Spearheading the Emotions and Memory Lab (Laboratoire Émotion et Mémoire) at the University of Geneva, Professor Ulrike Rimmele is a leading researcher on the effects of emotion and stress on learning. Professor Rimmele's work is mainly anchored in the Faculty of Psychology and Educational Sciences and the Swiss Center for Affective Sciences (CISA) at the University of Geneva, studying how emotions and stress influence lifelong learning and memory.
Dr. Rimmele employs an array of methods in her studies, including behavioral paradigms, immersive virtual reality, psychophysiological and pharmacological methods, and stimulating stressors for brain imaging to explore the intricate relationship between emotion, stress, and memory processes. Her research includes the effects of stress and socioeconomic factors on cognitive functions in older populations (Rimmele et al., 2022), focusing on the relationship between perceived stress, measured by the Perceived Stress Scale (PSS), and cognitive capacities. She explores the role of the beta-adrenergic system (the mechanism that controls the body's response to stress and exercises through adrenaline) in enhancing memory recall via emotional experiences (Rimmele et al., 2016). Her work also includes examining how suppressing cortisol during memory retrieval affects emotional memory, noting that extreme cortisol levels can impair memory due to an imbalance in mineralocorticoid receptor (MR) and glucocorticoid receptor (GR) activation (Rimmele et al., 2015).
KH: What led you to begin researching fields of emotion, stress, and their impacts on memory?
UR: For my Master’s thesis, I worked on a study where participants were administered either the stress hormone cortisol or a placebo. This was to measure cortisol’s effect on their memory recall of an emotional story. The literature exploring the connection between
emotion, stress, and learning sparked my interest in understanding the physiological mechanisms behind emotion and learning. After earning my Master’s degree in Neuroscience, I joined the Organisation for Economic Co-Operation and Development (OECD) to work on the project “Understanding the Brain: Towards a New Learning Science.” This project was divided into three networks, each with a
specific focus: literacy, numeracy, and lifelong learning. The research in each network was dedicated to exploring how insights from brain science could enhance the understanding and methods of teaching and learning in their respective areas. In addition to the initial three networks, a fourth area was identified in the project: how emotions influence learning. This was when I realized emotions' profound influence on learning and memory in numerous fields. Grasping the depth of the relationship between emotion and learning, I became aware of the potential for huge societal advancements. I then had the opportunity to conduct my postdoctoral research under the guidance of Professor Elizabeth Phelps, a globally recognized expert in the fields of emotion and memory, at New York University. Following this experience, I secured funding from the Swiss National Science Foundation, enabling me to establish my own laboratory dedicated to Emotion and Memory at the University of Geneva.
KH: Could you explain the wider potential applications of your research?
UR: My research, given the universality of emotion, stress, and learning, has applications in many fields. Currently, we aim to: 1) Contribute to building a comprehensive model of how humans construct emotional memories across the life span, bridging the separate research fields of affective and cognitive neuroscience with life span psychology. 2) Better understand the regulation processes that modulate emotional memories. 3) Investigate how existing memories can be altered in their emotional structure and content. The anticipated results will enhance our understanding of emotional and stress effects on memory and its regulation, potentially pushing the frontiers in education, healthy aging, and mental health. We hope our findings will transition from lab to clinic, improving patient outcomes. For instance, collaborating with Professor Antje Horsch and Ph.D. student Déborah Fort from the University of Lausanne, we examine how visual-spatial interventions, like playing Tetris, might change traumatic childbirth memories in mothers.
KH: How do you quantify emotional response to compare and correlate the independent and dependent variables in these studies?
UR: We quantify emotional responses by behavioral measures and physiological measures. Behavioral measures are ratings that participants provide or questionnaires that they fill out. For example, they rate stimuli on valence (negative to positive) and on arousal (calm to excited). They rate their emotional state with widely established questionnaires such as the PANAS questionnaire, which uses a 5-point scale for assessing mood, or the State-Trait Anxiety Inventory, which assesses temporary (state) and long-term (trait) levels of anxiety. Physiological measures that are used to assess emotional reactivity include skin conductance (sweat production) level, galvanic skin conductance response (electrical skin conductance changes), heart rate, heart rate variability, pupil dilation, blood pressure, cortisol levels in saliva, and brain measures such as waves obtained via electroencephalogram (EEG) and
scans from fMRI. We then do statistical tests to see how emotional responses can be linked to cognitive variables such as memory parameters. For example, our Nature Neuroscience paper showed that learning of neutral material can be enhanced after emotional material. Using skin conductance levels and multivariate and univariate brain imaging analyses, we showed that the enhanced memory encoding of neutral stimuli after emotional stimuli is accompanied by increased skin conductance levels and a shift of the brain into an emotional state.
