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Memory for objects declines when people move from one location to another (the location updating effect). However, it is unclear whether this is attributable to event model updating or to task demands. The focus here was on the degree of integration for probed-for information with the experienced environment. In prior research, the probes were verbal labels of visual objects. Experiment 1 assessed whether this was a consequence of an item-probe mismatch, as with transfer-appropriate processing. Visual probes were used to better coordinate what was seen with the nature of the memory probe. In Experiment 2, people received additional word pairs to remember, which were less well integrated with the environment, to assess whether the probed-for information needed to be well integrated. The results showed location updating effects in both cases. These data are consistent with an event cognition view that mental updating of a dynamic event disrupts memory.
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© 2010 The Psychonomic Society, Inc. 900
Previous work has shown that the architecture of the
environment interacts with the architecture of cognition
(Radvansky & Copeland, 2006). Not only do people in-
tegrate contextual information into their memories, but
how that context is structured and how it changes can
also influence memory effectiveness. Specifically, when
people move through doorways, memory for objects
that have been interacted with is reduced. This has been
interpreted from a situation model perspective (Zwaan
& Radvansky, 1998). However, because the term situa-
tion model is strongly associated with work in language
comprehension, we use the term event model and extend
these ideas to event cognition more broadly (Copeland,
Magliano, & Radvansky, 2006). The present study aimed
to further test the generality of the principle that when
there is an event boundary, thereby changing the event
context, there is a disruption in the availability of infor-
mation encountered as part of the prior event (Glenberg,
Meyer, & Lindem, 1987; Radvansky & Copeland, 2010;
Zwaan, 1996).
A direct assessment of the influence of changing events
on memory was illustrated in a study by Radvansky and
Copeland (2006), which is the basis for the present work.
In this study, people moved through a multiroom virtual
environment. Each room had one or two tables. A per-
son first picked up an object (colored solids; e.g., a red
cube or blue wedge) from a table and then moved to the
next table. The person set the object down and picked up
the next one. The person then moved to the table after
that, and so on. At critical points, people were probed
with the name of an object (e.g., red cube). These probes
occurred either halfway across a large room (no-shift
condition) or immediately after the person had entered
a new room (shift condition). Following Glenberg et al.
(1987), positive responses were to be made if the object
was either the one currently being carried or the one just
set down. Negative responses were for any other object.
Negative probes were recombinations of object and color
names from the two positive objects. So, if the object set
down was a green pole and the carried object was a red
cube, the negative probes could be either green cube or
red pole.
When an object was picked up, it disappeared, so there
was no visual reminder of what was being carried. Also,
when moving, people turned their backs on the object that
was just set down, so there was no visual reminder of it.
Finally, memory probes did not occur at every possible
location. This decreased the degree to which people an-
ticipated being probed.
The results showed that people made more errors if they
had moved to a new room. This is the location updating
effect. This forgetting effect was supported by a response
time difference, with people responding slower in the shift
than in the no-shift condition. When people updated their
event models, this compromised memory for the objects
in the environment.
The event cognition explanation is that the location up-
dating effect is a consequence of parsing a stream of events,
thereby reducing the availability of information prior to an
event shift (Kurby & Zacks, 2008; Speer, Reynolds, Swal-
low, & Zacks, 2009; Swallow, Zacks, & Abrams, 2009;
Zacks, Speer, & Reynolds, 2009). This is not an effect of
environmental context-dependent memory. Other work
that we have done has found that reinstating the context
does not improve performance. With location updating,
a person modifies his or her event model to adjust to the
Walking through doorways causes forgetting:
Environmental integration
Ga b r i e l a . ra d va n s k y , a n d r e a k. Ta m p l i n , a n d sa b i n e a . k r aw i e T z
University of Notre Dame, Notre Dame, Indiana
Memory for objects declines when people move from one location to another (the location updating effect).
However, it is unclear whether this is attributable to event model updating or to task demands. The focus here was
on the degree of integration for probed-for information with the experienced environment. In prior research, the
probes were verbal labels of visual objects. Experiment 1 assessed whether this was a consequence of an item–
probe mismatch, as with transfer-appropriate processing. Visual probes were used to better coordinate what was
seen with the nature of the memory probe. In Experiment 2, people received additional word pairs to remember,
which were less well integrated with the environment, to assess whether the probed-for information needed to
be well integrated. The results showed location updating effects in both cases. These data are consistent with an
event cognition view that mental updating of a dynamic event disrupts memory.
