neural mechanisms between chess experts and novices under time pressure. The underlying cognitive neural mechanism was carefully inspected by accessing the chess game performance between 20 local experienced and 20 inexperienced chess players with 1-minute and 5-minute time constraints. In addition, functional near-infrared spectroscopy (fNIRS) recordings were carried out for each individual from the two groups while playing a 1-minute or 5-minute chess game. It was discovered that under temporal constraints, players exhibited different patterns of functional connectivity in frontal-parietal regions, suggesting that temporal stress can enhance segmentation processes in chess games. In particular, the experienced group exhibited significantly enhanced functional connectivity networks under time pressure including the dorsolateral prefrontal cortex, inferior frontal gyrus, supramarginal gyrus, and postcentral gyrus, which demonstrated the important role of the segmentation process for experienced players under time pressure. Our study found that experienced players were able to enhance recall, reorganize, and integrate chunks to improve chess performance under time pressure.

Cost-benefit Tradeoff Mediates the Rule- to Memory-based Processing Transition during Practice

Practice not only improves task performance, but also changes task execution from rule- to memory-based processing by incorporating experiences from practice. However, how and when this change occurs is unclear. We tested the hypothesis that strategy transition in task learning results from cost-benefit analysis. Participants learned two task sequences and were then queried about the task type at a cued sequence and position. Behavioral improvement with practice can be accounted for by a computational model implementing cost-benefit analysis. Model-predicted strategy transition points are related to behavioral slowing and changes in fMRI activation patterns in the dorsolateral prefrontal cortex. Strategy transition is also related to increased pattern separation in the ventromedial prefrontal cortex. The cost-benefit analysis model outperforms alternative models (e.g., both strategies racing for being expressed in behavior) in accounting for empirical data. These findings support cost-benefit analysis as a mechanism of practice-induced strategy shift.

Long-Term Bridge Training Induces Functional Plasticity Changes in the Brain of Early-Adult Individuals

The aim of this study was to investigate the impact of extended bridge expertise on rapid perceptual processing and brain functional plasticity in early adulthood, utilizing functional magnetic resonance imaging (fMRI). In this investigation, we compared 6 high-level college bridge players with 25 college students lacking bridge experience, assessing their intelligence and working memory. Additionally, we scrutinized behavioral performance and whole-brain activation patterns during an image perceptual judgment task. Findings indicated significant group and interaction effects at the behavioral level. Bridge players exhibited prolonged reaction times and enhanced accuracy on card tasks. At the neural level, the activation level of bridge players in the occipital lobe exceeded that of ordinary college students, with more pronounced group effects in the motor area and inferior parietal lobule during card tasks. This implies that bridge expertise in early adulthood induces functional plasticity changes in regions associated with visual processing and automated mathematical computation.

Distinct brain network organizations between club players and novices under different difficulty levels

SIGNIFICANT

Chunk memory is one of the essential cognitive functions for high-expertise (HE) player to make efficient decisions. However, it remains unknown how the neural mechanisms of chunk memory processes mediate or alter chess players' performance when facing different opponents.

AIM

This study aimed at inspecting the significant brain networks associated with chunk memory, which would vary between club players and novices.

APPROACH

Functional networks and topological features of 20 club players (HE) and 20 novice players (LE) were compared at different levels of difficulty by means of functional near-infrared spectroscopy.

RESULTS

Behavioral performance indicated that the club player group was unaffected by differences in difficulty. Furthermore, the club player group demonstrated functional connectivity among the dorsolateral prefrontal cortex, the frontopolar cortex, the supramarginal gyrus, and the subcentral gyrus, as well as higher clustering coefficients and lower path lengths in the high-difficulty task.

CONCLUSIONS

The club player group illustrated significant frontal-parietal functional connectivity patterns and topological characteristics, suggesting enhanced chunking processes for improved chess performance.

Examining the importance of local and global patterns for familiarity detection in soccer action sequences

Pattern recognition is a defining characteristic of expertise across multiple domains. Given the dynamic interactions at local and global levels, team sports can provide a vehicle for investigating skilled pattern recognition. The aims of this study were to investigate whether global patterns could be recognised on the basis of localised relational information and if relations between certain display features were more important than others for successful pattern recognition. Elite (n = 20), skilled (n = 34) and less-skilled (n = 37) soccer players completed three recognition paradigms of stimuli presented in point-light format across three counterbalanced conditions: 'whole-part'; 'part-whole'; and 'whole-whole'. 'Whole' clips represented a 11 vs. 11 soccer match and 'part' clips presented the same passages of play with only two central attacking players or two peripheral players shown. Elite players recognised significantly more accurately than the skilled and less-skilled groups. Participants were significantly more accurate in the 'whole-whole' condition compared to others, and recognised stimuli featuring the two central attacking players significantly more accurately than those featuring peripheral players. Findings provide evidence that elite players can encode localised relations and then extrapolate this information to recognise more global macro patterns.

Expertise increases planning depth in human gameplay

A hallmark of human intelligence is the ability to plan multiple steps into the future1,2. Despite decades of research3-5, it is still debated whether skilled decision-makers plan more steps ahead than novices6-8. Traditionally, the study of expertise in planning has used board games such as chess, but the complexity of these games poses a barrier to quantitative estimates of planning depth. Conversely, common planning tasks in cognitive science often have a lower complexity9,10 and impose a ceiling for the depth to which any player can plan. Here we investigate expertise in a complex board game that offers ample opportunity for skilled players to plan deeply. We use model fitting methods to show that human behaviour can be captured using a computational cognitive model based on heuristic search. To validate this model, we predict human choices, response times and eye movements. We also perform a Turing test and a reconstruction experiment. Using the model, we find robust evidence for increased planning depth with expertise in both laboratory and large-scale mobile data. Experts memorize and reconstruct board features more accurately. Using complex tasks combined with precise behavioural modelling might expand our understanding of human planning and help to bridge the gap with progress in artificial intelligence.

