Search

Zeitschrift für empirische Hochschulforschung : ZeHf 5 (2021) 2, S. 162-183, Realistische Erwartungen und Passung zwischen Interessen und Studieninhalten sind zentrale Ansatzpunkte bei der Steuerung von Studienwahlentscheidungen. In einem neu entwickelten fachspezifischen Erwartungs- und Interessenstest (E × I - Test) für Psychologie werden erstmals Erwartungsdiskrepanzen und Interessen kombiniert betrachtet und dementsprechend auch übertroffene oder enttäuschte Erwartungen erfasst und rückgemeldet. Die zu den Studieninhalten des neuen Verfahrens entwickelten Items konnten annähernd perfekt den Studienfachbereichen zugeordnet werden und deckten diese weitgehend vollständig und gleichmäßig ab. 2,033 Studieninteressierte bearbeiteten den E × I - Test im Rahmen eines Online-Self-Assessments und fühlten sich danach informierter als vorher. Insgesamt bewerteten die Studieninteressierten das neue Verfahren positiv und 94% würden es weiterempfehlen. Auf Basis des vorgestellten Verfahrens für das Bachelor-Psychologiestudium könnten weitere E × I - Tests für die Orientierung in andere Studienfächer oder Berufe entwickelt und validiert werden, für welche sowohl spezifische Interessen als auch enttäuschte Erwartungen eine Rolle spielen. (DIPF/Orig.), Both, realistic expectations and fit between interests and study content are crucial to guide study choice decisions. A newly developed subject-specific Expectation-Interest Test (E × I - Test) for psychology considers, for the first time, expectation discrepancies and interests in combination. Thus, exceeded or disappointed expectations are assessed and reported back. It was shown that the newly developed items which represent study contents can be assigned almost perfectly to the study subject areas and cover them to a large extent completely and evenly. 2,033 prospective students completed the E × I - Test as part of an online self-assessment and felt more informed afterwards than before. Overall, prospective students rated the new procedure positively and 94% would recommend it to others. Based on the presented procedures for the bachelor psychology studies, further E × I - Tests could be developed and validated for orientation to other fields of study or professions, for which both specific interests and disappointed expectations play a role. (DIPF/Orig.)

It contains codebooks, data files and relevant scripts of a meta-analytic review on emotion-control interactions.

This is the second of a series of experiments on time-based expectancy for finger responses to vibrotactile stimulation. In this experiment, we induce time-based expectancy by pairing two events and two preparatory intervals. In a binary randomized response choice setting, participants respond by keypresses to vibrotactile stimulation to their fingers. Stimulus response mapping is compatible (i.e. respond with the finger that was stimulated), and stimuli are preceded by either a short or a long preparatory interval which predicts with 90% probability which finger will be stimulated next. This pairing of vibrotactile stimulation (left-right finger) and interval duration (short-long) is counterbalanced across participants. For half of the participants the short interval will predict stimulation on the left finger, and the long interval will predict stimulation on the right finger with 90% validity. For the other half, this relation will be inverted. We decide between two hypotheses: 1) Participants respond about equally fast to frequent combinations of interval duration and stimulation side than infrequent ones. Such finding would mean that participants did not form time-based expectancies to vibrotactile stimuli. 2) Participants respond faster to frequent than infrequent combinations of interval duration and stimulation side. Such finding would mean that participants build time-based expectancies to vibrotactile stimuli, and would be consistent with the time-based expectancy literature (see, Thomaschke et al., 2011; Thomaschke et al., 2015) We decide between these hypotheses by a Bayesian analogue to a paired sample t-test (Morey & Rouder, 2011). We cumulatively test participants until we reach a JZS Bayes factor over 5 for either of the hypotheses, or until we have tested 120 participants without reaching a JZS Bayes factor over 5. We collect data with the E-Prime program uploaded to this repository. We will pre-process the data as follows: We do not include participants with an overall mean RT or an overall mean error rate lying more than 2.5 SDs away from the sample mean. We do not include the first trial of each block, the first block, error trials, and trials following an error. Since we will compare two conditions observations (frequent vs. infrequent) with different number of, we will follow special recommendations to calculate the median RT. We will take the regular RT median for the infrequent condition and we will compare it with a special “average median” from the frequent condition, separately for the short and long intervals durations (for a more detailed explanation, see Miller, 1988) By frequent we mean trials with combinations of interval duration and stimulation side with 90% validity and as infrequent count trials with combinations of interval duration and stimulation side with 10% validity. We conduct the Bayesian t-test over these conditions. All further analyses will be of exploratory nature: For example, effects on error rates, effects of interval duration, etc. For following exploratory analyses, the script will be extended.

