limbic part of the brain conditions the body to be chemically trained to follow the mind in the process of understanding. This reptilian brain turns an experience into an emotional signature, influencing or even determining the decision-making process. As a result of studies in the field of neuromarketing, scientists have found that understanding the patterns and reactions in the subconscious mind of the customer, provides the key to how purchasing decisions are made. The study of the mechanisms of influencing the buyer determined a fusion between marketing, behavioral economics, neuroscience, social psychology and medical technologies, learning mechanisms, thus resulting in neuromarketing. The development of brain imaging technologies and their application beyond the medical sphere, has made possible new perspectives for researching consumer behavior. After the emergence of cognitive and social neurosciences, neuroeconomics was configured to analyze the decision-making process by studying cognitive patterns, neural patterns. (Egidi, G., 2008, pp. 73-76). Given these, new research indicates that the decision-making process does not occur at the conscious level, and the theory that consumers make decisions that maximize their own interests, based on reason, can no longer be supported. In this context, the emergence of neuromarketing occurs as a complement to the discoveries of neuroeconomics, in order to use neuroimaging investigation techniques for market research. Neuromarketing is the application of information and techniques from psychology and neuroscience in the field of marketing in order to research and examine brain activity in response to consumer behavior and decisions. Typical neuromarketing research activities include the direct use of brain imaging, scanning, or other brain activity measurement technologies to observe the consumer's response to certain elements of the product, such as packaging, brand, message, or advertising. The main objective of neuromarketing is to capitalize on the cognitive prejudices of a target audience to convince them to buy, potential buyers being triggered by consumer behavior by using a set of techniques in the field of psychology. ---------- https://sam.gov/opp/d005c5b47a5849d0a130a44e19f0bb86/view Reengineering Enabling Sleep Transitions in Operationally Restrictive Environments (RESTORE) Inactive Contract Opportunity Notice ID HR001125S0012 Related Notice Department/Ind. Agency DEPT OF DEFENSE Sub-tier DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA) Office DEF ADVANCED RESEARCH PROJECTS AGCY Classification Original Set Aside: Product Service Code: AC11 - NATIONAL DEFENSE R&D SERVICES; DEPARTMENT OF DEFENSE - MILITARY; BASIC RESEARCH NAICS Code: 541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology) Place of Performance: Description The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals that leverage emerging neuromodulation technologies to enhance sleep efficiency and performance under sleep-restricted conditions. The Reengineering Enabling Sleep Transitions in Operationally Restrictive Environments (RESTORE) program aims to develop multimodal, multitarget, noninvasive neuromodulation methods to repair disrupted sleep architectures caused by sleep restriction, with the ultimate goal of improving cognitive performance. Proposed research should investigate innovative approaches that enable revolutionary advances in the mechanisms of sleep related to performance psychology. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice. -------- https://www.researchgate.net/publication/398981151_Targeted_dream_incubation_at_a_distance_the_development_of_a_remote_and_sensor-free_tool_for_incubating_hypnagogic_dreams_and_mind-wandering Targeted dream incubation at a distance: the development of a remote and sensor-free tool for incubating hypnagogic dreams and mind-wandering May 2024Frontiers in Sleep 3:1258345 DOI:10.3389/frsle.2024.1258345 Authors: Lucas Bellaiche Adam Haar Horowitz Mason McClay Ryan Bottary Dan Denis Christina Chen Pattie Maes Paul Seli --------------- https://watermark02.silverchair.com/zpaf013.pdf Original Article Targeted dream incubation and dream self-efficacy Westley A. Youngren1,*,†, , Adam Haar Horowitz2,3,†, Victoria West Staples1, Michelle Carr4, Robert Stickgold3,5 and Pattie Maes2 1Department of Psychology and Counseling, University of Missouri, Kansas City, MO, USA, 2MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA, 3Center for Sleep and Cognition, Beth Israel Deaconess Medical Center, Boston, MA, USA, 4Department of Psychiatry and Addictology, University of Montreal, Montreal, QC, Canada and 5Department of Psychiatry, Harvard Medical School, Boston, MA, USA *Corresponding author. Westley A. Youngren, Department of Psychology and Counseling, University of Missouri, Kansas City, 1512 East 15th Street, Lawrence KS 66044, USA. Email: YoungrenWA@gmail.com. †These authors equally contributed to the work. This article is part of the Festschrift in honor of Dr. Robert Stickgold Collection. Abstract This preliminary study investigates the potential for a technique that enables purposeful guiding of dream content (Targeted Dream Incubation; TDI) to change the degree to which an individual feels in control of their dreams (Dream Self-Efficacy; DSE). DSE is a sub- set of a larger concept of self-efficacy relating to one’s belief in their own abilities and competencies. Examining DSE may be quite important, as past research has demonstrated that DSE may be linked to positive treatment outcomes in specific therapies, such as interventions for trauma-related nightmares. Furthermore, prior research has found that decreasing feelings of helplessness related to sleep has been shown to improve insomnia symptoms and daytime fatigue. Thus, our study sought to examine the relationship between TDI and DSE. We enrolled N = 25 participants in a TDI protocol conducted during a predominantly N1 sleep nap, where participants completed surveys before and after a TDI paradigm. Our results revealed that TDI was linked to DSE, with individuals reporting significantly higher levels of DSE after the TDI protocol. These results provide preliminary evidence for a technique (TDI) that could increase DSE with the overall aim of improving the efficacy of specific sleep-related interventions, such as treatments for trauma-related nightmares. Future