Name: generating strictly controlled stimuli for figure recognition experiments
Uploaded: 2019-03-18T14:00:00
Description: Watch this Scientific Journal Video about Generating Strictly Controlled Stimuli for Figure Recognition Experiments at JoVE.com

The author thanks Sydney Koke, MFA, and Maxine Garcia, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

The experiment was approved by the Hakuoh University Ethics Committee, Japan.
1. Experimental Setup
NOTE: The experimental environment consists of an LCD monitor and a response button box connected to a computer (PC for experiments). Each participant decides whether a presented pair of figures is the &#8216;same&#8217; or &#8216;different&#8217; by pressing one of the two buttons on a response box. There are three buttons on the box labeled &#8216;Enter&#8217;, &#8216...

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M., Weinstein, M., Rappaport, M., Anderson, N., Leonard, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stimulus+correlates+of+visual+pattern+recognition:+A+probability+approach.">Stimulus correlates of visual pattern recognition: A probability approach.</a> J Exp Psychol. 1 (1), 1-11 (1956).</li><li>Bethell-Fox, C. E., Shepard, R. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mental+rotation:+Effects+of+stimulus+complexity+and+familiarity.">Mental rotation: Effects of stimulus complexity and familiarity.</a> J Exp Psychol Hum Percept Perform. 1 (1), 12-23 (1988).</li><li>Attneave, F., Arnoult, M. 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D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mental+rotation+effect:+A+function+of+elementary+stimulus+discriminability.">Mental rotation effect: A function of elementary stimulus discriminability.</a> Perception. 11 (11), 1301-1316 (1996).</li><li>Kanbe, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Can+the+comparisons+of+feature+locations+explain+the+difficulty+in+discriminating+mirror-reflected+pairs+of+geometrical+figures+from+disoriented+identical+pairs.">Can the comparisons of feature locations explain the difficulty in discriminating mirror-reflected pairs of geometrical figures from disoriented identical pairs.</a> Symmetry. , 89-104 (2015).</li><li>Kanbe, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Are+line+lengths+critical+to+the+discrimination+of+axisymmetric+pairs+of+figures+from+disoriented+identical+pairs.">Are line lengths critical to the discrimination of axisymmetric pairs of figures from disoriented identical pairs.</a> Jpn Psychol Res. 1 (1), 36-46 (2019).</li><li>Treisman, A., Souther, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Search+asymmetry:+A+diagnostic+for+preattentive+processing+of+separable+features.">Search asymmetry: A diagnostic for preattentive processing of separable features.</a> J Exp Psychol Gen. 3 (3), 285-310 (1985).</li><li>Kanbe, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Which+is+more+critical+in+identification+of+random+figures,+endpoints+or+closures.">Which is more critical in identification of random figures, endpoints or closures.</a> Jpn Psychol Res. 51 (4), 235-245 (2009).</li><li>Julesz, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Textons,+the+elements+of+texture+perception,+and+their+interactions.">Textons, the elements of texture perception, and their interactions.</a> Nature. 290, 91-97 (1981).</li><li>Wolfe, J. 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The present method can be used to prepare a set of objectively definable stimulus figures for figure recognition experiments. The critical aspect of the method are the instructions within the pair generation program. Using a (6, n) database, the program can select appropriate candidate figures from the total (6, n) figures (protocol steps 2.2.1 and 2.2.2). Additionally, the program can sometimes calculate feature values of figures that are not stored in the database, as in the case of ...