Humans are able to intentionally forget previously learned information (as often measured using the directed forgetting, short DF, paradigm, for an overview see Pastötter et al., 2017). In the item-method of DF (see MacLeod, 1998 for a review), for instance, participants are instructed to memorize stimuli that are presented to them sequentially. Each sequentially presented stimulus is directly followed by a memory cue informing participants to either forget or remember the stimulus. People typically recall fewer to-be-forgotten (TBF) than to-be-remembered (TBR) stimuli (Bjork, 1970). Whereas various studies have already demonstrated that humans are able to intentionally forget previously learned information, only few studies have analyzed whether DF affects motor representations (Tempel & Frings, 2016) or incidentally learned information (e.g., Hockley et al., 2016; Jou, 2010). Recent studies provided first evidence that typical findings regarding retrieval-induced forgetting and effects of DF extend to motor memory (in particular, motor sequences, Tempel et al., 2016; Tempel & Frings, 2013, 2016) and stimulus-response (S-R) associations (Dreisbach & Bäuml, 2014). Stimulus-response (S-R) associations are formed when stimuli and responses repeatedly co-occur and thus bind together – a notion that is supported by (item-specific) repetition priming effects (see Logan, 1988, 1990). Here, participants’ responses are, for instance, generally faster for stimuli that require the same as opposed to a different, previously-executed response. The current study aims to gain a deeper understanding of the mechanisms underlying the DF effect on the retrieval of S-R associations. For this, we will investigate whether (not explicitly instructed) learned S-R associations can be intentionally forgotten based on forget/remember cues following stimuli. To address this question, we will combine the DF item-method paradigm and an item-specific priming paradigm assessing the encoding and retrieval of S-R associations (see below and also Hsu & Waszak, 2012; Moutsopoulou et al., 2015). Information on the task and study design Our study will consist of three major phases: (1) A learning, (2) a distraction, and (3) a test phase. 1. Learning Phase: During the learning phase, participants’ task is to classify images of objects as containing a mechanism or not. We will extend the DF paradigm to S-R mappings using a classification task (drawing on an item-specific priming paradigm; Hsu & Waszak, 2012; Moutsopoulou et al., 2015; Pfeuffer, Moutsopoulou et al., 2017). By categorizing the stimuli, participants encode S-R associations (stimulus-action, S-A, associations between stimuli and motor outputs according to the terminology provided by Moutsopoulou et al., 2015). Importantly, whether a left or right response is required for the classification of a specific stimulus will differ between stimuli and will be indicated by a task cue detailing the classification-response mapping prior to the stimulus’ presentation. For example, the task cue “M + N” will indicate that an object image has to be classified as “mechanic” by pressing a left key and as “non-mechanic” by pressing a right key. Conversely, the task cue “N + M” will indicate that a right key press is required for mechanic objects and a left key press for non-mechanic ones. Participants will respond to each stimulus four times (in four blocks, see detailed task description below) in the exact same way (i.e., same S-R mapping). Per block, participants will also be instructed to memorize some of the object images for a later memory test and forget others. Directly after the response to a stimulus, a memory cue will inform participants to either forget or remember the stimulus. The same memory cue will appear after each of the four presentations of a specific stimulus. 2. Distraction Phase: In a subsequent distractor task, participants will solve a visual working memory task (Corsi) for 1.5 minutes to spurge short-term memory. 3. Test Phase: In the test phase, participants will be presented once more with the stimuli from the learning phase (both TBF and TBR objects) and new object images. Importantly, for the old objects, half of the stimuli per memory condition, the S-R mapping will be the same as in the learning phase (item-specific response repetition between learning and test). For the other half of the stimuli, the S-R mapping will be the opposite (item-specific response switch between learning and test). Response switches are therefore defined as item-specific switches of S-R mappings between the learning and the test phase of a stimulus (e.g., the stimulus requires a right key press during all four presentations in the learning phase, but a left