KH: How do you simulate acute stress and various emotional states in your research studies?
UR: We are using material from databases that have been developed by researchers with the purpose of inducing emotion. For instance, several photo databases have been developed for which hundreds of participants saw the photos and rated them on several dimensions, such as pleasantness and arousal. At the University of Geneva, the Geneva Affective Picture Database (GAPD), a database containing 730 pictures, has been developed for emotion induction (Swiss Center for Affective Sciences, 2019). We also use emotional and neutral film and sound from databases. In a recent collaboration with Professor Luc Arnal, we began using human screams, which effectively induce negative emotions. Together with the Human Neuroscience Platform (HNP) at Campus Biotech, we have also developed a virtual reality in which we induce emotion in a more realistic real-life setting.
In our VR paradigm, participants see different objects in a room either paired with a loud aversive noise or with a control white noise tone. This VR paradigm is based on fear conditioning tasks, where a stimulus is typically shown, for example, a blue square, and then paired with an aversive stimulus, such as a loud sound. Then, participants typically show stronger physiological reactions to the blue square compared to a control stimulus, say, a yellow square that had never been paired with a loud sound. To induce acute stress, we also used several cognitive patterns that have been well-established in the scientific literature. For example, we used mentally challenging tasks like difficult math problems. We also have had participants give a presentation in front of an unknown audience. Stressors that include a social evaluative component most effectively induce a hormonal stress reaction.
KH: Given that there is variation in how individuals experience emotion, how have you navigated this variation in your research?
UR: Indeed, it is normal to have individual variations in the data we acquire. We can use so-called “within-subject designs” to understand whether an intervention is effectively changing an emotion. In within-subject designs, the same participants undergo two different conditions. For example, in one of our studies (Antypa et al. 2019), the participant was asked to suppress their emotion, say making a poker face, to the emotionally negative photos that we presented. In the other condition, the same participant was then asked to react normally to the emotional photos we presented. We found that arousal ratings to the emotionally negative photos were generally lower when participants made a poker face compared to when they normally reacted to the emotional photos condition. Since the data is from the same subject, the data can be compared to show the general trend in the response to the stimuli.
KH: What do you find particularly fascinating about your research?
UR: I find the interaction between mind and body fascinating. This interaction can go both ways in my research on emotion and memory. As such, I am specifically interested in the physiological and psychological mechanisms underlying emotion, learning, and memory. We can voluntarily change our physiology, which may influence our cognition and emotions. For example, breathing more slowly increases heart rate variability and may make us feel more calm. Similarly, thinking differently about a situation can decrease our negative emotions about this situation. We are currently working on studies in which we examine how different emotion regulation strategies affect not only the subjectively felt emotion but also the body's physiology and memory. We can also change physiology by giving certain medications. For example, we increased or decreased the levels of the stress hormone cortisol and then examined how this change in cortisol level affected emotion and memory.
KH: How do you deal with the language differences impacting the simulation of emotions in your studies?
UR: We use questionnaires and a mix of emotional and neutral words in our lab studies. When translating questionnaires into another language, we first translate them from English to the target language and then back to English. This ensures the translation retains the original meaning. Afterward, the translated questionnaire is validated through a study in the new language. We also use normed databases of emotional and neutral words. There are normative ratings for each word in the database from where they were created. For example, the Affective Norms for English Words (ANEW) has been created in the USA. For this database, participants were asked to rate each word for valence (negative to positive) on a scale from 1 to 9. One can use these normative ratings to create a positive, a neutral, and a negative word set. Negative words would be defined as words rated from 1 to 3. Neutral words are words that have a rating of valence of 4 to 6, and positive words have a rating between 7 to 9. We tested individual ratings in the lab to negative, neutral, and positive words and images. Typically, the individual ratings correspond well to the normative ratings. In our research, we use texts that describe an emotional and neutral story in three languages: English, French, and German. Participants in all language groups remembered more words from the emotional story than the neutral one, suggesting a potential universality, at least for these languages and texts, in conveying emotion and enhancing emotional memory. Then, of course, there are more specifics to each language and how emotions are expressed in each language that can be specific to this language and difficult to translate. To understand the impact of language differences on emotion perception, processing, and memory formation, further research and more detailed studies are needed, particularly on emotions across different languages.
