Attention represents the allocation of cognitive processing resources. Visual search refers to the attentional task that involves a scan of the visual environment to detect a particular object among a set of objects. Performing such tasks is useful in daily life in activities such as finding a product in the store, finding a friend in a crowd, in more specialized roles, such as performing quality control on an assembly line, and historically, finding food or avoiding predators in the natural environment. Enhancing an individual's attentional task capacity is highly desirable.
Many studies have shown that attentional abilities can be increased through repeated practice of a visual search task. See, CZERWINSKI, et al., Automatization and Training in Visual Search. The American Journal of Psychology 15(2) 271-315 (1992); HO, et al., Plasticity of Feature-Based Selection in Triple-Conjunction Search, Canadian Journal of Experimental Psychology 57(1) 48-60 (2003). These promising approaches demonstrate the appeal of visual search training, however, they are not without their limitations. In particular, research has shown that generalization of training of visual stimuli is related to the similarity of the stimuli. See, DUNCAN, et al., Visual Search and Stimulus Similarity, Psychological Review 96(3) 433-458 (1989); HO, et al., Age, Skill Transfer, and Conjunction Search. Journal of Gerontology 57B(3) 277-287 (2002). Thus, to be most effective, a visual search task should include primitive and varied visual stimuli. Furthermore, such tasks can be adapted in real-time to maximize challenge and efficacy to users.
Of particular difficulty are conjunction searches, searches in which the target object shares visual properties with distractor objects, such as color, shape, orientation, motion, and size. See, TREISMAN, et al., A feature-integration theory of attention. Cognitive Psychology 12 97-136 (1980); LOBLEY, et al., Perceptual learning in visual conjunction search, Perception 27 1245-1255 (1998). Conjunction search reduces stimulus-driven search and is thought to be driven by top-down processing, where perception is influenced by experience. Organic tasks involving visual search activate frontal eye field, superior colliculus, and multiple parietal areas in a robust and ecologically relevant manner. See, MULLER, et al., The functional neuroanatomy of visual conjunction search: a parametric fMRI study, Neurolmage 20, 1578-1590 (2003); DONNER, et al., Involvement of the human frontal eye field and multiple parietal areas in covert visual selection during conjunction search. European Journal of Neuroscience 12(9) 3407-3414 (2001).
What is needed are cognitive training exercises that train visual attentional abilities in an intuitive, engaging, and adaptively challenging way to enhance cognition.
Disclosed are novel cognitive training exercises that train visual attentional abilities in an intuitive, engaging, and adaptively challenging way to enhance cognition and related skills. The exercises engage users in a task where the user identities a unique object out of a set of objects as quickly as possible. As users progress through sequential trials, difficulty can be modulated by selecting various visual attributes that will best challenge the user and/or increasing the number and variation of the different object and/or types within the set of objects.
A goal of the exercises can be to scan multiple objects having various distinguishing attributes for an object that has no duplicate. The exercises require that the user/player visually search through multiple objects and quickly find the unique object.
It will be understood by those skilled in the art that methods and apparatuses for enhancing a cognitive ability of a user are disclosed, which may comprise: conducting, via a user interface display of a user computing device, a training session which may comprise: presenting, via the user interface display of the user computing device, a plurality of objects having at least two identifying parameters, at least two of the plurality of objects having the same at least two identifying parameters forming at least one group of objects having the same at least two identifying parameters and at least one of the objects having at least one unique identifying parameter thereby not duplicating the identifying parameters of the at least two objects in the at least one group of objects; and allowing the user, via the user interface display of the user computing device, to select an object as a proposed unique object.
According to other aspects of the disclosed subject matter the at least one group of objects may comprise a plurality of groups of objects and the at least one unique object may comprise one unique object. Additionally, the computing device may be configured to record whether the user successfully selected the at least one unique object as the proposed unique object. Other aspects may include, e.g., that each of the objects in the at least one group of objects may be identifiable as a member of the group by the combination of the at least two parameters selected from the group comprising: shape, size, color, texture, orientation, rotation direction and spin direction. Similarly the unique object may be identifiable as different from any member of the at least one group of objects by at least one of a parameter selected from the group comprising: shape, size, color, texture, orientation, rotation direction and spin direction.
Further aspects of the disclosed subject matter may include a complexity of training sessions wherein the complexity may be determined by the user computing device from at least one of a number of unique objects, a number of parameters per object in a group and a number of groups of objects. Aspects of the method and apparatus of the disclosed subject matter may also include enhancing the effectiveness of the cognitive training by requiring the user to complete training sessions of increasing complexity. Also, the complexity of the training sessions may increase or decrease according to a user performance during the current training session or a prior training session.