key press during the test phase). Response repetitions are in turn defined as item-specific repetitions of the required response between the learning and the test phase (e.g., the stimulus requires a right key press during both the learning and test phase). Typically, RTs and error rates for item-specific response repetitions between learning phase and test phase trials are lower as compared to item-specific response switches, indicating that S-R associations have been formed during the learning phase and were retrieved in the test phase. We refer to these effects as item-specific S-R effects. Trial structure and task instructions will be equivalent to the last appearance of stimuli during the learning phase except that no memory cues will be presented anymore. Participants will be instructed that they will only need to respond to stimuli fast and accurately and that there will be no memory cues for this phase. Participants will also be informed that there will be no later memory test. They are told that they will respond to both TBR and TBF stimuli and that they should simply respond as fast and accurately as possible regardless of the previous memory instruction. 4. Distraction Phase: Participants will again solve a visual working memory task (Corsi) for 1.5 minutes to spurge short-term memory. How we aim to measure a DF effect on S-R associations We will use the difference in RTs and error rates in the test phase between trials that require an item-specific response switch and an item-specific response repetition to determine a DF effect based on the remember/forget cues. In other words, we will measure the strength of item-specific S-R effects for TBF as compared to TBR stimuli. Applying the observations in typical DF paradigms to the context of S-R associations we expect the following observations: If DF influences the retrieval of S-R associations, S-R effects, the performance differences between item-specific response repetitions and response switches in the test phase (see Hypotheses section) should be smaller for TBF as compared to TBR stimuli. Additionally, we will assess a DF effect on S-R associations by looking at the decrease in RTs and error rates across the four presentations of a stimulus (repetition priming effect) in the learning phase and compare them between TBR and TBR stimuli.

Humans are able to intentionally forget previously learned information (as often measured using the directed forgetting, short DF, paradigm, for an overview see Pastötter, Tempel, & Bäuml, 2017): In the item-method of DF (see MacLeod, 1998 for a review), for instance, participants are instructed to memorize stimuli that are presented to them sequentially. Each sequentially presented stimulus is directly followed by a cue informing participants to either forget or remember the stimulus. People typically recall fewer to-be-forgotten (TBF) than to-be-remembered (TBR) stimuli (Bjork, 1970). Whereas various studies have already demonstrated that humans are able to intentionally forget previously learned information, only few studies have analyzed whether DF affects motor representations (Tempel & Frings, 2016) or incidentally learned information (e.g., Hockley, Ahmad, & Nicholson, 2016; Jou, 2010). Recent studies provided first evidence that typical findings regarding retrieval-induced forgetting and effects of DF extend to motor memory (in particular, motor sequences, Tempel, Aslan, & Frings, 2016; Tempel & Frings, 2013, 2016) and stimulus-response (S-R) associations (Dreisbach & Bäuml, 2014). Stimulus-response (S-R) associations are formed when stimuli and responses repeatedly co-occur and thus bind together – a notion that is supported by (item-specific) repetition priming effects (see Logan, 1988, 1990). Here, participants’ responses are, for instance, generally faster for stimuli that require the same as opposed to a different, previously-executed response. The current study aims to gain a deeper understanding of the mechanisms underlying the DF effect on the retrieval of S-R associations. For this, we will investigate whether (not explicitly instructed) learned S-R associations can be intentionally forgotten based on forget/remember cues following stimuli. To address this question, we will combine the DF item-method paradigm and an item-specific priming paradigm assessing the encoding and retrieval of S-R associations (see below and also Hsu & Waszak, 2012; Moutsopoulou, Yang, Desantis, & Waszak., 2015). ***Information on the task and study design*** Our study will consist of five major phases: (1) A learning, (2) a distraction, (3) a test, (4) another distraction, and (5) a recognition phase. 