Virtual reality-based training may improve visual memory and some aspects of sustained attention among healthy older adults - preliminary results of a randomized controlled study.

BACKGROUND/AIMS: Older age and cognitive inactivity have been associated with cognitive impairment, which in turn is linked to economic and societal burdens due to the high costs of care, especially for care homes and informal care. Emerging non-pharmacological interventions using new technologies, such as virtual reality (VR) delivered on a head-mounted display (HMD), might offer an alternative to maintain or improve cognition. The study aimed to evaluate the efficacy and safety of a VR-based Digital Therapeutics application for improving cognitive functions among healthy older adults. METHODS: Seventy-two healthy seniors (experimental group N = 35, control group N = 37), aged 65-85 years, were recruited by the Medical University of Lodz (Poland). Participants were randomly allocated to the experimental group (a VR-based cognitive training which consists of a warm-up module and three tasks, including one-back and dual-N-back) or to the control group (a regular VR headset app only showing nature videos). The exercises are performed in different 360-degree natural environments while listening to a preferred music genre and delivered on a head-mounted display (HMD). The 12-week intervention of 12 min was delivered at least three times per week (36 sessions). Compliance and performance were followed through a web-based application. Primary outcomes included attention and working memory (CNS-Vital Signs computerized cognitive battery). Secondary outcomes comprised other cognitive domains. Mixed linear models were constructed to elucidate the difference in pre- and post-intervention measures between the experimental and control groups. RESULTS: The users performed, on average, 39.8 sessions (range 1-100), and 60% performed more than 36 sessions. The experimental group achieved higher scores in the visual memory module (B = 7.767, p = 0.011) and in the one-back continuous performance test (in terms of correct responses: B = 2.057, p = 0.003 and omission errors: B = -1.950, p = 0.007) than the control group in the post-test assessment. The results were independent of participants' sex, age, and years of education. The differences in CNS Vital Signs' global score, working memory, executive function, reaction time, processing speed, simple and complex attention, verbal memory, cognitive flexibility, motor speed, and psychomotor speed were not statistically significant. CONCLUSIONS: VR-based cognitive training may prove to be a valuable, efficacious, and well-received tool in terms of improving visual memory and some aspect of sustainability of attention among healthy older adults. This is a preliminary analysis based on part of the obtained results to that point. Final conclusions will be drawn after the analysis of the target sample size. TRIAL REGISTRATION: Clinicaltrials.gov ID NCT05369897.

Tormenting thoughts: The posterior cingulate sulcus of the default mode network regulates valence of thoughts and activity in the brain's pain network during music listening.

Many individuals spend a significant amount of their time "mind-wandering". Mind-wandering often includes spontaneous, nonintentional thought, and a neural correlate of this kind of thought is the default mode network (DMN). Thoughts during mind-wandering can have positive or negative valence, but only little is known about the neural correlates of positive or negative thoughts. We used resting-state functional magnetic resonance imaging (fMRI) and music to evoke mind-wandering in n = 33 participants, with positive-sounding music eliciting thoughts with more positive valence and negative-sounding music eliciting thoughts with more negative valence. Applying purely data-driven analysis methods, we show that medial orbitofrontal cortex (mOFC, part of the ventromedial prefrontal cortex) and the posterior cingulate sulcus (likely area 23c of the posterior cingulate cortex), two sub-regions of the DMN, modulate the valence of thought-contents during mind-wandering. In addition, across two independent experiments, we observed that the posterior cingulate sulcus, a region involved in pain, shows valence-specific functional connectivity with core regions of the brain's putative pain network. Our results suggest that two DMN regions (mOFC and posterior cingulate sulcus) support the formation of negative spontaneous, nonintentional thoughts, and that the interplay between these structures with regions of the putative pain network forms a neural mechanism by which thoughts can become painful.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Trait Empathy Shapes Neural Responses Toward Sad Music.