Making sense of complexity: A qualitative 'Framework' analysis of naturopathic case management and clinical reasoning

BACKGROUND AND PURPOSE

The clinical encounter is inherently complex and uncertain. Naturopathic clinical practice is shaped by a traditional philosophy and practice guiding principles, with a therapeutic framework that incorporates a complex inter-systems approach. It is possible that this foundation may orient naturopathic practitioners to manage clinical complexity and uncertainty in a distinct manner. The aim of this study is to explore the perceptions of experienced naturopathic practitioners to the management of clinical complexity within naturopathic care.

MATERIALS AND METHODS

Twenty experienced Australian naturopathic practitioners participated across four focus groups, responding to semi-structured questions regarding their clinical reasoning strategies and case management processes. The data were analysed using a seven step Framework analysis method.

RESULTS

Three primary themes were identified: i) patient is encountered as a whole entity, ii) clinical reasoning is ampliative and explicative, and iii) treatment reflects systems thinking. Participants perceived a focus on the connections between various case elements, building a comprehensive internalised schematic of each case. Participants saw treatments as meeting various needs including prevention, symptom alleviation, causal mitigation, and support of innate healing processes.

CONCLUSION

Naturopathic practitioners perceive they clinically embody the traditional holistic philosophy of naturopathy as a systems orientation, incorporating traditional and contemporary bioscience knowledge. This appears to shape a distinct naturopathic case management approach, oriented to working with patients in a complexity-informed manner.

Visual expertise modulates resting-state brain network dynamics in radiologists: a degree centrality analysis

Visual expertise reflects accumulated experience in reviewing domain-specific images and has been shown to modulate brain function in task-specific functional magnetic resonance imaging studies. However, little is known about how visual experience modulates resting-state brain network dynamics. To explore this, we recruited 22 radiology interns and 22 matched healthy controls and used resting-state functional magnetic resonance imaging (rs-fMRI) and the degree centrality (DC) method to investigate changes in brain network dynamics. Our results revealed significant differences in DC between the RI and control group in brain regions associated with visual processing, decision making, memory, attention control, and working memory. Using a recursive feature elimination-support vector machine algorithm, we achieved a classification accuracy of 88.64%. Our findings suggest that visual experience modulates resting-state brain network dynamics in radiologists and provide new insights into the neural mechanisms of visual expertise.

Spotting lesions in thorax X-rays at a glance: holistic processing in radiology

Radiologists often need only a glance to grasp the essence of complex medical images. Here, we use paradigms and manipulations from perceptual learning and expertise fields to elicit mechanisms and limits of holistic processing in radiological expertise. In the first experiment, radiologists were significantly better at categorizing thorax X-rays when they were presented for 200 ms in an upright orientation than when they were presented upside-down. Medical students, in contrast, were guessing in both situations. When the presentation time was increased to 500 ms, allowing for a couple more glances, the radiologists improved their performance on the upright stimuli, but remained at the same level on the inverted presentation. The second experiment circumvented the holistic processing by immediately cueing a tissue within the X-rays, which may or may not contain a nodule. Radiologists were again better than medical students at recognizing whether the cued tissue was a nodule, but this time neither the inverted presentation nor additional time affected their performance. Our study demonstrates that holistic processing is most likely a continuous recurring process which is just as susceptible to the inversion effect as in other expertise domains. More importantly, our study also indicates that holistic-like processing readily occurs in complex stimuli (e.g., whole thorax X-rays) but is more difficult to find in uniform single parts of such stimuli (e.g., nodules).

Surface-Based Cortical Measures in Multimodal Association Brain Regions Predict Chess Expertise

The complex structure of the brain supports high-order cognition, which is crucial for mastering chess. Surface-based measures, including the fractional dimension (FD) and gyrification index (GI), may be more sensitive in detecting cortical changes relative to volumetric indexes. For this reason, structural magnetic resonance imaging data from 29 chess experts and 29 novice participants were analyzed using the CAT12 toolbox. FD and GI for each brain region were compared between the groups. A multivariate model was used to identify surface-based brain measures that can predict chess expertise. In chess experts, FD is increased in the left frontal operculum (p < 0.01), and this change correlates with the starting age of chess practice (ρ = −0.54, p < 0.01). FD is decreased in the right superior parietal lobule (p < 0.01). Chess expertise is predicted by the FD in a network of fronto-parieto-temporal regions and is associated with GI changes in the middle cingulate gyrus (p < 0.01) and the superior temporal sulcus (p < 0.01). Our findings add to the evidence that chess expertise is based on the complex properties of the brain surface of a network of transmodal association areas important for flexible high-level cognitive functions. Interestingly, these changes are associated with long-lasting practice, suggesting that neuroplastic effects develop over time.

Profiling dynamic decision-makers

From CEOs confronting competition to children playing board games, our professional and personal lives are full of dynamic decisions. Naturally, while playing the role of a decision-maker, people differ. To comprehend and analyze how they differ, first it is necessary to construct a profiling method that classifies dynamic decision-makers. Developing such a method is the main objective of our article. We equate dynamic decision-making with backward inducting. We rely on response times to construct the profiles. Our method has both descriptive power and predictive power: a subject’s profile resembles her reasoning process and forecasts the likelihood of her correctly backward inducting. To test the proposed profiling method, we use data generated by 22 different finite dynamic scenarios from the mobile app Blues and Reds. Our sample consists of 35,826 observations from 6,463 subjects located in 141 countries. We construct the profiles of our subjects, and, in a variety of exercises supported by an array of robustness checks, we successfully establish the predictive power of our profiling method.