1. Learning Phase: During the learning phase, participants’ task is to classify images of objects as containing a mechanism or not. We will extend the DF paradigm to S-R mappings using a classification task (drawing on an item-specific priming paradigm; Hsu & Waszak, 2012; Moutsopoulou, Yang, Desantis, & Waszak, 2015; Pfeuffer, Moutsopoulou, Pfister, Waszak, & Kiesel, 2017). By categorizing the stimuli, participants encode S-R associations (stimulus-action, S-A, associations between stimuli and motor outputs according to the terminology provided by Moutsopoulou et al., 2015). Importantly, whether a left or right response is required for the classification of a specific stimulus will differ between stimuli and will be indicated by a task-cue detailing the classification-response mapping prior to the stimulus’ presentation. For example, the task cue “M + N” will indicate that an object image has to be classified as “mechanic” by pressing a left key and as “non-mechanic” by pressing a right key. Conversely, the task cue “N + M” will indicate that a right key press is required for mechanic objects and a left key press for non-mechanic ones. Participants will respond to each stimulus four times (in four blocks, see detailed task description below) in the exact same way (i.e., same S-R mapping). In the fourth block, participants will also be instructed to memorize some of the object images for a later memory test. In this block, directly after the response to a stimulus, a cue will inform participants to either forget or remember the stimulus. 2. Distraction Phase: In a subsequent distractor task, participants will solve a visual working memory task for 1.5 minutes to spurge short-term memory. 3. Test Phase: In the test phase, participants will be presented once with the stimuli from the learning phase (both TBF and TBR objects). Importantly, for half of the stimuli, the S-R mapping are the same as in the learning phase (item-specific response repetition between learning and test). For the other half of the stimuli, the S-R mapping will be the opposite (item-specific response switch between learning and test). Response switches are therefore defined as item-specific switches of the stimuli´ S-R mappings between the learning and the test phase (e.g., stimulus requires a right key press during the learning phase, but a left key press during the test phase). Response repetitions are in turn defined as item-specific repetitions of the required response between the learning and the test phase (stimulus requires a right key press during both the learning and test phase). Typically, RTs and error rates for item-specific response repetitions between learning phase and test phase trials are lower as compared to item-specific response switches, indicating that S-R associations have been formed during the learning phase and were retrieved in the test phase. We refer to these effects as item-specific S-R effects. Trial structure and task instructions will be equivalent to the last appearance of stimuli during the learning phase. Again, after responding to each stimulus, the same remember or forget cue as in the 4th block of the learning phase will be presented. Participants will be reminded to only remember the TBR stimuli. 4. Distraction Phase: Participants will again solve a visual working memory task for 1.5 minutes to spurge short-term memory. 5. Recognition Phase: In the recognition phase, participants will be presented with all the object images from the learning phase and an equal number of new object images. Participants will be instructed to identify whether an object has previously been presented (category: “old”) or not (category: “new”) – regardless of its associated memory instruction – by pressing either left or right response key. On a given trial, an old or new stimulus image is presented in the center of the screen, and participants are instructed to categorize the stimulus as quickly and accurately as possible as either “old” or “new” according to the category labels that are displayed in the right or left upper screen corner. ***How we aim to measure a DF effect on S-R associations*** We will use the difference in RTs and error rates between trials that require an item-specific response switch and an item-specific response repetition to determine a DF effect based on the remember/forget cues. In other words, we will measure the strength of item-specific S-R effects for TBF as compared to TBR stimuli. Applying the observations in typical DF paradigms to the context of S-R associations we expect the following observations: If DF influences the retrieval of S-R associations, S-R effects, the performance differences between item-specific response repetitions and response switches (see Hypotheses section) should be smaller for TBF as compared to TBR stimuli.

