Computer-implemented method and system for cognitive measurements through gamification

Abstract

A computer-implemented method and system of cognitive measurements, providing a computer code to display a computer presentable object that is controllable by a user interface, the computer presentable object including a gaming part and a cognitive measurement part. The gaming part includes an infinite runner game, wherein an avatar is displayed on a constantly moving trail, which avatar is steerable by input from an input device of the computer. The cognitive measurement part is integrated with the gaming part. The cognitive measurement part is arranged to perform cognitive measurements comprising one or more standard cognitive tests. A cognitive performance report is generated based on a statistical model of the standard cognitive tests and based on results from the cognitive measurements obtained from the gaming object.

Description

[0001] Computer-implemented method and system for cognitive measurements through gamification

[0002] Technical field

[0003] The present disclosure relates to a computer-implemented method of cognitive measurements through gamification, a computer program for cognitive measurements through gamification, a computer-readable storage medium including a computer program for cognitive measurements through gamification, and a system configured for performing cognitive measurements through gamification.

[0004] Background

[0005] Gamification is the process of applying game design elements, such as scoring systems, graphical interface or narrative, to nongame environments, such as cognitive tasks or work context, to increase task performance and engagement. Gamification may be used in a variety of settings, such as in business, education or in the context of health care education to support desirable behavior. The use of games or gamelike tasks makes it possible to enhance voluntary engagement and decrease participant drop-out rates. Increased task engagement is especially important when cognitive tasks are used as a diagnostic tool because they rely upon the participant to perform the task to the best of their ability. Data obtained from individuals who lack motivation to perform the task may not be representative of their ability, and this can lead to misinterpretations of the result

[0006] Summary

[0007] A summary of aspects of certain examples disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects and / or a combination of aspects that may not be set forth. Known computer-based cognitive measurements may cause participatory fatigue leading to measurement noise, loss of accuracy in measurements, and many trials during measurement. Further, cognitive measurements of inhibitory response selection are typically bound to lab experimentation in strictly controlled environment, reducing ecological validity and flexibility in applying the approach. In addition, tradiational conflict-based cognitive assessment tools are highly behaviourally restrictive, which prevents them from capturing the dynamic nature of human cognition, such as the tendency to make error-correcting responses.

[0008] The present disclosure aims to reduce the number of required trials, reduce overall time spent measuring, reduce fatigue with the participants, increase measurement accuracy, increases flexibility and increases ecological validity of the test results. In one implementation, the present disclosure measures interference control, response inhibition, and response-rule switching in a less restrictive manner than traditional cognitive assessment tools by giving players movement control after an initial response and encouraging error-correcting responses.

[0009] According to an aspect of the present disclosure, a computer-implemented method of cognitive measurements is presented. The method may include a computer code which, when executed by one or more processors, causes a computer to display a computer presentable object that is controllable by a user interface. The computer presentable object may include a gaming part and a cognitive measurement part. The gaming part may include an infinite runner game, wherein an avatar is displayed on a constantly moving trail represented as an enclosed form in a third-person view. The avatar may be configured to constantly move forward in the enclosed form. The avatar may include a plurality of test subject representations. The avatar may be steerable by input from an input device. The cognitive measurement part may be integrated with the gaming part. The cognitive measurement part may be arranged to perform cognitive measurements including one or more cognitive tests, preferably one or more standard cognitive tests. The method may further include generating a cognitive performance report based on a statistical model of the one or more tests and based on results from the cognitive measurements obtained from the gaming object.

[0010] In an embodiment, the cognitive measurement part may be arranged to perform cognitive measurements including at least two cognitive tests. In an embodiment, the cognitive tests may include a reaction time task of a regular trial.

[0011] In an embodiment, the cognitive tests may include a flanker task of a flanker trial.

[0012] In an embodiment, the cognitive tests may include a stop-signal task of a stopsignal trial.

[0013] In an embodiment, the cognitive tests may include a reverse-control task of a reverse-control trial.

[0014] In an embodiment, the cognitive tests may include an Iowa gambling task of an Iowa gambling trial.

[0015] In an embodiment, the statistical model may align the gaming part with the cognitive measurement part.

[0016] In an embodiment, the method may further include obtaining one or more digital biomarkers of cognition from the cognitive performance report.

[0017] In an embodiment, the cognitive measurement part may integrate inhibitory control and decision-making challenges in the cognitive measurements.

[0018] In an embodiment, the cognitive measurement part may integrate error correcting input, such as a time to correct an error, in the cognitive measurements.

[0019] In an embodiment, the cognitive measurement part may include cognitive challenges that are controllable using the user interface and that are measurable by the cognitive measurements.

[0020] In an embodiment, the one or more cognitive tests may include a presentation of one or more trail task features inducing a cognitive measurement score depending on an interaction of the avatar with the one or more trail task features.

[0021] In an embodiment, the trail task feature may include a plurality of sections. Two or more of the sections may have different characteristics inducing a different cognitive measurement score.

[0022] In an embodiment, the enclosed form may be a three-dimensional tunnel.

[0023] In an embodiment, the avatar may include a group of an odd number and similar test subject representations. The representations in the group may be displayed on the trail side by side. The representations of the group may be configured for steering together based on the input from the input device.

[0024] In an embodiment, the group may include at least three, and preferably five test subject representations. In an embodiment, the one or more cognitive tests may include a presentation of a trail task feature. The avatar may include a group of an odd number and similar test subject representations. Guiding a central representation through a section of the trail task feature that matches a characteristic of the central representation may yield an encouragement to the user in the gaming part. Non-limiting examples of such encouragement are scoring points or increasing a streak count. Guiding a central representation through a section of the trail task feature that does not match a characteristic of the central representation may yield a discouragement to the user in the gaming part. Non-limiting examples of such discouragement are a reduction in points or decreasing a streak count.

[0025] In an embodiment, a user may guide the avatar through a rotating tunnel using the user interface.

[0026] In an embodiment, the method may include receiving a user input to perform an action with the avatar based on one or more characteristics of one or more representations in the avatar and based on one or more characteristics of the trail. A result of the cognitive measurements may be based on a result of the input and result of the action.

[0027] In an embodiment, the action may include steering the avatar such that a representation having a certain characteristic is aligned to a trail section that matches that characteristic and a result of the cognitive measurements is based on a result of the matching.

[0028] In an embodiment, the action may include steering the avatar such that one or more of the representations of the group move through a section of a ring object.

[0029] In an embodiment, the one or more representations are to be steered through a section of the ring having a specific color.

[0030] In an embodiment, the gaming part may further include prompting the user to decide between different items by providing input that corresponds to one of the different items. The cognitive measurement may incorporate the input representing user decision.

[0031] In an embodiment, the method may further include integrating the computer code into an existing system for cognitive measurements.

[0032] In an embodiment, the existing system may be a system for measuring socioeconomic status (SES). In an embodiment, the existing system may be a system for measuring effects of a medical treatment.

[0033] In an embodiment, the existing system may be a system for measuring effects in a clinical trial.

[0034] In an embodiment, the existing system may be a system for measuring effects of drugs.

[0035] In an embodiment, the existing system may be a lifestyle application for measuring effects of lifestyle interventions on cognitive abilities.

[0036] In an embodiment, the existing system may be a targeted advertising system.

[0037] In an embodiment, the existing system may be a system in support of human resources decisions.

[0038] In an embodiment, the existing system may be a system in support of forensic investigations.

[0039] In an embodiment, the existing system may be a system for measuring effects of stress.

[0040] In an embodiment, the existing system may be a preventive health system.

[0041] In an embodiment, the avatar may be steerable by binary user input from an input device. The gaming part may further be configured to accept the binary user input only during a predetermined time interval. The cognitive measurements obtained from the gaming object may be based on said binary user input received by the cognitive measurement part during said predetermined interval.

[0042] In an embodiment, the binary input may be selected from the group consisting of: i) pressing a key / button or not pressing a key / button and ii) pressing a key / button or pressing a different key / button.

[0043] In an embodiment, the gaming part may be configured to change the predetermined time interval based on a prior cognitive measurement.