research should aim to further confirm these results with a control condition and examine the effects of TDI within the context of behavioral sleep interventions. Key words: dreaming; targeted dream incubation; self-efficacy Statement of Significance This manuscript provides the first evidence that a novel sleep paradigm (Targeted Dream Incubation; TDI) may lead to increases in Dream Self-Efficacy (DSE), even within a sample that experiences frequent nightmares. These preliminary results are signifi- cant because past research has demonstrated that perceptions of self-efficacy directly impact treatment success and adherence, especially in interventions that target sleep-related disorders, such as Cognitive behavioral Therapy for Insomnia. Additionally, the results of this paper provide further meaning, as they provide rationale for future studies to further explore the relationship between the TDI protocol and DSE. In sum, the results of this manuscript provide novel findings that may be able to impact sleep-related treatments. Trauma-related nightmares (TRNs) are one of the most distress- ing and treatment-resistant features of posttraumatic stress disorder (PTSD), with intensely negative dream content caus- ing debilitating daytime stress [1]. Furthermore, TRNs are quite problematic clinically, having been linked to substance abuse, depression, suicide, and many other negative outcomes [1, 2]. The leading TRNs treatments are rescripting-based therapies, such as Imagery Rehearsal Therapy (IRT) and Exposure, Relaxation, and Rescripting Therapy (ERRT). Rescripting therapies focus primarily on behavioral sleep practices (such as sleep hygiene and stimulus control) and nightmare rescription (the process of rewriting a nightmare into a changed version of the dream and then reading/rehearsing this new version throughout the day and prior to falling asleep --------- herapies such as IRT [6]. With evidence of varying levels of effec- tiveness, research is needed in order to improve the efficacy of rescripting-oriented therapies, with the overall goal of reducing the effects of TRNs. Dream self-efficacy One particular mechanism that could impact response to rescripting-based therapies is patient confidence in their ability to have control and mastery over their dream content, also referred to as dream self-efficacy (DSE). DSE was first demonstrated by Miller et al., who reported that after a successful completion of a rescripting therapy, individuals’ internal self-efficacy (belief that one has control over what happens) centered around their dreams significantly increased [7]. This aligns with results from Rousseau et al. who demonstrated a significant relationship between night- mare reductions following IRT and an increase in perceived mas- tery over their dreams [6]. According to Rousseau, “The most frequently cited mechanism of action for IRT’s effectiveness was an increased sense of mastery. Sense of mastery is defined as the conviction patients have that they can control their dreams and nightmares; this feeling would be gained through concrete experiences of control” [6]. Additionally, Rousseau reported that dropout from IRT was often related to the client’s belief that they could not actually control or rescript elements of a dream. In addition to the link between rescripting therapies and DSE, prior research has reported that insomnia severity, dysfunctional beliefs about sleep, and depressive symptoms are all negatively correlated with one’s belief in their mastery of sleep [8]. There is also evidence that self-efficacy centered around sleep is neg- atively correlated with anxiety symptoms and positively corre- lated with subjective sleep quality [9]. Furthermore, it has been reported that perceived lack of control over nocturnal thoughts and lack of control over sleep are related to higher insomnia symptoms [10]. Aligned with this idea, alteration of small details in an otherwise traumatic dream, giving participants a sense of control over the dream state, has been shown to alleviate repeti- tive nightmares in a small case study [11]. Lastly, in veteran pop- ulations, reducing feelings of helplessness related to sleep has been shown to improve insomnia symptoms and daytime fatigue [12]. This background research provides ample evidence support- ing the idea that improving a subject’s sense of control and mas- tery over their sleep and dreaming could impact the effectiveness of rescripting-based therapies. Targeted dream incubation and DSE Importantly, it should be noted that situation-specific self-efficacy (e.g. mastery over work, control over health) is not considered trait-like and stable but instead can change with new experi- ences [13]. When considering ways to change DSE, one potential method could be targeted dream incubation (TDI). TDI is a tech- nique that induces dreams during sleep onset that incorporate targeted information, repeatedly presenting audio cues contain- ing the targeted information, which is then incubated during the sleep onset hypnagogic period and incorporated into dreams. TDI research has demonstrated that a high percentage of subjects (up to 92 per cent) report dreaming of the cued subject while under- going the incubation protocol [13, 14]. Considering these results, it is possible that TDI could be a technique used to increase DSE via concrete experiences of dream control. With the aforementioned in mind, our key aim was to pro- vide preliminary evidence on the relationship between TDI and DSE, with the ultimate goal as serving as pilot data for future more in-depth explorations between said variables. Specifically, we investigate whether firsthand experience of TDI is related to higher ratings on scales of DSE. If TDI is in fact successful at mod- ulating DSE, it could be used to modulate sleep-related beliefs before rescripting-oriented treatment begins and hopefully improve clinical outcomes. Materials and methods Participants We enrolled N = 28 participants (M age = 31.55, SD = 16.37) to participate in a daytime napping study. Gender composition of our sample was nearly equally split (female, n = 13; 52 per cent & male, n = 12; 48 per cent). Nearly half of our sample (n = 11; 44 per cent) reported frequent nightmares (ranging from 1 to 7 nightmares per week). Protocol Potential participants were recruited via virtual and hard- copy advertisements. Before