Situational Understanding in the Human and the Machine

The Air Force research programs envision developing AI technologies that will ensure battlespace dominance, by radical increases in the speed of battlespace understanding and decision-making. In the last half century, advances in AI have been concentrated in the area of machine learning. Recent experimental findings and insights in systems neuroscience, the biophysics of cognition, and other disciplines provide converging results that set the stage for technologies of machine understanding and machine-augmented Situational Understanding. This paper will review some of the key ideas and results in the literature, and outline new suggestions. We define situational understanding and the distinctions between understanding and awareness, consider examples of how understanding-or lack of it-manifest in performance, and review hypotheses concerning the underlying neuronal mechanisms. Suggestions for further R&D are motivated by these hypotheses and are centered on the notions of Active Inference and Virtual Associative Networks.

Are the advantages of chess expertise on visuo-spatial working-memory capacity domain specific or domain general?

Chess experts have repeatedly demonstrated exceptional recall of chessboards, which is weakened by disruption of the chessboard. However, chess experts still perform better than novices when recalling such disrupted chessboards, suggesting a somewhat generalized expertise effect. In the current study, we examined the extent of this generalized expertise effect on early processing of visuo-spatial working memory (VSWM), by comparing 14 chess experts (Elo rating > 2000) and 15 novices on a change-detection paradigm using disrupted chessboards, where attention had to be selectively deployed to either visual or spatial features, or divided across both features. The paradigm differed in the stimuli used (domain-specific chess pieces vs. novel visual shapes) to evaluate domain-general effects of chess expertise. Both experts and novices had greater memory discriminability for chess stimuli than for the unfamiliar stimuli, suggesting a salience advantage for familiar stimuli. Experts, however, demonstrated better memory discriminability than novices not only for chess stimuli presented on these disrupted chessboards, but also for novel, domain-general stimuli, particularly when detecting spatial changes. This expertise advantage was greater for chessboards with supra-capacity set sizes. For set sizes within the working-memory capacity, the expertise advantage was driven by enhanced selective attention to spatial features by chess experts when compared to visual features. However, any expertise-related VSWM advantage disappeared in the absence of the 8 × 8 chessboard display, which implicates the chessboard display as an essential perceptual aspect facilitating the "expert memory effect" in chess, albeit one that might generalize beyond strictly domain-relevant stimuli.

The impact of early musical training on striatal functional connectivity

Evidence from language, visual and sensorimotor learning suggests that training early in life is more effective. The present work explores the hypothesis that learning during sensitive periods involves distinct brain networks in addition to those involved when learning later in life. Expert pianists were tested who started their musical training early (<7 years of age; n = 21) or late (n = 15), but were matched for total lifetime practice. Motor timing expertise was assessed using a musical scale playing task. Brain activity at rest was measured using fMRI and compared with a control group of nonmusicians (n = 17). Functional connectivity from seeds in the striatum revealed a striatal-cortical-sensorimotor network that was observed only in the early-onset group. In this network, higher connectivity correlated with greater motor timing expertise, which resulted from early/late group differences in motor timing expertise. By contrast, networks that differentiated musicians and nonmusicians, namely a striatal-occipital-frontal-cerebellar network in which connectivity was higher in musicians, tended to not show differences between early and late musicians and not be correlated with motor timing expertise. These results parcel musical sensorimotor neuroplasticity into a set of musicianship-related networks and a distinct set of predominantly early-onset networks. The findings lend support to the possibility that we can learn skills more easily early in development because during sensitive periods we recruit distinct brain networks that are no longer implicated in learning later in life.

Determining Chess Game State from an Image

Identifying the configuration of chess pieces from an image of a chessboard is a problem in computer vision that has not yet been solved accurately. However, it is important for helping amateur chess players improve their games by facilitating automatic computer analysis without the overhead of manually entering the pieces. Current approaches are limited by the lack of large datasets and are not designed to adapt to unseen chess sets. This paper puts forth a new dataset synthesised from a 3D model that is an order of magnitude larger than existing ones. Trained on this dataset, a novel end-to-end chess recognition system is presented that combines traditional computer vision techniques with deep learning. It localises the chessboard using a RANSAC-based algorithm that computes a projective transformation of the board onto a regular grid. Using two convolutional neural networks, it then predicts an occupancy mask for the squares in the warped image and finally classifies the pieces. The described system achieves an error rate of 0.23% per square on the test set, 28 times better than the current state of the art. Further, a few-shot transfer learning approach is developed that is able to adapt the inference system to a previously unseen chess set using just two photos of the starting position, obtaining a per-square accuracy of 99.83% on images of that new chess set. The code, dataset, and trained models are made available online.

Altered Intrinsic and Casual Functional Connectivities of the Middle Temporal Visual Motion Area Subregions in Chess Experts

An outstanding chess player needs to accumulate massive visual and spatial information for chess configurations. Visual motion area (MT) is considered as a brain region specialized for visual motion perception and visuospatial attention processing. However, how long-term chess training shapes the functional connectivity patterns of MT, especially its functional subregions, has rarely been investigated. In our study, using resting-state functional connectivity (RSFC) and Granger causality analysis (GCA), we studied the changed functional couplings of MT subregions between 28 chess master players and 27 gender- and age-matched healthy novices to reveal the neural basis of long-term professional chess training. RSFC analysis identified decreased functional connections between right dorsal-anterior subregion (CI1.R) and left angular gyrus, and increased functional connections between right ventral-anterior MT subregion (CI2.R) and right superior temporal gyrus in chess experts. Moreover, GCA analyses further found increased mutual interactions of left angular gyrus and CI1.R in chess experts compared to novice players. These findings demonstrate that long-term professional chess training could enhance spatial perception and reconfiguration and semantic processing efficiency for superior performance.

