The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Individuals with high autistic traits exhibit altered interhemispheric brain functional connectivity patterns

Individuals with high autistic traits (AT) encounter challenges in social interaction, similar to autistic persons. Precise screening and focused interventions positively contribute to improving this situation. Functional connectivity analyses can measure information transmission and integration between brain regions, providing neurophysiological insights into these challenges. This study aimed to investigate the patterns of brain networks in high AT individuals to offer theoretical support for screening and intervention decisions. EEG data were collected during a 4-min resting state session with eyes open and closed from 48 participants. Using the Autism Spectrum Quotient (AQ) scale, participants were categorized into the high AT group (HAT, n = 15) and low AT groups (LAT, n = 15). We computed the interhemispheric and intrahemispheric alpha coherence in two groups. The correlation between physiological indices and AQ scores was also examined. Results revealed that HAT exhibited significantly lower alpha coherence in the homologous hemispheres of the occipital cortex compared to LAT during the eyes-closed resting state. Additionally, significant negative correlations were observed between the degree of AT (AQ scores) and the alpha coherence in the occipital cortex, as well as in the right frontal and left occipital regions. The findings indicated that high AT individuals exhibit decreased connectivity in the occipital region, potentially resulting in diminished ability to process social information from visual inputs. Our discovery contributes to a deeper comprehension of the neural underpinnings of social challenges in high AT individuals, providing neurophysiological signatures for screening and intervention strategies for this population.

Silicon Spike: An Arduino-based low-cost and open-access triggerbox to precisely control TMS devices

Transcranial magnetic stimulation (TMS) is a widely used tool in the field of clinical and cognitive neuroscience. To exploit its excellent temporal properties, TMS usually relies on triggerbox devices, which temporize the delivery of magnetic pulses according to the paradigm requirements. However, a main limitation of most of the widely used triggerbox devices is that they rely solely on the experimental computer processor, which might add temporal uncertainty in delivering the TMS pulse when the computer's resources are drained by other experimental devices or by task execution itself, especially during repetitive TMS or dual-coil protocols. We aimed at developing a low-cost and easily reproducible triggerbox device which could overcome these limitations by relying on an external processor to handle the timing precision. We used an Arduino Uno R4 Minima to build Silicon Spike, a low-cost ($60) triggerbox device. We tested the device's precision in delivering the TMS pulses under different working load conditions, and the impact over time. All of the tests were ecological, delivering real TMS pulses during dual-coil, repetitive, and patterned TMS protocols. We obtained extremely high precision (< 0.022 ms) in all of the tests. This means that, for smaller or longer latencies, the error remains negligible for TMS studies. Thus, the Silicon Spike device demonstrated microsecond precision in handling the TMS pulse delivery, establishing itself as a simple and yet precise device. We freely provide the source code and the hardware schematics, allowing anyone to reproduce our work.

A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm

The electroencephalographic alpha rhythm is one of the most robustly observed and widely studied empirical phenomena in all of neuroscience. However, despite its extensive implication in a wide range of cognitive processes and clinical pathologies, the mechanisms underlying alpha generation in neural circuits remain poorly understood. In this paper we offer a renewed foundation for research on this question, by undertaking a systematic comparison and synthesis of the most prominent theoretical models of alpha rhythmogenesis in the published literature. We focus on four models, each studied intensively by multiple authors over the past three decades: (i) Jansen-Rit, (ii) Moran-David-Friston, (iii) Robinson-Rennie-Wright, and (iv) Liley-Wright. Several common elements are identified, such as the use of second-order differential equations and sigmoidal potential-to-rate operators to represent population-level neural activity. Major differences are seen in other features such as wiring topologies and conduction delays. Through a series of mathematical analyses and numerical simulations, we nevertheless demonstrate that the selected models can be meaningfully compared, by associating parameters and circuit motifs of analogous biological significance. With this established, we conduct explorations of rate constant and synaptic connectivity parameter spaces, with the aim of identifying common patterns in key behaviours, such as the role of excitatory-inhibitory interactions in the generation of oscillations. Finally, using linear stability analysis we identify two qualitatively different alpha-generating dynamical regimes across the models: (i) noise-driven fluctuations and (ii) self-sustained limit-cycle oscillations, emerging due to an Andronov-Hopf bifurcation. The comprehensive survey and synthesis developed here can, we suggest, be used to help guide future theoretical and experimental work aimed at disambiguating these and other candidate theories of alpha rhythmogenesis.

Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia

Objective

To evaluate the efficacy of EEG neurofeedback (EEG-NF) combined with pharmacological treatment on positive and negative symptoms in schizophrenia.

Methods

Randomized controlled trials (RCTs) were searched in CNKI, Wanfang, VIP, PubMed, Web of Science, Cochrane, and Embase databases until January 25, 2025. Literature quality was assessed using the PEDro and CRED-NF checklists. Meta-analysis and publication bias tests were performed using RevMan 5.4.1 and Stata 18.0, respectively, with evidence quality evaluated via GRADEpro.

Results

Fourteen studies (1371 patients) were included. EEG-NF combined with pharmacological treatment significantly improved positive (SMD=-0.87) and negative symptoms (SMD=-1.28). Subgroup analysis showed greater improvement in patients aged ≥45 years (positive: SMD=-1.05; negative: SMD=-1.64). For positive symptoms, better outcomes were observed with intervention periods ≥8 weeks, frequency ≥4 times/week, and disease duration ≥5 years (SMD=-1.04, -0.94, -0.94). For negative symptoms, better outcomes were seen with intervention periods ≥8 weeks, frequency ≥4 times/week, and disease duration <5 years (SMD=-1.34, -1.68, -1.26). Mental and emotional disorders treatment regimens targeting sensorimotor rhythm (SMR) and beta waves showed significant improvement in both positive (SMD=-0.98) and negative symptoms (SMD=-1.49).

Conclusion

EEG-NF combined with pharmacological treatment effectively improves schizophrenia symptoms. A regimen of ≥4 sessions/week for ≥8 weeks, targeting SMR and beta waves, is recommended. However, publication bias may limit the generalizability of findings. Future research should prioritize larger-scale, multicenter studies to evaluate long-term efficacy and mechanisms.

Systematic Review Registration

www.crd.york.ac.uk, identifier CRD42024593505.

A human electrophysiological biomarker of Fragile X Syndrome is shared in V1 of Fmr1 KO mice and caused by loss of FMRP in cortical excitatory neurons

Predicting clinical therapeutic outcomes from preclinical animal studies remains an obstacle to developing treatments for neuropsychiatric disorders. Electrophysiological biomarkers analyzed consistently across species could bridge this divide. In humans, alpha oscillations in the resting state electroencephalogram (rsEEG) are altered in many disorders, but these disruptions have not yet been characterized in animal models. Here, we employ a uniform analytical method to show in males with fragile X syndrome (FXS) that the slowed alpha oscillations observed in adults are also present in children and in visual cortex of adult and juvenile Fmr1 -/y mice. We find that alpha-like oscillations in mice reflect the differential activity of two classes of inhibitory interneurons, but the phenotype is caused by deletion of Fmr1 specifically in cortical excitatory neurons. These results provide a framework for studying alpha oscillation disruptions across species, advance understanding of a critical rsEEG signature in the human brain and inform the cellular basis for a putative biomarker of FXS.

Aperiodic (1/f) Neural Activity Robustly Tracks Symptom Severity Changes in Treatment-Resistant Depression

BACKGROUND

A reliable physiological biomarker for major depressive disorder is essential for developing and optimizing neuromodulatory treatment paradigms. In this study, we investigated a passive electrophysiologic biomarker that tracks changes in depressive symptom severity on the order of minutes to hours.

METHODS

We analyzed brief recordings from intracranial electrodes implanted deep in the brain during a clinical trial of deep brain stimulation for treatment-resistant depression in 5 human participants (nfemale = 3, nmale = 2). This surgical setting allowed for precise temporal and spatial sensitivity in the ventromedial prefrontal cortex, a challenging area to measure. We focused on the aperiodic slope of the power spectral density, a metric that reflects the balance of activity across all frequency bands and may serve as a proxy for excitatory/inhibitory balance in the brain.

RESULTS

Our findings demonstrated that shifts in aperiodic slope correlated with depression severity, with flatter (less negative) slopes indicating reduced depression severity. This significant correlation was observed in all 5 participants, particularly in the ventromedial prefrontal cortex.

CONCLUSIONS

This biomarker offers a new way to track patient responses to major depressive disorder treatment, thus paving the way for individualized therapies in both intracranial and noninvasive monitoring contexts.