participating, all candidates were screened for inclusion and exclusion criteria (inclusion: being 18 years old or older; exclusion: not experiencing a current psychotic episode and not currently taking any sleep medications). Once screened, participants arrived at the laboratory in the afternoon between the hours of 12:00 pm and 04:00 pm, optimizing for the postprandial increase in sleepiness. All participants were told the experiment investigated the relationship between rest and cogni- tive flexibility. After reading and signing consent forms, subjects completed an online battery of questionnaires. All subjects were then asked to put on a sleep mask, the Dormio headworn sys- tem, and the Hypnodyne ZMax EEG before lying down and being asked to fall asleep [15]. Subjects were given a 1-h sleep oppor- tunity. Once sleep onset occurred, participants were awakened after 2 epochs of visually scored N1 sleep. During each wakeup, the Dormio device triggered prerecorded audio prompts that requested and then recorded a verbal dream report from the subject. Once subjects finished speaking, the system asked about their sleep state (“And were you asleep?”), to which subjects had been previously instructed to respond “Awake,” “Halfway” or “Asleep.” Participants were then instructed to “remember to think of a tree” and go back to sleep. After the sleep opportunity, dream reports were confirmed via self-reported confirmations, following methods from Horowitz and Horowitz [14, 16]. Ten minutes after their last verbal report, all subjects completed another battery of questionnaires. Upon completion of these surveys, subjects were instructed to keep and submit a dream journal for 1 week and completed another battery of questionnaires after 1 week. Subjects completed a collection of assessments at four-time points relative to the study: (1) during recruitment for the study, (2) immediately prior to TDI, (3) directly after TDI, and (4) 1 week after TDI. We refer to these four-time points as “recruitment,” “pre-TDI,” “post-TDI” and “one-week post-TDI” in our analysis. TDI methods During the TDI protocol, all subjects underwent a prompted hypna- gogic nap, using auditory incubation delivered via the Dormio system to incubate the chosen dream theme (“tree”). Upon lying down, the Downloaded from https://academic.oup.com/sleepadvances/article/6/2/zpaf013/8063926 by guest on 10 January 2026 Youngren et al. | 3 Dormio instructed participants to “think of a tree.” Once entry into hypnagogia was determined (immediately after two epochs of vis- ually scored N1 sleep was detected), the Dormio alerted participants they were falling asleep (“You’re falling asleep”), asked participants to verbally report the thoughts they were currently having (“Please tell me, what’s going through your mind”), and recorded their verbal response. The system then instructed them to think of the dream prompt (“Remember to think of a tree”) and to go back to sleep (“You can fall back asleep now”). This loop of events was repeated for a total experiment time of 1 h, facilitating multiple entrances to and exits from N1 (although other stages of sleep may have been experi- enced). At the end of the last loop, the experimenter instructed the participant to wake up fully. TDI methods based on Horowitz and Horowitz et al. [14, 17]. Measures Sleep staging. Sleep was scored using a Hypnodyne ZMax EEG. Hypnodyne streams two EEG channels, F7 and F8, both referenced to Fpz. Performance evaluations of the Zmax relative to polysomnogra- phy indicate acceptable levels of sensitivity (68.3 per cent) and inter-rater reliability (Cohen’s Kappa = 57.3; with some limita- tions on staging due to lack of occipital channels) [15, 17]. Visual scoring of N1 sleep was done according to the AASM Manual for Sleep Scoring [18]. Epochs of 30s were used, and awakenings were done after two subsequent epochs of N1 sleep were scored. Assessing incubation. For the purposes of assessing incubation, a direct reference to “tree” is defined as an unambiguous mention of any part of a tree (including tree, forest, branch, or root) while indirect references included sensations, objects, locations, or themes related to “tree” (such as plant, bush, or other tree-like objects), adapting methods from Wamsley and Horowitz [17, 19]. Dream self-efficacy. To assess DSE related to dream content, we used a DSE ques- tionnaire adapted in past research to assess self-efficacy related to dreaming [6]. Both a composite DSE score and two individual items “To what extent do you feel able to control the content of your dreams?” and “When it comes to bad dreams, what will be will be; they are out of my control.” were examined to determine which specific aspects of DSE are impacted. Nightmare frequency. The frequency of nightmares was assessed by the Nightmare Frequency Questionnaire (NFQ) and nightmare-related distress was assessed via the Nightmare Distress Questionnaire (NDQ) [17, 20]. The NFQ is a 3-item self-report questionnaire that gauges the frequency of nightmare occurrences, while the NDQ is a 13-item self-report scale that assesses distress caused by night- mares [20, 21]. Dream journal. After the TDI protocol, participants were asked to keep an elec- tronic dream journal. Participants were asked to write (electroni- cally) down their dreams in a journal each morning immediately after awakening. After writing their dream(s) they were then asked to report if the dreams were related to a “tree” in any way. After completing the journal for a week, participants copy and pasted the contents of their dream journal into the electronically sent survey (that included the 1-week postsurvey battery). Analyses Descriptive analyses were used to examine sample characteris- tics, as well as percentage of successful dream incubation (for total TDI sessions, not individual attempts). Using linear regres- sions, success of incubations will be examined as a predictor of changes in DSE following TDI (both immediately and 1-week follow-up). In order to examine our primary aim (the effect of TDI on DSE) one-way repeated measure ANOVA analyses were used (while controlling for gender and age differences) to examine the differences in DSE scores across three time-points (pre-TDI, post-TDI, 1-week post-TDI). To further examine what aspects of DSE were being impacted, when examining DSE pre-TDI, post- TDI, and 1-week post-TDI we examined