Psychonomic Bulletin & Review
2010, 17 (6), 900-904
doi:10.3758/PBR.17.6.900
G. A. Radvansky, gabriel.a.radvansky.1@nd.edu
En v i r o n m E n ta l in t E g r at i o n 901
red cube). The rest received standard verbal probes. In ad-
dition, we altered how people navigated the environment.
In prior work, people used arrow keys on a keyboard with
their left hand, and they responded by pressing buttons on
a mouse held in their right. In Experiment 1, people used
a joystick to navigate and responded using two buttons on
the joystick.
Method
Participants
. Forty-nine people (28 female) from the University
of Notre Dame were given partial course credit for their participa-
tion. Twenty-four were in the text-probe condition, and 25 were in
the picture-probe condition.
Materials and Apparatus
. The virtual spaces were created
using the Valve Hammer program. This is the program used to cre-
ate environments for the Half-Life video game. The displays were
presented on a 66-in.-diagonal rear projection SmartBoard using
a PC-compatible computer, with people seated about 1 m from
the display, the room was darkened, and people wore headphones
(so they could hear their “own footsteps”). The virtual space was
a 53-room environment in which the rooms were of one of two
sizes, with the large rooms being twice as long as the small rooms.
This difference in room size allowed for the distance traveled to
be equated in the shift and no-shift conditions, the only difference
being whether a change in location occurred. In each room were one
or two tables. Each table was placed along a wall in the room. In
the small rooms there was only a single table, whereas in the large
rooms there was a table on each half of the room. At one end of the
table was the object the participant was to pick up. The other half
of the table was empty. This is where the object being carried was
to be put down. Finally, the two doorways in the room were never
on the same wall.
The objects were made by combining colors and shapes. The col-
ors used were red, orange, yellow, green, blue, purple, white, gray,
brown, and black. The objects were all regular geometric shapes:
cube, wedge, pole, disc, cross (X), and cone.
Procedure
. After giving informed consent, people were seated
in front of the display. Their task was to pick up an object from one
room, go to the next room, place the object on the empty part of the
table, pick up the next object, proceed to the next room, and so forth.
When an object was picked up, it disappeared. Thus, a person could
not see what he/she was currently carrying. When it was dropped
off, it appeared on the table. Picking up and putting down objects
was done by touching the appropriate end of the table.
To have people progress through the rooms in the required order,
after they entered a room the door of entry closed. The door to
the next room did not open until the person put down the carried
object and picked up the new object. The doorway to the next room
always required the person to turn away from the table in the cur-
rent room.
There were 48 probe trials. Thus, not every possible test point
had a probe. On probe trials, immediately upon entering a room or
crossing halfway through a larger room, people were presented with
a probe that appeared in the middle of the screen. This probe was
either an image of an object or a color and shape name. People were
to respond “yes” if the probe was either the object that was currently
being carried or the one that had just been set down, and to respond
“no” to all other probes. The negative probes were generated by re-
combining the object and color for these two objects. For example,
if the carried object was a white cube, and the object set down was
a red wedge, a negative probe might be red cube. Half of the probes
occurred after a spatial shift, and half did not.
A joystick was held in the dominant hand for movement. For re-
sponding, a button pressed by the index f inger (the trigger) was used
for a positive response and a button on the top of the joystick was
pressed with the thumb for a negative response. There were 24 posi-
tive probes and 24 negative probes.
new setting (Radvansky & Copeland, 2010). Information
that continues to be relevant across the two events is main-
tained, and information that was relevant to the prior event
is removed. This event model updating should extend to a
range of circumstances.
The present work explored the dependency of this ef-
fect on how well integrated the information in the mem-
ory probe is with the environmental context. It may vary
with the degree of integration, where degree of integra-
tion refers to how much the probed-for information is part
and parcel of the event in which a person is embedded.
From a broader theoretical perspective, it is well known
that context information is stored in memory traces (e.g.,
Smith & Vela, 2001). However, instead of assessing the
influence of context as a retrieval cue, we assessed the
degree to which changes in context influence memory.
One could argue that the degree to which information is
tied to a particular context would modulate the influence
of a change in context on later memory retrieval. Thus,
the focus here is on the degree to which the probed-for
information is embedded in the context of the structure
of the on going event. In the present work, we explored
this by using memory probes that were more (Experi-
ment 1) or less (Experiment 2) tied to the experienced
environment.
EXPERIMENT 1
In the Radvansky and Copeland (2006) study, although
people saw images of objects, verbal probes were used.
