On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, for the first section of Chapter 1 came from the nine volumes of the Kodansha. Perceptual learning in speech and statistical learning may also draw (partly) on the same underlying cognitive abilities, such as working memory and attention. Keywords: Autobiographical memory, false memory, memory conjunction error, imagination, . All were fluent English speakers with no history of learning disabilities, ), the relationship between perceptual detail and false memory construction is not .. Article; |; PubReader; |; ePub (beta); |; PDF (K); |; Citation.
The digit symbol substitution task is a paper-and-pencil test that was derived from the Wechsler Adult Intelligence Scale Test Wechsler, Performance was measured by the number of correctly converted digits in 90 s, meaning that higher scores reflected higher information processing speed. The Trail Making Test was administered to obtain a measure of attention switching control. The paper-and-pencil test contained two parts.
In Part A, participants were asked to connect numbers as quickly as possible in ascending order i. The Part B page had both numbers and letters randomly spread over the page. Participants now had to alternately join numbers and letters in ascending order i. In both parts, 25 items had to be connected and the total time to complete each part was measured. Higher scores indicated higher costs of switching between letters and numbers, therefore, poorer attention switching control.
Linguistic measure Vocabulary knowledge. A vocabulary test in the form of multiple choice questions was administered to obtain a measure of linguistic knowledge Andringa et al.
The computerized test was administered in Excel Courier font size The vocabulary test consisted of 60 items.
There was no time limit or pressure to complete the test. Performance was measured by test accuracy, that is, the proportion of correct answers out of Higher scores thus reflected greater vocabulary knowledge. Statistical Learning Materials and design To investigate statistical learning, we adopted the artificial grammar learning—serial reaction time RT paradigm Misyak et al. This paradigm has typically been used in studies on statistical learning in language processing and has been found to link to individual language processing abilities Misyak et al.
As artificial grammar learning simulates language learning processes, the task makes use of auditory presented sound sequences such as non-words. However, as we wanted to investigate whether individuals' ability to adapt to an unfamiliar speech condition could be predicted by a general ability to implicitly detect regularities, we used visual and non-linguistic stimuli in the statistical learning task. That is, we applied a rigorous test for the relationship between statistical learning and perceptual learning by preventing that a relationship between both measures of learning was specific for auditory and linguistic processing.
Target shapes were sequentially highlighted by a visual marker and participants' task was to click as fast as possible on the highlighted target. The first target was always one on the left side of the screen i. The second target was only highlighted after the participant had clicked on the first target item. Crucially, which of the two items in the right-hand column would be highlighted was predictable on the basis of the first target [e.
Structure of the statistical learning task. A Structure of the grammar in which the first target is always displayed on the left side of the screen and the second target is always displayed on the right side of the screen. B Procedure of a grammatical trial during the exposure phase. Materials consisted of eight familiar, geometrical shapes drawn with a single, continuous black line.
The shapes were divided into two grammatical subsets of four shapes each i. Within each set, two items were selected to appear as first targets i. Therefore, four combinations of shapes were grammatical within each set, resulting in a total set of eight grammatical combinations see Figure 2A.
Target items were presented along with distractors in a rectangular grid display on the computer screen see Figure 2B. Distractor items were shapes from the subset that was currently not tested and the two distractor shapes on the screen formed a grammatical combination themselves. Thus, within a grammatical trial, the transitional probability from the first to the second target was 1, as the first target could only be followed by the target from the same subset.
Within the grammar, however, the transitional probability between two adjacent items was 0. Target positions were randomly assigned such that it was unpredictable whether a first or second target would be displayed in the upper or lower row of a particular column. The artificial grammar learning task was composed of blocks and split into an exposure phase, a test phase and a recovery phase.
During the exposure phase, participants could learn the grammar by picking up on the co-occurrence probabilities of the shapes. In total, the exposure phase consisted of 16 grammatical blocks. In these ungrammatical blocks, the original grammar was reversed, such that a target was followed by targets of the other competing subset. Participants who implicitly learned the grammar should show a drop in performance as they would need to correct their predictions, resulting in a slowed response to the second target.
This measure of learning is widely accepted in the literature on implicit learning Janacsek and Nemeth, Therefore, statistical learning was operationalized by the difference in task performance between the last four blocks of the exposure phase blocks 13—16 and the subsequent ungrammatical test phase blocks 17— The recovery phase again consisted of two grammatical blocks and serves as a control phase.
If participants learned the grammar, by re-introducing the regularities in the recovery phase, participants' performance should not decrease any further. Procedure The artificial grammar learning task was presented in E-prime Schneider et al. Participants were informed that they had to click on two successive targets and that the first target would be located in the first column and the second target would be located in the second column. Each trial started with the presentation of the visual display that consisted of the four shapes and two grid lines, marking the four quadrants on the screen.