both a composite DSE score and from the two aforementioned individual items. Lastly, pairwise comparison analyses were used to examine differences in DSE scores between different time points. For post hoc analy- ses, nonparametric analyses were used to examine participants who reported frequent nightmares and participants who did not report frequent nightmares (all while controlling for gender and age differences). Results Dream incorporation Three subjects were excluded from analyses for failure to fall asleep. Of the 25 participants included in the analysis, 23 of them (92 per cent) reported at least one direct incorporation of the theme “Tree” during N1 sleep. On average, participants reported 1.96 incorporations in 4.83 N1 episodes during the 1-h nap; 40.6 per cent of awakenings were accompanied by direct incorpora- tions of a tree into a dream report. Of the 25 participants included in the analysis, 10 (42 per cent) reported direct incorporation in the week following TDI (assessed via dream journal reports). This success rate is similar to past studies using the Dormio [14, 16, 22]. Primary analyses Results showed that the time relative to the period of TDI (pre- TDI, post-TDI, and 1-week post-TDI) led to statistically significant differences in DSE responses (F (2, 46) = 5.31, p = .008). Analyses indicated a significant increase in DSE composite responses imme- diately after the period of TDI (pre-TDI vs. post-TDI; DSE = 1.02; p = .003; Figure 1), with no further significant change in responses 1 week later (post-TDI vs 1 week later, p = .86). Additionally, we found a significant difference between pre-TDI and 1-week post- TDI in the DSE composite score (μ = 0.50, p = .042). However, we did not find a significant difference between the pre-TDI and 1-week post-TDI with either of the individual items (p > .05). For differences on individual DSE items between pre, post, and 1-week post-TDI see Figures 2 and 3. Post hoc analyses demonstrate that the effect of TDI on DSE correlates with the degree of direct incorporation of incubation themes into dreams, wherein more effective incubation increases postsleep DSE incrementally. The degree of success of the TDI pro- tocol is predictive of the change in DSE from the pre-TDI period to both immediately after the TDI period (β = 0.6, p < .05, R2 = 0.19) and 1-week following the TDI period (β = 0.35, p < .05, R2 = 0.12). Nightmares Subjects reporting a nightmare frequency of ≥1 nightmare/week at recruitment (n = 11) did not have any significant differences Downloaded from https://academic.oup.com/sleepadvances/article/6/2/zpaf013/8063926 by guest on 10 January 2026 ----------- https://www.researchgate.net/publication/389686563_Targeted_dream_incubation_and_dream_self-efficacy Targeted dream incubation and dream self-efficacy March 2025SLEEP Advances 6(2) DOI:10.1093/sleepadvances/zpaf013 LicenseCC BY-NC-ND 4.0 Authors: Westley A Youngren Adam Haar Horowitz Massachusetts Institute of Technology Victoria West Staples Michelle Carr This preliminary study investigates the potential for a technique that enables purposeful guiding of dream content (Targeted Dream Incubation; TDI) to change the degree to which an individual feels in control of their dreams (Dream Self-Efficacy; DSE). DSE is a subset of a larger concept of self-efficacy relating to one’s belief in their own abilities and competencies. Examining DSE may be quite important, as past research has demonstrated that DSE may be linked to positive treatment outcomes in specific therapies, such as interventions for trauma-related nightmares. Furthermore, prior research has found that decreasing feelings of helplessness related to sleep has been shown to improve insomnia symptoms and daytime fatigue. Thus, our study sought to examine the relationship between TDI and DSE. We enrolled N = 25 participants in a TDI protocol conducted during a predominantly N1 sleep nap, where participants completed surveys before and after a TDI paradigm. Our results revealed that TDI was linked to DSE, with individuals reporting significantly higher levels of DSE after the TDI protocol. These results provide preliminary evidence for a technique (TDI) that could increase DSE with the overall aim of improving the efficacy of specific sleep-related interventions, such as treatments for trauma-related nightmares. Future research should aim to further confirm these results with a control condition and examine the effects of TDI within the context of behavioral sleep interventions. -------- https://esrs.eu/news/sleep-science-friday/early-career-network-age-of-technology/ Early Career Network Committee 2024-2026: Sleep in the Age of Technology ByESRS 17 January 2025 Picture of Dr. Adriana Michalak Dr. Adriana Michalak Postdoctoral Fellow in Dream Engineering at the IMT School for Advanced Studies Lucca, Italy. Chair & Board Representative of Early Career Network (ECN). Vice-Chair of Gender Equality Forum (GEF). More on LinkedIn. 2024-2026 Vision of the Early Career Network We, the members of the Early Career Network (ECN), are excited to present our 2024-2026 theme, ‘Sleep in the Age of Technology’. Our goal is to explore how technological advancements can enhance sleep research and clinical practice, while also considering the ethical use of Artificial Intelligence (AI) and its relationship to sustainability. Stay tuned for webinars, interviews, and journal clubs on this timely topic! Technological Innovations in Sleep Medical-grade AI-driven examinations and wearable devices are transforming sleep medicine by enabling faster diagnosis and personalized treatments. Future advancements, such as integrating AI with home-based monitoring systems, could further revolutionize sleep research and longitudinal health data acquisition, providing better insights into chronic conditions, lifestyle factors, and long-term health trends. Alongside this, the rise of non-medical apps and devices, like sleep trackers, raises questions about their effectiveness and potential risks, such as orthosomnia—an unhealthy fixation on perfecting sleep data that can actually worsen sleep quality. Which commercial tools are genuinely effective, and which are simply clever marketing tactics designed to capitalize on customer data? A dialogue between technology experts, the scientific community, clinicians and consumers is essential to enhance societal technological