[0044] In an embodiment, the statistical model may be based on a plurality of cognitive tests. Preferably, the statistical model is based on a plurality of cognitive test at once

[0045] In an embodiment, the cognitive measurement part may track differences in inputs in the gaming part as a trail feature is varied within the same game scenario.

[0046] In an embodiment, the varying trail feature may be a presence or an absence of a representation of ice or fire and / or a color of at least one representation. According to an aspect of the present disclosure, a computer program is presented. The computer program may include instruction which, when the program is executed by one or more processors, cause the one or more processors to carry out the computer-implemented method of cognitive measurements having one or more of the above identified features.

[0047] According to an aspect of the present disclosure, a computer-readable storage medium is presented. The computer-readable storage medium may include instructions which, when executed by one or more processors, cause the one or more processors to carry out the computer-implemented method of cognitive measurements having one or more of the above identified features.

[0048] According to an aspect of the present disclosure, a system configured for performing cognitive measurements is presented. The system may include one or more processors, a memory, a display and a user interface. The memory may store a computer program for execution by the one or more processors. The one or more processors may be configured to execute the computer program. The computer program may include computer program code that causes the system to output a computer presentable object on the display. The computer presentable object may be controllable by the user interface. The computer presentable object may include a gaming part and a cognitive measurement part. The gaming part may include an infinite runner game. An avatar may be displayed on a constantly moving trail, which avatar may be steerable by input from the input device. The cognitive measurement part may be integrated with the gaming part. The cognitive measurement part may be arranged to perform cognitive measurements including one or more cognitive tests, preferably one or more standard cognitive tests. The system may be arranged to generate a cognitive performance report based on a statistical model of the one or more cognitive tests and based on results from the cognitive measurements obtained from the gaming object.

[0049] In an embodiment, the one or more processors of the system may further be configured to carry out the computer-implemented method of cognitive measurements having one or more of the above identified features.

[0050] Advantageously, the present disclosure enables integration of multiple cognitive measurements into a single interactive experience. Statistical models may be aligned with the activity and several cognitive processes may be measured in one integrated environment. Thus, balancing engagement and quality of cognitive measurements can be achieved.

[0051] Brief description of the Drawings

[0052] Embodiments of the present disclosure will now be described, by way of example only, with reference to the accompanying schematic drawings in which corresponding reference symbol indicate corresponding parts, in which:

[0053] Figs. 1-4 show screenshots of an example infinite runner game for cognitive measurements according to example embodiments of the present disclosure;

[0054] Fig. 5 is a flow chart of a method according to an example embodiment of the present disclosure;

[0055] Fig. 6 is an example embodiment of a computing system for implementing certain aspects of the present technology;

[0056] Fig. 7 shows a simplified evidence accumulation process representation of two response types. For the correct first response, evidence accumulates to evoke a correct first response. For the error-correcting response, evidence accumulates to evoke an initial incorrect response and then continues to accumulate and later evokes an error-correcting response; and

[0057] Fig. 8 shows a competition between response initiation (go) and inhibition (stop) processes. In the top part, the go process reaches the finish line before the stop process, leading to an initial response that is later stopped. In the bottom part, the stop process reaches the finish line before the stop process. SSD, stop-signal delay, is the time between the target presentation and the stop-signal presentation. TTS, time-to-stop, is the time between the onset of the stop-signal and the late stop. SSRT is the stop-signal reaction time.

[0058] The figures are intended for illustrative purposes only, and do not serve as restriction of the scope of the protection as laid down by the claims.

[0059] Detailed description

[0060] It will be readily understood that the components of the embodiments as generally described herein and illustrated in the appended figures could be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of various embodiments, as represented in the figures, is not intended to limit the scope of the present disclosure but is merely representative of various embodiments. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0061] The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the present disclosure is, therefore, indicated by the appended claims rather than by this detailed description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

[0062] Reference throughout this specification to features, advantages, or similar language does not imply that all of the features and advantages that may be realized with the present disclosure should be or are in any single example of the present disclosure. Rather, language referring to the features and advantages is understood to mean that a specific feature, advantage, or characteristic described in connection with an embodiment is included in at least one embodiment of the present disclosure. Thus, discussions of the features and advantages, and similar language, throughout this specification may, but do not necessarily, refer to the same example.

[0063] Furthermore, the described features, advantages, and characteristics of the present disclosure may be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize, in light of the description herein, that the present disclosure can be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the present disclosure. Reference throughout this specification to "one embodiment," "an embodiment," or similar language means that a particular feature, structure, or characteristic described in connection with the indicated embodiment is included in at least one embodiment of the present disclosure. Thus, the phrases "in one embodiment," "in an embodiment," and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment. Game-based cognitive measurement systems (GCMSs) aim to improve user experience (UX) during cognitive assessment by using game-like elements such as leaderboards and 3D graphics. Known systems typically only moderately improve UX, because GCMSs mimic standard cognitive tasks by creating unnecessarily rigid and tightly controlled measurement systems which severely constrain players’ freedom.

[0064] Gamification involves the integration of game-design features, such as rewards, sounds, and narratives, into a pre-existing cognitive task. In gamified tasks, the gameplay mechanics may remain simple, repetitive, and task-like, while the game-like features such as improved graphics, or points system, are expected to enhance participants’ engagement. Alternatively, games may start with theories of cognition, and create a gameplay loop designed to measure specific cognitive functions. Theory- first custom games are more diverse, and may resemble commercial games, yet typically have simple task-like mechanics. Commercial games are rarely used for cognitive assessment. When used for assessment, their features are typically either correlated individually with the results of established tasks or are used together used to predict performance on established tasks.

[0065] From studies where player experience and engagement are compared between a game and a standard task, it has been found that game-based cognitive assessments tend to be more engaging than typical tasks, yet the differences tend to be small-to-moderate. Common gamification techniques typically do not significantly reduce attrition in longitudinal cognitive testing studies. The limited benefits of known gamified tasks are not surprising, since they are designed to maintain the exact mechanics of cognitive tasks, and to obtain the same response patterns obtained by the original tasks. Thus, they carry over many of the engagement-limiting features of the cognitive tasks they are based on, such as repetitiveness and limited response freedom.

[0066] The present disclosure provides a different type of game design for cognitive assessment, where maintaining an organic gameplay loop allows the cognitive tests to be played like a game, instead of just looking like a game.

[0067] The present disclosure gives players substantial freedom in GCMSs through inhibitory control and decision-making elements that allows players to continuously control an avatar through a digital space filled with hazards. The digital space preferably includes an infinite tunnel enabling rich, valid, and reliable cognitive measurements.

[0068] The present disclosure provides a core game loop that is aligned with a measurement structured underlying cognitive tasks to derive cognitive measurements and compute digital biomarkers of cognition. A participant of a cognitive test is a player of a game at the same time.

[0069] The core game loop may include a fully functional infinite runner game and exploits continuously running processes that update what players see (i.e. , stimuli) by presenting known cognitive challenges that are commonly used in cognitive tasks. Here, the term “infinite runner” is to be understood to mean to be moving in the game along an infinite trail by any means, such as walking, flying, driving, or any other form of movement. In some implementations, the infinite runner environment of the present disclosure provides for mostly continuous control of the movement of an avatar by a user / player. For example, the infinite runner environment of the present disclosure provides for a control of the movement of an avatar by a user / player that is at least 70%, and preferably at least 85% continuous. This is in contrast to typical methods for cognitive measurements, where the control is discrete.

[0070] The infinite runner of the present disclosure may be implemented as a tunnel runner that integrates cognitive challenges to inhibitory control and decision-making under uncertainty into a game. Cognitive challenges may be based on Simon, flanker, stop-signal and / or Iowa gambling tasks, which are recognized by the National Institute of Mental Health’s Research Domain Criteria, and may be used to study individual differences in cognitive function and psychopathology. When integrating the challenges into the core game loop, continuous and game-like player control can be maintained alongside a less repetitive experience. To maintain player control while integrating these cognitive challenges, the challenges are aligned with the game’s core gameplay, i.e., continuously moving through a tunnel while avoiding obstacles.