At the start of each trial, the mouse cursor was located in the center of the screen.
The visual marker appeared in the middle of the first target shape ms after the onset of the visual display, and was shown until the participant clicked on the marked picture. After the participant had responded, the mouse cursor was automatically set back to the center of the screen to ensure the same distance for all click responses. The second visual marker same red cross now marking the second target shape appeared ms after the first click. This time interval was implemented in the design to allow for prediction effects, even in the adults who had slower processing.
This time interval had been successfully applied in an earlier study on implicit sequence learning in older adults Salthouse et al.
Participants could not make errors: Clicking on a distractor shape or outside the target picture before giving a correct click resulted in a higher RT. The intertrial-interval was ms.
After each block, a small break of ms was implemented to avoid fatigue effects. During this break, participants saw the block number of the upcoming block and a reminder to click as quickly as possible.
It took approximately 20 min to complete the task. To assess statistical learning, we measured latencies from target highlighting to the subsequent mouse response.
Facilitation scores were calculated to index individuals' sensitivity to implicit regularities. The facilitation score was calculated by dividing the RT to the first, unpredictable target within a trial by the RT to the second, predictable target within the same trial. Thus, RT to the first target served as baseline performance within each trial. This was important to minimize biases of task learning and motor performance, particularly for those older adults who may have had little practice in using a computer mouse.
During the course of the experiment, RTs may generally get faster as older adults get more experienced in using a mouse. By implementing a new baseline within each new trial, such motor learning should be accounted for. If participants cannot predict which target will be highlighted next, their RTs to both targets within a trial will be similar and will result in a facilitation score of 1.
During the exposure phase, learning manifests itself in an increasing facilitation score. That is, if participants learn to predict the second target, RTs to the second item will be faster and, therefore, shorter compared to the first, unpredictable target RTs.
Perceptual Learning Materials and design Sixty Dutch sentences were noise-vocoded to create an unfamiliar speech condition to which participants needed to adapt. In noise-vocoded speech, frequency information in the signal is replaced by noise while preserving the original amplitude structure over time. The speech signal was split into multiple non-overlapping frequency bands, which approximately matched equal distances on the basilar membrane Greenwood, From each frequency band the smoothed amplitude envelope was derived and imposed on wide-band noise in the same frequency range.
In a last step, these modulated noise bands were recombined, creating a speech signal that sounded like a harsh robot voice. All signal editing was done in Praat Boersma and Weenink, An important characteristic of noise-vocoded speech is that the comprehension level of the speech signal can easily be manipulated by varying the number of frequency bands.
The more frequency bands are used to decompose the speech signal, the more detail of the original temporal and amplitude structure is preserved and the more intelligible the speech signal is. However, when presented with speech noise-vocoded with fewer bands, participants only reach this level of performance after a certain amount of exposure. The maximal amount of learning or intelligibility improvement can be observed if the starting level is neither too high nor too low, so that sufficient information can be derived from the acoustic materials to initiate learning while at the same time allowing for sizeable improvement see Peelle and Wingfield, We initially tried to provide participants with an individual starting level from which they could still show improvement.
In a separate pilot study, we therefore assigned 23 older adults to a specific noise-vocoding condition i. Inspection of the data showed that participants' starting level clustered according to band condition.
Relatedly, the correlation between SRT result and initial performance on the noise-vocoded speech was weak. As our attempt to individualize starting levels on the basis of a speech-in-noise task was not successful, we aimed to provide a roughly similar starting level for both age groups.
Based on the results of the pilot study, we decided to present older adults with speech that was vocoded with 5 bands corner values using 5 frequency bands: As younger adults understand more when being exposed to the same degradation as older adults Peelle and Wingfield, ; Sheldon et al. Consequently, we were able to see sizeable and comparable amounts of improvement over the course of exposure in both age groups. Sentences were selected from audiological test materials Versfeld et al.
Each sentence had a length of eight or nine syllables and contained four keywords. Keywords in the selected set of sentences included a noun, verb and preposition.
The fourth keyword was an adjective, adverb or a second noun. Practice sentences had the same length as test items a list of all sentences used in the current study is provided in Supplementary Material.
Procedure An auditory sentence identification task was administered to investigate perceptual learning using the experiment program E-prime Schneider et al. Participants listened to the noise-vocoded sentences and were asked to identify and repeat these sentences. They were encouraged to guess if they were unsure. Participants were first presented with five practice trials. First, participants listened to three clear sentences to familiarize them with the task and the speaker.
Moreover, these practice trials were used to check whether participants' memory span was sufficient to perform the task given clear input, which was the case for all participants.