literacy. We look forward to addressing the benefits and pitfalls of current technological advancements in clinical and non-clinical sleep research during our ‘Sleep in the Age of Technology’ webinar series. Let’s Keep Together for a Sustainable Future Building on the efforts of the ECN Committee 2022-2024, we will continue to focus on sustainability, particularly within the context of AI. Further advancements in AI and sleep research requires a well-planned approach, rather than an over-reliance on increasingly larger models, that come with a significant environmental footprint, including high energy consumption and water usage for cooling systems. Therefore, if you are an AI expert in sleep research, we encourage you to report the CO₂ impact and energy consumption associated with training new models to help acknowledge and mitigate their environmental costs. Our Network for Early Career Sleep Researchers and Clinicians In celebration of the ECN’s 11th anniversary, we continue to strengthen our peer network of early-career sleep researchers and clinicians, believing that collaboration and support can lead to greater success and advancement within the field. We aim to engage with you through our social media channels to get to know you better! Our goal is to make the ECN LinkedIn group along with our LinkedIn and BlueSky profiles a friendly space for networking, sharing ideas, and celebrating our shared passion for sleep research. Sleep in the Age of Technology Without further ado, we are activating our neural networks to deliver great content related to Sleep in the Age of Technology, optimized for technological awareness and ethical considerations, engineered with sustainability at its core—all powered by the best speakers!# With best wishes, Adriana, Anna, Lieve, Laura, Matias, Michaela & Monisha, Your Early Career Network Committee 2024-2026 ----------- ESRS Reminders 2025 eSleep Congress Registration for the Public Health Track is now available Register Today 2025_Sleep Medicine_Open for Application ESRS Sleep Medicine Examination Only 2 weeks left to apply Apply now 2025 Sleep and Breathing Register by 27 January, 2025 for the early-bird discounted fee. Register Now Order Sleep Medicine Textbook Recent publications from ESRS members Jones-Tabah et al (2024),The Parkinson’s disease risk gene cathepsin B promotes fibrillar alpha-synuclein clearance, lysosomal function and glucocerebrosidase activity in dopaminergic neurons. Mol Neurodegener -====== https://pmc.ncbi.nlm.nih.gov/articles/PMC11239541/ Frontiers in Psychiatry logo Front Psychiatry . 2024 Jun 28;15:1413961. doi: 10.3389/fpsyt.2024.1413961 Effects of transcranial magnetic stimulation on sleep structure and quality in children with autism Juan Yan 1, Yan Zhang 2,*, Junjie Wang 1, Guidong Zhu 2, Kaijie Fang 1 PMCID: PMC11239541 PMID: 39006818 Abstract Introduction Sleep disorders are common in children with autism spectrum disorder (ASD). Transcranial magnetic stimulation (TMS) can influence the excitability of neuronal cells in stimulated areas, leading to improvements in sleep and other autistic symptoms. However, studies on clinical mechanisms of TMS in treating sleep disorders associated with ASD are limited. Therefore, we aimed to explore the effects of TMS on sleep structure and quality in children with ASD. Methods Between January 2020 and December 2021, recruitment was advertised through child and adolescent outpatient clinics and online platforms by the Hangzhou Seventh People’s Hospital and Lishui Second People’s Hospital. Sixty children with ASD who met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, were selected and randomly divided into the active TMS and sham TMS treatment groups. Thirty healthy children of the same age were recruited as controls. The active TMS group received bilateral low-frequency (0.5 Hz) TMS targeting the dorsolateral prefrontal cortex on both sides in children with ASD, whereas the sham TMS group received sham stimulation with the same stimulation time and location as the experimental group. Both groups were treated for 6 weeks, and the participants were assessed using the Sleep Disturbance Scale for Children (SDSC) before treatment, at 3 weeks, and at 6 weeks of intervention. Independent sample t-tests and difference t-tests were used for statistical analysis of the data. Results No significant differences were observed in general demographic variables, such as age and sex, between the ASD and control groups (P>0.05). Independent sample t-test analysis showed that the total SDSC score, difficulty falling asleep, sleep maintenance, awakening disorders, sleep-wake transition disorders, excessive daytime sleepiness, and nocturnal hyperhidrosis scores were significantly higher in the ASD group than in the control group (P<0.05). Before treatment, no significant differences were observed in the factor or total SDSC scores between the sham TMS group and the active TMS group (P>0.05). After 15 and 30 treatment sessions, the total SDSC score, difficulty falling asleep, sleep maintenance, sleep-wake transition disorders, and excessive daytime sleepiness scores were significantly higher in the sham TMS group than in the active TMS group (P<0.05). The difference t-test analysis showed that after 30 treatment sessions, the reduction rates of the total SDSC score, difficulty falling asleep, sleep maintenance, awakening disorders, sleep-wake transition disorders, excessive daytime sleepiness, and nocturnal hyperhidrosis dimensions were significantly higher in the active TMS group than in the sham TMS group (P<0.05). ------------- https://esrs.eu/news/sleep-science-friday/targeted-memory-reactivation-during-sleep/ Targeted memory reactivation during sleep ByESRS 30 August 2024 Picture of Dr. Rebeca Sifuentes Ortega Dr. Rebeca Sifuentes Ortega Affiliated with the Neuropsychology and Functional Neuroimaging Research Unit (UR2NF) at the Université Libre de Bruxelles, Belgium. She recently completed her PhD, which focused on sensory information processing and memory consolidation during sleep. More on Research Gate Does targeted memory reactivation during slow-wave sleep and rapid eye movement sleep have differential effects on mnemonic discrimination and generalization? In the following interview, Rebeca Sifuentes Ortega will discuss her latest research, which she co-authored (as lead author), entitled “Does targeted memory reactivation during slow-wave sleep and rapid eye movement sleep have differential effects on mnemonic discrimination and generalization?”