KH: Finally, in light of your foremost expertise on the topic, do you have any insights for enhancing learning efficiency and retention in educational settings?
UR: In our class on “How emotion affects memory over the lifespan,” Monika Riegel, a postdoctoral fellow in my lab, and I have implemented findings of four critical elements of efficient learning strategies inspired by the AGES model of learning (Davachi et al., 2010). The AGES model by Davachi defines four critical elements of efficient learning strategies: attention, generation, emotions, and spaced learning. First and foremost, studies have shown that after approximately 20 minutes of attention and in an ideal setting, a frequent refresher (a brief activity change to improve focus) is needed over the typical lesson in most schools, ranging from 40 to 60 minutes. I would also add that despite prevalent myths that multitasking aids with productivity, research indicates it merely disrupts learning. We are especially prone to be distracted by materials of the same modality—such as two inputs both involving language processing—which can significantly disrupt our learning process. Engaging with newly presented ideas by forming your own connections, even if they're initially incorrect, has also been proven to enhance learning outcomes significantly. For example, a study (Kornell et al.) demonstrated that using eight seconds to generate a response that turns out to be wrong (i.e., knowledge generation) followed by five seconds of studying the correct response (i.e., traditional learning) produces better recall than merely studying the
correct response for the full 13 seconds. This process, called generation, also contributes to a student’s sense of agency by enhancing their sense of agency (SoA). The SoA allows a person to differentiate outcomes caused by the person themselves from those not. The agency is inherent in students’ ability to regulate, control, and monitor their own learning (Code et al., 2020). Prior research (Murty et al., 2015; Hon & Yeo, 2021; Houser et al., 2022.) has shown that the simple act of choosing can increase the individuals’ sense of agency–having control–over their learning experience and enhance declarative memory formation (a system that allows us to recall facts and events consciously).
Emotions have similarly been found to boost memory performance. In particular, emotional arousal leads to activation of the amygdala, a brain structure that is thought to modulate activity in other brain structures, such as the hippocampus. With this modulation mechanism, the memory becomes enhanced for emotional events, particularly the core information of the emotional event (McGaugh 2000). The stress hormone noradrenaline secreted in the brain plays a role in this memory-enhancing mechanism of amygdala-hippocampal modulation, leading to memory enhancement for emotionally arousing events. Another factor that enhances learning is spaced learning. While cramming prior to the exam session may help to achieve a good exam grade, a short-term effect, such a method is an inefficient, rather detrimental, learning strategy in the long term. (Hartwig & Dunlosky, 2012). In contrast, spaced repetition over time leads to higher retrieval rates of new information and builds stronger long-term memory (Litman & Davachi, 2008). Any kind of spacing learning, whether minutes, hours, or days, is better than no spacing. Another study (Cepeda et al., 2008) further shows that the longer the gap between the first and second learning session (“the gap”), the higher the retrieval rate is in the long term (1-5 years). In addition to the factors explained by the AGES model, it is crucial to emphasize how important sleep is for memory. Taking a sleep break between learning, particularly short sleep, helps memory consolidation (Tambini et al., 2010; Diekelmann and Born, 2010). It was demonstrated that during sleep periods, our memories are consolidated via a hippocampal replay and consolidated into a more general knowledge via interactions with the prefrontal cortex (Litman & Davachi, 2008).
About the Authors
Kei Hayashi (’26), Chawanvit Tangwongsiri (’26), and Buse Toksöz (’26) are currently students at Institut Le Rosey in Switzerland. Lara Ota is a first-year medical student at UMC Hamburg.
