Here we discuss the relation between memory and two fundamental types of Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has .. On the relationship between autobiographical memory and perceptual learning. a full model of autobiographical memory must consider cognitive processes Key words: anterograde amnesia, retrograde amnesia, perceptual disorders, temporal .. with either agnosia or amnesia, not the relation between the two; only three . PH reportedly had some trouble learning new visual material, but had only. tion memory and perceptual memory introduced by Jacoby and Dallas (). ment 2 is a replication of the naming procedure, with a smaller set of stimuli and.
Participants had normal or corrected-to-normal vision. Age-related hearing loss is prevalent in older adults Lin et al. Poorer hearing may affect perceptual learning as auditory input contains less detail, thereby interfering with accessing and retuning low-level representations. Participants' auditory function was assessed by measuring air-conduction pure tone thresholds with the aid of an Oscilla USB screening audiometer.
As age-related hearing loss particularly affects sensitivity to high frequencies, a high-frequency pure tone average [PTAH] was taken as index of hearing acuity.
Only the PTAH of the best ear was entered in the analysis, as all auditory stimuli were presented binaurally. None of the participants wore hearing aids in daily life, however.
Higher thresholds reflected poorer hearing. Mean thresholds at different frequencies per age group are given in Figure 1. Mean hearing threshold in dB HL at 0. Error bars indicate two standard error from the mean. Cognitive measures Working memory. Participants performed a digit span backward task as an index of working memory capacity.
Memory: Enduring Traces of Perceptual and Reflective Attention
The test was a computerized variant of the digit span backward task included in the Wechsler Adult Intelligence Scale Test Wechsler, and presented via E-prime 1. Participants were asked to report back sequences of digits in reverse order. Digits were presented in a large white font Arial, font size against a black background. Each digit was presented for 1 s with an interval of 1 s between the consecutive digits of a sequence.
Sequence length increased stepwise from two to seven digits and performance on each sequence length was tested on two different trials all participants were presented with all sequence lengths, regardless of their performance on earlier easier trials. The actual test trials were preceded by two practice trials with a sequence length of three to familiarize participants with the task. Participants had to recall 12 test sequences in total.
Individual performance was operationalized as the proportion of correctly reported sequences out of Information processing speed was assessed by means of a digit symbol substitution task.
Participants had to convert as many digits as possible into assigned symbols in a fixed amount of time 90 s. 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.
Memory: Enduring Traces of Perceptual and Reflective Attention
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. The publisher's final edited version of this article is available at Neuron See other articles in PMC that cite the published article. Abstract Attention and memory are typically studied as separate topics, but they are highly intertwined. Here we discuss the relation between memory and two fundamental types of attention: We consider three key questions for advancing a cognitive neuroscience of attention and memory: To what extent do perception and reflection share representational areas?
To what extent are the control processes that select, maintain, and manipulate perceptual and reflective information subserved by common areas and networks? During perception and reflection, to what extent are common areas responsible for binding features together to create complex, episodic memories and for reviving them later? Considering similarities and differences in perceptual and reflective attention helps integrate a broad range of findings and raises important unresolved issues.
Different research traditions tend to emphasize either attentional phenomena Posner et al. Here we focus on the similarities and differences across these domains and an emerging picture of how they interact. We build, in particular, on two previous theoretical frameworks: Reflective processes are directed at internal representations, such as thoughts, memories, imagery, decision options, problem solving, and self-directed processes.
That is, reflective processes can operate on representations in the absence of corresponding external stimuli or independent of current external input e. At any given moment, not all features, objects and events in the environment or in the mind can be processed equally Marois and Ivanoff, Although the border between perceiving and reflecting can be fuzzy, there are meaningful differences.
Logically, perceiving and thinking are unlikely to engage exactly the same neural hardware or have exactly the same memorial consequences.
That would produce an epistemological quagmire in which we could not tell fact from fantasy in perceiving, thinking or remembering Johnson, On the other hand, if there were no interaction between perception and reflection, we would not be able to constructively and creatively cumulate knowledge across experiences of perceiving and thinking. To what extent do perception and reflection activate the same representational and processing regions? To what extent do they have similar and different memorial consequences?
Under what conditions do they operate independently and by what mechanisms do they interact? Our review and PRAM framework lead us to several hypotheses that invite further testing. However, the extent to which they engage the same or different representations within these areas is an open question. The degree of overlap should predict the extent to which perception and reflection influence each other and how likely they are to be confused, for example, in source memory tasks.
The resulting configural representations bind multiple features e. Are there differences in configural processing active during both perception and reflection? Perceptual attention Sensory information e. Perceptual attention selects and modulates this information according to current task goals. In the PRAM framework, such processing yields persisting records traces or memories. Because most research has used visual stimuli, our review will focus on the visual modality.