These probes were not well integrated with the experi-
enced visual–spatial context. There was a mismatch of
probe and target, such as that observed with transfer-
appropriate processing (Kolers & Roediger, 1984). In-
consistencies between how information is encoded and
retrieved can hinder memory, opening a window to further
disruptions, such as those produced by location updat-
ing. Similarly, in a study by Swallow et al. (2009), people
were probed for objects seen in films: For objects that
were relevant across event boundaries (as our probed-for
objects were) and that were actually fixated during film
viewing, Swallow et al. found poorer memory following
an event shift when the task emphasized conceptual qual-
ities (e.g., did you see a spatula or a pot?), but not when
the task emphasized perceptual qualities (e.g., which of
two pots did you see?). Thus, location updating may be
disruptive when the probe task emphasizes conceptual
qualities (e.g., using verbal labels of seen objects), but
not when it emphasizes perceptual qualities (e.g., using
pictures of objects).
Another view is that updating an event model follow-
ing a location shift disrupts memory for information as-
sociated with a prior location (the objects in the previous
room), even if it continues to be task relevant. How the
information is probed for, whether verbal or visual, would
be of minor consequence.
To test between these two accounts, in Experiment 1
half of the people received probes that were pictures of the
objects (e.g., an image of a red cube rather than the words
902 ra d va n s k y , ta m p l i n , a n d kr aw i E t z
EXPERIMENT 2
Experiment 2 assessed the availability of information
that is less well integrated with the environment. Specif i-
cally, in addition to memory for the objects, we assessed
memory for word pairs that did not refer to features of
the context in which they were encountered. They were
random word pairs that were presented simply to be re-
membered. When a probe was presented, it could be either
an object name or a word pair.
Object probes were the same as in Experiment 1. For
the word pairs, we used adjective–noun pairs (e.g., ethnic–
cake) to parallel the structure of the object names (e.g.,
white wedge). These word pairs were nonsensical, further
separating them from the environment. Moreover, adjec-
tives and nouns were repeated, in different combinations,
over the course of the trials, just like the object color and
shape names. This also allowed for some proactive interfer-
ence, making the task more demanding.
One possibility was that, because the word pairs were
not contextually well integrated, they would be loosely as-
sociated with the event model and would be isolated from
the effects of location updating. As such, there would be a
location updating effect for the objects, but not word pairs.
In contrast, an alternative view would be that the wide
range of information processed as part of the ongoing situ-
ation would be integrated into the event model (e.g., Swal-
low et al., 2009), even if it was not well integrated with the
external event. Thus, location updating would compromise
memory for the word pairs as well as the objects.
Method
Participants
. Forty people (20 female) from the University of
Notre Dame were given partial course credit for participation. The
data from two additional people were dropped because their error
rates were close to chance.
Materials and Procedure
. The same apparatus and a similar
set of materials and procedures were used as in Experiment 1, with
some important differences. First, the virtual space was a 74-room
environment. Second, to parallel the color–shape names, the word
pairs were adjective–noun combinations. These words were matched
to the color and object names for number of letters, syllables, and
word frequency, although the combinations were less meaningful.
The adjectives used were marine, ethnic, third, chief, meet, north,
dank, large, select, six, and fast. The nouns were cake, cuff, feat,
lamp, wharf, Q, and V (two letters were used because the shapes
were referred to by letters; i.e., T and X). The adjectives and nouns
were repeated across trials just as the object color and shape names.
Negative word probes were recombinations of adjectives and nouns
from the two most recently seen word pairs. Prior to picking up each
object, a word pair was displayed for 2 sec. The task was to hold it
in memory in case it was probed for at one of the probe locations.
Arrow keys on the keyboard and the mouse buttons were used to
move and respond to probes, respectively.
For the critical trials, upon entering a room or crossing the half-
way point of a large room, people were presented with a probe that
could be either an object or a word pair. When the probe was an
object, the task was the same as in Experiment 1. In comparison,
when it was a word pair, the person indicated whether it was the to-
be-remembered word pair. There were 48 probe trials.
There were 24 positive and 24 negative object probes. For the
word pair probes, there were 12 positive and 12 negative probes.
Half of the probes in each condition occurred after a location shift,
and half did not.
Results
The error rate and response time data are reported in
Table 1 and were submitted to 2 (probe type: text vs. pic-
ture probes) 3 2 (shift condition: no-shift vs. shift) mixed
ANOVAs, with the first factor between subjects and the
other factor within subjects. For the error rates, the main
effect of probe type was not signif icant [F(1,46) 5 2.12,
MSe 5 .022, p 5 .15], but the effect of shift was [F(1,46) 5
4.26, MSe 5 .035, p 5 .05], with people making more er-
rors when there was a shift than when there was not. The
interaction was not significant (Fs , 1). Thus, there was
forgetting after moving from one location to another, but
the nature of the probe (picture or verbal) had no mean-
ingful effect.