Additional Links
Emotions and Memory Lab Website: https://www.unige.ch/fapse/emotion-and-memory/
Swiss Center of Affective Sciences Website: https://www.unige.ch/cisa/
Geneva University Neurocenter on Ulrike Rimmele’s work: https://neurocenter-unige.ch/research-groups/ulrike-rimmele/
Publications by Ulrike Rimmele: https://www.researchgate.net/profile/Ulrike-Rimmele-2/2
Stress research in Switzerland: https://www.stressnetwork.ch/
References:
Dr. Rimmele employs an array of methods in her studies, including behavioral paradigms, immersive virtual reality, psychophysiological and pharmacological methods, and stimulating stressors for brain imaging to explore the intricate relationship between emotion, stress, and memory processes. Her research includes the effects of stress and socioeconomic factors on cognitive functions in older populations (Rimmele et al., 2022), focusing on the relationship between perceived stress, measured by the Perceived Stress Scale (PSS), and cognitive capacities. She explores the role of the beta-adrenergic system (the mechanism that controls the body's response to stress and exercises through adrenaline) in enhancing memory recall via emotional experiences (Rimmele et al., 2016). Her work also includes examining how suppressing cortisol during memory retrieval affects emotional memory, noting that extreme cortisol levels can impair memory due to an imbalance in mineralocorticoid receptor (MR) and glucocorticoid receptor (GR) activation (Rimmele et al., 2015).
KH: What led you to begin researching fields of emotion, stress, and their impacts on memory?
UR: For my Master’s thesis, I worked on a study where participants were administered either the stress hormone cortisol or a placebo. This was to measure cortisol’s effect on their memory recall of an emotional story. The literature exploring the connection between
emotion, stress, and learning sparked my interest in understanding the physiological mechanisms behind emotion and learning. After earning my Master’s degree in Neuroscience, I joined the Organisation for Economic Co-Operation and Development (OECD) to work on the project “Understanding the Brain: Towards a New Learning Science.” This project was divided into three networks, each with a
specific focus: literacy, numeracy, and lifelong learning. The research in each network was dedicated to exploring how insights from brain science could enhance the understanding and methods of teaching and learning in their respective areas. In addition to the initial three networks, a fourth area was identified in the project: how emotions influence learning. This was when I realized emotions' profound influence on learning and memory in numerous fields. Grasping the depth of the relationship between emotion and learning, I became aware of the potential for huge societal advancements. I then had the opportunity to conduct my postdoctoral research under the guidance of Professor Elizabeth Phelps, a globally recognized expert in the fields of emotion and memory, at New York University. Following this experience, I secured funding from the Swiss National Science Foundation, enabling me to establish my own laboratory dedicated to Emotion and Memory at the University of Geneva.
KH: Could you explain the wider potential applications of your research?
UR: My research, given the universality of emotion, stress, and learning, has applications in many fields. Currently, we aim to: 1) Contribute to building a comprehensive model of how humans construct emotional memories across the life span, bridging the separate research fields of affective and cognitive neuroscience with life span psychology. 2) Better understand the regulation processes that modulate emotional memories. 3) Investigate how existing memories can be altered in their emotional structure and content. The anticipated results will enhance our understanding of emotional and stress effects on memory and its regulation, potentially pushing the frontiers in education, healthy aging, and mental health. We hope our findings will transition from lab to clinic, improving patient outcomes. For instance, collaborating with Professor Antje Horsch and Ph.D. student Déborah Fort from the University of Lausanne, we examine how visual-spatial interventions, like playing Tetris, might change traumatic childbirth memories in mothers.
KH: How do you quantify emotional response to compare and correlate the independent and dependent variables in these studies?
UR: We quantify emotional responses by behavioral measures and physiological measures. Behavioral measures are ratings that participants provide or questionnaires that they fill out. For example, they rate stimuli on valence (negative to positive) and on arousal (calm to excited). They rate their emotional state with widely established questionnaires such as the PANAS questionnaire, which uses a 5-point scale for assessing mood, or the State-Trait Anxiety Inventory, which assesses temporary (state) and long-term (trait) levels of anxiety. Physiological measures that are used to assess emotional reactivity include skin conductance (sweat production) level, galvanic skin conductance response (electrical skin conductance changes), heart rate, heart rate variability, pupil dilation, blood pressure, cortisol levels in saliva, and brain measures such as waves obtained via electroencephalogram (EEG) and
scans from fMRI. We then do statistical tests to see how emotional responses can be linked to cognitive variables such as memory parameters. For example, our Nature Neuroscience paper showed that learning of neutral material can be enhanced after emotional material. Using skin conductance levels and multivariate and univariate brain imaging analyses, we showed that the enhanced memory encoding of neutral stimuli after emotional stimuli is accompanied by increased skin conductance levels and a shift of the brain into an emotional state.