Dynamics of the Prefrontal Cortex during Chess-Based Problem-Solving Tasks in Competition-Experienced Chess Players: An fNIR Study

This study aimed to compare the dynamics of the prefrontal cortex (PFC), between adult and adolescent chess players, during chess-based problem-solving tasks of increasing level of difficulty, relying on the identification of changes in oxygenated hemoglobin (HbO2) and hemoglobin (HHb) through the functional near-infrared spectroscopy (fNIRS) method. Thirty male federated chess players (mean age: 24.15 ± 12.84 years), divided into adults and adolescents, participated in this cross-sectional study. Participants were asked to solve three chess problems with different difficulties (low, medium, and high) while changes in HbO2 and HHb were measured over the PFC in real-time with an fNIRS system. Results indicated that the left prefrontal cortex (L-PFC) increased its activation with the difficulty of the task in both adolescents and adults. Interestingly, differences in the PFC dynamics but not in the overall performance were found between adults and adolescents. Our findings contributed to a better understanding of the PFC resources mobilized during complex tasks in both adults and adolescents.

Reduced Thalamus Volume and Enhanced Thalamus and Fronto-Parietal Network Integration in the Chess Experts

The ability of chess experts depends to a large extent on spatial visual processing, attention, and working memory, all of which are thought to be mediated by the thalamus. This study explored whether continued practice and rehearsal over a long period of time results in structural changes in the thalamic region. We found smaller gray matter volume regions in the thalami of expert Chinese chess players in comparison with novice players. We then used these regions as seeds for resting-state functional connectivity analysis and observed significantly strengthened integration between the thalamus and fronto-parietal network in expert Chinese chess players. This strengthened integration that includes a group of brain regions showing an increase in activation to external stimulation, particularly during tasks relying on working memory and attention. Our findings demonstrate structural changes in the thalamus caused by a wide range of engagement in chess problem solving, and that this strengthened functional integration with widely distributed circuitry better supports high-level cognitive control of behavior.

Expertise effects on attention and eye-movement control during visual search: Evidence from the domain of music reading

Experts in many domains use their domain-specific knowledge to rapidly locate relevant information. To explore this ability in music reading, we contrasted the eye movements of 30 expert musicians (with at least 10 years of music reading training) and 30 non-musicians (who could not read music) while they completed a visual search task that required them to match a section of a complex piano music score (i.e., the search template) to its identical counterpart within a larger music score (i.e., the search array). Critically, both the search template and array were presented simultaneously throughout each trial in the experiment, which allowed for visual comparisons between the search template and the array. Relative to the non-musicians, the experts had higher accuracy and also spent more time looking at the relevant regions and less time looking at irrelevant regions. Also, as evidence that the experts and non-musicians adopted qualitatively different search strategies, the experts spent more time than non-musicians looking at the search template at the beginning of the trial, and the experts returned to this region less often than non-musicians. Taken together, our results indicate that experts use domain-specific knowledge in the form of "chunks" (Chase & Simon, 1973a, 1973b) and "templates" (Gobet & Simon, 1996b, 2000) to acquire accurate representations of highly complex search templates.

Parsing rooms: the role of the PPA and RSC in perceiving object relations and spatial layout

The perception of a scene involves grasping the global space of the scene, usually called the spatial layout, as well as the objects in the scene and the relations between them. The main brain areas involved in scene perception, the parahippocampal place area (PPA) and retrosplenial cortex (RSC), are supposed to mostly support the processing of spatial layout. Here we manipulated the objects and their relations either by arranging objects within rooms in a common way or by scattering them randomly. The rooms were then varied for spatial layout by keeping or removing the walls of the room, a typical layout manipulation. We then combined a visual search paradigm, where participants actively search for an object within the room, with multivariate pattern analysis (MVPA). Both left and right PPA were sensitive to the layout properties, but the right PPA was also sensitive to the object relations even when the information about objects and their relations is used in the cross-categorization procedure on novel stimuli. The left and right RSC were sensitive to both spatial layout and object relations, but could only use the information about object relations for cross-categorization to novel stimuli. These effects were restricted to the PPA and RSC, as other control brain areas did not display the same pattern of results. Our results underline the importance of employing paradigms that require participants to explicitly retrieve domain-specific processes and indicate that objects and their relations are processed in the scene areas to a larger extent than previously assumed.

Changed hub and functional connectivity patterns of the posterior fusiform gyrus in chess experts

The hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, the effects of long-term practice on functional network hubs in chess experts are largely undefined. Here, we investigated whether alterations of hubs can be detected in chess experts using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods. We first mapped the whole-brain voxel-wise functional connectivity and calculated the functional connectivity strength (FCS) map in each of the 28 chess players and 27 gender- and age-matched healthy novice players. Whole-brain resting-state functional connectivity analyses for the changed hub areas were conducted to further elucidate the corresponding changes of functional connectivity patterns in chess players. The hub analysis revealed increased FCS in the right posterior fusiform gyrus of the chess players, which was supported by analyses of this area's regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and fractional amplitude of low frequency fluctuations (fALFF). The following functional connectivity analyses revealed increased functional connectivities between the right posterior fusiform gyrus and the visuospatial attention and motor networks in chess players. These findings demonstrate that cognitive expertise has a positive influence on the functions of the brain regions associated with the chess expertise and that increased functional connections might in turn facilitate within and between networks communication for expert behavior to get superior performance.