Individuals with a predisposition to empathize engage with sad music in a compelling way, experiencing overall more pleasurable emotions. However, the neural mechanisms underlying these music-related experiences in empathic individuals are unknown. The present study tested whether dispositional empathy modulates neural responses to sad compared with happy music. Twenty-four participants underwent fMRI while listening to 4-min blocks of music evoking sadness or happiness. Using voxel-wise regression, we found a positive correlation between trait empathy (with scores assessed by the Interpersonal Reactivity Index) and eigenvector centrality values in the ventromedial prefrontal cortex (vmPFC), including the medial orbitofrontal cortex (mOFC). We then performed a functional connectivity (FC) analysis to detect network nodes showing stronger FC with the vmPFC/mOFC during the presentation of sad versus happy music. By doing so, we identified a "music-empathy" network (vmPFC/mOFC, dorsomedial prefrontal cortex, primary visual cortex, bilateral claustrum and putamen, and cerebellum) that is spontaneously recruited while listening to sad music and includes brain regions that support the coding of compassion, mentalizing, and visual mental imagery. Importantly, our findings extend the current understanding of empathic behaviors to the musical domain and pinpoint sad music as an effective stimulus to be employed in social neuroscience research.

Earliest amyloid and tau deposition modulate the influence of limbic networks during closed-loop hippocampal downregulation.

Research into hippocampal self-regulation abilities may help determine the clinical significance of hippocampal hyperactivity throughout the pathophysiological continuum of Alzheimer's disease. In this study, we aimed to identify the effects of amyloid-ß peptide 42 (amyloid-ß42) and phosphorylated tau on the patterns of functional connectomics involved in hippocampal downregulation. We identified 48 cognitively unimpaired participants (22 with elevated CSF amyloid-ß peptide 42 levels, 15 with elevated CSF phosphorylated tau levels, mean age of 62.705 ± 4.628 years), from the population-based 'Alzheimer's and Families' study, with baseline MRI, CSF biomarkers, APOE genotyping and neuropsychological evaluation. We developed a closed-loop, real-time functional MRI neurofeedback task with virtual reality and tailored it for training downregulation of hippocampal subfield cornu ammonis 1 (CA1). Neurofeedback performance score, cognitive reserve score, hippocampal volume, number of apolipoprotein ε4 alleles and sex were controlled for as confounds in all cross-sectional analyses. First, using voxel-wise multiple regression analysis and controlling for CSF biomarkers, we identified the effect of healthy ageing on eigenvector centrality, a measure of each voxel's overall influence based on iterative whole-brain connectomics, during hippocampal CA1 downregulation. Then, controlling for age, we identified the effects of abnormal CSF amyloid-ß42 and phosphorylated tau levels on eigenvector centrality during hippocampal CA1 downregulation. Across subjects, our main findings during hippocampal downregulation were: (i) in the absence of abnormal biomarkers, age correlated with eigenvector centrality negatively in the insula and midcingulate cortex, and positively in the inferior temporal gyrus; (ii) abnormal CSF amyloid-ß42 (<1098) correlated negatively with eigenvector centrality in the anterior cingulate cortex and primary motor cortex; and (iii) abnormal CSF phosphorylated tau levels (>19.2) correlated with eigenvector centrality positively in the ventral striatum, anterior cingulate and somatosensory cortex, and negatively in the precuneus and orbitofrontal cortex. During resting state functional MRI, similar eigenvector centrality patterns in the cingulate had previously been associated to CSF biomarkers in mild cognitive impairment and dementia patients. Using the developed closed-loop paradigm, we observed such patterns, which are characteristic of advanced disease stages, during a much earlier presymptomatic phase. In the absence of CSF biomarkers, our non-invasive, interactive, adaptive and gamified neuroimaging procedure may provide important information for clinical prognosis and monitoring of therapeutic efficacy. We have released the developed paradigm and analysis pipeline as open-source software to facilitate replication studies.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

The effects of psychiatric history and age on self-regulation of the default mode network.

Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (na = 74) and a healthy control group (nb = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.

Superficial amygdala and hippocampal activity during affective music listening observed at 3 T but not 1.5 T fMRI.