KH: How do you simulate acute stress and various emotional states in your research studies?
UR: We are using material from databases that have been developed by researchers with the purpose of inducing emotion. For instance, several photo databases have been developed for which hundreds of participants saw the photos and rated them on several dimensions, such as pleasantness and arousal. At the University of Geneva, the Geneva Affective Picture Database (GAPD), a database containing 730 pictures, has been developed for emotion induction (Swiss Center for Affective Sciences, 2019). We also use emotional and neutral film and sound from databases. In a recent collaboration with Professor Luc Arnal, we began using human screams, which effectively induce negative emotions. Together with the Human Neuroscience Platform (HNP) at Campus Biotech, we have also developed a virtual reality in which we induce emotion in a more realistic real-life setting.
In our VR paradigm, participants see different objects in a room either paired with a loud aversive noise or with a control white noise tone. This VR paradigm is based on fear conditioning tasks, where a stimulus is typically shown, for example, a blue square, and then paired with an aversive stimulus, such as a loud sound. Then, participants typically show stronger physiological reactions to the blue square compared to a control stimulus, say, a yellow square that had never been paired with a loud sound. To induce acute stress, we also used several cognitive patterns that have been well-established in the scientific literature. For example, we used mentally challenging tasks like difficult math problems. We also have had participants give a presentation in front of an unknown audience. Stressors that include a social evaluative component most effectively induce a hormonal stress reaction.
KH: Given that there is variation in how individuals experience emotion, how have you navigated this variation in your research?
UR: Indeed, it is normal to have individual variations in the data we acquire. We can use so-called “within-subject designs” to understand whether an intervention is effectively changing an emotion. In within-subject designs, the same participants undergo two different conditions. For example, in one of our studies (Antypa et al. 2019), the participant was asked to suppress their emotion, say making a poker face, to the emotionally negative photos that we presented. In the other condition, the same participant was then asked to react normally to the emotional photos we presented. We found that arousal ratings to the emotionally negative photos were generally lower when participants made a poker face compared to when they normally reacted to the emotional photos condition. Since the data is from the same subject, the data can be compared to show the general trend in the response to the stimuli.
KH: What do you find particularly fascinating about your research?
UR: I find the interaction between mind and body fascinating. This interaction can go both ways in my research on emotion and memory. As such, I am specifically interested in the physiological and psychological mechanisms underlying emotion, learning, and memory. We can voluntarily change our physiology, which may influence our cognition and emotions. For example, breathing more slowly increases heart rate variability and may make us feel more calm. Similarly, thinking differently about a situation can decrease our negative emotions about this situation. We are currently working on studies in which we examine how different emotion regulation strategies affect not only the subjectively felt emotion but also the body's physiology and memory. We can also change physiology by giving certain medications. For example, we increased or decreased the levels of the stress hormone cortisol and then examined how this change in cortisol level affected emotion and memory.
KH: How do you deal with the language differences impacting the simulation of emotions in your studies?
UR: We use questionnaires and a mix of emotional and neutral words in our lab studies. When translating questionnaires into another language, we first translate them from English to the target language and then back to English. This ensures the translation retains the original meaning. Afterward, the translated questionnaire is validated through a study in the new language. We also use normed databases of emotional and neutral words. There are normative ratings for each word in the database from where they were created. For example, the Affective Norms for English Words (ANEW) has been created in the USA. For this database, participants were asked to rate each word for valence (negative to positive) on a scale from 1 to 9. One can use these normative ratings to create a positive, a neutral, and a negative word set. Negative words would be defined as words rated from 1 to 3. Neutral words are words that have a rating of valence of 4 to 6, and positive words have a rating between 7 to 9. We tested individual ratings in the lab to negative, neutral, and positive words and images. Typically, the individual ratings correspond well to the normative ratings. In our research, we use texts that describe an emotional and neutral story in three languages: English, French, and German. Participants in all language groups remembered more words from the emotional story than the neutral one, suggesting a potential universality, at least for these languages and texts, in conveying emotion and enhancing emotional memory. Then, of course, there are more specifics to each language and how emotions are expressed in each language that can be specific to this language and difficult to translate. To understand the impact of language differences on emotion perception, processing, and memory formation, further research and more detailed studies are needed, particularly on emotions across different languages.