[0071] Furthermore, the continuous control over interaction with the cognitive assessment system, uniquely provides players with natural opportunities and incentives to correct mistaken initial responses. Furthermore, this may increase the players’ sense of control. In particular, a player who made an initial, incorrect, response is then given an opportunity to provide one or more further responses to correct the initial error. This increases the potential benefits of cognitive games such as the present disclosure, which tend to evoke relatively high rates of mistaken initial responses that are ignored by reaction-time-based measurements, leading to the acquisition of more data and increased measurement efficiency. Error-correcting responses can reflect the same cognitive functions measured with initial response data and are expected to provide new cognitive measurement opportunities. Thus, attempts to capture the dynamic nature of human cognition with less restrictive cognitive games could benefit from using error-correcting responses to improve cognitive assessment and provide new measurement opportunities.

[0072] Cognitive tasks are commonly used in cognitive psychology and neuroscience research to investigate processes such as attention, inhibition, decision-making, and response control. Examples of cognitive tasks are reaction time tasks of a regular trial (such as response accuracy and / or reaction time measurement), flanker tasks of a flanker trial, stop-signal tasks of a stop-signal trial, Simon tasks of a Simon trial, reverse-control tasks of a reverse-control trial and Iowa gambling tasks of an Iowa gambling trial.

[0073] The Flanker task is a cognitive task that may be used to examine the ability to inhibit irrelevant information and focus on relevant information. In this task, participants are presented with a central target stimulus surrounded by distractor stimuli (flankers). The task requires participants to respond based on the characteristics of the target stimulus while ignoring the distracting flankers. The critical manipulation in the Flanker task is the congruency between the target and flankers. In congruent trials, the flankers have the same response-relevant characteristics as the target, while in incongruent trials, the flankers have different response-relevant characteristics. The task measures the interference caused by incongruent flankers and provides insights into selective attention and response inhibition.

[0074] The Stop-Signal Task may be used to assess response inhibition, specifically the ability to inhibit a prepotent motor response. In this task, participants are typically asked to respond quickly to a go signal (e.g., a left or right arrow) by pressing a corresponding button. Occasionally, a stop signal (e.g., an auditory tone) is presented after the go signal, indicating that participants should withhold their response and not press the button. The stop signal is presented with a variable delay following the go signal, which is adjusted based on the participant's performance to maintain a certain level of difficulty. The Stop-Signal Task measures the stop-signal reaction time, which reflects the speed of inhibiting a response after the stop signal is presented. It provides insights into response inhibition processes and impulse control.

[0075] The Simon task is a cognitive task that may be used to study the phenomenon of stimulus-response compatibility. It involves presenting participants with a stimulus and instructing them to respond based on a specific stimulus feature (e.g., direction). The critical manipulation in the Simon task is the spatial relationship between the stimulus location and the required response. If the spatial location of the stimulus and the response button are compatible (e.g., stimulus on the left, response on the left), it is considered a congruent trial. If they are incompatible (e.g., stimulus on the left, response on the right), it is an incongruent trial. The task measures the interference caused by the incongruent trials and provides insights into the processing of spatial information.

[0076] The Iowa Gambling Task is a decision-making task designed to simulate real- life decision-making under uncertainty. The IGT may be used to study decision-making processes, risk-taking behavior, and the ability to learn from feedback.

[0077] Such cognitive tasks may be used to study cognition, individual differences, and psychopathology, and are paradigmatic examples of high-assessment, low- engagement measurements. The cognitive tasks are recognized by the National Institute of Mental Health (NIMH) research domain criteria.

[0078] In an embodiment, a tunnel runner game may be presented to a participant to measure inhibitory control and decision-making under uncertainty, drawing from cognitive challenges defined by the flanker, Simon, stop-signal, and / or Iowa gambling tasks. These tasks may be used to study individual differences in cognitive function and psychopathology and are recognized by the National Institute of Mental Health’s Research Domain Criteria.

[0079] Inhibitory control refers to the ability to prevent behavior, cognition, and affect from being captured by inappropriate habits and irrelevant stimuli. Inhibitory control enables individuals to flexibly engage in goal-directed behaviors rather than being driven by inappropriate habits and irrelevant external stimuli. Inhibitory control is divided into interference control, the shielding of behavior from irrelevant stimuli, and response inhibition, the suppression of potent and inappropriate behavioral responses. Interference control, a crucial part of selective attention, may be measured by the flanker and Simon tasks. Flanker tasks typically use a central stimulus, such as an arrow pointing to the left, surrounded by arrows that can match or mismatch the central stimulus by pointing in the opposite direction. Although participants are asked to respond only to the central stimulus, mismatches with the flanking arrows consistently increase participants’ reaction times and the prevalence of response errors, known as the flanker effect. Whereas in typical Simon tasks, participants are asked to use their left arm in response to a red shape and their right arm in response to a green shape. However, in some trials, the shape appears on the side opposite to the arm that should be used, creating stimulus-response incompatibility. This interference increases response times and the prevalence of response errors, known as the Simon effect. The magnitude of conflict effect serves as an indicator of interference control.

[0080] Response inhibition, a crucial part of self-control, may be measured with the stop-signal task. In a typical stop-signal task, participants are always presented with a go signal, such as an arrow pointing left or right, which is followed by a delayed stop signal in typically up to 25% of trials. Participants’ stop-signal reaction time (SSRT), a measure of response inhibition, is then inferred based on the horse race model. This model assumes that stop and go responses depend on a competition between two independent cognitive ’runners’, a go runner and a stop runner, with the ’winner’ determining whether a response will be performed or withheld.

[0081] Decision-making under uncertainty refers to the ability to choose between alternative behavioral options based on their expected consequences and potential risks. A key distinction in decision-making research pertains to the information given to participants about the uncertain consequences of different options, leading to two key categories: decision-making under risk and decision-making under ambiguity. Decision-making under risk refers to situations in which decision outcomes are uncertain and their probabilities are known. Decision-making under ambiguity refers to situations in which outcomes are uncertain and their probabilities are unknown, where ambiguity is overcome by exploring the available decision space and learning from feedback.

[0082] The Iowa gambling task is a staple of decision-making research, which was extensively used with both clinical and nonclinical populations. A typical version of the Iowa gambling task asks participants to repeatedly decide between four cards, with two being ‘good cards,’ which result in a net gain in the long run, and the other two being ‘bad cards’ that result in a net loss in the long run. Picking a good card always results in a moderate reward (e.g., 50 points). One good card leads to a loss of, e.g., 50 points on, e.g., 50% of times, whereas the good other card leads to a larger loss (e.g., 250 points) on , e.g., 10% of times. Picking a bad card always gives a larger immediate reward (e.g., 100 points) than the good cards. However, one bad card gives a large loss (e.g., 250 points) on, e.g., 50% of times, whereas the other bad card results in an even larger loss (e.g., 1250 points) on, e.g., 10% of times. Thus, participants are expected to overcome ambiguity by learning from repeated feedback, at which point the task shifts toward decision-making under risk. A similar Iowa gambling task may be integrated with the tunnel runner.

[0083] Challenge-based game design of the present disclosure may include three main components: (i) a cognitive challenge that has been based on research in the cognitive sciences, (ii) a game-design pattern that aligns with the cognitive challenge, and (iii) a statistical model that allows generating insights about cognitive performance from game-based events.

[0084] In an embodiment, multiple cognitive challenges may be added into the gameplay loop of an infinite runner. A player controls its avatar in the form of a group of representations of the player. Preferably an odd number of representations are used to enable having central representations, e.g., three or preferably five representations. Non-limiting examples of representations are rats, cats or other animals or objects, whose movements may be controlled by the participant using a user interface of the computer. An example of a trail of the gameplay includes a tunnel, pipe, or another enclosed form. The trail may be cylindrically shaped or have another suitable closed shape. The gameplay may be set up as the representations trying to escape via the trail. The trail may be layered with traps and obstacles that can slow and hurt the representations.

[0085] In an example embodiment, the trail includes a tunnel, and the representations are presented as rats. In this example, the gameplay may be set up as five rats trying to escape a secret lab via the tunnel. The tunnel may be layered with traps and obstacles that can slow and hurt the rats. In an embodiment, the tunnel may be rotating while the avatar is moving through the tunnel. This example embodiment also applies to other forms of representations.

