Analyzing spatial data from mouse tracker methodology: An entropic approach

Entropy as a Window Into Behavioral Phase Transitions: Unveiling Contextual Dynamics in Affordance-Based Reaching

Prior work has demonstrated the presence of hysteresis effects in the control of affordance-guided behavior, in that behavioral transitions around a critical action boundary vary with directions of change in said action boundary. To date, research on this topic has overlooked the influence of the global context on these phenomena. We employ an affordance-based reaching task, whereby participants were asked to move a target to a goal by passing through one of two apertures (size variable or size constant). It was found that the direction of change in the size of the variable aperture influenced the point of behavioral transitions, and this effect interacted with the location of a given goal. In addition, we considered fluctuations in the entropy of participants' reach trajectories as a window into the nature of the behavioral phase transitions. Differences in the structure of entropy were found depending on the direction of change in the size variable aperture. These results are discussed in light of a dynamical systems approach, and recommendations for future work are made.

Hands-on false memories: a combined study with distributional semantics and mouse-tracking

Although mouse-tracking has been seen as a real-time window into different aspects of human decision-making processes, currently little is known about how the decision process unfolds in veridical and false memory retrieval. Here, we directly investigated decision-making processes by predicting participants' performance in a mouse-tracking version of a typical Deese-Roediger-McDermott (DRM) task through distributional semantic models, a usage-based approach to meaning. Participants were required to study lists of associated words and then to perform a recognition task with the mouse. Results showed that mouse trajectories were extensively affected by the semantic similarity between the words presented in the recognition phase and the ones previously studied. In particular, the higher the semantic similarity, the larger the conflict driving the choice and the higher the irregularity in the trajectory when correctly rejecting new words (i.e., the false memory items). Conversely, on the temporal evolution of the decision, our results showed that semantic similarity affects more complex temporal measures indexing the online decision processes subserving task performance. Together, these findings demonstrate that semantic similarity can affect human behavior at the level of motor control, testifying its influence on online decision-making processes. More generally, our findings complement previous seminal theories on false memory and provide insights into the impact of the semantic memory structure on different decision-making components.

The action dynamics of approach-avoidance conflict during decision-making

Approach-avoidance conflict is observed in the competing motivations towards the benefits and away from the costs of a decision. The current study investigates the action dynamics of response motion during such conflicts in an attempt to characterise their dynamic resolution. An approach-avoidance conflict was generated by varying the appetitive consequences of a decision (i.e., point rewards and shorter participation time) in the presence of simultaneous aversive consequences (i.e., shock probability). Across two experiments, approach-avoidance conflict differentially affected response trajectories. Approach trajectories were less complex than avoidance trajectories and, as approach and avoidance motivations neared equipotentiality, response trajectories were more deflected from the shortest route to the eventual choice. Consistency in the location of approach and avoidance response options reduced variability in performance enabling more sensitive estimates of dynamic conflict. The time course of competing influences on response trajectories including trial-to-trial effects and conflict between approach and avoidance were estimated using regression analyses. We discuss these findings in terms of a dynamic theory of approach-avoidance that we hope will lead to insights of practical relevance in the field of maladaptive avoidance.

Dissociating sub-processes of aftereffects of completed intentions and costs to the ongoing task in prospective memory: A mouse-tracking approach

In the present study, we used mouse tracking to investigate two processes underlying prospective memory (PM) retrieval: First, we aimed to explore to what extent spontaneous retrieval of already completed PM intentions is supported by reflexive-associative and discrepancy-plus-search processes. Second, we aimed to disentangle whether costs to an ongoing task during the pursuit of a PM intention are associated with presumably resource-demanding monitoring processes or with a presumably resource-sparing strategic delay of ongoing-task responses. Our third aim was to explore the interaction of processes underlying costs to the ongoing task and processes of spontaneous retrieval. Our analyses replicated response-time patterns from previous studies indicating aftereffects of completed intentions and costs to ongoing-task performance, as well as increased aftereffects while pursuing a PM intention. Notably, based on our mouse-tracking analyses, we argue that aftereffects of completed intentions are best explained by a reflexive initiation of an already completed intention. If the completed intention is not performed in its entirety (i.e., no commission error), the reflexive initiation of the completed intention is followed by a subsequent movement correction that most likely represents a time-consuming response-verification process. Regarding performance costs in the ongoing task, our analyses suggest that actively pursuing a PM intention most likely leads to a strategic delay of ongoing activities. Lastly, we found that pursuing a novel PM task after intention completion exacerbated orienting responses to all deviant stimuli, exacerbated the readiness to initiate the completed intention reflexively, and substantially prolonged the response-verification process following this reflexive intention retrieval.