For the response time analysis, errors were excluded,
and we trimmed the data by removing response times
faster than 200 msec and slower than 10,000 msec. Then
the data were submitted to the van Selst and Jolicœur
(1994) trimming procedure, which is based on the num-
ber of observations per cell, with 6% of the data being
dropped. Again, while the main effect of probe type was
not significant (F , 1), the effect of shift was [F(1,46) 5
21.15, MSe 5 133,469, p 5 .001], with people respond-
ing slower following the shift as opposed to the no-shift
conditions. The interaction was not signif icant [F(1,46) 5
1.67, MSe 5 133,469, p 5 .20].
Discussion
Experiment 1 assessed whether the location updat-
ing effect was due to poorer integration of the memory
probes with event context because of their verbal nature.
However, this effect was present for both visual and verbal
probes. This is consistent with the view that when partici-
pants move from one location to another, information that
was relevant in the prior location becomes generally less
available. People are creating event models of the ongoing
circumstances, and updating these models can make some
information less available. The apparent discrepancy be-
tween our findings and those of Swallow et al. (2009) re-
garding conceptual versus perceptual processing is likely
due to methodological differences. For example, they
manipulated the nature of the memory task, whereas we
always used recognition. Moreover, objects were the focus
of our task but were often incidental in the film scenes
in the Swallow et al. work. Finally, having people use a
joystick to navigate the environment had no discernible
influence on performance.
Table 1
Error Rates (Proportions) and Response Times (RTs,
in Milliseconds), With Standard Errors, for Experiment 1
Error Rate RT
M SE M SE
Text Probes
No shift .10 .01 1,317 79
Shift .16 .03 1,564 119
Picture Probes
No shift .15 .03 1,322 59
Shift .20 .04 1,761 138
En v i r o n m E n ta l in t E g r at i o n 903
and needed to be maintained. Thus, the event shift had
a broad-based impact on memory. These data are in line
with other event cognition findings in which informa-
tion was affected by the process of updating the changing
event model.
The present research is also consistent with a range of
findings in spatial cognition that show the importance of
spatial regions. For example, spatial regions can be used
to integrate and segregate information in long-term mem-
ory, thereby influencing the pattern of retrieval interfer-
ence (e.g., Radvansky, 1999, 2005; Radvansky, Spieler, &
Zacks, 1993; Radvansky & Zacks, 1991) and the retrieval
of information from a mental map (e.g., Bower & Rinck,
2001; McNamara, 1986; Thorndyke, 1981). In research
on narrative comprehension, memory for objects declines
when there has been a shift in location (e.g., Curiel & Rad-
vansky, 2002; Glenberg et al., 1987; Morrow, Greenspan,
& Bower, 1987; Radvansky & Copeland, 2010; Rinck &
Bower, 1995). Also, people read more slowly when they
encounter a spatial shift in a text (Zwaan, Magliano, &
Graesser, 1995; Zwaan, Radvansky, Hilliard, & Curiel,
1998) and organize narrative information by spatial re-
gions (Radvansky, 1999; Radvansky et al., 1993; Rad-
vansky & Zacks, 1991; Zwaan, Langston, & Graesser,
1995), even with more perceptual events, such as narrative
film (Magliano, Miller, & Zwaan, 2001).
In sum, walking through doorways reduces the avail-
ability of information in memory. This is relatively unaf-
fected by the degree of integration of the information with
the surrounding environmental context. Movement from
one location to another disrupts cognition. Ongoing and
future research is aimed at understanding the underlying
causes of this forgetting.
AUTHOR NOTE
We thank Daniel Blakely, Mark Bohay, Abbi Daugherty, Erica
Nason, Patrick O’Keefe, Jenny Walls, Megan Cefferillo, and Brittany
Gragg for their assistance in collecting the data. We also thank Jeff
Smith and Mike Villano for their programming expertise. This research
was supported in part by a grant from the Army Research Institute,
ARMY-DASW01-02-K-0003, and by funding from J. Chris Forsythe of
Sandia National Laboratories. Please address correspondence to G. A.
Radvansky, Department of Psychology, University of Notre Dame, Notre
Dame, IN 46556 (e-mail: gabriel.a.radvansky.1@nd.edu).
Note—Accepted by Cathleen M. Moore’s editorial team.