KH: Finally, in light of your foremost expertise on the topic, do you have any insights for enhancing learning efficiency and retention in educational settings?
UR: In our class on “How emotion affects memory over the lifespan,” Monika Riegel, a postdoctoral fellow in my lab, and I have implemented findings of four critical elements of efficient learning strategies inspired by the AGES model of learning (Davachi et al., 2010). The AGES model by Davachi defines four critical elements of efficient learning strategies: attention, generation, emotions, and spaced learning. First and foremost, studies have shown that after approximately 20 minutes of attention and in an ideal setting, a frequent refresher (a brief activity change to improve focus) is needed over the typical lesson in most schools, ranging from 40 to 60 minutes. I would also add that despite prevalent myths that multitasking aids with productivity, research indicates it merely disrupts learning. We are especially prone to be distracted by materials of the same modality—such as two inputs both involving language processing—which can significantly disrupt our learning process. Engaging with newly presented ideas by forming your own connections, even if they're initially incorrect, has also been proven to enhance learning outcomes significantly. For example, a study (Kornell et al.) demonstrated that using eight seconds to generate a response that turns out to be wrong (i.e., knowledge generation) followed by five seconds of studying the correct response (i.e., traditional learning) produces better recall than merely studying the
correct response for the full 13 seconds. This process, called generation, also contributes to a student’s sense of agency by enhancing their sense of agency (SoA). The SoA allows a person to differentiate outcomes caused by the person themselves from those not. The agency is inherent in students’ ability to regulate, control, and monitor their own learning (Code et al., 2020). Prior research (Murty et al., 2015; Hon & Yeo, 2021; Houser et al., 2022.) has shown that the simple act of choosing can increase the individuals’ sense of agency–having control–over their learning experience and enhance declarative memory formation (a system that allows us to recall facts and events consciously).
Emotions have similarly been found to boost memory performance. In particular, emotional arousal leads to activation of the amygdala, a brain structure that is thought to modulate activity in other brain structures, such as the hippocampus. With this modulation mechanism, the memory becomes enhanced for emotional events, particularly the core information of the emotional event (McGaugh 2000). The stress hormone noradrenaline secreted in the brain plays a role in this memory-enhancing mechanism of amygdala-hippocampal modulation, leading to memory enhancement for emotionally arousing events. Another factor that enhances learning is spaced learning. While cramming prior to the exam session may help to achieve a good exam grade, a short-term effect, such a method is an inefficient, rather detrimental, learning strategy in the long term. (Hartwig & Dunlosky, 2012). In contrast, spaced repetition over time leads to higher retrieval rates of new information and builds stronger long-term memory (Litman & Davachi, 2008). Any kind of spacing learning, whether minutes, hours, or days, is better than no spacing. Another study (Cepeda et al., 2008) further shows that the longer the gap between the first and second learning session (“the gap”), the higher the retrieval rate is in the long term (1-5 years). In addition to the factors explained by the AGES model, it is crucial to emphasize how important sleep is for memory. Taking a sleep break between learning, particularly short sleep, helps memory consolidation (Tambini et al., 2010; Diekelmann and Born, 2010). It was demonstrated that during sleep periods, our memories are consolidated via a hippocampal replay and consolidated into a more general knowledge via interactions with the prefrontal cortex (Litman & Davachi, 2008).
About the Authors
Kei Hayashi (’26), Chawanvit Tangwongsiri (’26), and Buse Toksöz (’26) are currently students at Institut Le Rosey in Switzerland. Lara Ota is a first-year medical student at UMC Hamburg.