Using mouse cursor tracking to investigate online cognition: Preserving methodological ingenuity while moving toward reproducible science

Mouse cursor tracking has become a prominent method for characterizing cognitive processes, used in a wide variety of domains of psychological science. Researchers have demonstrated considerable ingenuity in the application of the approach, but the methodology has not undergone systematic analysis to facilitate the development of best practices. Furthermore, recent research has demonstrated effects of experimental design features on a number of mousetracking outcomes. We conducted a systematic review of the mouse-tracking literature to survey the reporting and spread of mouse variables (Cursor speed, Sampling rate, Training), physical characteristics of the experiments (Stimulus position, Response box position) and response requirements (Start procedure, Response procedure, Response deadline). This survey reveals that there is room for improvement in reporting practices, especially of subtler design features that researchers may have assumed would not impact research results (e.g., Cursor speed). We provide recommendations for future best practices in mouse-tracking studies and consider how best to standardize the mouse-tracking literature without excessively constraining the methodological flexibility that is essential to the field.

A State Space Approach to Dynamic Modeling of Mouse-Tracking Data

Mouse-tracking recording techniques are becoming very attractive in experimental psychology. They provide an effective means of enhancing the measurement of some real-time cognitive processes involved in categorization, decision-making, and lexical decision tasks. Mouse-tracking data are commonly analyzed using a two-step procedure which first summarizes individuals' hand trajectories with independent measures, and then applies standard statistical models on them. However, this approach can be problematic in many cases. In particular, it does not provide a direct way to capitalize the richness of hand movement variability within a consistent and unified representation. In this article we present a novel, unified framework for mouse-tracking data. Unlike standard approaches to mouse-tracking, our proposal uses stochastic state-space modeling to represent the observed trajectories in terms of both individual movement dynamics and experimental variables. The model is estimated via a Metropolis-Hastings algorithm coupled with a non-linear recursive filter. The characteristics and potentials of the proposed approach are illustrated using a lexical decision case study. The results highlighted how dynamic modeling of mouse-tracking data can considerably improve the analysis of mouse-tracking tasks and the conclusions researchers can draw from them.

Resolving the Human–Object Divide in Sexual Objectification: How We Settle the Categorization Conflict When Categorizing Objectified and Nonobjectified Human Targets

Using a mouse-tracking technique, we measured the strength and the temporal unfolding of the conflict when people categorize objectified and nonobjectified human stimuli in the human or object category. We recorded participants’ hand movements when they categorized male and female, objectified and nonobjectified, human, and doll-like stimuli in the person and object categories. As expected, objectified women created a stronger categorization conflict compared to all other human stimuli. The nature of the mouse trajectories indicated that this response competition was caused by the distractor (object category) rather than the target (person category) and showed to be smooth rather than abrupt suggesting dynamic competition between the object–human categories rather than the sequential unfolding of a dual process. These findings demonstrate that the human–object divide fades when women (but not men) are objectified. The implications of the current findings for theorizing on processes of sexual objectification are discussed.

A Maximum Entropy Procedure to Solve Likelihood Equations

In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero, we propose an alternative strategy where the score is instead used as an external informative constraint to the maximization of the convex Shannon’s entropy function. The problem involves the reparameterization of the score parameters as expected values of discrete probability distributions where probabilities need to be estimated. This leads to a simpler situation where parameters are searched in smaller (hyper) simplex space. We assessed our proposal by means of empirical case studies and a simulation study, the latter involving the most critical case of logistic regression under data separation. The results suggested that the maximum entropy reformulation of the score problem solves the likelihood equation problem. Similarly, when maximum likelihood estimation is difficult, as is the case of logistic regression under separation, the maximum entropy proposal achieved results (numerically) comparable to those obtained by the Firth’s bias-corrected approach. Overall, these first findings reveal that a maximum entropy solution can be considered as an alternative technique to solve the likelihood equation.