. 1. The current study has focused on the targeted memory reactivation and its implications for memory performance in different sleep stages. How would you define TMR? Targeted Memory Reactivation, or TMR, is a technique based on the observation that learning-related patterns of neuronal activity spontaneously reactivate during sleep. This natural process is believed to aid in the stabilization and integration of memories into long-term storage. TMR builds on this concept by creating associations between specific sensory cues—like sounds, smells, or words— and learning material while participants are awake. Then, these cues, or reminders, are presented again during sleep without waking the person, potentially leading to improved memory performance for the cued associations during a post-sleep test. The idea behind TMR is that by reactivating these memory traces during sleep, we can influence how effectively these memories are consolidated or transformed in the brain. For instance, research has shown that using TMR during non-REM sleep stages N2 and N3 can effectively modify memory consolidation processes, resulting in improved post-sleep memory performance, although the effects are generally small to moderate. 2. What were the hypotheses addressed in this research? Could you describe the aim of your study and main objectives? Our study aimed to investigate whether TMR has different effects on memory depending on whether it is applied during SWS or REM sleep. Specifically, we wanted to see if TMR during these different sleep stages would influence two key memory processes: mnemonic discrimination (the ability to distinguish between very similar items) and memory generalization (the ability to extract commonalities across items in a semantic category). Our objective was to understand if these processes are uniquely supported by different stages of sleep, providing insights into how sleep contributes to memory transformation. We had two main hypotheses. First, based on the well-established effect of non-REM TMR to improve memory consolidation, we hypothesized that TMR during SWS would strengthen specific memory traces. In other words, we expected participants to have better recall of details and more precise memory discrimination for category items linked to the cues replayed during this state (these items were pictures of objects from distinct semantic categories). Second, considering some evidence that REM TMR may promote memory generalization, we hypothesized that reactivating a subset of learned categories during REM sleep would lead participants to better generalize across similar, but previously unseen, items at the expense of losing specific memory details. 3.TMR is considered a research tool. Portray the study design and methods. Forty-eight healthy adults, aged 20-35, were randomly assigned to either an SWS TMR group or a REM TMR group. During the experimental night, participants completed a mnemonic discrimination task, where they memorized sound-picture pairs of eight semantic categories. After this, polysomnography was used to monitor sleep stages and TMR was conducted by playing a subset of sounds associated with the picture categories either during SWS or REM sleep. Memory performance was assessed again after sleep to evaluate how TMR impacted mnemonic discrimination, memory for specific details, and generalization. 4. Could you describe the main outcomes? Are there any study limitations? The main outcomes of the study showed that TMR during sleep did not result in significant differences in memory performance between the SWS and REM TMR groups. Specifically, our measures of memory specificity and generalization did not differ between the TMR groups or between reactivated and non-reactivated categories. An exploratory analysis suggested that TMR might enhance mnemonic discrimination for highly similar items, regardless of the sleep state during which TMR was performed. However, further research is needed to better understand the effect of TMR on discriminating items with varying levels of similarity. Several limitations may explain the lack of significant findings in the study. First, although previous research has shown it to be feasible, using a single sound cue to reactivate multiple items within a category could have caused interference, weakening the association between the sound and specific objects within a category, potentially reducing the effectiveness of TMR. Another possibility is that the mnemonic discrimination task, a kind of recognition memory task, used might not have been sensitive enough to detect subtle effects of TMR on memory performance. 5. Which future perspectives could this study disclose? In this study we expanded the scope of TMR research by exploring its effects beyond merely strengthening specific memories, focusing on other memory transformation processes and investigating TMR during REM sleep, which has been less studied compared to non-REM sleep. Our study shows that TMR effects are not always consistent, and perhaps depend on the type of memory being reactivated and the nature of the associations formed during learning. Although we did not find effects of TMR on memory, our study sets the stage for future research to optimize TMR techniques and better understand the conditions under which TMR might significantly influence memory consolidation and transformation. While our study focused on immediate post-sleep performance, future studies examining generalization or gist abstraction could explore whether TMR’s benefits become more apparent over days or weeks, potentially revealing effects that are not evident in the short term. Additionally, future research might also examine the differential impact of TMR on other types of memory tasks to identify which cognitive processes are most susceptible to enhancement through TMR. Link to Paper: Sifuentes Ortega R, Peigneux P. (2024), Does Targeted Memory Reactivation during SWS and REM sleep have differential effects on mnemonic discrimination and generalization? Sleep. Recent publications from ESRS members G Ravindran KK et al (2024), Reliable Contactless Monitoring of Heart Rate, Breathing Rate, and Breathing Disturbance During Sleep in Aging: Digital Health Technology Evaluation