Spatial distinctiveness effect in categorisation

A. OKER, R. VERSACE, L. ORTIZ SPATIAL DISTINCTIVENESS

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Spatial Distinctiveness effect in Categorization

- Brief Article -

Ali M. OKER, Rémy VERSACE, and Lydie ORTIZ

Université Lyon 2

Institut de Psychologie

Laboratoire d’Etude des Mécanismes Cognitifs (EMC)

5, avenue Pierre Mendès-France

69676 BRON Cedex, FRANCE

[email protected]

[email protected]

[email protected]

Running title: Spatial Distinctiveness

Key-words: Distinctiveness, categorization, multiple trace memory, context


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Abstract

The aim of the present study was to show that the probability of an item being retrieved is

proportional to its spatial distinctiveness, and that this distinctiveness effect can be obtained in

an implicit memory task. The participants were presented with two phases in which they had

to categorize pictures of objects as either “kitchen utensils” or “do-it-yourself tools”. In our

encoding phase, the pictures were successively presented in different positions on the screen.

The positions were arranged in one of two different configurations: a “distinctive condition”

in which the pictures were placed in two circles, one central and one peripheral, such that the

distance between the pictures was greater when they were in a peripheral positions than in a

central position, and a “non distinctive” condition, in which the distance between the pictures

was constant irrespective of their central or peripheral position. In the test phase, the same

pictures were presented for categorization, mixed with new pictures at the centre of the

screen. The results clearly confirmed our expectations.

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In 1960, Murdock defined distinctiveness as the extent to which a given stimulus

“stands out” from other stimuli and noted that the concept of distinctiveness refers to the

relationship between a given stimulus and one or more comparison stimuli, and if there are no

comparison stimuli, the concept of distinctiveness is simply not applicable (Murdock, 1960).

Many studies of memory have shown that items or events that stand out from others in a

series are usually more readily recalled than items that do not stand out in the same way (for a

recent review, see Hunt & Worthen, 2006). The distinctiveness effect can be obtained by

manipulating various dimensions of interest. For example, the addition of an interval between

items in a list will make them more temporally distinctive (Glenberg & Swanson, 1986; Neath

& Crowder, 1990; for a review, see Neath, 1993). An item can also be more distinctive after

its physical properties have been manipulated (Calkins, 1894; von Restorff, 1933; cited in

Koffka, 1935).

Most studies of the distinctiveness effect have focused exclusively on identifying the

properties of the stimulus (for a review, see Wallace, 1965). In an extreme case of

distinctiveness manipulation, von Restorff presented participants with two lists of ten items,

each consisting of nine nonsense syllables and one number or nine numbers and one nonsense

syllable, respectively. After a distractor period lasting 10 minutes, a free recall test showed

that the isolated items were recalled better than the non-isolated items. Other experiments of

the isolation effect (e.g., Rabinowitz & Andrews, 1973) have required participants to learn

lists of items consisting of nonwords and one real word or of words printed in black capital

letters with the exception of one word printed in red capital letters.

The most important original feature of our study was to show that the specificity of an

item can be varied not just by manipulating the properties of the item itself but also by

manipulating the contextual information associated with the item during encoding. Indeed, the

importance of contextual information in the distinctiveness effect has already been evoked by


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Smith and Hunt (2000), who assumed that distinctive processes will be ineffective in retrieval

unless the original encoding context is reinstated.

The importance of contextual information in the distinctiveness effect has also been

referred to in many accounts of serial position effects in free recall. For example, according to

the contextual retrieval hypothesis (Glenberg, Bradley, Stevenson, Kraus, Tkachuk, Gretz,

Fish & Turpin, 1980), the efficiency of recall depends on the efficiency of the reactivation of

the encoding context of the items by the test context, and therefore on the specificity of the

encoding context.

In the temporal distinctiveness hypothesis proposed by Neath (1993; see also Nairme,

Neath, Serra, & Byun, 1997), the context is the temporal position of an item, and this account

assumes that the probability of recalling an item is proportional to its temporal distinctiveness

as estimated by its summed temporal distance from the other items in the list.

The study reported here had two aims: first, we wanted to show that the temporal

distinctiveness hypothesis can be extended to form a spatial distinctiveness hypothesis. We

postulated that the probability of an item being retrieved is proportional to its spatial

distinctiveness from the other items to be encoded. However, the role of contextual

information in our hypothesis is different from that postulated by Smith and Hunt (2000).