The purpose of this study was to compare 3 T and 1.5 T fMRI results during emotional music listening. Stimuli comprised of psychoacoustically balanced instrumental musical pieces, with three different affective expressions (fear, neutral, joy). Participants (N=32) were split into two groups, one subjected to fMRI scanning using 3 T and another group scanned using 1.5 T. Whole brain t-tests (corrected for multiple comparisons) compared joy and fear in each of the two groups. The 3 T group showed significant activity differences between joy and fear localized in bilateral superficial amygdala, bilateral hippocampus and bilateral auditory cortex. The 1.5 T group showed significant activity differences between joy and fear localized in bilateral auditory cortex and cuneus. This is the first study to compare results obtained under different field strengths with regard to affective processes elicited by means of auditory/musical stimulation. The findings raise concern over false negatives in the superficial amygdala and hippocampus in affective studies conducted under 1.5 T and caution that imaging improvements due to increasing magnetic field strength can be influenced by region-specific characteristics.

Functional centrality of amygdala, striatum and hypothalamus in a "small-world" network underlying joy: an fMRI study with music.

Current knowledge about small-world networks underlying emotions is sparse, and confined to functional magnetic resonance imaging (fMRI) studies using resting-state paradigms. This fMRI study applied Eigenvector Centrality Mapping (ECM) and functional connectivity analysis to reveal neural small-world networks underlying joy and fear. Joy and fear were evoked using music, presented in 4-min blocks. Results show that the superficial amygdala (SF), laterobasal amygdala (LB), striatum, and hypothalamus function as computational hubs during joy. Out of these computational hubs, the amygdala nuclei showed the highest centrality values. The SF showed functional connectivity during joy with the mediodorsal thalamus (MD) and nucleus accumbens (Nac), suggesting that SF, MD, and Nac modulate approach behavior in response to positive social signals such as joyful music. The striatum was functionally connected during joy with the LB, as well as with premotor cortex, areas 1 and 7a, hippocampus, insula and cingulate cortex, showing that sensorimotor, attentional, and emotional processes converge in the striatum during music perception. The hypothalamus showed functional connectivity during joy with hippocampus and MD, suggesting that hypothalamic endocrine activity is modulated by hippocampal and thalamic activity during sustained periods of music-evoked emotion. Our study indicates high centrality of the amygdala nuclei groups within a functional network underlying joy, suggesting that these nuclei play a central role for the modulation of emotion-specific activity within this network.

Religious Chanting and Self-Related Brain Regions: A Multi-Modal Neuroimaging Study.

This protocol presents a multi-modal neuroimaging approach to explore the potential brain activity associated with repetitive religious chanting, a widespread form of mind training in both Eastern and Western cultures. High-density electroencephalogram (EEG), with its superior temporal resolution, allows for capturing the dynamic changes in brain activity during religious chanting. Through source localization methods, these can be attributed to various alternative potential brain region sources. Twenty practitioners of religious chanting were measured with EEG. However, the spatial resolution of EEG is less precise, in comparison to functional magnetic resonance imaging (fMRI). Thus, one highly experienced practitioner underwent an fMRI scanning session to guide the source localization more precisely. The fMRI data helped guide the selection of EEG source localization, making the calculation of K-means of the EEG source localization in the group of 20 intermediate practitioners more precise and reliable. This method enhanced EEG's ability to identify the brain regions specifically engaged during religious chanting, particularly the cardinal role of the posterior cingulate cortex (PCC). The PCC is a brain area related to focus and self-referential processing. These multimodal neuroimaging and neurophysiological results reveal that repetitive religious chanting can induce lower centrality and higher delta-wave power compared to non-religious chanting and resting state conditions. The combination of fMRI and EEG source analysis provides a more detailed understanding of the brain's response to repetitive religious chanting. The protocol contributes significantly to the research on the neural mechanisms involved in religious and meditative practices, which is becoming more prominent nowadays. The results of this study could have significant implications for developing future neurofeedback techniques and psychological interventions.

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback.

Objective: The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf. Methods: We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted. Results: Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing. Conclusion: This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.

The Effectiveness of Virtual Reality-Based Training on Cognitive, Social, and Physical Functioning in High-Functioning Older Adults (CoSoPhy FX): 2-Arm, Parallel-Group Randomized Controlled Trial.