The Double Take of Expertise: Neural Expansion Is Associated With Outstanding Performance

The performance of experts seems almost effortless. The neural-efficiency hypothesis takes this into account, suggesting that because of practice and automatization of procedures, experts require fewer brain resources. Here, I argue that the way the brain accommodates complex skills does indeed have to do with the nature of experts’ performance. However, instead of exhibiting less brain activation, experts’ performance actually engages more brain areas. Behind the seemingly effortless performance of experts lies a complex cognitive system that relies on knowledge about the domain of expertise. Unlike novices, who need to execute one process at a time, experts are able to recognize an object, retrieve its function, and connect it to another object simultaneously. The expert brain deals with this computational burden by engaging not only specific brain areas in one hemisphere but also the same (homologous) area in the opposite hemisphere. This phenomenon, which I call the double take of expertise, has been observed in a number of expertise domains. I describe it here in object- and pattern-recognition tasks in the domain of chess. I also discuss the importance of the study of expertise for our understanding of the human brain in general.

A network view on brain regions involved in experts' object and pattern recognition: Implications for the neural mechanisms of skilled visual perception

Skilled visual object and pattern recognition form the basis of many everyday behaviours. The game of chess has often been used as a model case for studying how long-term experience aides in perceiving objects and their spatio-functional interrelations. Earlier research revealed two brain regions, posterior middle temporal gyrus (pMTG) and collateral sulcus (CoS), to be linked to chess experts' superior object and pattern recognition, respectively. Here we elucidated the brain networks these two expertise-related regions are embedded in, employing resting-state functional connectivity analysis and meta-analytic connectivity modelling with the BrainMap database. pMTG was preferentially connected with dorsal visual stream areas and a parieto-prefrontal network for action planning, while CoS was preferentially connected with posterior medial cortex and hippocampus, linked to scene perception, perspective-taking and navigation. Functional profiling using BrainMap meta-data revealed that pMTG was linked to semantic processing as well as inhibition and attention, while CoS was linked to face and shape perception as well as passive viewing. Our findings suggest that pMTG subserves skilled object recognition by mediating the link between object identity and object affordances, while CoS subserves skilled pattern recognition by linking the position of individual objects with typical spatio-functional layouts of their environment stored in memory.

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Recent advances of neuroimaging methodology and artificial intelligence have resulted in renewed interest in board games like chess and Baduk (called Go game in the West) and have provided clues as to the mechanisms behind the games. However, an interesting question that remains to be answered is whether the board game expertise as one of cognitive skills goes beyond just being good at the trained game and how it maps on networks associated with cognitive abilities that are not directly trained. To address this issue, we examined functional activity and connectivity in Baduk experts, compared to novices, while performing a visual n-back working memory (WM) task. We found that experts, compared to novices, had greater activation in superior parietal cortex during face WM, though there were no group differences in behavioral performances. Using a data-driven, whole-brain multivariate approach, we also found significant group differences in the multivariate pattern of connectivity in frontal pole and inferior parietal cortex, further showing greater connectivity between frontal and parietal regions and between frontal and temporal regions in experts. Our findings suggest that long-term trained Baduk experts have the reorganization of functional interactions between brain regions even for untrained cognitive ability.

What Does "Being an Expert" Mean to the Brain? Functional Specificity and Connectivity in Expertise

To what extent is varying cognitive expertise reflected in the brain's functional specificity and connectivity? We addressed this question by examining expertise in mathematics based on the fact that mathematical skills are one of the most critical cognitive abilities known to be a good predictor of academic achievement. We investigated processing of hierarchical structures, which is a fundamental process for building complex cognitive architecture. Experts and nonexperts in mathematics participated in processing hierarchical structures using algebraic expressions. Results showed that a modulating effect depending on expertise was observed specifically in nonexperts in the left inferior frontal gyrus around pars triangularis and frontal sulcus, the left intraparietal sulcus, and the right inferior parietal lobule. This expertise-dependent pattern of activation led to a crucial dissociation within the left prefrontal cortex. More interestingly, task-related functional networks were also modulated differently in the frontoparietal network for relatively good performance and in the frontostriatal network for poor performance. The present study indicates that a high level of expertise is evident in a small number of specific brain regions, whereas a low level of expertise is reflected by broadly distributed brain areas, along with divergent functional connectivity between experts and nonexperts.

Chess databases as a research vehicle in psychology: Modeling large data

The game of chess has often been used for psychological investigations, particularly in cognitive science. The clear-cut rules and well-defined environment of chess provide a model for investigations of basic cognitive processes, such as perception, memory, and problem solving, while the precise rating system for the measurement of skill has enabled investigations of individual differences and expertise-related effects. In the present study, we focus on another appealing feature of chess—namely, the large archive databases associated with the game. The German national chess database presented in this study represents a fruitful ground for the investigation of multiple longitudinal research questions, since it collects the data of over 130,000 players and spans over 25 years. The German chess database collects the data of all players, including hobby players, and all tournaments played. This results in a rich and complete collection of the skill, age, and activity of the whole population of chess players in Germany. The database therefore complements the commonly used expertise approach in cognitive science by opening up new possibilities for the investigation of multiple factors that underlie expertise and skill acquisition. Since large datasets are not common in psychology, their introduction also raises the question of optimal and efficient statistical analysis. We offer the database for download and illustrate how it can be used by providing concrete examples and a step-by-step tutorial using different statistical analyses on a range of topics, including skill development over the lifetime, birth cohort effects, effects of activity and inactivity on skill, and gender differences.