This paper describes a method for generating strictly controlled and objectively defined stimulus figures for studies on the recognition of random figures. The stimuli are called (6 point, n line) or (6, n) figures. A (6, n) figure consists of n line segments that are spanned between n pairs of points located at the vertices of an invisible regular hexagon. Figure 1 shows an example of a (6, 4) figure that is specified by four pairs of labels for the vertices of an invisible regular hexagon. The labels designate the line segments of the figure (see Figure 1). Let us call this specification of figures a line specification format.
Formerly, the author calculated the graph theoretical structural properties of (6, n) figures (called invariant features, or more specifically graph invariants1) and non-invariant properties (called superficial features) for figures with n = 1 to 6 and stored the feature values in a database. Invariant features reflect the structural (more precisely, topological) properties and superficial features reflect the non-topological and mostly metric properties of a given figure.
A record number in the database uniquely identifies a figure in the line specification format. Therefore, an exhaustive search for specific values of invariant and/or superficial feature values in the database enables the retrieval of the record numbers for the figures that satisfy the conditions from the total set of (6, n) figures. The retrieved figures can serve as the stimuli for an experiment. Each record in the database contains variables that include the isomorphic set to which the figure belongs; various graph invariants, such as the number of cycles, circumference, point covering number, number of critical points, radius, number of central points, number of components, maximum degree, number of maximum degree points, number of isolated points, and number of endpoints; non-graph feature values, such as the number of intersections, and jaggedness of the contours defined by vertices and intersections; and superficial feature values, such as locations of the invariant features and (in the case in which there are plural locations) the directions formed by plural locations. For example, a cycle indicates a closed sequence of line segments, a degree of a point is the number of line segments incident with that point, an isolated point is a point with a degree of 0, and an endpoint is a point with a degree of 1. Using the invariant feature values of the database, all (6, n) figures from n = 1 to 6 can be sorted into the numbers of isomorphic sets shown in Appendix 11. See Figure 2 for an example of the stored information in each record.
Note that the figures that belong to each isomorphic set are topologically equivalent despite differences in shape. Several studies have claimed that topological structures are perceived prior to more specific properties of given figures2,3,4,5. By systematically changing stimulus figures, the author claimed that detections and comparisons of invariant features precede the detections and comparisons of superficial features6. The present experiment is an attempt to clarify whether the superficial feature of line length is critical in the recognition of figure pairs under the condition that invariant feature values are all equivalent between the figure pairs (i.e., mutually isomorphic).
The types of stimulus figures that are used in experiments is critically important to figure recognition research. There are two types of stimulus figures: those that are randomly generated and those that are generated ad hoc for the purpose of a study. To reduce confounds associated with factors not under experimental control, the use of randomly generated figures is generally considered to be more appropriate. There are several types of random figures, for example, random histograms7 and random matrices8, but the most frequently used random figures in visual recognition research in psychology are random polygons9. A general rule for making random polygons is to connect randomly distributed locations of n points in a square area with line segments in such a manner that the perimeter of the line segment is mostly convex and then color inside the perimeter. A frequently used objective index for random polygons is the number of flections of the perimeter of a polygon, which represents the complexity of the figure10,11,12. As the inside of the figure is colored in, structural properties regarding its perimeter are limited to the number of flections. Additionally, with the exception of the number of flections, no information is given about either the entire set of random polygons or the relationship between distinct random polygons.
The figures in axisymmetric (Ax) pairs of figures are known to be more difficult to discriminate than non-identical pairs in a task to decide whether a given pair of figures is rotated-to-be-identical (Idr)13,14,15. The two figures in an Idr pair and those in an Ax pair are mutually isomorphic and have corresponding line segments that are the same length. However, whether sameness of line lengths between the two figures in a pair increases the difficulty of discrimination of a non-identical pair compared with that of an Ax pair is unclear. In this experiment, participant discrimination performance was compared between Ax pairs and non-identical, non-axisymmetric (Nd) pairs. The differences in line lengths were experimentally controlled between the two figures. Because of the precedence of detecting invariant feature value differences prior to superficial feature value differences during figure recognition5, the Nd figure pairs were set to be mutually isomorphic so that line length differences would not be confounded with invariant feature value differences.
Experiment 1 in the author-used (6, 5) figure pairs to examine the hypothesis that the lack of line length differences influenced the level of difficulty of discrimination of the figures in Ax pairs15. The results demonstrated that the latencies were shorter for Nd 0 (viz., no difference in total line length between paired figures) pairs compared with those for Ax pairs, which indicated that the hypothesis was unsupportable. It was argued that superficial feature value differences not under experimental control are more likely to be present in complex figures, and participants might make use of these. Interestingly, several studies have claimed that the presence of a cycle is preattentively detected16,17. By contrast, Julesz claimed that the presence of an endpoint was detected at an early stage of the segregation of figures from the background18.
To address this, simpler (6, 4) figure pairs were chosen to examine the hypothesis. Out of nine isomorphic sets of (6, 4) figures, the figures that belonged to two isomorphic sets were used as stimuli. Both sets of figures shared easily detectable invariant features of (an) endpoint(s) and a cycle (i.e., a triangle) in common. See the example figures of nine isomorphic sets in Figure 3. Additionally, see the column of p = 6 and q = 4 in Appendix 11.
Three basic pair types were generated: Idr, Ax, and Nd pairs. The total line length of a cycle (more specifically, a triangle) was equalized between the two figures in each pair for all pair types. Using this constraint, respective triangles of a figure pair became either mutually identical or Ax in shape. Nd pairs were further subcategorized according to differences in the lengths of endlines between the two figures in each pair, with the unit of length set as the side of an invisible regular hexagon. This yielded Nd 0, Nd 0.27, Nd 0.73, and Nd 1 pairs (i.e., the line length differences ranged from 0 to 1). As the presence of an intersection of line segments is known to be preattentively detected19, figures with intersecting line segments were excluded from the stimuli. See the examples of Idr, Ax, Nd 0, Nd 0.73, and Nd 1 pairs in Figure 4. To avoid the biased expectations of the participants, the number of Idr (&#8216;same&#8217;) pairs was set to be the same as the sum of Ax (&#8216;different&#8217;) and Nd (&#8216;different&#8217;) pairs.