[0086] The obstacles may be represented as one or more trail task features including a plurality of sections having certain characteristics, such as one or more colored rings divided into, e.g., six equally sized sections. Two or more of the sections may be characterized by different characteristics. In particular, two sections, e.g., the starting section and the ‘dead zone’ opposite to the staring section, may always be colored gray, whereas the four remaining sections may each be given a distinct color in each trial. A player may control the avatars’ movement direction by providing binary input, for example, a first user input such as pressing a specific key, e.g., “A”, to move the avatar in a first direction, e.g., to the left side of the tunnel, and providing a second user input such as pressing another specific key, e.g., “L”, to move the avatar in a second, different, preferably opposite, direction, e.g., to the right side. A third user input such as longer button pressing may result in further movement in a specified direction. Players are free to use the inputs in any sequence they prefer or that fits the game pattern.

[0087] The players’ goal in each trial may include getting the central representation through the only section that matches a characteristic of a central representation. In one implementation, the characteristic is a color, but it can also be a number, shape, type of animal, direction, texture, pattern, etc. Whenever the representation passes through the correct section, the player may receive an encouragement, such as a reward, e.g., a point, and an additional encouragement, such as a reward, e.g., extra points, e.g., depending on their current streak - the number of correct sections they passed in a row in the preceding trials. Passing through a wrong section may be followed by a discouragement. For example, the user / player may receive no reward (e.g., points), a reward may be taken away, and / or the user may have to restart the streak count. Correct and incorrect outcomes may also result in visual feedback. E.g., passing through incorrect sections may result in a penalty or negative consequence(s), such as causing a red X mark to appear on the screen's center, alongside a short vignette akin to a blink from pain. A reward for passing through correct sections may include a green checkmark appearing alongside a streak count.

[0088] For regular trials, the central representation and the (in this example four) flanker representations, that surround the central representation may be assigned the same characteristic, such as color, for a specific time after the trail task feature (e.g., the ring) is presented. For example, the central representation may be assigned a first characteristic, such as a specific color, for a first time period, e.g., 350 milliseconds, and the flanker representations may be assigned a first characteristic, such as the specific color, for a second time period, e.g., for 433 milliseconds, after a trail task feature, e.g., the ring, is presented.

[0089] In the regular trials the representations may only be moved following an assignment of a characteristic, for example, color assignments, and the player has a predetermined (short) time period, e.g., 1.317 milliseconds, to ensure the representations pass through the correct section of the trail task feature. Passing through a correct section may result in the time between characteristic (e.g., color) assignment and obstacle collision to be reduced, e.g., by 16.6 milliseconds, whereas passing through an incorrect section may increase time until collision by, e.g., 66.6 milliseconds.

[0090] For flanker trials a mismatching flanker trial may be performed. In mismatching flanker trials, inspired by the flanker effect, a flanker representation, may be assigned the characteristic, e.g., color, of the section that is different from, preferably opposite to, to the correct characteristic (e.g., color) of the target section of the trail task feature. A predetermined time period of, e.g., 83 milliseconds between characteristic / color assignments may be specified. In one example, mismatching flanker representations may have the color of the ring section that is opposite to the correct section. Since the flanker representations typically match the correct section on 50% of trials, participants may be instructed to ignore them.

[0091] During stop trials, inspired by the stop-signal task, the trail is provided with a user notification feature that acts as a stop-signal. In an embodiment, the representations may be surrounded by a stop-signal, e.g., displayed in the form of lava, predatory animal(s), thorns, text, etc., soon after characteristic (e.g., color) assignment, and the player may be instructed to avoid providing user input of movement, such as pressing a movement key. Stop trials may be independent from the assignment of flanker characteristics, such that the central representation and flanker representation characteristics (e.g., colors) are equally likely to match or mismatch in stop trials. The stop-signal may appear for a specific predetermined time interval, e.g., 250 milliseconds, after the central representation is assigned a characteristic (e.g., color). A stop-signal delay may be adapted by a player performance tracker. There may be multiple types of trackers, such as one for stop-signal trials alongside matching flanker trials, and another for stop-signal trials with mismatching flankers. Responding after the stop-signal may make the stop-signal (here, lava) appear earlier, e.g., 50 milliseconds earlier, giving the player more time for response inhibition. Successful inhibition may cause the stop-signal to appear later, e.g., 50 milliseconds later, giving the player less time for inhibition. Each tracker typically converges at around 50% nonresponse rate, which is desirable for inferring players’ stop-signal reaction time.

[0092] During reverse-control trials, inspired by the Simon effect, the trail may be provided with a reverse-control notification feature. In one implementation, the tunnel walls may be covered in, e.g., ice as soon as a new trail task feature, such as a ring, is shown. Consequently, the key mapping may be reversed. A player may control the avatars’ movement direction by providing a first user input such as pressing a specific key, e.g., “A”, to move the avatar in a second direction, e.g., to the right side of the tunnel, and providing a second user input such as pressing another specific key, e.g., “L”, to move the avatar in a first, different direction, e.g., to the left side. In other words, pressing “A“ moves the representations to the right, whereas pressing “L” moves the representations to the left. This may create a stimulus-response incompatibility, as reaching the section on one side of the screen requires movement of the opposite arm.

[0093] For IGT, during breaks from the core gameplay loop, the player may be presented with an intermediate task, during which the user is prompted to decide between different items by providing input that corresponds to one of the different items. In one implementation, the player is prompted to make snacking choices inspired by the IGT, which is characterized in that the choices with the best immediate reward have the worst long-term consequences. The player may be repeatedly asked to decide between a plurality of items, e.g., four boxes, by providing user input, here, pressing on a number that corresponds with the number on a box. The item chosen could have a reward or it could have a penalty associated with it. In an embodiment, the picked box could hide one or more awards, e.g., one or two watermelons. Some boxes may contain one watermelon rewarding the player with, e.g., 50 points, and the other boxes may contain two watermelons rewarding, e.g., 100 points. Furthermore, a box may sometimes hide a penalty such as one or more traps, e.g., a bear trap that costs, e.g., 50 points, two traps that cost, e.g., 100 points.

[0094] During the game play, the results of the cognitive tests, including a record of test subject inputs in response to various trail features, the sequence of test subject’s inputs, and the timing and nature of the of test subject’s inputs, may be stored in a memory for later assessment. The stage of the game itself and / or the points in the score and streak may be stored together with the results of the cognitive test.

[0095] A cognitive performance report may be generated based on a statistical model representative of the performed cognitive tests and using results from the cognitive measurements.

[0096] In an example, hierarchical regression models are fit using R packages Ime4 for model fitting alongside ImerTest for hypothesis testing. Hierarchical regression models may be used to account for interactions between cognitive challenges, i.e. , overlaps between, e.g., ice and flanker challenges, and the clustering of responses at the level of an individual participant. Thereby enabling a single model to estimate performance on multiple cognitive tests. When estimating individual differences in RT, accuracy, and decision quality, (joint) maximally specified Bayesian hierarchical regression models may be used. These models allow many parameters (such as variance) to differ as a function of trial features and the individual respondent. By modeling response patterns, Bayesian hierarchical regression models can considerably improve the estimation of individual differences and their correlates in cognitive tasks and allow the estimation of measurement reliability directly from the models’ posterior distributions.

[0097] Individual differences involving binary outcomes, e.g., accuracy and decisionmaking quality, may be estimated with hierarchical Bayesian logistic regression; continuous outcomes, e.g., RT, may be estimated with Gaussian or Ex-Gaussian models. SSRTs may be estimated via the integration method. Ex-Gaussian regression models, which model responses as a mixture of Gaussian and exponential distributions, may be used because they have been fruitfully applied to the analysis of conflict tasks such as flanker and Simon tasks.

[0098] Fig. 1 shows a screenshot 100 of an example infinite runner game, where the avatar takes the form of five rats 102. The trail is presented as a tunnel, represented by three-dimensional segments 110 that move on the display towards the viewer to create the effect of moving through the tunnel in a third-person view. Generally, in a third person view the camera allows you to see the character(s) you're controlling. It is behind the player so that you often see their back as you move through the world.