Preserved Expert Object Recognition in a Case of Visual Hemiagnosia

We examined a stroke patient (HWS) with a unilateral lesion of the right medial ventral visual stream, involving the right fusiform and parahippocampal gyri. In a number of object recognition tests with lateralized presentations of target stimuli, HWS showed significant symptoms of hemiagnosia with contralesional recognition deficits for everyday objects. We further explored the patient's capacities of visual expertise that were acquired before the current perceptual impairment became effective. We confronted him with objects he was an expert for already before stroke onset and compared this performance with the recognition of familiar everyday objects. HWS was able to identify significantly more of the specific (“expert”) than of the everyday objects on the affected contralesional side. This observation of better expert object recognition in visual hemiagnosia allows for several interpretations. The results may be caused by enhanced information processing for expert objects in the ventral system in the affected or the intact hemisphere. Expert knowledge could trigger top–down mechanisms supporting object recognition despite of impaired basic functions of object processing. More importantly, the current work demonstrates that top–down mechanisms of visual expertise influence object recognition at an early stage, probably before visual object information propagates to modules of higher object recognition. Because HWS showed a lesion to the fusiform gyrus and spared capacities of expert object recognition, the current study emphasizes possible contributions of areas outside the ventral stream to visual expertise.

Measuring nonvisual knowledge about object categories: The Semantic Vanderbilt Expertise Test

How much do people differ in their abilities to recognize objects, and what is the source of these differences? To address the first question, psychologists have created visual learning tests including the Cambridge Face Memory Test (Duchaine & Nakayama, 2006) and the Vanderbilt Expertise Test (VET; McGugin et al., 2012). The second question requires consideration of the influences of both innate potential and experience, but experience is difficult to measure. One solution is to measure the products of experience beyond perceptual knowledge-specifically, nonvisual semantic knowledge. For instance, the relation between semantic and perceptual knowledge can help clarify the nature of object recognition deficits in brain-damaged patients (Barton, Hanif, & Ashraf, Brain, 132, 3456-3466, 2009). We present a reliable measure of nonperceptual knowledge in a format applicable across categories. The Semantic Vanderbilt Expertise Test (SVET) measures knowledge of relevant category-specific nomenclature. We present SVETs for eight categories: cars, planes, Transformers, dinosaurs, shoes, birds, leaves, and mushrooms. The SVET demonstrated good reliability and domain-specific validity. We found partial support for the idea that the only source of domain-specific shared variance between the VET and SVET is experience with a category. We also demonstrated the utility of the SVET-Bird in experts. The SVET can facilitate the study of individual differences in visual recognition.

Identifying the Micro-relations Underpinning Familiarity Detection in Dynamic Displays Containing Multiple Objects

We identified the important micro-relations that are perceived when attempting to recognize patterns in stimuli consisting of multiple dynamic objects. Skilled and less-skilled participants were presented with point light display sequences representing dynamic patterns in an invasion sport and were subsequently required to make familiarity based recognition judgments in three different conditions, each of which contained only a select number of features that were present at initial viewing. No differences in recognition accuracy were observed between skilled and less-skilled participants when just objects located in the periphery were presented. Yet, when presented with the relative motions of two centrally located attacking objects only, skilled participants were significantly more accurate than less-skilled participants and their recognition accuracy improved further when a target object was included against which these relative motions could be judged. Skilled participants can perceive and recognize global patterns on the basis of centrally located relational information.

Methylphenidate, modafinil, and caffeine for cognitive enhancement in chess: A double-blind, randomised controlled trial

Stimulants and caffeine have been proposed for cognitive enhancement by healthy subjects. This study investigated whether performance in chess - a competitive mind game requiring highly complex cognitive skills - can be enhanced by methylphenidate, modafinil or caffeine. In a phase IV, randomized, double-blind, placebo-controlled trial, 39 male chess players received 2×200mg modafinil, 2×20mg methylphenidate, and 2×200mg caffeine or placebo in a 4×4 crossover design. They played twenty 15-minute games during two sessions against a chess program (Fritz 12; adapted to players' strength) and completed several neuropsychological tests. Marked substance effects were observed since all three substances significantly increased average reflection time per game compared to placebo resulting in a significantly increased number of games lost on time with all three treatments. Treatment effects on chess performance were not seen if all games (n=3059) were analysed. Only when controlling for game duration as well as when excluding those games lost on time, both modafinil and methylphenidate enhanced chess performance as demonstrated by significantly higher scores in the remaining 2876 games compared to placebo. In conjunction with results from neuropsychological testing we conclude that modifying effects of stimulants on complex cognitive tasks may in particular result from more reflective decision making processes. When not under time pressure, such effects may result in enhanced performance. Yet, under time constraints more reflective decision making may not improve or even have detrimental effects on complex task performance.

Testing the Limits of Skill Transfer for Scrabble Experts in Behavior and Brain

We investigated transfer of the skills developed by competitive Scrabble players. Previous studies reported superior performance for Scrabble experts on the lexical decision task (LDT), suggesting near transfer of Scrabble skills. Here we investigated the potential for far transfer to a symbol decision task (SDT); in particular, transfer of enhanced long-term working memory for vertically presented stimuli. Our behavioral results showed no evidence for far transfer. Despite years of intensive practice, Scrabble experts were no faster and no more accurate than controls in the SDT. However, our fMRI and EEG data from the SDT suggest that the neural repertoire that Scrabble experts develop supports task performance even outside of the practiced domain, in a non-linguistic context. The regions engaged during the SDT were different across groups: controls engaged temporal-frontal regions, whereas Scrabble experts engaged posterior visual and temporal-parietal regions. In Scrabble experts, activity related to Scrabble skill (anagramming scores) included regions associated with visual-spatial processing and long-term working memory, and overlapped with regions previously shown to be associated with Scrabble expertise in the near transfer task (LDT). Analysis of source waveforms within these regions showed that participants with higher anagramming scores had larger P300 amplitudes, potentially reflecting greater working memory capacity, or less variability in the participants who performed the task more efficiently. Thus, the neuroimaging results provide evidence of brain transfer in the absence of behavioral transfer, providing new clues about the consequences of long-term training associated with competitive Scrabble expertise.