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M SE M SE
Object Probes
No shift .18 .02 1,747 82
Shift .23 .03 1,978 101
Word Pair Probes
No shift .08 .02 1,234 45
Shift .14 .02 1,306 64
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... The most prominent example of this is the location updating effect, which refers to the decline in memory that results when an agent moves from one location to another [e.g., passing through a doorway; e.g., 39,51,52]. In a series of experiments conducted by Radvansky and colleagues [39,51,52], participants navigated a series of rooms while picking up and setting down different objects in each room. ...
... The most prominent example of this is the location updating effect, which refers to the decline in memory that results when an agent moves from one location to another [e.g., passing through a doorway; e.g., 39,51,52]. In a series of experiments conducted by Radvansky and colleagues [39,51,52], participants navigated a series of rooms while picking up and setting down different objects in each room. During this, participants' recognition memory for the objects was tested. ...
... This finding was even more pronounced when participants moved through multiple rooms, therefore crossing multiple event boundaries [51]. The effect occurs in both VR [38,39,51,52] and physical laboratory environments [51], as well as in people's imagination [53]. It has been found when word pairs were used instead of objects [52], when the rooms were separated by transparent "glass" walls allowing participants to preview the next location [54], when recall was tested as opposed to recognition [55], and for both younger and older adults [56]. ...
Article
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Misinformation regarding the cause of an event often continues to influence an individual’s event-related reasoning, even after they have received a retraction. This is known as the continued influence effect (CIE). Dominant theoretical models of the CIE have suggested the effect arises primarily from failures to retrieve the correction. However, recent research has implicated information integration and memory updating processes in the CIE. As a behavioural test of integration, we applied an event segmentation approach to the CIE paradigm. Event segmentation theory suggests that incoming information is parsed into distinct events separated by event boundaries, which can have implications for memory. As such, when an individual encodes an event report that contains a retraction, the presence of event boundaries should impair retraction integration and memory updating, resulting in an enhanced CIE. Experiments 1 and 2 employed spatial event segmentation boundaries in an attempt to manipulate the ease with which a retraction can be integrated into a participant’s mental event model. While Experiment 1 showed no impact of an event boundary, Experiment 2 yielded evidence that an event boundary resulted in a reduced CIE. To the extent that this finding reflects enhanced retrieval of the retraction relative to the misinformation, it is more in line with retrieval accounts of the CIE.
... For example, when you get up from the couch in the living room to go to the kitchen, you sometimes forget what you wanted to do as soon as you walk through the door. This effect is called the location updating or doorway effect, and has been extensively studied (Lawrence & Peterson, 2016;McFadyen et al., 2021;Pettijohn & Radvansky, 2018a, 2018bRadvansky et al., 2010Radvansky et al., , 2011Radvansky & Copeland, 2006;Seel et al., 2019). For example, Radvansky (2006) asked participants to navigate through a series of rooms that contained objects on top of tables. ...
... In a number of studies on the related location updating effect, it has been shown that when people walk through a door, they forget information (Lawrence & Peterson, 2016;McFadyen et al., 2021;Pettijohn & Radvansky, 2018a, 2018bRadvansky et al., 2010Radvansky et al., , 2011Radvansky & Copeland, 2006;Seel et al., 2019; (in terms of a location updating effect), but only for passive movement and when working memory load was high. Furthermore, passive versus active navigation can also be interpreted as different levels of "immersion" in a VE. ...
... In contrast, each study that found boundary effects of any kind (deleterious or beneficial, e.g., for item memory and for temporal order memory respectively) used non-linear environments (Horner et al., 2016;Lawrence & Peterson, 2016;Logie & Donaldson, 2021;Pettijohn & Radvansky, 2018a, 2018bRadvansky et al., 2010Radvansky et al., , 2011Radvansky and colleagues (2021), where the VE was highly immersive and non-linear, but each hexagonal room was otherwise identical (same layout and colouring etc.), which largely failed to replicate the location updating effect and when they did, it manifested in increased false alarms rate instead of the expected reduction in hit rates. All in all, it seems that having a complex environment with distinct rooms is a necessary condition to find robust boundary effects. ...