[0099] Obstacles are represented as colored rings 104 divided into six equally sized sections 106 (only one of the sections has been identified). Two sections, the starting section and the ‘dead zone’ opposite to it, are always colored gray, whereas the four remaining sections are each given a distinct color in each trial. The player controls the rats’ movement direction by pressing “A” to move them to the left side of the tunnel, and “L” to move them to the right side. With longer button pressing resulting in further movement in a specified direction. The players goal in each trial is to get the central rat 108 through the one section that matches its color.

[0100] Whenever the central rat 108 passes through the correct section 106, the player receives at least one point, and extra points depending on their streak - the number of correct sections they passed in a row in the preceding trials. Whereas passing through a wrong section gives no points and resets the streak count. Correct and incorrect outcomes result in differential visual feedback as passing through incorrect sections causes a red X mark to appear on the screen's center alongside a short vignette akin to a blink from pain; whereas passing through correct sections leads a green plus mark to appear alongside a streak count.

[0101] In regular (non-conflict) trials, the central rat and the four flanker rats - which surround the central rat - are assigned the same color for 350 and 433 milliseconds, respectively, after the ring 104 is presented. The rats 102 can only be moved following color assignment, and the player has 1.317 milliseconds to ensure they pass through the correct section 106. Time until obstacle-collision may be adapted via an algorithm such that passing through the correct section reduces the time between colorassignment and obstacle collision, whereas passing through the incorrect section increases time until collision. This performance tracking may be designed to result in success rates of about 80%.

[0102] In mismatching flanker trials, inspired by the flanker effect, the flanker rats next to the central rat 108 are assigned the color of the section opposite to the correct section. A time difference of 83 milliseconds between color assignments is specified to increase individual differences. Since the flanker rats match the correct section on 50% of trials, the player is instructed to ignore them. Note that the algorithm adapting the time the player has before collision is as affected by regular mismatching flanker trials as it is by regular matching flanker trials. These trials enable the measurement of players’ capacity for interference control via the differences between RTs and accuracy on matching and mismatching flanker trials.

[0103] Fig. 2 shows a screenshot 200 of the example infinitive runner game during lava trials, inspired by the stop-signal task. The rats 102 are surrounded by lava (a stop signal) represented by a lava texture 210 on the tunnel, soon after color-assignment, requiring the player to avoid pressing a movement key. Stop signal trials are independent from the assignment of flanker colors, making the central and flanker rats’ colors equally likely to match or mismatch in lava trials. At first, the stop-signal appears 250 milliseconds after the central rat is assigned a color, and the stop-signal delay (SSD) is adapted based on player performance, with SSD in matching flanker trials being adapted independently of the SSD in mismatching flanker trials. Specifically, moving the rats after the lava appears results in the lava appearing 50 milliseconds earlier, giving the player more time for response inhibition. Whereas successful inhibition will cause the lava to appear 50 milliseconds later, giving the player less time for inhibition. This should result in a response rate of around 50%, which is desirable for inferring players’ SSRT. Furthermore, if the rats 102 enter the lava, the player continually loses points until they bring the rats back to the starting point.

[0104] Fig. 3 show a screenshot 300 of the example infinitive runner game during ice trials, inspired by the Simon effect. The tunnel gets filled with ice represented by an ice texture 310 on the tunnel, as soon as the rats 102 are presented with a new ring 302. Consequently, the key mapping is flipped as indicated by the bitmap 304, such that pressing “A” moves the rats 102 to the right, whereas pressing “L” moves them to the left. This creates stimulus-response incompatibility, as reaching the section on one side of the screen requires movement of the opposite arm. However, this significantly deviates from the Simon task, since spatial features have a role in determining the correct choices, which may result in a challenge to cognitive flexibility. The presentation of ice trials does not depend on the color of the flankers, such that matching and mismatching flanker trials are equally spread across ice trials. Ice trials may overlap with fire trials. Fig. 4 shows a screenshot 400 of the example infinitive runner game during breaks from the game's running loop. The player is presented with snacking choices inspired by the IGT. The player is repeatedly asked to decide between four boxes 402 by pressing on a number that corresponds with the number on top of a box of their choice. The picked box may reveal one or two slices of melons, rewarding the player with 5 or 10 points, respectively. Furthermore, the picked box sometimes reveals 1 , 5, or 25 traps, corresponding to a loss of 5, 25, and 125 points. Such that boxes 1-2 always reward 10 points, but cost 25 points on 50% of trials, or 125 on 10% of trials; whereas boxes 3-4 always reward 5 points, but cost 5 points on 50% of trials, or 25 on 10% of trials. This creates a scenario where choices giving larger immediate rewards are detrimental in the long run.

[0105] Definition and measurement of error-correcting responses implemented in the applicable embodiments of the present disclosure can be conducted according to leading cognitive models of speeded binary decision-making and response inhibition. Importantly, as the present disclosure enables different types of error-correcting behaviours, such as response-switching in non-lava trials and late stopping in lava trials, and these different behaviours are generally modelled using different frameworks, distinct theoretical perspectives for each type of error-correcting behaviour should be applied. Specifically, it is expected that error-correcting responses that involve response-switching result from an evidence accumulation process, which is the dominant perspective on speeded binary decisions. In contrast, error-correcting responses involving late stopping in lava trials are expected to result from a competition between two independent cognitive processes, which is the dominant perspective in the stop-signal literature.

[0106] EXAMPLES

[0107] In the following, examples of error-correction and examples of tunnel runner implementations are presented.

[0108] Error-Correction

[0109] Error-correction in non-lava trials.

[0110] In non-lava trials, we assumed that the timing and nature of players’ responses depend on the dynamics of an evidence accumulation process. The core of the evidence accumulation perspective involves the accumulation of evidence until it reaches a response boundary for one of the competing decisions. Once enough evidence has accumulated to reach a response boundary, a corresponding response is initiated. We assume that the evidence accumulation process does not terminate once a response boundary is reached; rather, the evidence accumulation process continues and could lead to a reversal of the initial response. Thus, the time from target presentation to a correct first response or to an error-correcting response each reflect the time required for the evidence accumulation process to reach the correct response boundary. Consequently, in non-lava trials, we measured error-correcting responses as the time between the central rat’s color assignment and the initiation of the reversal of an incorrect first response. A simplified evidence accumulation process is illustrated in Figure 7.

[0111] Error-correction in lava trials.

[0112] In lava trials, we assume that go and stop responses are determined by a competition between two independent cognitive processes, as outlined by the independent race model. From this perspective, the winner of a competition between a ‘go runner’ and a ‘stop runner’ determines whether a response is initiated or inhibited. Thus, stop-signal reaction time (SSRT), which is calculated in typical stopsignal tasks, is an estimate of the time it takes the stop runner to reach the competition’s ‘finish line’ and prevent a response. We assume that the stop runner does not ‘quit’ once a go response is initiated and can reach the finish line in time to inhibit the ongoing response, as shown in Figure 8. Thus, the time from the presentation of a stop-signal to the inhibition of the initial go response, the time-to- stop (TTS), is a function of the time it takes for the stop runner to reach the finish line in trials where the go runner made it first. This means that both TTS and SSRT measurements should reflect the time it takes for the stop runner to reach the finish line. However, since players may inhibit their responses for reasons other than the stop-signal, TTS measurements require response inhibition to be followed by a corrective response, showing clear recognition of the mistaken initial response.

[0113] Given our assumption that players’ late stopping responses reflect a continuation of the same cognitive functions responsible for their stop-signal reaction times (SSRTs), we expected players’ time-to-stop (TTS) to show a flanker effect comparable to the one observed on SSRT. Furthermore, we expected SSRT and TTS measures to strongly correlate. To assess these expectations, we calculated SSRTs via the integration method and players’ TTS via hierarchical regression models with fixed and random terms for intercept and trial type.

[0114] Table 1. Conflict effects on error-correcting responses and their comparisons with conflict effects on first responses. RT1 is the time to correct first responses, RT2 is the time to error-correcting responses, SSRT is stop-signal reaction time, and TTS is time-to-stop. Confidence intervals and significance levels were based on hierarchical regression models for all but the last row, which is based on paired-sample t-tests. All measurements are at the millisecond unit. * Significant difference.