Additional Links
Emotions and Memory Lab Website: https://www.unige.ch/fapse/emotion-and-memory/
Swiss Center of Affective Sciences Website: https://www.unige.ch/cisa/
Geneva University Neurocenter on Ulrike Rimmele’s work: https://neurocenter-unige.ch/research-groups/ulrike-rimmele/
Publications by Ulrike Rimmele: https://www.researchgate.net/profile/Ulrike-Rimmele-2/2
Stress research in Switzerland: https://www.stressnetwork.ch/
References:
- Rimmele, U., Ballhausen, N., Ihle, A., & Kliegel, M. (2022). In Older Adults, Perceived Stress and Self-Efficacy Are Associated with Verbal Fluency, Reasoning, and Prospective Memory (Moderated by Socioeconomic Position). Brain sciences, 12(2), 244. https://doi.org/10.3390/brainsci12020244
- Rimmele, U., Lackovic, S. F., Tobe, R. H., Leventhal, B. L., & Phelps, E. A. (2016, June 28). Beta-adrenergic blockade at memory encoding, but not retrieval, decreases the subjective sense of recollection. Journal of Cognitive Neuroscience. https://pubmed.ncbi.nlm.nih.gov/26942318
- Rimmele, U., Besedovsky, L., Lange, T., & Born, J. (2015, February 11). Emotional memory can be persistently weakened by suppressing cortisol during retrieval. Neurobiology of Learning and Memory https://pubmed.ncbi.nlm.nih.gov/25680817/
- Swiss Center for Affective Sciences. (2019, February 20). University of Geneva. https://www.unige.ch/cisa/research/materials-and-online-research/research-material/
- Antypa, D., Cabrita, M. D. R., Vuilleumier, P., & Rimmele, U. (2019, April 9). Cortisol suppression after memory reactivation impairs later memory performance. Psychoneuroendocrinology. https://www.sciencedirect.com/science/article/abs/pii/S0306453018312381
- Davachi, L., Kiefer, T., Rock, D., & Rock, L. (2010). Learning that lasts through AGES. NeuroLeadership Journal, (3).
- Kornell, N., Hays, M. J., & Bjork, R. A. (2009). Unsuccessful retrieval attempts enhance subsequent learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(4), 989–998. https://doi.org/10.1037/a0015729
- Code, J. (2020). Agency for Learning: Intention, Motivation, Self-Efficacy, and Self-Regulation. Frontiers in Education, 5(19). https://doi.org/10.3389/feduc.2020.00019
- Murty, V. P., DuBrow, S., & Davachi, L. (2015). The Simple Act of Choosing Influences Declarative Memory. Journal of Neuroscience, 35(16), 6255-6264. https://doi.org/10.1523/JNEUROSCI.4181-14.2015
- Hon, N., & Yeo, N. (2021). Having a sense of agency can improve memory. Psychonomic Bulletin & Review, 28, 946–952. https://doi.org/10.3758/s13423-020-01849-x
- Houser, T. M., Tompary, A., & Murty, V. P. (2022). Agency enhances temporal order memory in an interactive exploration game. Psychonomic Bulletin & Review, 29, 2219–2228. https://doi.org/10.3758/s13423-022-02152-7
- McGaugh, J. L. (2004). The amygdala modulates the consolidation of memories of emotionally arousing experiences. Annual Review of Neuroscience, 27, 1-28. https://doi.org/10.1146/annurev.neuro.27.070203.144157
- Hartwig, M. K., & Dunlosky, J. (2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19, 126–134. https://doi.org/10.3758/s13423-011-0181-y
- Litman, L., & Davachi, L. (2008). Distributed learning enhances relational memory consolidation. Learning & Memory, 15, 711-716. http://www.learnmem.org/cgi/doi/10.1101/lm.1132008
- Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline. Psychological Science, 19(11), 1095-1102. https://journals.sagepub.com/doi/abs/10.1111/j.1467-9280.2008.02209.x
- Tambini, A., Ketz, N., & Davachi, L. (2010). Enhanced brain correlations during rest are related to memory for recent experiences. Neuron, 65(2), 280-290. https://doi.org/10.1016/j.neuron.2010.01.001
- Diekelmann, S., & Born, J. (2010). The memory function of sleep. Nature Reviews Neuroscience, 11,114-126.