Thesis
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The Predictive Interactive Multiple Memory Systems (PIMMS) framework has been used to explain how novelty, or more precisely “prediction error”, boosts memory encoding. In this thesis, I explored several other phenomena in the animal and human literature that PIMMS cannot yet explain but should. PIMMS predicts that unexpected information will be better encoded than expected information. However recent work has suggested that expected information can also be better remembered than less expected information. By using a range of expectancies for the location of objects with an immersive virtual reality (iVR) kitchen, I showed that memory is a “U-shaped” function of expectancy, with best memory for highly expected or highly unexpected locations relative to intermediate levels of expectancy. Using OSF-registered Bayesian inference, this U-shape was consistent across four experiments. While the advantage for highly unexpected locations is consistent with PIMMS, the advantage for highly expected locations is not. Importantly, the advantage for expected locations was not simply due to a guessing bias when the location was forgotten, suggesting that the advantage arises during encoding rather than just at retrieval. This U-shape is consistent with another framework - the SLIMM framework - which proposes that different brain regions support the two ends of the U-shape, such that the advantage for unexpected information should be associated with recollection of contextual information via a medial temporal lobe system (like in PIMMS), while the advantage for expected information should be associated with a feeling of familiarity based on rapid cortical consolidation enabled by a medial prefrontal cortex system. However, when I asked participants to indicate recollection or familiarity at retrieval, both ends of the U-shape continuum were associated with higher recollection, while there was no detectable effect of expectancy on familiarity. I consider why this SLIMM prediction may therefore be incorrect. Another finding in the literature concerns the effect of novelty on unrelated information shortly preceding or succeeding the novel experience. PIMMS says nothing about this penumbra effect, which has been related to plasticity-related proteins triggered by the novel experience (so-called “behavioural tagging”). Since participants report that their first iVR experience is highly novel, I submitted a Registered Report to test whether iVR affected memory for unrelated words that were encountered prior to entering the iVR room. In short, the finding was that there is no evidence that novelty improves memory performance for information learned before experiencing something novel. Possible reasons for the failure of finding an effect were discussed. A final limitation of PIMMS I considered was the effect of “boundaries” in continuous stimuli, which are known to affect memory for the temporal order of information. While boundaries might be generated by prediction errors, PIMMS is silent on how they affect temporal order memory. Using a movie featuring a series of rooms, I tested whether memory for the temporal order of objects encountered in those rooms is affected by doorways between rooms and/or by surprising/perceptual changes within a room. Unfortunately, I was unable to replicate a previous report where temporal order memory was worse for pairs of objects in different rooms (i.e., either side of a doorway) than objects in the same room, let alone either sides of a surprising/perceptual change within a room. Taken together, my findings and the literature demonstrate the multiple potential factors that determine how novelty affects memory encoding (and consolidation), which require a more comprehensive theoretical framework than currently available.
... Numerous iterations of this experiment have explored the robustness of the doorway effect. These studies have found that the effect persists regardless of the type of probe (text vs. images [18], recognition vs. recall [10]), travel time [8,9], the level of immersion (small screens, big screens, or real-life environments [16]; active vs. passive interaction; [11], real or imagined; [6,12]), age [17], whether the dividing wall is transparent or opaque [8], whether there were additional items to remember [18], or whether participants were probed after returning to the room the item was first encoded in [16]. ...
... Numerous iterations of this experiment have explored the robustness of the doorway effect. These studies have found that the effect persists regardless of the type of probe (text vs. images [18], recognition vs. recall [10]), travel time [8,9], the level of immersion (small screens, big screens, or real-life environments [16]; active vs. passive interaction; [11], real or imagined; [6,12]), age [17], whether the dividing wall is transparent or opaque [8], whether there were additional items to remember [18], or whether participants were probed after returning to the room the item was first encoded in [16]. ...
... Radvansky et al. [16] stated that 16 pairs of participants would be required to detect the doorway effect using an independent-samples t-test. Previous studies report significant effects from samples between 40 and 60 participants [6,9,15,16,18], as well as smaller samples of 16-30 [10, 11, 17]. ...
Article
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Background The ‘doorway effect’, or ‘location updating effect’, claims that we tend to forget items of recent significance immediately after crossing a boundary. Previous research suggests that such a forgetting effect occurs both at physical boundaries (e.g., moving from one room to another via a door) and metaphysical boundaries (e.g., imagining traversing a doorway, or even when moving from one desktop window to another on a computer). Here, we aimed to conceptually replicate this effect using virtual and physical environments. Methods Across four experiments, we measured participants’ hit and false alarm rates to memory probes for items recently encountered either in the same or previous room. Experiments 1 and 2 used highly immersive virtual reality without and with working memory load (Experiments 1 and 2, respectively). Experiment 3 used passive video watching and Experiment 4 used active real-life movement. Data analysis was conducted using frequentist as well as Bayesian inference statistics. Results Across this series of experiments, we observed no significant effect of doorways on forgetting. In Experiment 2, however, signal detection was impaired when participants responded to probes after moving through doorways, such that false alarm rates were increased for mismatched recognition probes. Thus, under working memory load, memory was more susceptible to interference after moving through doorways. Conclusions This study presents evidence that is inconsistent with the location updating effect as it has previously been reported. Our findings call into question the generalisability and robustness of this effect to slight paradigm alterations and, indeed, what factors contributed to the effect observed in previous studies.