According to still other aspects of the disclosed subject matter a computer readable medium is disclosed which stores software that, when executed by a computing device, causes the computing device to perform methods which may comprise: operating a user interface display of a user computing device to conduct a training session which in turn may comprise: presenting a plurality of objects having at least two identifying parameters, at least two of the plurality of objects having the same at least two identifying parameters forming at least one group of objects having the same at least two identifying parameters and at least one of the objects having at least one unique identifying parameter thereby not duplicating the identifying parameters of the at least two objects in the at least one group of objects; and allowing the user to select an object as a proposed unique object.
All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.
The novel features of the disclosure are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the disclosure are utilized, and the accompanying drawings of which:
A gameplay disclosed herein enables a user to view multiple objects and make a selection of one of the objects based on the selected object's uniqueness relative to one or more groups of other objects displayed. In an aspect of the disclosure, as illustrated herein, a suitable object is an abstract shape with one or more distinguishing features. For example, where three objects are presented, two objects are configurable such that the objects have the same characteristics, while the third object is configurable so that it may have some overlapping characteristics but has at least one characteristic that is not shared with the group formed from the first two objects. Objects presented can include a plurality of objects in one or more groups where each group of objects shares overlapping characteristics.
In one implementation, as illustrated in
The user can select an object from objects 101, 102, 104 using a variety of mechanisms. For example, the object could be selected by pointing a curser and clicking a mouse on the desired location, or by using other pointing devices in a two dimensional (2D) or three dimensional (3D) space, or by touching the location desired on a touch-sensitive input device.
Each object can be represented by a shape, for example, a stylized asteroid in space. By way of example objects 101 can be represented as circles of a first color and objects 102 can be represented as triangles of the first color or a second color (in
A status bar 130 may be provided on the screen display 100 which provides feedback on an elapsed time 132 and a difficulty level 134.
Turning now to
Feedback to the user of whether the selected object was a duplicate of other objects on the screen and which object is unique is further illustrated, by way of example, in
As illustrated, for example, in
After an object is selected, feedback may be given. For example, if the response was correct, as indicated above, then the correct response is confirmed. If the response was incorrect, then feedback may be provided. One or more additional opportunities may be provided to select a correct answer.
A suitable mechanism for illustrating a correct response as discussed above can be presented is shown in the screen display 400 of
Multiple trials in a session may be presented to the user, each of which can display a new set of objects. A correct response also increases the score by a function of the difficulty of the trial. After a fixed duration of repeatedly answering these trials, the session of exercises can be ended as shown in the process flow diagram of
Every set can be configurable to provide at least one unique object. Each object can further be configured to comprise several visual properties/parameters. Properties/parameters can include, for example, color, shape, texture, orientation, rotation, and spin. Other properties/parameters include, size, shading, skew, animation, and component makeup. The color of the subsets/groups of like objects and of the unique object can be randomly selected from a palette. Each color may also have a distinct combination of hue, saturation, and brightness that may also be distinct when viewed through a filter for common forms of color-blindness. The shape of the unique object can be randomly selected from a palette of distinct shapes. In some trials, the unique object may only be distinguishable by a unique texture that modulates the brightness of the surface of the object, such as by stripes, dots, and other patterns. In other implementations, other images could be superimposed on the object or overlap the silhouette of the object. In some trials, the unique object may be distinguished only by a unique rotation of the shape. Additionally, each rotation and shape combination(s) can be unique. In some trials, the unique object may be distinguishable by a clockwise or counterclockwise spinning animation. In these trials, e.g., to avoid ambiguity, each shape can further be configured to present a distinct image on each frame of animation in which it spins. In other implementations, the properties could be varied in a generative manner, rather than chosen from a fixed palette.
Besides the unique object, each sub-set/group also can contain a duplicate object(s) and areas in the visual field may contain no object. On most trials, there may be multiple varieties of duplicate objects. Typically, the attributes of a duplicate object differ from the unique object by at least one property. For example, a trial may have two shapes (square and circle) and two colors (red and blue). A unique object may be selected, such as a blue square, provided that there is a duplicates of the red square. If the trial has two varieties of duplicate objects, then one of the varieties may be comprised of duplicates of the same shape yet different color from the unique object, such as a red square, provided that none of the groups of squares are composed of red squares, and the other variety may be comprised of duplicates of the same color yet different shape as the unique object, provided that none of the groups are composed of blue circles.