These authors assumed that distinctive processes require the reinstatement of the original

encoding context during the test. In the spatial distinctiveness hypothesis, the spatial

contextual information is thought to permit the encoding of a more distinct memory trace,

thus increasing the efficiency of item retrieval at test time even if the original spatial position

of the item is not reinstated.

Our second objective was to show that distinctiveness effects are not restricted to

explicit memory tasks, contrary both to the general assumption made in the literature (e.g.

Rajaram, 1998; Smith & Hunt, 2000) and to the temporal distinctiveness hypothesis which


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was formulated in order to explain serial position effects in free recall. Indeed, the fact that

the distinctiveness effect can emerge in the absence of recollection at test time has already

been demonstrated by Geraci and Rajaram (2004). These authors suggested that the

distinctiveness effect depends on the repetition of the type of processing that occurred during

the study phase and might therefore emerge even in the absence of recollection (see also Hunt

& McDaniel, 1993). As stated above, our hypothesis is that the spatial isolation of an item

during the encoding phase will increase the distinctiveness of the corresponding memory

trace. Therefore, if the type of processing that occurred during the study phase recurs at test

time then items that were more isolated during the study phase should be processed more

efficiently, whatever the explicit or implicit nature of the retrieval and even if the spatial

position of the item is different at test time and encoding

In the experiment reported here, the participants were presented with two phases in

which they had to categorize pictures of objects as “kitchen utensils” or “do-it-yourself tools”.

In the first phase, the pictures were successively presented in different positions on the screen.

The positions were determined using two different configurations which are illustrated in

Figures 1a and 1b. In one configuration (Figure 1a, named the “distinctive condition”), the

pictures were regularly spaced on two circles, one central and one peripheral, such that the

distance between the pictures was greater in the peripheral position than in the central

position. In contrast, in the second configuration (Figure 1b, the non-distinctive condition),

the distance between the pictures was constant irrespective of whether they were in central or

peripheral position. In contrast, in the second phase, the pictures were presented in the centre

of the screen while the participants performed the same categorization task. The same pictures

as in the encoding phase were presented, mixed with pictures of new objects.

- Insert figure 1a about here - - Insert figure 1b about here –


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Experiment

Method

Participants

48 native French-speaking students from the University of Lyon 2, France, were tested. All

had normal to corrected-to-normal vision and none suffered from daltonism. No participant

was familiar with the issues being investigated in this study.

Apparatus and Stimuli

The experiment was carried out on an Apple eMac microcomputer, with a 17’’ monitor (1024

x 768 resolution, 89 Hz, and millions of colors), using Psyscope software (Cohen,

McWhinney, Flatt, & Provost, 1993). The distance between the participants' heads and the

screen was maintained at a constant distance of 45 cm by means of a chin rest. A set of 28

colored photographs of objects was used (24 experimental objects and 4 objects for the

practice trials). 14 of these objects were kitchen utensils, while the other 14 represented do-it-

yourself tools. All the objects were pictured against a white background and were presented in

a 0.85 cm x 0.85 cm rectangle. 16 squares (0.85 x 0.85 cm) were defined on the screen using

two different configurations (see Figure 1). In the two configurations, the squares were

arranged in two circles: one subtended at a visual angle of 5.2° to the center of the screen and

the other circle subtended at a visual angle of 9.9° to the center of the screen as viewed by the

participant. These two positions correspond to the central and peripheral experimental

conditions as described below. In one configuration (termed the "distinctive condition"), the

squares were spaced at regular intervals on the circle in such a way that the distance between

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each square was greater in the peripheral than in the central position. In contrast, in the second

configuration (termed the "non-distinctive condition"), the distance between the squares was

constant irrespective of the central or peripheral position.

Procedure and Design

After completing a consent form, each participant was tested individually in a session that

lasted approximately 20 minutes. The experiment was divided into two phases: an encoding

and a test phase.

In the encoding phase, the participants were told that pictures of objects would appear

in squares located at different positions on the screen, and that their task was to categorize the

objects as quickly and accurately as possible as “kitchen utensils” or “do-it-yourself tools”.