BACKGROUND: Virtual reality (VR) has emerged as a promising technology for enhancing the health care of older individuals, particularly in the domains of cognition, physical activity, and social engagement. However, existing VR products and services have limited availability and affordability; hence, there is a need for a scientifically validated and personalized VR service to be used by older adults in their homes, which can improve their overall physical, cognitive, and social well-being. OBJECTIVE: The main purpose of the CoSoPhy FX (Cognitive, Social, and Physical Effects) study was to analyze the effects of a VR-based digital therapeutics app on the cognitive, social, and physical performance abilities of healthy (high-functioning) older adults. This paper presents the study protocol and the results from the recruitment phase. METHODS: A group of 188 healthy older adults aged 65-85 years, recruited at the Medical University of Lodz, Poland, were randomly allocated to the experimental group (VR dual-task training program) or to the control group (using a VR headset app showing nature videos). A total of 3 cognitive exercises were performed in various 360° nature environments delivered via a VR head-mounted display; the participants listened to their preferred music genre. Each patient received 3 sessions of 12 minutes per week for 12 weeks, totaling a minimum of 36 sessions per participant. Attention and working memory (Central Nervous System Vital Signs computerized cognitive battery) were used as primary outcomes, while other cognitive domains in the Central Nervous System Vital Signs battery, quality of life (World Health Organization-5 Well-Being Index), health-related quality of life (EQ-5D-5L), and anxiety (General Anxiety Disorder 7-item questionnaire) were the secondary outcomes. The group-by-time interaction was determined using linear mixed models with participants' individual slopes. RESULTS: In total, 122 (39%) of the initial 310 participants failed to meet the inclusion criteria, resulting in a recruitment rate of 61% (188/310). Among the participants, 68 successfully completed the intervention and 62 completed the control treatment. The data are currently being analyzed, and we plan to publish the results by the end of September 2024. CONCLUSIONS: VR interventions have significant potential among healthy older individuals. VR can address various aspects of well-being by stimulating cognitive functions, promoting physical activity, and facilitating social interaction. However, challenges such as physical discomfort, technology acceptance, safety concerns, and cost must be considered when implementing them for older adults. Further research is needed to determine the long-term effects of VR-based interventions, optimal intervention designs, and the specific populations that would benefit most. TRIAL REGISTRATION: ClinicalTrials.gov NCT05369897; https://clinicaltrials.gov/study/NCT05369897. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53261.

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping.

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

The roles of superficial amygdala and auditory cortex in music-evoked fear and joy.

This study investigates neural correlates of music-evoked fear and joy with fMRI. Studies on neural correlates of music-evoked fear are scant, and there are only a few studies on neural correlates of joy in general. Eighteen individuals listened to excerpts of fear-evoking, joy-evoking, as well as neutral music and rated their own emotional state in terms of valence, arousal, fear, and joy. Results show that BOLD signal intensity increased during joy, and decreased during fear (compared to the neutral condition) in bilateral auditory cortex (AC) and bilateral superficial amygdala (SF). In the right primary somatosensory cortex (area 3b) BOLD signals increased during exposure to fear-evoking music. While emotion-specific activity in AC increased with increasing duration of each trial, SF responded phasically in the beginning of the stimulus, and then SF activity declined. Psychophysiological Interaction (PPI) analysis revealed extensive emotion-specific functional connectivity of AC with insula, cingulate cortex, as well as with visual, and parietal attentional structures. These findings show that the auditory cortex functions as a central hub of an affective-attentional network that is more extensive than previously believed. PPI analyses also showed functional connectivity of SF with AC during the joy condition, taken to reflect that SF is sensitive to social signals with positive valence. During fear music, SF showed functional connectivity with visual cortex and area 7 of the superior parietal lobule, taken to reflect increased visual alertness and an involuntary shift of attention during the perception of auditory signals of danger.

Eigenvector centrality and its variability over time are promising indicators of alterations in brain function due to early amyloid deposition.