... Periodically, participants received a memory probe that asked about the object they are currently carrying. Across a number of studies conducted in virtualworlds, it has been demonstrated that memory for a recently encountered object is worse when a participant has traversed through a doorway in between picking up an object and receiving the memory probe, compared to when they have travelled an equivalent distance within the same room (Radvansky & Copeland, 2006: see also Horner, Bisby, Wang, Bogus, & Burgess, 2016;Radvansky, Tamplin, & Krawietz, 2010;Radvansky, Krawietz, & Tamplin, 2011;Seel, Easton, McGregor, Buckley, & Eacott, 2019). Under the framework provided by event cognition models, these results can be interpreted as the boundaries of the rooms defining event boundaries (Radvansky et al., , 2010. ...
... Across a number of studies conducted in virtualworlds, it has been demonstrated that memory for a recently encountered object is worse when a participant has traversed through a doorway in between picking up an object and receiving the memory probe, compared to when they have travelled an equivalent distance within the same room (Radvansky & Copeland, 2006: see also Horner, Bisby, Wang, Bogus, & Burgess, 2016;Radvansky, Tamplin, & Krawietz, 2010;Radvansky, Krawietz, & Tamplin, 2011;Seel, Easton, McGregor, Buckley, & Eacott, 2019). Under the framework provided by event cognition models, these results can be interpreted as the boundaries of the rooms defining event boundaries (Radvansky et al., , 2010. Here, probes administered after passing through a doorway require memory for an object that was encountered in an event model that is no longer active, whereas memory probes administered within the same room require memory for an object that was encountered in the currently active event model. ...
Article
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Physical boundaries in our environment have been observed to define separate events in episodic memory. To date, however, there is little evidence that the spatial properties of boundaries exert any control over event memories. To examine this possibility, we conducted four experiments that took manipulations involving boundaries that have been demonstrated to influence spatial representations, and adapted them for use in an episodic object memory paradigm. Here, participants were given 15 min to freely explore an environment that contained 36 objects, equally dispersed among six discriminable buildings. In a subsequent test of object-location binding, participants were required to indicate where they remembered encountering the objects. In Experiment 1 the spatial properties of the building boundaries were identical; however, in Experiment 2 the boundaries were differentiated by their geometric shape and the location of the doorways in the buildings. In the test phases of these experiments, we observed a shift from a bias towards remembering the positions of objects within a building but not the building itself (Experiment 1), to a bias towards remembering which building an object was in but not the location within the building (Experiment 2). In Experiment 3, the buildings shared the same geometry but were differentiated by the locations of doorways, and we observed no significant differences between response types. Finally, in Experiment 4, the buildings were uniquely shaped but shared the same doorway location, and we observed a bias towards remembering the positions of objects within a building. In addition, exploratory analyses of non-spatial interference revealed more correct recall for objects housed in the first building a participant visited during exploration, compared to all other buildings. Together, our data indicates that the location of doorways in boundaries and, to a lesser extent, boundary geometries influence event models, and that a primacy effect can be observed in the recall of multiple object-location bindings.
... While the optical information available from the UAV is mathematically sufficient to accurately update position, humans are imperfect integrators, and errors can accumulate. Furthermore, research on mental models of space (Radvansky et al., 2010) has found that humans develop rich but temporary representations of space that are discarded when action in the space is no longer anticipated (e.g., when one leaves a room). Whether through accumulated error or active loss of a representation, catastrophic failure occurs when the user loses all sense of the location and orientation of the UAV. ...
Article
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Field geologists are increasingly using unmanned aerial vehicles (UAVs or drones), although their use involves significant cognitive challenges for which geologists are not well trained. On the basis of surveying the user community and documenting experts’ use in the field, we identified five major problems, most of which are aligned with well-documented limits on cognitive performance. First, the images being sent from the UAV portray the landscape from multiple different view directions. Second, even with a constant view direction, the ability to move the UAV or zoom the camera lens results in rapid changes in visual scale. Third, the images from the UAVs are displayed too quickly for users, even experts, to assimilate efficiently. Fourth, it is relatively easy to get lost when flying, particularly if the user is unfamiliar with the area or with UAV use. Fifth, physical limitations on flight time are a source of stress, which renders the operator less effective. Many of the strategies currently employed by field geologists, such as postprocessing and photogrammetry, can reduce these problems. We summarize the cognitive science basis for these issues and provide some new strategies that are designed to overcome these limitations and promote more effective UAV use in the field. The goal is to make UAV-based geological interpretations in the field possible by recognizing and reducing cognitive load.