[0115] As shown in Table 1 , we found flanker effects on players’ TTS in both studies 1 (m = 15.2 ms, t(90.4) = 4.61 , p < .001) and 2 (m = 15.5 ms, t(87) = 4.2, p < .001), which paired-samples t-tests showed were not significantly different from (though quantitatively shorter than) the flanker effects on SSRT in studies 1 (m = -2.6 ms, t(96) = -0.46, p = .628) and 2 (m = -4.4 ms, t(88) = -0.88, p = .382). Furthermore, as shown in Figure 7, players’ SSRT scores strongly correlated with their TTS scores in both studies 1 (r = .76, 95% Cl: .65 - .83, t(95) = 11.24, p < .001) and 2 (r = .74, 95% Cl: .63 - .82, t(87) = 10.39, p < .001). These results led us to conclude that players’ TTS reflected a continuation of the cognitive processes measured by their SSRT.

[0116] We supplemented first-response-based measurements with error-correcting responses in two ways. For ice and flanker effects, we used hierarchical regression models with fixed and random effects of trial type and response type and only a fixed effect for their interaction. This model structure embodied the assumption that individual differences in conflict effects were shared between response types. For SSRT calculations, we z-transformed players’ TTS as estimated by hierarchical regression with fixed and random intercept and only a fixed trial type effect. We then averaged players’ z-transformed TTS with their z-transformed SSRT calculated separately per matching and mismatching flanker trials.

[0117] Table 2. Reliability of measurements based on first responses only, and on first responses combined with error-correcting responses. SSRT is stop-signal reaction time. Reliability was estimated via odd-even split-halves for the ice and flanker effects and via McDonald’s co for SSRT.

[0118] As shown in Table 2, supplementing first-response-based measurements with error-correcting responses resulted in modest yet consistent increments to our measurements’ reliability that ranged from .008 to .046 for flanker effect and SSRT measurements. The SSRT and flanker effect estimates obtained from first response data were nearly identical to those obtained by combining first response and errorcorrection data (rs = .97). In contrast, modest reliability reductions of -.027 and -.012 were seen in studies 1 and 2’s measures of the ice effects, and the two measurement approaches were not as strongly correlated (study 1 : r = ..86; study 2: r = .93) as before. These results suggest that error-correcting responses can increase the reliability of cognitive measurements when cognitive continuity holds, as was the case for the flanker effect and SSRT, and may otherwise decrease measurement reliability, as was the case for the ice effect.

[0119] To assess the potential of error-correcting responses as separate cognitive measurements, we estimated individual differences and measurement noise using hierarchical regressions that considered first response data separately from errorcorrection data. For the ice and flanker effects on RT 1 and RT2, the models contained fixed and random terms for intercept and trial type. For the TTS, the models included fixed and random intercepts, and only a fixed trial type term since individual differences due to trial type (the flanker effect on TTS) were minimal. As shown in Table 3, RT2 measures of flanker and ice effects were no more precise than RT1 measures. This means that the game’s RT2 conflict effect measures, similarly to the RT1 conflict effect measures, require hundreds of response trials to achieve acceptable measurement reliability on their own. In contrast, the TTS measure showed very high precision, sufficient to achieve excellent split-half reliability of .924 and .936 in studies 1 and 2.

[0120] Table 3. Precision of the different measurements, defined as the ratio between the standard deviation of individual differences and of the measurement noise estimated by a statistical model. RT1 is the time to correct first responses, RT2 is the time to error-correcting responses, SSRT is stop-signal reaction time, and TTS is time-to- stop.

[0121] Tunnel Runner

[0122] Examples of an infinite runner game.

[0123] In an example, the tunnel runner is an infinite runner game that may be built in Unity 3D using the Unity Experimental Framework (UXF) and in which players move their avatars through a tunnel. The infinite runner game may involve a player- controlled avatar constantly moving through a virtual space. The Infinite runner game give players continuous control over their avatars’ movements, is challenging and responsive, and provides clear and immediate feedback in terms of rewards and penalties. Furthermore, infinite runners create time constraints and allow the presentation of stimulus in a controlled manner, thereby facilitating the measurement of response time and accuracy under different conditions. Thus, the infinite runner game provides an enjoyable experience while enabling for cognitive assessment.

[0124] In an example, the tunnel runner is premised on the escape of an avatar in the form of five test subject representations, in this example five rats, from a mad scientist’s lab via a tunnel filled with traps and obstacles, which are used to present cognitive challenges to inhibitory control and decision-making under uncertainty that are inspired by flanker, Simon, stop-signal, and Iowa gambling tasks. As the rats run through the tunnel, they encounter obstacles represented as colored rings divided into six equally sized sections. Two sections — the rats’ starting section at the bottom of the tunnel and the ‘dead zone’ at the top of the tunnel — are always colored gray, while each of the four remaining sections is given a different color in each trial. This design ensures that there is always an optimal way to respond to a trial. The control scheme is easily accessible to a broad population of participants, where players control the rats’ movement direction by pressing a specific key, e.g., the A key, to rotate them to the left and another specific key, e.g., the L key, to rotate them to the right. To encourage accurate first responding, a trial’s first button press results in a slightly faster rotation than later button pressing. The game gives players continuous control over the rats’ rotation for more than, e.g., 80% of playtime, with the explicit goal of getting the central rat through the one section that matches its color.

[0125] In this example, whenever the central rat passes through the correct section, the player receives, e.g., one point and extra points corresponding to their streak — the number of correct sections they passed in a row in preceding trials. Passing through a wrong section resets the streak count. The streak mechanic is meant to facilitate a sense of reward and to promote correct responses. Correct and incorrect trial outcomes result in different visual feedback to inform players of their mistake, provide a sense of responsiveness, and facilitate correct responses. Passing through incorrect sections causes a red X mark, to appear on the screen’s center, accompanied by a short vignette effect meant to be similar to a blink from pain, while passing through correct sections results in a green plus mark that appears next to a streak count, representing the points earned in the trial.

[0126] Examples of trial types. In an example, the game’s core gameplay may include regular (non-conflict) trials and an avatar in the form of five test subject representations, in this example five rats. In this example, the central rats and the four flanker rats — which surround the central rat — are assigned the same color at, e.g., 433 and, e.g., 350 milliseconds, respectively, after the obstacle ring, such as ring 104 in Fig. 1 , is first presented. The rats can only be rotated after color assignment, leaving the player, in this example, with 1 ,317 milliseconds to ensure that they pass through the correct section of the obstacle before the next trial starts. While the time until color assignment is static, the time until obstacle collision is adapted so that passing through the correct section reduces the time between the next color assignment and obstacle collision, whereas passing through the incorrect section increases the time until the next collision. An adaptation algorithm may facilitate success rates of about 80% per player, which is challenging and encourages correct first responses without feeling unfair.

[0127] In an example, the tunnel runner may have a single set of regular running trials that are compared against multiple sets of conflict trials, with the purpose of decreasing tunnel runner’s repetitiveness while increasing its efficiency compared to typical cognitive tasks and games. In this example, there may be three types of conflict trials that challenge players’ inhibitory control and intuitively fit the game’s gameplay and narrative without being too demanding or confusing. A central target may be surrounded with similar-looking yet misleading flankers to create a challenge to interference control similar to flanker tasks’ flanker effect. Furthermore, stimulusresponse incompatibility may be created by reversing the game’s controls on some trials such that, like in a Simon task, responding to one side of the screen requires players to press a button on the opposite side of their controller, e.g., keyboard. Moreover, players’ response inhibition may be challenged with a delayed stop-signal. In an example, the tunnel runner applying these three cognitive tests may include mismatching flanker trials to create flanker-like interference, ice trials to create stimulus-response incompatibility, and lava trials that use a delayed stop-signal. Such cognitive challenges enable measurements of players’ interference control and response inhibition.

[0128] In an example, the game’s core gameplay may include mismatching flanker trials. In this example, players are told that flanker test subject representations, e.g., flanker rats, are trying to help but often go wrong and should be ignored. In 50% of trials, the flanker rats’ color matches the color of the section opposite the correct section, creating mismatching flanker trials which are inspired by flanker tasks. Based on studies of the flanker task, a time difference of, e.g., 83 milliseconds may be specified between the color assignments of the flankers and the central rat with the aim of enhancing individual differences by increasing the challenge’s difficulty. The algorithm adapting the time players have from color assignment to collision is as sensitive to regular mismatching flanker trials as it is to regular matching flanker trials.