Comparing speech and nonspeech context effects across timescales in coarticulatory contexts

Context effects are ubiquitous in speech perception and reflect the ability of human listeners to successfully perceive highly variable speech signals. In the study of how listeners compensate for coarticulatory variability, past studies have used similar effects speech and tone analogues of speech as strong support for speech-neutral, general auditory mechanisms for compensation for coarticulation. In this manuscript, we revisit compensation for coarticulation by replacing standard button-press responses with mouse-tracking responses and examining both standard geometric measures of uncertainty as well as newer information-theoretic measures that separate fast from slow mouse movements. We found that when our analyses were restricted to end-state responses, tones and speech contexts appeared to produce similar effects. However, a more detailed time-course analysis revealed systematic differences between speech and tone contexts such that listeners' responses to speech contexts, but not to tone contexts, changed across the experimental session. Analyses of the time course of effects within trials using mouse tracking indicated that speech contexts elicited fewer x-position flips but more area under the curve (AUC) and maximum deviation (MD), and they did so in the slower portions of mouse-tracking movements. Our results indicate critical differences between the time course of speech and nonspeech context effects and that general auditory explanations, motivated by their apparent similarity, be reexamined.

Bringing the Nonlinearity of the Movement System to Gestural Theories of Language Use: Multifractal Structure of Spoken English Supports the Compensation for Coarticulation in Human Speech Perception

Coarticulation is the tendency for speech vocalization and articulation even at the phonemic level to change with context, and compensation for coarticulation (CfC) reflects the striking human ability to perceive phonemic stability despite this variability. A current controversy centers on whether CfC depends on contrast between formants of a speech-signal spectrogram-specifically, contrast between offset formants concluding context stimuli and onset formants opening the target sound-or on speech-sound variability specific to the coordinative movement of speech articulators (e.g., vocal folds, postural muscles, lips, tongues). This manuscript aims to encode that coordinative-movement context in terms of speech-signal multifractal structure and to determine whether speech's multifractal structure might explain the crucial gestural support for any proposed spectral contrast. We asked human participants to categorize individual target stimuli drawn from an 11-step [ga]-to-[da] continuum as either phonemes "GA" or "DA." Three groups each heard a specific-type context stimulus preceding target stimuli: either real-speech [al] or [a], sine-wave tones at the third-formant offset frequency of either [al] or [aɹ], and either simulated-speech contexts [al] or [aɹ]. Here, simulating speech contexts involved randomizing the sequence of relatively homogeneous pitch periods within vowel-sound [a] of each [al] and [aɹ]. Crucially, simulated-speech contexts had the same offset and extremely similar vowel formants as and, to additional naïve participants, sounded identical to real-speech contexts. However, randomization distorted original speech-context multifractality, and effects of spectral contrast following speech only appeared after regression modeling of trial-by-trial "GA" judgments controlled for context-stimulus multifractality. Furthermore, simulated-speech contexts elicited faster responses (like tone contexts do) and weakened known biases in CfC, suggesting that spectral contrast depends on the nonlinear interactions across multiple scales that articulatory gestures express through the speech signal. Traditional mouse-tracking behaviors measured as participants moved their computer-mouse cursor to register their "GA"-or-"DA" decisions with mouse-clicks suggest that listening to speech leads the movement system to resonate with the multifractality of context stimuli. We interpret these results as shedding light on a new multifractal terrain upon which to found a better understanding in which movement systems play an important role in shaping how speech perception makes use of acoustic information.

Doing psychological science by hand

Over the past decade, mouse-tracking in choice tasks has become a popular method across psychological science. This method exploits hand movements as a measure of multiple response activations that can be tracked continuously over hundreds of milliseconds. Whereas early mouse-tracking research focused on specific debates, researchers have realized the methodology has far broader theoretical value. This more recent work demonstrates that mouse-tracking is a widely applicable measure across the field, capable of exposing the micro-structure of real-time decisions including their component processes and millisecond-resolution time-course in ways that inform theory. In the article, recent advances in the mouse-tracking approach are described, and comparisons with the gold standard measure of reaction time and other temporally-sensitive methodologies are provided. Future directions, including mapping to neural representations with brain-imaging and ways to improve our theoretical understanding of mouse-tracking methodology, are discussed.