Humans are able to intentionally forget previously learned information (as often measured using the directed forgetting, short DF, paradigm, for an overview see Pastötter et al., 2017). In the item-method of DF (see MacLeod, 1998 for a review), for instance, participants are instructed to memorize stimuli that are presented to them sequentially. Each sequentially presented stimulus is directly followed by a memory cue informing participants to either forget or remember the stimulus. People typically recall fewer to-be-forgotten (TBF) than to-be-remembered (TBR) stimuli (Bjork, 1970). Whereas various studies have already demonstrated that humans are able to intentionally forget previously learned information, only few studies have analyzed whether DF affects motor representations (Tempel & Frings, 2016) or incidentally learned information (e.g., Hockley et al., 2016; Jou, 2010). Recent studies provided first evidence that typical findings regarding retrieval-induced forgetting and effects of DF extend to motor memory (in particular, motor sequences, Tempel et al., 2016; Tempel & Frings, 2013, 2016) and stimulus-response (S-R) associations (Dreisbach & Bäuml, 2014). Stimulus-response (S-R) associations are formed when stimuli and responses repeatedly co-occur and thus bind together – a notion that is supported by (item-specific) repetition priming effects (see Logan, 1988, 1990). Here, participants’ responses are, for instance, generally faster for stimuli that require the same as opposed to a different, previously-executed response. The current study aims to gain a deeper understanding of the mechanisms underlying the DF effect on the retrieval of S-R associations. For this, we will investigate whether (not explicitly instructed) learned S-R associations can be intentionally forgotten based on forget/remember cues following stimuli. To address this question, we will combine the DF item-method paradigm and an item-specific priming paradigm assessing the encoding and retrieval of S-R associations (see below and also Hsu & Waszak, 2012; Moutsopoulou et al., 2015). Information on the task and study design Our study will consist of three major phases: (1) A learning, (2) a distraction, and (3) a test phase. 1. Learning Phase: We will extend the DF paradigm to S-R mappings using a classification task (drawing on an item-specific priming paradigm; Hsu & Waszak, 2012; Moutsopoulou et al., 2015; Pfeuffer, Moutsopoulou et al., 2017). During the learning phase, participants’ task is to classify words (referring to concrete objects) as animate or inanimate (animacy task). By categorizing the stimuli, participants encode S-R associations (stimulus-action, S-A, associations between stimuli and motor outputs according to the terminology provided by Moutsopoulou et al., 2015). Importantly, whether a left or right response is required for an animate/inanimate classification of a specific stimulus will differ between stimuli and will be indicated by a task cue detailing the classification-response mapping prior to the stimulus’ presentation. For example, the task cue “A + I” will indicate that a word has to be classified as “animate” by pressing a left key and as “inanimate” by pressing a right key. Conversely, the task cue “I + A” will indicate that a right key press is required for words denoting animate stimuli and a left key press for words denoting inanimate stimuli. At the same time, participants will be instructed to memorize some of the words for a later memory test and forget others. Directly after the response to a stimulus, a memory cue will inform participants to either forget or remember the stimulus. 2. Distraction Phase: In a subsequent distractor task, participants will solve a visual working memory task (Corsi) for 1.5 minutes to spurge short-term memory. 3. Test Phase: In the test phase, participants will be presented once more with the stimuli from the learning phase (both TBF and TBR words) and new words. Importantly, for the old words, half of the stimuli per memory condition, the S-R mapping will be the same as in the learning phase (item-specific response repetition between learning and test). For the other half of the stimuli, the S-R mapping will be the opposite (item-specific response switch between learning and test). Response switches are therefore defined as item-specific switches of S-R mappings between the learning and the test phase of a stimulus (e.g., the stimulus requires a right key press in the learning phase, but a left key press in the test phase). Response repetitions are, in turn, defined as item-specific repetitions of the required response between the learning and the test phase (e.g., the stimulus requires a right key press in both the learning and test phase). Typically, RTs and error rates for item-specific response repetitions between learning phase and test trials are lower as compared to item-specific response switches, indicating that S-R associations have been formed during the learning phase and were retrieved in the test phase. We refer to this effect as item-specific S-R effect. Trial structure and task instructions in the test phase will be equivalent to the learning phase except that no memory cues will be presented anymore. Participants will be instructed that they will only need to respond to stimuli fast and accurately and that there will be no memory cues for this phase. Participants will also be informed that there will be no later memory test. They are told that they will respond to both TBR and TBF stimuli and that they should simply respond as fast and accurately as possible regardless of the previous memory instruction. How we aim to measure a DF effect on S-R associations We will use the difference in RTs and error rates in the test phase between trials that require an item-specific response switch and an item-specific response repetition (S-R effect) to determine a DF effect based on the remember/forget cues. In other words, we will measure the strength of item-specific S-R effects for TBF as compared to TBR stimuli. If there was a DF effect on the retrieval or encoding of S-R associations, the performance differences between item-specific response repetitions and response switches (S-R effect) in the test phase (see Hypotheses section) should be smaller for TBF as compared to TBR stimuli.