Then participants listened to two sentences that were noise-vocoded with only two frequency bands to present them with the type of degradation. This more difficult condition with fewer bands was chosen to make sure that no learning could occur during the practice phase e.
Practice trials were identical for all participants and were presented in the same order. In contrast, the 60 test sentences were presented in random order for each participant, so that observed learning effects would be independent of inherent intelligibility differences between sentences e.
Participants heard a short ms 3. After each sentence, the researcher scored the number of correctly repeated keywords 0—4 online. The next trial started immediately after the researcher had confirmed the scoring of the previous trial. Participants' answers were audiorecorded to allow for later checking of their responses.
Experimental Procedure Measures of younger adults were obtained in a single experimental session. Testing was spread over two sessions for the older adults, as they also participated in a different study. During the first session, older adults performed the background measures described above. The second session consisted of the statistical learning and the perceptual learning task and followed within a month on the first session. In both age groups, tasks were presented in a fixed order. Although the order differed between younger and older adults, the statistical learning task was always presented before the perceptual learning task.
All participants were tested individually in a sound-attenuating booth to minimize distraction. Before the start of each task, participants received verbal and printed task instructions. Participants could ask questions at any time. Between tasks, participants were encouraged to take small breaks. Data Analysis Statistical modeling To assess learning performance, we implemented linear mixed-effects models using the lmer function from the lme4 package Bates et al.
In this way, both participants and items could be assessed as random factors and the maximal random slope structure of models could be defined to reduce the probability of a type 1 error Barr et al.
First, we modeled statistical and perceptual learning performance as a function of age group to assess whether younger and older adults differed in their learning performance. Second, we analyzed the contributions of individual abilities in learning separately within each group as our focus was on individual differences within the respective age groups. Thus, the modeling process that is described here was applied to the statistical learning data and to the perceptual learning data of both age groups.
Linear regression models are based on the assumption that the predictors included in the analysis do not show collinearity Baayen, Although some predictor measures were intercorrelated see Section Performance on Background Measureswe did not control for these intercorrelations for two reasons. Second, simultaneous inclusion of correlated measures in the analysis has been shown to provide a more reliable interpretation of estimates than inclusion of residualized variables York, ; Wurm and Fisicaro, Statistical learning was defined as a drop in performance in the test phase blocks 17—18 compared to the performance at the end of the exposure phase blocks 13— Therefore, in models of statistical learning, the fixed categorical variable phase exposure vs.
Additionally, two control variables and the corresponding two- and three-way interactions with phase were included in models of statistical learning. Given the directionality of Western writing systems, we expected a first target position effect as participants may click faster on a target in the upper left quadrant than in the lower left quadrant. We also expected the drop in facilitation score during the test phase to be less distinct in trials with the first target appearing in the upper left quadrant, such that target position was expected to interact with the amount of learning.
Moreover, the alignment of targets was thought to affect second target RTs. Note that the experimental program always set the mouse back to the center of the screen after each click. Despite this automatic mouse reset, participants tended to also move the mouse back to the center of the screen.
By doing that, participants unintentionally initiated a movement toward the diagonal shape. Therefore, we assumed that participants would be faster in responding to the second target if targets were arranged diagonally rather than horizontally see Figure 2which would result in higher facilitation scores. This direction effect may interact with the effect of removing the regularities, such that the grammaticality effect be decreased for the diagonal movements.
In models of perceptual learning, the number of correctly repeated keywords per sentence served as index of recognition performance and was entered as numerical dependent variable into the model. As perceptual learning was defined as the improvement in speech understanding over exposure, we split the experiment into six blocks, containing 10 sentences each and added block as numerical measure of exposure to the model.
However, before block was included in the analysis, we performed a log-transformation of block, as perceptual learning has typically been described by fast initial learning that levels off with increasing exposure see also Figure 4. The transformation of block therefore provided us with an index of exposure that took this non-linear improvement curve into account and converted the improvement over exposure into a linear scale 1.
In the first step of the analysis, we identified the maximal random slope structure of our models to allow for the fact that different participants or items may vary with regard to how sensitive they are with respect to the variables at hand Cunnings, ; Barr et al.
Changes in the random-slope structure were evaluated by means of the Akaike information criterion AIC. As we were interested in the predictors of individual amount of learning, a random participant slope of phase was included in all models of statistical learning. Accordingly, in models of perceptual learning, a random participant slope of block was inserted.
Autobiographical memory - Wikipedia
That is, all models calculated the learning effect i. After determining the maximal random slope structure, we first performed an age group comparison by testing the interactions between age group and the respective index of learning i.