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			<td height="21" style="height:21px;width:216px;">PC for stimulus preparation</td>
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			<td>Takei Kiki</td>
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			<td>custom item</td>
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			<td>NEC&#160;</td>
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			<td height="21" style="height:21px;width:216px;">Pair generation program</td>
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			<td height="21" style="height:21px;width:216px;">Database file</td>
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			<td>self-made</td>
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			<td height="42" style="height:42px;width:216px;">Stimulus presentation program&#160;</td>
			<td style="width:71px;">Takei Kiki</td>
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generating strictly controlled stimuli for figure recognition experiments

This protocol introduces a method for generating strictly controlled and objectively defined stimuli for figure recognition experiments. A (6, n) figure consists of n line segments that are spanned between n pairs of points located at the vertices of an invisible regular hexagon. The structural properties (graph invariants) and superficial features (non-graph invariants) of each (6, n) figure with n values ranging from 1 to 6 are calculated and stored in a database. Using this database, experimenters can systematically extract appropriate figures depending on the purpose of the experiment. Furthermore, if the database does not contain necessary information, new feature values can sometimes be calculated ad hoc from the formation of a specific (6, n) figure. Let us call a mirror-reflected pair of figures an axisymmetric (Ax) pair. An Ax pair of figures is known to be more difficult to discriminate than a non-identical pair in the decision of whether the shapes of a given pair are rotated-to-be-identical (Idr). The purpose of the present experiment is to examine whether the sameness of line lengths between two figures in a pair causes the discrimination of the pair to be as difficult as that of an Ax pair. Mutually isomorphic figures share common structural properties despite differences in shape. Ax pairs and Idr pairs are special cases of isomorphic pairs. Furthermore, an Ax pair and Idr pair share most of the superficial feature values, except the relative direction from one location to another location across an axis of symmetry is opposite for an Ax pair. Three types of mutually isomorphic (6, 4) figure pairs were generated: Idr; Ax; and non-identical, non-axisymmetric, isomorphic (Nd) pairs. Nd pairs were further classified into three subcategories according to the superficial feature values of the degree of line length differences.