This scientific commentary refers to 'Eigenvector centrality dynamics are related to Alzheimer's disease pathological changes in non-demented individuals', by Lorenzini et al. (https://doi.org/10.1093/braincomms/fcad088).

Sensorimotor synchronization to music reduces pain.

Pain-reducing effects of music listening are well-established, but the effects are small and their clinical relevance questionable. Recent theoretical advances, however, have proposed that synchronizing to music, such as clapping, tapping or dancing, has evolutionarily important social effects that are associated with activation of the endogenous opioid system (which supports both analgesia and social bonding). Thus, active sensorimotor synchronization to music could have stronger analgesic effects than simply listening to music. In this study, we show that sensorimotor synchronization to music significantly amplifies the pain-reducing effects of music listening. Using pressure algometry to the fingernails, pain stimuli were delivered to n = 59 healthy adults either during music listening or silence, while either performing an active tapping task or a passive control task. Compared to silence without tapping, music with tapping (but not simply listening to music) reduced pain with a large, clinically significant, effect size (d = 0.93). Simply tapping without music did not elicit such an effect. Our analyses indicate that both attentional and emotional mechanisms drive the pain-reducing effects of sensorimotor synchronization to music, and that tapping to music in addition to merely listening to music may enhance pain-reducing effects in both clinical contexts and everyday life. The study was registered as a clinical trial at ClinicalTrials.gov (registration number NCT05267795), and the trial was first posted on 04/03/2022.

Brain-correlates of processing local dependencies within a statistical learning paradigm.

Statistical learning refers to the implicit mechanism of extracting regularities in our environment. Numerous studies have investigated the neural basis of statistical learning. However, how the brain responds to violations of auditory regularities based on prior (implicit) learning requires further investigation. Here, we used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of processing events that are irregular based on learned local dependencies. A stream of consecutive sound triplets was presented. Unbeknown to the subjects, triplets were either (a) standard, namely triplets ending with a high probability sound or, (b) statistical deviants, namely triplets ending with a low probability sound. Participants (n = 33) underwent a learning phase outside the scanner followed by an fMRI session. Processing of statistical deviants activated a set of regions encompassing the superior temporal gyrus bilaterally, the right deep frontal operculum including lateral orbitofrontal cortex, and the right premotor cortex. Our results demonstrate that the violation of local dependencies within a statistical learning paradigm does not only engage sensory processes, but is instead reminiscent of the activation pattern during the processing of local syntactic structures in music and language, reflecting the online adaptations required for predictive coding in the context of statistical learning.

Study protocol for the Alzheimer and music therapy study: An RCT to compare the efficacy of music therapy and physical activity on brain plasticity, depressive symptoms, and cognitive decline, in a population with and at risk for Alzheimer's disease.

BACKGROUND: There is anecdotal evidence for beneficial effects of music therapy in patients with Alzheimer's Disease (AD). However, there is a lack of rigorous research investigating this issue. The aim of this study is to evaluate the effects of music therapy and physical activity on brain plasticity, mood, and cognition in a population with AD and at risk for AD. METHODS: One-hundred and thirty-five participants with memory complaints will be recruited for a parallel, three-arm Randomized Controlled Trial (RCT). Inclusion criteria are a diagnosis of mild (early) AD or mild cognitive impairment (MCI), or memory complaints without other neuropsychiatric pathology. Participants are randomised into either a music therapy intervention (singing lessons), an active control group (physical activity) or a passive control group (no intervention) for 12 months. The primary outcomes are the brain age gap, measured via magnetic resonance imaging (MRI), and depressive symptoms. Secondary outcomes include cognitive performance, activities of daily living, brain structure (voxel-based morphometry and diffusion tensor imaging), and brain function (resting-state functional MRI). TRIAL STATUS: Screening of participants began in April 2018. A total of 84 participants have been recruited and started intervention, out of which 48 participants have completed 12 months of intervention and post-intervention assessment. DISCUSSION: Addressing the need for rigorous longitudinal data for the effectiveness of music therapy in people with and at risk for developing AD, this trial aims to enhance knowledge regarding cost-effective interventions with potentially high clinical applicability. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03444181, registered on February 23, 2018.

Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks.

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.