[0129] In an example, the game’s core gameplay may include lava trials. In this example, players are told that most of the tunnel can be covered by lava, which hurts the test subject representations, e.g., rats, on touch. This results in lava trials, inspired by stop-signal tasks, where the rats are surrounded by lava (serving a stop signal) after color-assignment. Touching the lava, which can only be prevented by not moving the rats from the starting point, leads to a loss of points and resets one’s streak. Whenever the rats enter the lava, players keep losing points until they rotate the rats back to the starting point. Lava trials are independent of the assignment of flanker colors, so the colors of the central and flanker rats are equally likely to match or mismatch in lava trials. At the first lava trial, the stop-signal appears at a delay of, e.g., 300 milliseconds after the central rat is assigned a color, following which the stopsignal delay (SSD) is adapted based on the player’s performance. SSD in matching flanker trials is adapted independently of the SSD in mismatching flanker trials. As in typical stop-signal tasks, moving the rats after the stop signal results in lava appearing, e.g., 50 milliseconds earlier, giving players more time for response inhibition. Whereas successful inhibition causes the lava to appear, e.g., 50 milliseconds later, giving players less time for inhibition. This adaptation should lead players to avoid responding at around 50% of lava trials, which is desirable for inferring SSRT.

[0130] In an example, the game’s core gameplay may include ice trials. In this example, players are told that the tunnel can be covered by ice, which reverses the rotation of the test subject representation, e.g., the rats’ rotation. During ice trials, inspired by the stimulus-response incompatibility effect in Simon tasks, the tunnel is filled with ice once the rats are presented with a new obstacle. The ice reverses the key mapping so that pressing, e.g., A moves the rats to the right, whereas pressing, e.g., L moves them to the left. This response reversal is meant to create stimulus-response incompatibility, as reaching the section on one side of the screen requires using a button on the opposite side of the controller, e.g., keyboard. However, this challenge significantly deviates from typical stimulus-response incompatibility measures such as Simon tasks, since spatial features determine the correct choices in tunnel runner, whereas they are irrelevant in Simon tasks. The presentation of ice trials is independent of flanker trials, such that matching and mismatching flanker trials are equally spread across ice trials. On rare occasions, ice trials overlap with fire trials to create a sense that stop signals might occur during ice trials and, therefore, ensure that ice trials are comparable to regular trials. As lava trials may otherwise selectively affect response caution in non-ice trials.

[0131] In an example the game’s core gameplay may include snacking trials. In this example, tunnel runner’s fast pace and varied cognitive challenges make it highly demanding for players’ inhibitory control and it is ensured that players take relatively long breaks from the game’s running trials without wasting players’ time. The breaks are used to implement a slower cognitive challenge that is less demanding for players’ inhibitory control. Consequently, during breaks from tunnel runner’s running trials, a challenge to players’ decision-making under uncertainty is presented as series of snacking choices whose consequences are structured similarly to Iowa gambling tasks.

[0132] During snacking trials, players may be told that they discovered a hidden room filled with boxes and are repeatedly asked to decide between four boxes by pressing a number that corresponds to the box of their choice. The selected box could reveal one or two presents, e.g., slices of melons, which rewards players with, e.g., 5 or 10 points, respectively. Furthermore, the chosen box sometimes reveals, e.g., 1 , 5, or 25 traps, corresponding to a loss of, e.g., 5, 25, and 125 points. Boxes 1-2 always reward, e.g., 10 points, but cost, e.g., 25 points on 50% of trials, or, e.g., 125 on 10% of trials; while boxes 3-4 always reward, e.g., 5 points, but cost, e.g., 5 points on 50% of trials, or, e.g., 25 points on 10% of trials. Creating a decision-making under uncertainty scenario where, as in Iowa gambling tasks, choices with larger immediate rewards are detrimental in the long run.

[0133] The game’s running trials of the present disclosure preferably requires test subjects to match between two stimuli, the obstacle and the central test subject representation, e.g., central rat, based on the trial’s characteristics instead of responding to a single stimulus as is typical in known cognitive tasks. This increased complexity affects test subjects’ response tendencies. Furthermore, tunnel runner allows test subjects to correct mistaken first movements, which may reduce response caution in players’ first responses. Tunnel runner is also typically about two-times longer than a traditional flanker, stop-signal or Simon task and efficiently combines several cognitive challenges into a single game. Thus, the game may require more effort to complete. Lastly, players’ decisions in the game’s decision-making challenge influence a pool of points they worked hard to obtain, unlike the initial batch of points freely given in the Iowa gambling task. This difference in framing may influence decisions-making patterns. The present disclosure may be used to implement cognitive measures into interactive systems, shortening the time of cognitive measures, increasing engagement and enabling re-test reliability.

[0134] For example, universities and research groups may use the present disclosure to shorten measurement times of cognitive tasks, to improve measurement quality, and to bring tests into research environments that are usually difficult to approach, e.g., in socioeconomic status (SES) testing. Further, the effects of lifestyle interventions, e.g., stress reduction, may be assessed in clinical trials.

[0135] For example, the pharmaceutical industry may use the present disclosure in testing effects of drugs on people and to identify positive and negative cognitive effects. Digital biomarkers have been under investigation and show promising outcomes. The fast, reliable, engaging approach provided by the present disclosure may be used as an endpoint in clinical studies.

[0136] For example, in lifestyle applications the present disclosure may demonstrate the effects of lifestyle interventions on cognitive abilities; an additional feature that next to intervention allows for personal assessment.

[0137] For example, for marketing purposes the present disclosure may be implemented into commercial video games, where differences in cognitive performance may be assessed linked to personal circumstances such as intoxication, stress, and tiredness, which outcome may be used for targeted advertisement, e.g., for stress relief programs or items. For example, in preventive health at scale cognitive data obtained using the present disclosure may allow for early detection of cognitive changes, e.g., cognitive decline due to dementia.

[0138] Fig. 5 is a flow chart 500 of an example embodiment of the present disclosure.

[0139] In step 510 a computer code may be provided which, when executed by one or more processors, causes a computer to display a computer presentable object that is controllable by a user interface. The computer presentable object may include a gaming part and a cognitive measurement part. The gaming part may include an infinite runner game, wherein an avatar is displayed on a constantly moving trail, which avatar is steerable by input from an input device of the computer. The cognitive measurement part may be integrated with the gaming part.

[0140] Steps 512 and 514 may be part of step 510. In step 512 the gaming part may be presented and controlled by the player / user through the user interface. In step 514 the cognitive measurement part may be presented and interacted with by the player / user through the user interface.

[0141] The cognitive measurement part may be arranged to perform cognitive measurements comprising one or more standard cognitive tests. The player / user may perform multiple cognitive tests, as depicted by the arrow from step 514 back to step 514. The same or different cognitive tests may thus be performed in a row. After one or more cognitive tests, the computer program may return to the gaming part, as depicted by the arrow from step 514 to step 512.

[0142] The method may further include generating 520 a cognitive performance report based on a statistical model of the one or more standard cognitive tests and based on results from the cognitive measurements obtained from the gaming object.

[0143] FIG. 6 shows an example embodiment of a computing system 600 for implementing certain aspects of the present technology. In various examples, the computing system 600 can be any computing device implementing the computer- implemented method of cognitive measurements described herein.

[0144] The computing system 600 can include any component of a computing system described herein which components of the system are in communication with each other using connection 605. The connection 605 can be a physical connection via a bus, or a direct connection into processor 610, such as in a chipset architecture. The connection 605 can also be a virtual connection, networked connection, or logical connection.

[0145] In some implementations, the computing system 600 is a distributed system in which the functions described in this disclosure can be distributed within a datacenter, multiple data centers, a peer network, etc. In some embodiments, one or more of the described system components represents many such components each performing some or all of the functions for which the component is described. In some embodiments, the components can be physical or virtual devices.

[0146] The example system 600 includes at least one processing unit (CPU or processor) 610 and a connection 605 that couples various system components including system memory 615, such as read-only memory (ROM) 620 and randomaccess memory (RAM) 625 to processor 610. The computing system 600 can include a cache of high-speed memory 612 connected directly with, in close proximity to, or integrated as part of the processor 610.