As Nd 0.27 pairs were found to only exist in the figures of isomorphic set 2, the subsequent analysis did not include the results for Nd 0.27 pairs. The hypothesis of the present study was that the sameness of line lengths between the two figures in Nd pairs would make them as difficult to discriminate as Ax figure pairs.
The results of the experiment are shown in Figure 7. Error rates were significantly different acr...

Watch this Scientific Journal Video about Generating Strictly Controlled Stimuli for Figure Recognition Experiments at JoVE.com

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

This protocol describes a method for an experiment that examines whether specific graph and non-graph properties (features) are relevant to the recognition of figures. The method uses a database that stores various feature values of respective figures called (6 point, n line) figures.

This protocol introduces a method for generating strictly controlled and objectively defined stimuli for figure recognition experiments. A (6, n) figure ...

This protocol can be used to generate strictly controlled and objectively defined stimuli for figure recognition experiments. Using a 16 figure database, you can select a stimulus figures that satisfy prescribed values of structure and superficial geometric properties. The experimental environment consists of a liquid crystal display monitor, and a response button box connected to a computer.There are three buttons on the box labeled Enter, F6, and F5.By pressing the Enter button, the current screen will proceed to the consecutive screen. The F6 button is for responses using the index finger, and the F5 button is for responses using the middle finger. To enable the examination of various hypotheses that concern the criticality of a certain feature in the recognition of figures in a fairly objective manner, insert a floppy disk into the floppy disc unit connected to the computer, that will be used for the stimulus preparation, and open the pair generation program.Then use the keyboard to input a random number as an initial value for the random number generation function, and input either one or two using the keyboard, as the digital specifier. To prepare a stimulus set for a participant, sequentially write a presentation number, digital state, pair type with a tag, number of line segments, and four pairs of vertex labels in the line specification format of the left and right figures of each trial to the floppy disk unit, simultaneously echoing these values on the screen. After obtaining written, informed consent from the participant, show sample figure pairs to demonstrate to the participant how they will be asked to decide whether a presented pair of figures is identical in shape, regardless of their orientations, as quickly and accurately as possible.When the participant is ready, start the stimulus presentation program on the computer for experiments, and click Identity Decision Task and Participant Information, to enter the participant's name, sex, and age. When all of the information has been entered, click End of Specification and Read Stimulus. Then select the PRBLM2.DAT file in the floppy disk drive and click Open on the file specification screen. Next, seat the participant in front of the monitor, with their head on the chin rest, and confirm a 60 centimeter distance from the participant's forehead to the monitor. Then click Execution to start the experiment.If the instruction screen shows the digital state one, instruct the participant to press the F6 key with the index finger when the figures are the same, and to press the F5 key with the middle finger when the figures are different. After the digital state has been determined, have the participant press Enter once on the response box, and then once again in response to the Ready prompt on the screen, to start the trial. Upon the presentation of a pair of practice pairs on the stimulus screen, have the participant press the F6 or F5 key as soon as a decision is reached.If the response was correct, the decision was correct will appear on the feedback message screen. If the response was incorrect, the decision was erroneous will appear on the screen. After reading the feedback message, have the participant press enter to proceed and respond to the next prompt screen.When all of the practice trials are complete, start of the test trials will appear. Have the participant begin the trial using the same response buttons as used for the practice trials. In this representative experiment, the error and latency rates were significantly different across the pair types, with exception of the difference in latency between the asymmetric and non-identical zero pairs.The error rates and latency data both suggest that the non identical 0.73 and one pairs are easily discriminable compared with asymmetric pairs. However, the nearly absent difference in latency between the non-identical zero pairs, and the asymmetric pairs, strongly suggests the the sameness of the line lengths caused the asymmetric pairs to be more difficult to discriminate. It is important to select geometrically appropriate figure pairs with the use of the database, and ad-hoc creations, according to your research questions.If you appropriately select figures with specific feature values, you can examine the criticality of individual features during the figure recognition tests.

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