Modeling eye movement patterns to characterize perceptual skill in image-based diagnostic reasoning processes

Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. In this article, we present a hierarchical probabilistic framework to discover the stereotypical and idiosyncratic viewing behaviors exhibited with expertise-specific groups. Through these patterned eye movement behaviors we are able to elicit the domain-specific knowledge and perceptual skills from the subjects whose eye movements are recorded during diagnostic reasoning processes on medical images. Analyzing experts' eye movement patterns provides us insight into cognitive strategies exploited to solve complex perceptual reasoning tasks. An experiment was conducted to collect both eye movement and verbal narrative data from three groups of subjects with different levels or no medical training (eleven board-certified dermatologists, four dermatologists in training and thirteen undergraduates) while they were examining and describing 50 photographic dermatological images. We use a hidden Markov model to describe each subject's eye movement sequence combined with hierarchical stochastic processes to capture and differentiate the discovered eye movement patterns shared by multiple subjects within and among the three groups. Independent experts' annotations of diagnostic conceptual units of thought in the transcribed verbal narratives are time-aligned with discovered eye movement patterns to help interpret the patterns' meanings. By mapping eye movement patterns to thought units, we uncover the relationships between visual and linguistic elements of their reasoning and perceptual processes, and show the manner in which these subjects varied their behaviors while parsing the images. We also show that inferred eye movement patterns characterize groups of similar temporal and spatial properties, and specify a subset of distinctive eye movement patterns which are commonly exhibited across multiple images. Based on the combinations of the occurrences of these eye movement patterns, we are able to categorize the images from the perspective of experts' viewing strategies in a novel way. In each category, images share similar lesion distributions and configurations. Our results show that modeling with multi-modal data, representative of physicians' diagnostic viewing behaviors and thought processes, is feasible and informative to gain insights into physicians' cognitive strategies, as well as medical image understanding.

Revisiting the Role of the Fusiform Face Area in Expertise

The fusiform face area (FFA) is considered to be a highly specialized brain module because of its central importance for face perception. However, many researchers claim that the FFA is a general visual expertise module that distinguishes between individual examples within a single category. Here, I circumvent the shortcomings of some previous studies on the FFA controversy by using chess stimuli, which do not visually resemble faces, together with more sensitive methods of analysis such as multivariate pattern analysis. I also extend the previous research by presenting chess positions, complex scenes with multiple objects, and their interrelations to chess experts and novices as well as isolated chess objects. The first experiment demonstrates that chess expertise modulated the FFA activation when chess positions were presented. In contrast, single chess objects did not produce different activation patterns among experts and novices even when the multivariate pattern analysis was used. The second experiment focused on the single chess objects and featured an explicit task of identifying the chess objects but failed to demonstrate expertise effects in the FFA. The experiments provide support for the general expertise view of the FFA function but also extend the scope of our understanding about the function of the FFA. The FFA does not merely distinguish between different exemplars within the same category of stimuli. More likely, it parses complex multiobject stimuli that contain numerous functional and spatial relations.

Exploring the quantum speed limit with computer games

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. 'Gamification'--the application of game elements in a non-game context--is an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit, EteRNA and EyeWire have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity). Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

The Perils of Automaticity

Classical theories of skill acquisition propose that automatization (i.e., performance requires progressively less attention as experience is acquired) is a defining characteristic of expertise in a variety of domains (e.g., Fitts & Posner, 1967 ). Automaticity is believed to enhance smooth and efficient skill execution by allowing performers to focus on strategic elements of performance rather than on the mechanical details that govern task implementation ( Williams & Ford, 2008 ). By contrast, conscious processing (i.e., paying conscious attention to one's action during motor execution) has been found to disrupt skilled movement and performance proficiency (e.g., Beilock & Carr, 2001 ). On the basis of this evidence, researchers have tended to extol the virtues of automaticity. However, few researchers have considered the wide range of empirical evidence which indicates that highly automated behaviors can, on occasion, lead to a series of errors that may prove deleterious to skilled performance. Therefore, the purpose of the current paper is to highlight the perils, rather than the virtues, of automaticity. We draw on Reason's (1990) classification scheme of everyday errors to show how an overreliance on automated procedures may lead to 3 specific performance errors (i.e., mistakes, slips, and lapses) in a variety of skill domains (e.g., sport, dance, music). We conclude by arguing that skilled performance requires the dynamic interplay of automatic processing and conscious processing in order to avoid performance errors and to meet the contextually contingent demands that characterize competitive environments in a range of skill domains.

Cognitive Expertise: An ALE Meta-Analysis

Expert performance constitutes the endpoint of skill acquisition and is accompanied by widespread neuroplastic changes. To reveal common mechanisms of reorganization associated with long-term expertise in a cognitive domain (mental calculation, chess, language, memory, music without motor involvement), we used activation likelihood estimation meta-analysis and compared brain activation of experts to nonexperts. Twenty-six studies matched inclusion criteria, most of which reported an increase and not a decrease of activation foci in experts. Increased activation occurred in the left rolandic operculum (OP 4) and left primary auditory cortex and in bilateral premotor cortex in studies that used auditory stimulation. In studies with visual stimulation, experts showed enhanced activation in the right inferior parietal cortex (area PGp) and the right lingual gyrus. Experts' brain activation patterns seem to be characterized by enhanced or additional activity in domain-specific primary, association, and motor structures, confirming that learning is localized and very specialized.