Study. JMIR Mhealth Uhealth. Schwarz EI et al (2024), Sex differences in sleep and sleep-disordered breathing. Curr Opin Pulm Med. Knutzen SM et al (2024), Efficacy of eHealth Versus In-Person Cognitive Behavioral Therapy for Insomnia: Systematic Review and Meta-Analysis of Equivalence. JMIR Ment Health. Lepeu G, van Maren E et al (2024), The critical dynamics of hippocampal seizures. Nat Commun. ------------- President's Message September 2024 Dear Friends and Colleagues, As we enter the final countdown to Sleep Europe 2024, and my final President`s newsletter, I want to take a moment to reflect on the past four years and thank you, the membership of ESRS, for entrusting me to lead the society. Over the past four years, ESRS went through a lot of firsts in its 52 year history. We held our first virtual congress and started a new tradition by offering a fully virtual event (eSleep) in odd years which we are already planning to continue into 2025.  ESRS initiated and funded the Sleep Europe Foundation (sef) to support the next generation of sleep researchers. We now offer more Sleep Europe travel grants to support participation of early career researchers, families, and lower income countries. We are also encouraging sustainable travel with designated grants as well as offering digital participation at the highly discounted rate of 40 EUR colleagues from lower and lower-middle-income countries. We aim to make sleep science accessible to all. Even outside of the traditional congress, we have established a tradition of webinars covering hot topics and new research in a timely manner. As the voice of sleep in Europe, ESRS have established formal connections and joint programming with relevant societies like the EPA and FENS and strengthened our working relationships with the European Respiratory Society (ERS) via a signed Memorandum of Understanding and the continuation of the Sleep and Breathing conference. ESRS has also supported the revision and publication of European guidelines for clinical practice. I am proud that we were able to hold in person Sleep Science Schools in 2021 and 2023 and ESRS offered its first Paediatric Sleep School in 2024. This year ANSS hosted Beyond Boundaries in person once again as well with a successful course taking place in Georgia, one of our newest ANSS member countries. These are just some of the highlights, from the past four years. The ESRS could not have accomplished all of this without the support of the staff which has now grown to five part time individuals and three project based contractors. After nine years with the ESRS, Axel Wiechmann will deliver his final examination this month. Erica Schwebs has been promoted to Education Manager and Ana Rocha was hired as Marketing Manager. I am confident the society is in good hands for continued success. I was elected in a virtual meeting and am very much looking forward to shaking the hand of the next ESRS President later this month in Seville with all of you.  Please be reminded that the Call for Nominations for positions on the ESRS Board and Scientific Committee will close in less than one week. If you have been considering submitting a nomination, now is the time to act. These positions are important for steering the strategic direction of our society, and your contributions are highly valued. This year, all voting is being conducted online. Voting on Bylaws amendments is currently open and you will be able to vote for Board and Scientific Committee positions from 12 – 25 September. You will need to login to your ESRS account, if you are unsure of your password, please reset it now. I remind you to attend the ESRS Business Meeting in Seville on Thursday, 26 September at 19:00 CEST, as we welcome in newly elected officers and present the ESRS update. Last but certainly not least, I can hardly believe that we have over 3,200 participants already registered to attend Sleep Europe where more than 1600 scientific posters will be on display. This will be the largest and most influential gathering of sleep professionals in Europe. If you have not yet planned to be in Seville, you can still register right up until the start of the congress to join us onsite or digitally Kind regards, Pierre-Hervé Luppi ---------- https://pubmed.ncbi.nlm.nih.gov/28694337/ Full text links HighWire full text link Actions Page navigation Title & authors Abstract Figures Similar articles Cited by References Publication types MeSH terms Related information LinkOut - more resources J Neurosci . 2017 Aug 9;37(32):7748-7758. doi: 10.1523/JNEUROSCI.3537-16.2017. Epub 2017 Jul 10. Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories Javiera P Oyarzún 1 2 , Joaquín Morís 3 , David Luque 4 5 , Ruth de Diego-Balaguer 6 2 7 8 , Lluís Fuentemilla 6 2 8 Affiliations Affiliations 1 Department of Cognition, Development and Educational Psychology, University of Barcelona, 08035 Barcelona, Spain, javi.oyarzunb@gmail.com. 2 Cognition and Brain Plasticity Group, IDIBELL, Bellvitge Biomedical Research Institute, L'Hospitalet de Llobregat, 08097 Barcelona, Spain. 3 Department of Psychology, University of Oviedo, 33003 Oviedo, Spain. 4 Instituto de Investigación Biomédica de Málaga, University of Málaga, 29071 Málaga, Spain. 5 School of Psychology, University of New South Wales Sydney, Sydney, New South Wales 2052, Australia. 6 Department of Cognition, Development and Educational Psychology, University of Barcelona, 08035 Barcelona, Spain. 