Task difficulty can be moderated by a set of parameters, which may be increased to adapt to a user's skill, e.g., as illustrated by the process flow diagram of
Turning now to a game play process flow diagram 500 of
Turning now to
The user may be is introduced to the training exercise via a short interactive tutorial describing the gameplay elements, as illustrated in
As shown in
As illustrated in the screen display 900 of
Turning now to
To optimize training by ensuring that trial response times remain under an optimal or target time, an animation can be utilized to hint at what displayed object is the unique object. For example, after a set number of seconds, a highlighting circle of triangles 212 could be displayed on the screen around the unique object, e.g., the flower petal shape 208 such as is shown in
The current time remaining in the training session and level of difficulty currently achieved during the session can be displayed to the user in a display, e.g., as illustrated in
Before and/or after the main gameplay, the user can be presented with a track of progress, as illustrated by way of example in
As illustrated in the process flow diagram of
The systems and methods according to aspects of the disclosed subject matter may utilize a variety of computer systems, communications devices, networks and/or digital/logic devices for operation. Each may in turn utilize a suitable computing device which can be manufactured with, loaded with and/or fetch from some storage device, and then execute, instructions that cause the computing device to perform a method according to aspects of the disclosed subject matter. A computing device can include without limitation a mobile user device such as a mobile phone, a smart phone and a cellular phone, a personal digital assistant (“PDA”), such as a BlackBerry, a tablet, a laptop and the like. In at least some configurations, a user can execute a browser application over a network, such as the Internet, to view and interact with digital content, such as screen displays. Access could be over or partially over other forms of computing and/or communications networks. A user may access a web-browser, e.g., to provide access to applications and data and other content located on a web-site or a web-page of a web-site.
A suitable computing device may include a processor to perform logic and other computing operations, e.g., a stand-alone computer processing unit (“CPU”), or hard wired logic as in a microcontroller, or a combination of both, and may execute instructions according to its operating system and the instructions to perform the steps of the method. The user's computing device may be part of a network of computing devices and the methods of the disclosed subject matter may be performed by different computing devices, perhaps in different physical locations, cooperating or otherwise interacting to perform a disclosed method. For example, a user's portable computing device may run an app alone or in conjunction with a remote computing device, such as a server on the Internet. For purposes of the present application, the term “computing device” shall include any and all of the above discussed logic circuitry, communications devices and digital processing capabilities or combinations of these.
Certain embodiments of the disclosed subject matter may be described for illustrative purposes as steps of a method which may be executed on a computing device executing software, and illustrated, by way of example only, as a block diagram of a process flow. Such may also be considered as a software flow chart. Such block diagrams and like operational illustrations of a method performed or the operation of a computing device and any combination of blocks in a block diagram, can illustrate, as examples, software program code/instructions that can be provided to the computing device or at least abbreviated statements of the functionalities and operations performed by the computing device in executing the instructions. Some possible alternate implementations may involve the function, functionalities and operations noted in the blocks of a block diagram occurring out of the order noted in the block diagram, including occurring simultaneously or nearly so, or in another order or not occurring at all.
The instructions may be stored on a suitable “machine readable medium” within a computing device or in communication with or otherwise accessible to the computing device. As used in the present application a machine readable medium is a tangible storage device and the instructions are stored in a non-transitory way. At the same time, during operation, the instructions may at some times be transitory, e.g., in transit from a remote storage device to a computing device over a communication link. However, when the machine readable medium is tangible and non-transitory, the instructions will be stored, for at least some period of time, in a memory storage device, such as a RAM, a ROM, a magnetic or optical disc storage device, or the like, arrays and/or combinations of which may form a local cache memory, e.g., residing on a processor integrated circuit, a local main memory, e.g., housed within an enclosure for a processor of a computing device, a local electronic or disc hard drive, a remote storage location connected to a local server or a remote server access over a network, or the like. When so stored, the software will constitute a “machine readable medium,” that is both tangible and stores the instructions in a non-transitory form. At a minimum, therefore, the machine readable medium storing instructions for execution on an associated computing device will be “tangible” and “non-transitory” at the time of execution of instructions by a processor of a computing device and when the instructions are being stored for subsequent access by a computing device.
While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.
This application claims the benefit of U.S. Provisional Application No. 61/885,918, filed Oct. 2, 2013, entitled Systems and Methods for a Search Driven, Visual Attention Task for Enhancing Cognition, by David Ethan Kennerly, et al., which application is incorporated herein by reference.
Number | Date | Country | |
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61885918 | Oct 2013 | US |