Cognitive-Affective Maps (Thagard, 2010), hereafter named CAMs, represent concepts and their affective connotation on a given topic of interest. Our goal is to take a further look on how elaborating a CAM of someone other can change one’s opinion. We will measure this potential opinion change by use of modified versions of the questionnaires Technology Acceptance Model 3 (Venkatesh & Bala, 2008), Ethics Scales Inventory (Reidenbach & Robin, 1988), Positive And Negative Affect Schedule (Watson, Clark & Tellegen, 1988) and Conflict Management Scale (Austin, Gregory & Martin, 2009) and by asking subjects to draw a CAM representing their opinion.

Based on stimulus–response (S-R) associations, the presentation of a certain stimulus can automatically trigger associated responses (e.g., Henson, et al., 2014; Hommel, 1998; Logan, 1990). S-R associations are formed when stimuli and responses co-occur and thus bind together – a notion that is supported by (item-specific) repetition priming effects (see Logan, 1988, 1990). Here, participants’ responses are, for instance, generally faster for items that require the same as opposed to a different, previously not executed response. Such item-specific S-R priming effects are in turn composed of item-specific stimulus–action (S-A) priming effects and stimulus–classification (S-C) priming effects. That is, S-R associations can be divided into two components: S-A associations between stimuli and motor outputs and S-C associations between stimuli and their task-specific semantic classifications (see Hsu & Waszak, 2012; Moutsopoulou et al., 2015). These two components of S-R associations are assumed to be independent (e.g., Pfeuffer et al., 2019). S-A and S-C associations are investigated using item-specific priming paradigms (e.g., Hsu & Waszak, 2012; Moutsopoulou et al., 2015; Pfeuffer et al., 2017). Here, the classification task participants perform upon an item can either repeat or switch between its prime and probe instance (e.g., prime classification according to mechanisms; probe: classification according to size). Similarly, the required action (left vs. right key press) independently repeats or switches between prime and probe instance of a specific item. Differences in response times, RTs, and error rates between probe trials that require an item-specific action repetition versus switch and item-specific classification repetition versus switch reflect the impact of S-A and S-C associations retrieved during probe trials. That is, both influences on encoding during prime trials and influences on retrieval during probe trials may contribute to item-specific S-A and S-C priming effects. Surprisingly, no study has yet investigated whether and how the timing of the task cues (i.e., the temporal relation of stimulus and task instructions and/or corresponding processing) affects the encoding and/or retrieval of S-A and S-C associations. In a first study, we thus manipulated the timing of the task cue relative to stimulus presentation (i.e., task cue presented before, simultaneously with, or after the stimulus) during prime and probe trials. One central finding of this study was that prime task cue timing during S-A/S-C encoding affected S-A and S-C associations. Item-specific S-A and S-C priming effects in the probe trials were weakened when the task cue was presented after the stimulus as compared to when it was presented before or simultaneously with the stimulus. The present study aims to assess two contrary hypotheses regarding the mechanisms underlying this influence of prime task cue timing on item-specific S-A/S-C priming effects: Perception-Processing Overlap Hypothesis: The greater the overlap between the percept of the stimulus and the task-dependent processing of the stimulus (based on the task cue) is, the stronger is the corresponding item-specific S-A/S-C association. In the previous Experiment 1, in the prime after condition, there was no temporal overlap between the percept of the stimulus and the task-dependent processing of the stimulus. That is, the stimulus was not on-screen anymore when the task cue was presented and participants actually performed the classification task and determined the correct action. In contrast, in the prime before condition, participants were instructed about the task classification- and action-mappings information before to onset of the stimulus. Thus, task-relevant processing as well as processing of the stimulus and its perception occurred in parallel upon stimulus presentation. The