They were told to give their responses by pressing the appropriate key on the keyboard. Half

of the subjects used their right hand to respond “kitchen utensil” and their left hand to respond

“do-it-yourself tool” while the opposite design was used for the other participants. 16 of the

24 experimental stimuli were used. The other 8 stimuli were used as new stimuli in the test

phase. The encoding phase consisted of 16 trials with one object from each category

appearing in each position on the screen. The 8 stimuli presented in central position for one

third of the subjects were presented in peripheral position for another third and were used as

new stimuli for the final third of the subjects. The order of presentation of the different

experimental conditions was randomized. The pictures were presented using the distinctive

configuration for half (24) of the participants and the non-distinctive configuration for the

other half (24) of the participants.

Each trial began with the presentation of a fixation point in the center of the screen

together with 16 empty squares. The fixation point disappeared after 1500 ms, and a cue (a

small x) was displayed in the center of one of the squares for 1500 ms. This cue indicated to


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the participant that an image would appear in the corresponding square. The image was then

displayed in the cued square for 2000 ms. To ensure a constant exposure duration for all the

stimuli, the image remained on the screen even if the participant responded before the period

of 2000 ms had elapsed.

In the test phase, the participants had to perform a categorization task involving 24

pictures: the 8 old pictures which had appeared in central position during the encoding phase,

the 8 old pictures which had appeared in peripheral position during the encoding phase, and 8

new pictures. The pictures were presented successively in the centre of the screen, and were

preceded by a fixation point that was displayed for 1000 ms. The target remained on the

screen until the subject categorized the picture as a “kitchen utensil” or “do-it-yourself tool”.

The intertrial interval was 1500 ms and the order of presentation of the different experimental

conditions was randomized. The 24 experimental trials were preceded by 4 practice trials.

The encoding phase and the test phases were separated by a distracting task which lasted

approximately 5 minutes. This task consisted of simple mental arithmetic. Our aim was to

reduce the likelihood of contamination due to explicit retrieval processes in the test phase to

the minimum possible.

Results

Mean correct response latencies and error rates were calculated across the subjects for

each experimental condition. Latencies more than three standard deviations above or below

the mean were excluded (less than 5% of the data). The mean correct latencies and error rates

for the different experimental conditions are presented in table 1.

--- Insert table 1 about here ---


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Separate repeated measures analyses of variance were performed on latencies and error

rates with Configuration (Distinctive and non distinctive) as the between-subjects variable

and Item Type (old central, old peripheral and new) as the within-subject variable.

The analysis of the error rates revealed no main effect or interaction. This result could

be explained by ceiling effects since the overall level of correct responses was 92%. The

analysis of the latencies revealed a significant main effect of Item Type, F(2,92)=57.57;

MSE=117287; p<0.01, and an interaction between Item Type and Configuration

F(2,92)=5.162; MSE=10516; p<0.01. Planned comparisons revealed that in the “distinctive

condition”: a) old pictures presented in central condition were categorized more rapidly than

new pictures, F(1,23)=23.974; MSE= 38138.4 ; p<0.0005; b) old pictures presented in

peripheral condition were categorized more rapidly than new pictures, F(1,23)=48.871;

MSE=77743.4; p<0,0005; and c) old pictures presented in peripheral condition were

categorized more rapidly than old pictures presented in central condition, F(1,23) = 4.386;

MSE= 6977.9; p<0.05.

In contrast, in the “non-distinctive condition”, old pictures were categorized more

rapidly than new pictures (F(1,23)=61.351; MSE=152402.3; p<0.0005 for the central vs. new

comparison and F(1,23)=41.630; MSE=103414.07; p<0,0005 for the peripheral vs. new

comparison). However, no significant difference was observed between old pictures presented

in peripheral condition and old pictures presented in central condition, F< 1. We did not

perform a subsequent planned comparison between old objects in the “non-distinctive” and

“distinctive” conditions due to the possibility that sampling errors might have led to overall

differences in latencies as a result of the fact that these conditions were tested as between-

subjects variable.


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Discussion and Conclusion

The objective of the present study was to show that the probability of an item being

retrieved is proportional to its spatial distinctiveness from the other items that are to be

encoded. In our spatial distinctiveness hypothesis, the more spatially isolated an item is from

the other items, the more distinct its memory trace should be compared to the traces of the

other items. A distinctive spatial context is therefore assumed to increase the efficiency of

item retrieval at test time, even if the original spatial position of the item is not restored.