What is special about expertise? Visual expertise reveals the interactive nature of real-world object recognition

Ever since Diamond and Carey (1986. J. Exp. Psychol.: Gen., vol. 115, pp. 107-117) seminal work, the main model for studying expertise in visual object recognition ("visual expertise") has been face perception. The underlying assumption was that since faces may be considered the ultimate domain of visual expertise, any face-processing signature might actually be a general characteristic of visual expertise. However, while humans are clearly experts in face recognition, visual expertise is not restricted to faces and can be observed in a variety of domains. This raises the question of whether face recognition is in fact the right model to study visual expertise, and if not, what are the common cognitive and neural characteristics of visual expertise. The current perspective article addresses this question by revisiting past and recent neuroimaging and behavioural works on visual expertise. The view of visual expertise that emerges from these works is that expertise is a unique phenomenon, with distinctive neural and cognitive characteristics. Specifically, visual expertise is a controlled, interactive process that develops from the reciprocal interactions between the visual system and multiple top-down factors, including semantic knowledge, top-down attentional control, and task relevance. These interactions enable the ability to flexibly access domain-specific information at multiple scales and levels guided by multiple recognition goals. Extensive visual experience with a given object category culminates in the recruitment of these multiple systems, and is reflected in widespread neural activity, extending well beyond visual cortex, to include higher-level cortical areas.

Metacognition and action: a new pathway to understanding social and cognitive aspects of expertise in sport

For over a century, psychologists have investigated the mental processes of expert performers – people who display exceptional knowledge and/or skills in specific fields of human achievement. Since the 1960s, expertise researchers have made considerable progress in understanding the cognitive and neural mechanisms that underlie such exceptional performance. Whereas the first modern studies of expertise were conducted in relatively formal knowledge domains such as chess, more recent investigations have explored elite performance in dynamic perceptual-motor activities such as sport. Unfortunately, although these studies have led to the identification of certain domain-free generalizations about expert-novice differences, they shed little light on an important issue: namely, experts’ metacognitive activities or their insights into, and regulation of, their own mental processes. In an effort to rectify this oversight, the present paper argues that metacognitive processes and inferences play an important if neglected role in expertise. In particular, we suggest that metacognition (including such processes as “meta-attention,” “meta-imagery” and “meta-memory,” as well as social aspects of this construct) provides a window on the genesis of expert performance. Following a critique of the standard empirical approach to expertise, we explore some research on “metacognition” and “metacognitive inference” among experts in sport. After that, we provide a brief evaluation of the relationship between psychological skills training and metacognition and comment on the measurement of metacognitive processes. Finally, we summarize our conclusions and outline some potentially new directions for research on metacognition in action.

Expert vs. novice differences in the detection of relevant information during a chess game: evidence from eye movements

The present study explored the ability of expert and novice chess players to rapidly distinguish between regions of a chessboard that were relevant to the best move on the board, and regions of the board that were irrelevant. Accordingly, we monitored the eye movements of expert and novice chess players, while they selected white's best move for a variety of chess problems. To manipulate relevancy, we constructed two different versions of each chess problem in the experiment, and we counterbalanced these versions across participants. These two versions of each problem were identical except that a single piece was changed from a bishop to a knight. This subtle change reversed the relevancy map of the board, such that regions that were relevant in one version of the board were now irrelevant (and vice versa). Using this paradigm, we demonstrated that both the experts and novices spent more time fixating the relevant relative to the irrelevant regions of the board. However, the experts were faster at detecting relevant information than the novices, as shown by the finding that experts (but not novices) were able to distinguish between relevant and irrelevant information during the early part of the trial. These findings further demonstrate the domain-related perceptual processing advantage of chess experts, using an experimental paradigm that allowed us to manipulate relevancy under tightly controlled conditions.

Quick concurrent responses to global and local cognitive information underlie intuitive understanding in board-game experts

Experts have the superior cognitive capability of quickly understanding complex information in their domain; however, little is known about the neural processes underlying this ability. Here, using a board game named shogi (Japanese chess), we investigated the brain activity in expert players that was involved in their quick understanding of board-game patterns. The frontal area responded only to meaningful game positions, whereas the temporal area responded to both game and random positions with the same latency (200 ms). Subsequent to these quick responses, the temporal and parietal areas responded only to game positions, with a latency of 700 ms. During the responses, enhanced phase synchronization between these areas was observed. Thus, experts first responded to global cognitive information that was specific to game positions and to local cognitive information that was common to game and random positions concurrently. These types of information were integrated via neural synchronization at the posterior areas. As these properties were specific to experts, much of the experts' advantage in understanding game positions occurred within 1 s of perception.

An adaptive toolbox approach to the route to expertise in sport

Expertise is characterized by fast decision-making which is highly adaptive to new situations. Here we propose that athletes use a toolbox of heuristics which they develop on their route to expertise. The development of heuristics occurs within the context of the athletes’ natural abilities, past experiences, developed skills, and situational context, but does not pertain to any of these factors separately. This is a novel approach because it integrates separate factors into a comprehensive heuristic description. The novelty of this approach lies within the integration of separate factors determining expertise into a comprehensive heuristic description. It is our contention that talent identification methods and talent development models should therefore be geared toward the assessment and development of specific heuristics. Specifically, in addition to identifying and developing separate natural abilities and skills as per usual, heuristics should be identified and developed. The application of heuristics to talent and expertise models can bring the field one step away from dichotomized models of nature and nurture toward a comprehensive approach to the route to expertise.