same was the case for the prime condition where stimulus and task cue appeared at the same time (referred to as the prime with condition). Thus, the perception-processing overlap hypothesis can explain why item-specific S-A/S-C priming effects in the probe were reduced when task cues were presented after the stimulus in its prime trials as compared to before or with the stimulus. Pre-Classification Hypothesis: In the prime after condition, participants had to process the stimulus already before the task cue was presented. As participants did not yet know which classification would be needed, they might classify the stimulus according to both classification tasks initially, thereby associating the stimulus with both classifications and the corresponding actions (or, alternatively, they may have pre-classified the stimulus based on the prior trial’s classification task). When the task cue was subsequently presented, participants then strengthened the prepared S-A/S-C links. This resulted in observable, but still weaker item-specific S-A/S-C priming effects in the probe trial for the prime after condition. In contrast to the prime before and prime with condition in which the stimulus appeared after/with the task cue and a pre-classification was not adaptive. To distinguish between the two hypotheses, in a second experiment, we will contrast the prime with condition with several prime after conditions differing in terms of the temporal overlap of stimulus and task cue (i.e., perceptual-processing overlap). Please refer to the attached Figure in the Design Plan and Analysis Plan section for an illustration of the experimental manipulation. In all prime after conditions, we will first present the stimulus for at least a duration of 1000ms. Following this 1000ms stimulus presentation, we gradually manipulate the temporal overlap of stimulus and task cue (0, 100 ms, 300 ms, 500 ms, 1000ms). If the task cue was presented for less than 1000 ms, task cue presentation will continue after stimulus offset until the task cue was present for 1000 ms in each condition (unless participants respond beforehand). Nevertheless, participants will be instructed to respond as soon as stimulus and task cue have been presented in all conditions. The second attached Figure in the Design Plan and Analysis Plan section illustrates the predicted results that align with the tests we pre-register in the next section. The perception-processing overlap hypothesis predicts that S-C priming effects in the probe should increase with the temporal overlap of stimulus and task cue, that is the related processes. At a temporal overlap of 1000ms, the temporal overlap in the prime with and prime after condition are the same and the only difference is that the stimulus has already been presented for 1000 ms in the prime after condition. Thus, based on the perception-processing overlap hypothesis there should be no difference between the prime after and prime with condition anymore as the overlap of stimulus perception and task-related processing in the two conditions is identical. In contrast, the pre-classification hypothesis predicts that the S-C priming effects (note, that we will also investigate the S-A priming effects but focus on the S-C priming effects in the present preregistration as S-A priming effects are weaker than S-C priming effects) in the probe should not change as a function of the temporal overlap, because participants can already prepare for and associate both classifications with the stimulus during the first 1000ms of stimulus presentation in the prime after condition. Thus, the pre-classification hypothesis predicts that S-C priming effects in the probe will be reduced in the prime after as compared to prime with condition regardless of the temporal overlap of stimulus and task cue. If both assumed processes play a role, S-C priming effects should gradually increase in the prime after condition with increasing temporal overlap (perception-processing overlap hypothesis). At a temporal overlap of 1000ms, however, S-C priming effects should be weaker in the prime after condition than in the prime with condition. That is, even though perception-processing overlap is the same in the prime with and prime after overlap 1000 ms condition, participants pre-activated and associated both classifications with the stimulus during the initial 1000 ms of stimulus presentation in the prime after condition. This leads to reduced S-C priming effects as compared to the prime with condition.