When we presented our distinctive configuration on screen, we wanted to make clear

visually that the distance between objects in peripheral locations is greater than the distance

between objects in central locations, thus providing a distinctive marker in the form of a

memory trace for these objects. The idea was that in our non-distinctive configuration, there

would be no difference in distance between central and peripheral objects and that there

would therefore be no distinctive marker for these objects. The results of our experiment

clearly confirm these assumptions. In the distinctive configuration condition, the items

encoded in peripheral positions were categorized more rapidly than the items encoded in

central positions. In contrast, when the distance between the items was controlled (in the non-

distinctive configuration condition), no difference appeared between the items encoded in

peripheral positions and the items encoded in central positions. At the same time, it is difficult

to say when and to what extent the distances between objects provide a distinctive marker for

them. Therefore, a fruitful avenue of future research would be to examine the distance

threshold at which a target becomes distinctive1 by comparing different proportional distances

between them.

1 Our thanks to an anonymous European Journal of Cognitive Psychology reviewer for this idea


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By using an analogy with visual perception, we showed that inserting space between

items in the visual field can make an item more distinctive spatially, in the same way as

inserting an interval between items in a list makes them more distinctive temporally.

Another objective of our research was to show that this spatial distinctiveness can be

revealed within an implicit memory task. Indeed, contrary to the general assumption made in

the literature (e.g. Rajaram, 1998; Smith & Hunt, 2000), which suggests that distintiveness

effects are restricted to explicit memory tasks, we observed that a categorization task can be

sensitive to spatial distinctiveness effect. Moreover, for Smith and Hunt (2000), intentional

memory instructions permit the reinstatement of the original context which they assumed to

lie at the root of the distinctiveness effect. In the paradigm we present here, the subjects

received no memory instructions due to the fact that the spatial context of the items was

presented in an incidental learning phase. Furthermore, contrary to Smith and Hunt’s

assumption that distinctive processes require the reinstatement of the original encoding

context during the test, no context was reinstated during the test phase in our study; every

item was presented in the centre of the screen. Hence, our findings are in line with those

obtained by Geraci & Rajaram (2004) which indicated that the distinctiveness effect can

emerge in the absence of recollection at test time.

Our results are difficult to interpret within the framework of an abstractive memory

perspective (e.g., Anderson, 1983; Squire, 1987; Tulving, 1984, 1995) in which semantic

categorization is assumed to imply a stable abstractive knowledge, as a result of which

retrieval should not be greatly influenced by the contextual encoding condition. Within this

logic, Tulving supposes that abstract knowledge results from a consolidation process between

episodic and semantic memories. Thus, conceptual information remains purely amodal in

semantic memory, since the contextual information from our former experiences has already

been lost during this consolidation process (Tulving, 1984; Tulving & Schacter, 1990).

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In contrast, these results can be considered as strong evidence in favor of the episodic or

multiple traces memory models (e.g., Hintzman, 1986; Whittlesea, 1987; Logan, 1988;

Versace, Labeye, Badard, & Rose, 2008) in which memory is described as a unique system

that continuously stores the traces of single specific experiences. In these models, the explicit

as well as implicit recovery of any form of knowledge from a stimulus is described as the

emergence of the activation of all the traces related to the stimulus. If there is a consolidation

process, it is more likely to be the result of the number of times that an object has been seen

or a particular situation has been experienced. A memory trace fully encodes all the episodic

information relating to a context pattern, background information or simply the situation in

which a given object has been seen. Consequently, a semantic categorization task, like that

used in the present study, should also be dependent on the distinctiveness of the trace.


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Figure 1a Figure 1b

Table 1. Mean Response Times (RTs) and Error Rates (ERs) for each experimental condition

(Standard errors are in parentheses).

Item Type Central Peripheral New

Configuration

RT (ms) ER(%) RT (ms) ER(%) RT (ms) ER(%) Distinctive 601,3 (13,2) 8,8 (2,4) 584,3 (12,9) 8,8 (2,5) 641,2 (15) 11,4 (2,6)

Non Distinctive 572,8 (11,8) 6,7 (1,9) 586,9 (14,1) 6,2 (1,8) 652,5 (16,8) 8,3 (2)

Spatial distinctiveness effect in categorisation

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