[0147] The processor 610 can include any general-purpose processor and a hardware service or software service, such as services 632, 634, and 636 stored in storage device 630, configured to control the processor 610 as well as a special-purpose processor where software instructions are incorporated into the actual processor design. The processor 610 may essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

[0148] To enable user interaction, the computing system 600 includes an input device 645, which can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture or graphical input, keyboard, mouse, motion input, speech, etc. The computing system 600 can also include an output device 635, which can be one or more of a number of output mechanisms known to those of skill in the art. In some instances, multimodal systems can enable a user to provide multiple types of input / output to communicate with the computing system 600. The computing system 600 can include a communications interface 640, which can generally govern and manage the user input and system output. There is no restriction on operating on any particular hardware arrangement, and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed. A storage device 630 can be a non-volatile memory device and can be a hard disk or other types of computer readable media which can store data that are accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices, digital versatile disks, cartridges, random access memories (RAMs), read-only memory (ROM), and / or some combination of these devices.

[0149] The storage device 630 can include software services, servers, services, etc., that when the code that defines such software is executed by the processor 610, it causes the system to perform a function. In some embodiments, a hardware service that performs a particular function can include the software component stored in a computer-readable medium in connection with the necessary hardware components, such as a processor 610, a connection 605, an output device 635, etc., to carry out the function.

Claims

CLAIMS1. A computer-implemented method of cognitive measurements, comprising: providing a computer code which, when executed by one or more processors, causes a computer to display a computer presentable object that is controllable by a user interface, wherein the computer presentable object comprises a gaming part and a cognitive measurement part, wherein the gaming part comprises an infinite runner game, wherein an avatar is displayed on a constantly moving trail represented as an enclosed form in a third- person view, wherein the avatar is configured to constantly move forward in the enclosed form, which avatar comprises a plurality of test subject representations and is steerable by input from an input device of the computer, wherein the cognitive measurement part is integrated with the gaming part, wherein the cognitive measurement part is arranged to perform cognitive measurements comprising one or more cognitive tests, and wherein the method further comprises generating a cognitive performance report based on a statistical model of the one or more cognitive tests and based on results from the cognitive measurements obtained from the gaming object.

2. The method according to claim 1 , wherein the cognitive measurement part is arranged to perform cognitive measurements comprising one or more standard cognitive tests.

3. The method according to claim 1 or claim 2, wherein the cognitive tests include at least one of: a reaction time task of a regular trial; a flanker task of a flanker trial; a stop-signal task of a stop-signal trial; a reverse-control task of a reverse-control trial; an Iowa gambling task of an Iowa gambling trial.

4. The method according to any one of the preceding claims, wherein the statistical model aligns the gaming part with the cognitive measurement part.

5. The method according to any one of the preceding claims, further comprising obtaining digital biomarkers of cognition from the cognitive performance report.

6. The method according to any one of the preceding claims, wherein the cognitive measurement part integrates inhibitory control and decision-making challenges in the cognitive measurements.

7. The method according to any one of the preceding claims, wherein the cognitive measurement part integrates error correcting input, such as a time to correct an error, in the cognitive measurements.

8. The method according to any one of the preceding claims, wherein the cognitive measurement part comprises cognitive challenges that are controllable using the user interface and that are measurable by the cognitive measurements.

9. The method according to any one of the preceding claims, wherein the one or more cognitive tests comprises a presentation of one or more trail task features inducing a cognitive measurement score depending on an interaction of the avatar with the one or more trail task features.

10. The method according to claim 9, wherein the trail task feature comprises a plurality of sections, wherein two or more of the sections have different characteristics inducing a different cognitive measurement score.

11. The method according to claim 8, wherein the enclosed form is a three- dimensional tunnel.

12. The method according to claim 11 , wherein the avatar comprises a group of an odd number and similar test subject representations, wherein the representations inthe group are displayed on the trail side by side, and wherein the representations of the group are configured for steering together based on the input from the input device.

13. The method according to claim 12, wherein the group comprises at least three, and preferably five test subject representations.

14. The method according to any one of the preceding claims, wherein the one or more cognitive tests comprises a presentation of a trail task feature, wherein the avatar comprises a group of an odd number and similar test subject representations, and wherein guiding a central representation through a section of the trail task feature that matches a characteristic of the central representation yields an encouragement to the user in the gaming part, and wherein guiding a central representation through a section of the trail task feature that does not match a characteristic of the central representation yields a discouragement to the user in the gaming part.

15. The method according to any one of the preceding claims, wherein a user guides the avatar through a rotating tunnel using the user interface.

16. The method according to any one of the preceding claims, comprising receiving a user input to perform an action based on one or more characteristics of one or more representations of the avatar and based on one or more characteristics of the trail, wherein a result of the cognitive measurements is based on the input and result of the action.

17. The method according to claim 16, wherein the action comprises steering the avatar such that a representation having a certain characteristic is aligned to a trail section that matches that characteristic and a result of the cognitive measurements is based on a result of the matching.

18. The method according to claim 16, wherein the action comprises steering the avatar such that one or more of the representations of the group move through a section of a ring object.

19. The method according to claim 18, wherein the one or more representations of are to be steered through a section of the ring having a specific color.

20. The method according to any one of the preceding claims, wherein the gaming part further comprises prompting the user to decide between different items by providing input that corresponds to one of the different items and the cognitive measurement incorporates the input representing user decision.

21. The method according to any one of the preceding claims, further comprising integrating the computer code into an existing system for cognitive measurements.

22. The method according to claim 21 , wherein the existing system is one of: a system for measuring socioeconomic status, SES; a system for measuring effects of a medical treatment; a system for measuring effects in a clinical trial; a system for measuring effects of drugs; a lifestyle application for measuring effects of lifestyle interventions on cognitive abilities; a targeted advertising system; a system in support of human resources decisions; a system in support of forensic investigations; a system for measuring effects of stress; and a preventive health system.

23. The method according to any one of the preceding claims, wherein the avatar is steerable by binary user input from an input device, wherein the gaming part is further configured to accept the binary user input only during a predetermined time interval, and wherein the cognitive measurements obtained from the gaming object are based on said binary user input received by the cognitive measurement part during said predetermined interval.

24. The method according to claim 23, wherein the binary input is selected from the group consisting of: i) pressing a key / button or not pressing a key / button and ii) pressing a key / button or pressing a different key / button.

25. The method according to claim 23 or claim 24, wherein the gaming part is configured to change the predetermined time interval based on a prior cognitive measurement.

26. The method according to any one of the preceding claims, wherein the statistical model is based on a plurality of cognitive tests.

27. The method according to any one of the preceding claims, wherein the cognitive measurement part tracks differences in inputs in the gaming part as a trail feature is varied within the same game scenario.

28. The method according to claim 27, wherein the varying trail feature is a presence or an absence of a representation of ice or fire and / or a color of at least one representation.

29. A computer program comprising instruction which, when the program is executed by one or more processors, cause the one or more processors to carry out the method according to any one of the claims 1-28.

30. A computer-readable storage medium comprising instructions which, when executed by one or more processors, cause the one or more processors to carry out the method according to any one of the claims 1-28.

31. A system configured for performing cognitive measurements, the system comprising one or more processors, a memory, a display and a user interface, wherein the memory stores a computer program for execution by the one or more processors, wherein the one or more processors are configured to execute the computer program,wherein the computer program comprises computer program code that causes the system to output a computer presentable object on the display, wherein the computer presentable object is controllable by the user interface, wherein the computer presentable object comprises a gaming part and a cognitive measurement part, wherein the gaming part comprises an infinite runner game, wherein an avatar is displayed on a constantly moving trail, which avatar is steerable by input from the input device, wherein the cognitive measurement part is integrated with the gaming part, wherein the cognitive measurement part is arranged to perform cognitive measurements comprising one or more cognitive tests, and wherein the system is arranged to generate a cognitive performance report based on a statistical model of the one or more cognitive tests and based on results from the cognitive measurements obtained from the gaming object.

32. The system according to claim 31 , wherein the one or more processors are configured to carry out the method according to any one of the claims 1-28.

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