... Consequently, our minds have evolved to partly reset as we move between defined spaces. "The Doorway Effect" is a common phenomenon where we might walk into the kitchen only to forget why we did so (Radvansky et al., 2010). Since our goal is immersion in the liminal space, clarity to that moment when we cross from one space to another aids suspension of disbelief: demanding a decision and commitment from us to either stay in our ordinary reality or to step across the border and into the liminal journey. ...
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As ubiquitous technology is increasingly mediating our relationships with the world and others, we argue that the sublime is struggling to find room in product design primarily aimed at commercial and transactional goals such as speed and efficiency. We suggest a new category of products to promote deeper and more meaningful experiences, specifically those offering liminality, transcendence, and personal transformation. This paper introduces a conceptual framework and related three-step design approach that looks at narrative participation in design through abstractions to promote, hold and deepen more complex emotions. We explore implications from a theoretical point of view and suggest some liminal product design ideas as examples of how the model might be applied in practice.
... For example, Fiedler et al. (2005) showed that, while keeping the space and time parameters constant, priming effects (e.g., detecting aggressive stimuli following a picture showing an aggressive act) vanished when prime and target were not encoded into the same mental episode. Similarly, Radvansky, Tamplin, and Krawietz (2010) showed that people were more likely to forget what they just put down on a table when they crossed a symbolic event boundary (i.e., leaving a room) compared to when they walked the same distance within the same room. ...
Article
Evaluative Conditioning (EC) research shows that people learn their likes and dislikes due to the co-occurrence of stimuli (CS and US) in the environment. Most recent EC research addressed processes underlying this phenomenon: how do people acquire their likes and dislikes? We address the question of when people learn from co-occurrences. To understand when learning occurs rather than how it occurs, we apply a dual-force perspective (Bless & Fiedler, 2006). We propose that the environment provides a bottom-up force, for example, via spatial and temporal closeness of CS and US. The organism provides a top-down force, for example, by active inferences or existing knowledge about CS and US. We propose that these forces jointly determine when people learn from co-occurrences. We tested this dual-force perspective by creating experimental conditions that should lead to EC effects from both associative and propositional EC process models but should prevent EC effects from a dual-force perspective. Across four pre-registered laboratory experiments (N = 568) and two pre-registered online experiments (N = 440), we found that changing the top-down force weakened and eliminated (Experiments 1–3) or reinstated EC effects (Experiment 4), using a backward (Experiments 1–4) or forward conditioning procedure (Experiment 5–6), while keeping the environmental bottom-up force constant (Experiment 6). Independent of the how question (e.g., associative or propositional), these results support the dual-force perspective as a framework to predict when people learn their likes and dislikes from the co-occurrence of CS and US in the environment.
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This study investigated to what extent people can develop global spatial representations of a multi-room environment through one-shot physical walking between rooms. In Experiment 1, the participants learned objects’ locations in one room of an immersive virtual environment. They were blindfolded and led to walk to a testing position either within the same room (within-boundary) or in an adjacent novel room (across-boundary). They conducted judgments of relative direction (JRD) based on the remembered locations of objects. The participants’ actual perspectives and imagined perspectives of JRD trials were manipulated to be aligned or misaligned (i.e., faced the same or opposite cardinal directions). The results showed better JRD performances for the aligned perspectives than the misaligned perspectives in the across-boundary condition; this global sensorimotor alignment effect was comparable with the effect in the within-boundary condition. Experiments 2-6 further examined global sensorimotor alignment effects after across-boundary walking. Experiments 2-3 manipulated factors related to encoding global relations (i.e., explicit instructions to attend to walking and keep track of spatial relations, and visual cues for navigational affordance to another space). Experiments 4-6 manipulated factors related to retrieving global relations in JRD (i.e., learning orientation as one imagined perspective, learning position and orientation as the imagined viewpoint, and the number of imagined perspectives). The results showed robust global sensorimotor alignment effects in all experiments, indicating that the participants updated actual headings relative to remembered objects in the other room. Global spatial updating might be the primary mechanism for developing global spatial representations of a multiscale environment.
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