Individualized Spectral Features in First-Episode and Drug-Naïve Major Depressive Disorder: Insights From Periodic and Aperiodic Electroencephalography Analysis

BACKGROUND

The detection of abnormal brain activity plays an important role in the early diagnosis and treatment of major depressive disorder (MDD). Recent studies have shown that the decomposition of the electroencephalography (EEG) spectrum into periodic and aperiodic components is useful for identifying the drivers of electrophysiologic abnormalities and avoiding individual differences.

METHODS

In this study, we aimed to elucidate the pathological changes in individualized periodic and aperiodic activities and their relationships with the symptoms of MDD. EEG data in the eyes-closed resting state were continuously recorded from 97 first-episode and drug-naïve patients with MDD and 90 healthy control participants. Both periodic oscillations and aperiodic components were obtained via the fitting oscillations and one-over f (FOOOF) algorithm and then used to compute individualized spectral features.

RESULTS

Patients with MDD presented higher canonical alpha and beta band power but lower aperiodic-adjusted alpha and beta power. Furthermore, we found that alpha power was strongly correlated with the age of patients but not with disease symptoms. The aperiodic intercept was lower in the parieto-occipital region and was positively correlated with Hamilton Depression Rating Scale scores after accounting for age and sex. In the asymmetry analysis, alpha activity appeared asymmetrical only in the healthy control group, whereas aperiodic activity was symmetrical in both groups.

CONCLUSIONS

The findings of this study provide insights into the role of abnormal neural spiking activity and impaired neuroplasticity in MDD progression and suggest that the aperiodic intercept in resting-state EEG may be a potential biomarker of MDD.

Alpha rhythm slowing in temporal lobe epilepsy across scalp EEG and MEG

EEG slowing is reported in various neurological disorders including Alzheimer's, Parkinson's and Epilepsy. Here, we investigate alpha rhythm slowing in individuals with refractory temporal lobe epilepsy compared with healthy controls, using scalp EEG and magnetoencephalography. We retrospectively analysed data from 17 (46) healthy controls and 22 (24) individuals with temporal lobe epilepsy who underwent scalp EEG and magnetoencephalography recordings as part of presurgical evaluation. Resting-state, eyes-closed recordings were source reconstructed using the standardized low-resolution brain electrographic tomography method. We extracted slow 6-9 Hz and fast 10-11 Hz alpha relative band power and calculated the alpha power ratio by dividing slow alpha by fast alpha. This ratio was computed for all brain regions in all individuals. Alpha oscillations were slower in individuals with temporal lobe epilepsy than controls (P< 0.05). This effect was present in both the ipsilateral and contralateral hemispheres and across widespread brain regions. Alpha slowing in temporal lobe epilepsy was found in both EEG and magnetoencephalography recordings. We interpret greater slow alpha as greater deviation from health.

Childhood trauma is associated with developmental trajectories of EEG coherence, alcohol-related outcomes, and PTSD symptoms

BACKGROUND

Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

METHODS

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

RESULTS

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = -0.07, p = 0.02) and PFI (ß = -0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = -0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = -1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

CONCLUSIONS

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

Revolutionizing our understanding of Parkinson's disease: Dr. Heinz Reichmann's pioneering research and future research direction

Millions of individuals around the world are afflicted with Parkinson's disease (PD), a prevalent and incapacitating neurodegenerative disorder. Dr. Reichmann, a distinguished professor and neurologist, has made substantial advancements in the domain of PD research, encompassing both fundamental scientific investigations and practical applications. His research has illuminated the etiology and treatment of PD, as well as the function of energy metabolism and premotor symptoms. As a precursor to a number of neurotransmitters and neuromodulators that are implicated in the pathophysiology of PD, he has also investigated the application of tryptophan (Trp) derivatives in the disease. His principal findings and insights are summarized and synthesized in this narrative review article, which also emphasizes the challenges and implications for future PD research. This narrative review aims to identify and analyze the key contributions of Reichmann to the field of PD research, with the ultimate goal of informing future research directions in the domain. By examining Reichmann's work, the study seeks to provide a comprehensive understanding of his major contributions and how they can be applied to advance the diagnosis and treatment of PD. This paper also explores the potential intersection of Reichmann's findings with emerging avenues, such as the investigation of Trp and its metabolites, particularly kynurenines, which could lead to new insights and potential therapeutic strategies for managing neurodegenerative disorders like PD.