7 ICREA, Catalan Institution for Research and Advanced Studies, 08010 Barcelona, Spain, and. 8 Institute of Neurosciences, University of Barcelona, 08035 Barcelona, Spain. PMID: 28694337 PMCID: PMC6596642 DOI: 10.1523/JNEUROSCI.3537-16.2017 Abstract System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength.SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks. Keywords: EEG; episodic memory; reactivation; sleep; strengthening; weakening. Copyright © 2017 the authors 0270-6474/17/377748-11$15.00/0. ----------- https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2018.00028/full ORIGINAL RESEARCH article Front. Hum. Neurosci., 06 February 2018 Sec. Brain Imaging and Stimulation Volume 12 - 2018 | https://doi.org/10.3389/fnhum.2018.00028 Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation Renee E. ShimizuRenee E. Shimizu1Patrick M. ConnollyPatrick M. Connolly1Nicola Cellini,Nicola Cellini2,3Diana M. ArmstrongDiana M. Armstrong4Lexus T. HernandezLexus T. Hernandez2Rolando EstradaRolando Estrada1Mario AguilarMario Aguilar1Michael P. WeisendMichael P. Weisend4Sara C. MednickSara C. Mednick2Stephen B. Simons*Stephen B. Simons1* 1Teledyne Scientific & Imaging, Durham, NC, United States 2Department of Psychology, University of California, Riverside, Riverside, CA, United States 3Department of General Psychology, University of Padova, Padova, Italy 4Rio Grande Neurosciences, Dayton, OH, United States Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12–15 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks. Introduction Sleep may facilitate the transformation of recent fragile memories into stable long-term memories. Compared with an equivalent period of wake, performance in several memory domains demonstrates a greater magnitude of improvement after sleep (Rasch and Born, 2013). Several electrophysiological features of non-rapid eye movement (NREM) sleep have been linked with memory consolidation, with the majority of these studies focusing on the role of slow wave activity, which refers to the low-frequency oscillations (0.05–4 Hz) that characterize deeper NREM sleep (e.g., Gais et al., 2002; Wilhelm et al., 2014). Slow oscillations (SOs) originate in the cortex and reflect synchronized neural fluctuations between hyperpolarized down-states and depolarized up-states. Spindles, another prominent NREM sleep feature consisting of 9–15 Hz oscillatory bursts, have gained attention for their role in hippocampal-cortical communication and declarative memory consolidation during sleep. Correlational studies have shown that the number of sleep spindles increases following hippocampal-dependent learning (Eschenko et al., 2006) and spindles are temporally coupled with hippocampal sharp wave ripples in rodents (Siapas and Wilson, 1998) and in humans (Staresina et al., 2015). They may facilitate the integration of newly learned information with existing knowledge (Tamminen et al., 2013) and are correlated with better retention of declarative memories in humans (Gais et al., 2002; Schabus et al., 2004; Clemens et al., 2005; Schmidt et al., 2006). A third electrophysiological feature of NREM sleep are hippocampal sharp wave-ripples, short high-frequency bursts that coincide with reactivations of neurons that were active during learning (e.g., Wilson and McNaughton, 1994). Temporal coupling of SOs, spindles, and hippocampal sharp wave-ripples may be a key mechanism underlying the hippocampal-neocortical dialog characteristic of systems consolidation. The drug zolpidem (Ambien) increased the temporal consistency of spindle occurrences during the down-to-up phase of slow oscillations (Niknazar et al., 2015). Furthermore, later performance improvement was correlated with this spindle/SO timing. This suggests that declarative memory consolidation is facilitated when thalamic spindles coincide with the down-to-up phase of cortical SOs. Thus SOs may provide a top-down temporal frame for these oscillatory events (Crunelli and Hughes, 2010; Lemieux et al., 2014). Specifically, individual hippocampal sharp wave ripple events appear to be nested in the trough of succeeding spindles (Timofeev and Bazhenov, 2005; Staresina et al., 2015), and these spindle-ripple events may represent a bottom-up mechanism whereby reactivated hippocampal memory information (coded in ripples) is passed to spindles, which then reach neocortical networks via the SO (Born et al., 2006; Diekelmann and Born, 2010). Recently, Yordanova et al. (2017) have shown that the temporal coupling of SO up-states and spindles is greater in the hemisphere that had been activated during prior learning. Targeted memory reactivation (TMR) has been successful in enhancing memory during sleep using external stimulation. The TMR approach associates sensory stimuli (e.g., odor or sound cue) with target information during encoding and then presents the same cues during sleep to facilitate memory consolidation, including visuospatial (Rasch et al., 2007; Rudoy et al., 2009; van Dongen et al., 2012; Creery et al., 2015), verbal memories (Schreiner and Rasch, 2014; Batterink and Paller, 2017) and fear extinction (He et al., 2015). The strength of specific memory enhancement appears to depend on the timing relative to the phase of the SO, although most studies have thus far delivered cues using an open-loop approach during NREM stage 3 sleep (Batterink et al., 2016). Batterink et al. (2016) demonstrated that the largest memory benefit occurred when TMR cues were delivered during the descending phase of the SO down state, which presumably allowed for the cue information to be processed by the cortex and hippocampus during their up states. This suggests that the largest memory benefits may be realized when the cues are delivered during the transition from cortical down states to up states. In the current study, we developed a novel method to enhance sleep spindles and spatial navigation skills using closed-loop targeted memory reactivation (CL-TMR) time-locked to the down-state to up-state transitions (DUPTs) of SOs. We tested navigation ability at multiple time points across 3 days in order to determine when the benefits of CL-TMR emerge, and how long they are observed. DUPTs were targeted to increase the likelihood of affecting spindles during the rising phase and peak of the SO. In this study, we did not investigate whether the closed-loop cue delivery confers significant benefit when compared with an open-loop approach. Multiple studies suggest that TMR may be most effective when time-locked to the DUPTs (Niknazar et al., 2015; Batterink et al., 2016), and a recent non-peer reviewed study has shown that when cues are delivered during the down state, memory enhancement is superior when compared with the effect observed when cues are delivered during the up state (Göldi et al., unpublished). The goal of this study was to develop a robust methodology for reliably delivering stimuli during DUPTs and to demonstrate that CL-TMR can be used to drive performance gains in ecologically valid, complex learning tasks over longer periods of time. ---------- https://news.va.gov/ VA Health and Benefits App The VA Health and Benefits mobile app puts your VA health and benefit information and resources at your fingertips — anywhere, anytime! 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