As younger and older adults may differ with respect to the effects of target position and target alignment on their learning performance, all possible two-way interactions between grammaticality, age group, target alignment and first target position and the three-way interactions between 1 age group, grammaticality and target position and between 2 age group, grammaticality and target alignment were included in the age group comparison of statistical learning.
The source of a known memory is attributed to an external source, not personal memory. This can often lead to source-monitoring errorwherein a person may believe that a memory is theirs when the information actually came from an external source. Recalling positive personal experiences can be used to maintain desirable moods or alter undesirable moods.
Memory perspectives[ edit ] People often re-experience visual images when remembering events. One aspect of these images is their perspective.
The field perspective is the type of autobiographical memory recalled from the field of perspective that occurred when the memory was encoded. The field of view in such memories corresponds to that of the original situation. The observer perspective is an autobiographical memory recalled from an observer position, i.
The event is viewed from an external vantage point. There is a wide variation in the spatial locations of this external vantage point, with the location of these perspectives depending on the event being recalled.
Some of the moderators that change individuals' recalled perspectives are memory age, emotionality, and self-awareness. Recent memories are often experienced in the field perspective; as memory age increases, there is also an increase in the amount of observer memories.
People living in Eastern cultures are more likely to recall memories through an observer point of view than those living in Western cultures. For example, Easterners are more likely than Westerners to use observer perspective when remembering events where they are at the center of attention like giving a presentation, having a birthday party, etc. Each culture has its own unique set of factors that affect the way people perceive the world around them, such as uncertainty avoidance, masculinity, and power distance.
Western society has been found to be more individualisticwith people being more independent and stressing less importance on familial ties or the approval of others. Westerners are said to have a more "inside-out view" of the world, and unknowingly project their current emotions onto the world around them. This practice is called egocentric projection.
For example, when a person is feeling guilty about something he did earlier, he will perceive the people around him as also feeling guilty. These different perceptions across cultures of how one is viewed by others leads to different amounts of field or observer recall. This is because in "center-of-attention" memories, the person is conscious about the way they are presenting themselves and instinctively try to envision how others were perceiving them.
Studies also show that events with greater social interaction and significance produce more observer memories in women than events with low or no social interaction or significance. For many people it can be too difficult to use this perspective to recall the event. In this way a record of true autobiographical memories can be collected.
Chu and Downes found ample evidence that odour cues are particularly good at cueing autobiographical memories. Emotional memories are reactivated more, they are remembered better and have more attention devoted to them.
All memories fade, and the emotions linked with them become less intense over time. Past failures seem farther away than past achievements, regardless if the actual length of time is the same. Remembering negative events can prevent us from acting overconfident or repeating the same mistake, and we can learn from them in order to make better decisions in the future. The effect of mood-congruent memorywherein the mood of an individual can influence the mood of the memories they recall, is a key factor in the development of depressive symptoms for conditions such as dysphoria or major depressive disorder.
Individuals with mild to moderate Dysphoria show an abnormal trend of the fading affect bias. The negative memories of dysphoric individuals did not fade as quickly relative to control groups, and positive memories faded slightly faster.
One possible explanation suggests that, in relation to mood-congruent memory theory, the mood of the individual at the time of recall rather than the time of encoding has a stronger effect on the longevity of negative memories. Depression impacts the retrieval of autobiographical memories. Adolescents with depression tend to rate their memories as more accurate and vivid than never-depressed adolescents, and the content of recollection is different.
Childhood or infantile amnesia The reminiscence bump Infantile amnesia concerns memories from very early childhood, before age 6; very few memories before age 3 are available. The retention function is the recollection of events in the first 20 to 30 most recent years of an individual's life.
This results in more memories for events closest to the present, a recency effect. Finally, there is the reminiscence bump occurring after around age 40, marked by an increase in the retrieval of memories from ages 10 to For adolescents and young adults the reminiscence bump and the recency effect coincide. Episodic to semantic shift[ edit ] Piolino, Desgranges, Benali, and Eustache investigated age effects on autobiographical memory using an autobiographical questionnaire which distinguished between the recall of semantic and episodic memory.
They proposed a transition from episodic to semantic memory in autobiographical memory recollection with increased age. Using four groups of adults aged 40—79, Piolino and colleagues found evidence for a greater decline in episodic memories with longer retention intervals and a more substantial age-related decline in recall of episodic memory than semantic memory. They also found support for the three components of autobiographical memory, as modelled by David Rubin and colleagues.
Recent memories retention interval are episodic. Older memories are semanticized, becoming more resilient reminiscence bump. With the passing of time, autobiographical memories may consist more of general information than specific details of a particular event or time. In one study where participants recalled events from five life periods, older adults concentrated more on semantic details which were not tied to a distinct temporal or spatial context.
Younger participants reported more episodic details such as activities, locations, perceptions, and thoughts.