Toward neuroscientific understanding in posttraumatic growth: Scoping review identifying electrophysiological neurofeedback training targets for brain-based research

Improved neural understanding of posttraumatic growth (PTG) is required for effective trauma care. PTG is the advantageous psychological change some individuals derive from their struggle to overcome trauma. This comprehensive review critically examined the limited neural PTG research, to identify electrophysiological training targets for future research examining neurofeedback to enhance PTG, and provides novel insights into the emerging neural theory of PTG. PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) informed the process. Findings from the studies N=8 (participants N=765) revealed PTG was correlated with left-lateralised alpha frequency power patterns. Specifically, PTG was associated with lower left frontal alpha power, higher left central alpha power, and lower parietal alpha power. Differences between studies may identify different components of PTG-related neural circuitry, or represent variations in PTG and sub-factor strength, mechanistic differences between studies, or the potential confounding presence of posttraumatic stress disorder (PTSD). While lower alpha power has been associated with higher PTSD in existing literature, higher left central alpha power was associated with lower PTSD. Therefore, alpha upregulation neurofeedback delivered over the sensorimotor cortices of the brain, around left central EEG electrode C3, presented the most promising neurofeedback target.

Associations between ADHD symptoms, executive function and frontal EEG in college students

INTRODUCTION

This study aims to assess whether electroencephalogram (EEG) spectral power change scores (e.g. task spectral power subtracted from resting state spectral power) across three different frequency bands, alpha (8-12 Hz), theta (4-7 Hz), and beta (13-30 Hz), predicts self-reported attention-deficit hyperactivity disorder (ADHD) symptoms using the Adult ADHD Self-Report Scale (ASRS) over and above self-reported executive function (EF) abilities using the Behavior Rating Inventory of Executive Function (BRIEF-A) Global Executive Composite (GEC) T-scores for adults.

METHODS

Data were collected at a rural, mid-sized southeastern university (N = 52) and participants received course credit for participation. Participants self-reported ADHD symptoms and EF abilities before completing eyes open resting state and the attention network test (ANT), a common flanker task that measures ability to orient attention, stay alert, and resolve conflict (i.e. distractor arrows) while recording EEG spectral power at electrodes F3 and F4. Bivariate correlations determine associations between EEG measures and self-reported ADHD symptoms and EF abilities. Linear regressions were used to assess whether EEG change scores were predictive of ADHD symptoms over and above EF abilities.

RESULTS

High correlation coefficients were found only when comparing the ASRS and BRIEF-A GEC T-scores (r = .822, p <.001). Regression analyses produced significant results indicating EEG spectral change scores were predictive of ADHD symptoms, over and above GEC T-Scores, for the alpha band but not the theta and beta bands. Additionally, we found an inverse relationship when comparing change scores in the alpha band across the right (F4) and left (F3) hemispheres supporting the theory of frontal asymmetry for individuals with increased ADHD symptoms.

CONCLUSION

This study is the first to assess the predictive ability of EEG spectral power change scores in predicting ADHD symptoms, which are not solely explained by deficits in executive control. Past research has indicated significant differences when comparing task and resting state spectral power indicating change scores might have some utility in measuring cognitive load, specifically in the alpha band, which has been associated with inhibition, working memory, and anticipation of stimuli. Further research should be conducted to assess the utility change scores might have in providing an objective measure related to a clinical population with ADHD.

Test-Retest Reliability of EEG Aperiodic Components in Resting and Mental Task States

Aperiodic activity is derived from the electroencephalography (EEG) power spectrum and reflects changes in the slope and shifts of the broadband spectrum. Studies have shown inconsistent test-retest reliability of the aperiodic components. This study systematically measured how the test-retest reliability of the aperiodic components was affected by data duration (1, 2, 3, 4, and 5 min), states (resting with eyes closed, resting with eyes open, performing mental arithmetic, recalling the events of the day, and mentally singing songs), and methods (the Fitting Oscillations and One-Over-F (FOOOF) and Linear Mixed-Effects Regression (LMER)) at both short (90-min) and long (one-month) intervals. The results showed that aperiodic components had fair, good, or excellent test-retest reliability (ranging from 0.53 to 0.91) at both short and long intervals. It is recommended that better reliability of the aperiodic components be obtained using data durations longer than 3 min, the resting state with eyes closed, the mental arithmetic task state, and the LMER method.

Neurofeedback technique for treating male schizophrenia patients with impulsive behavior: a randomized controlled study

Background

Schizophrenia is one of the most severe mental disorders, frequently associated with aggression and violence, particularly in male patients. The underlying mechanisms of violent behavior in these patients remain unclear, limiting effective treatment options and highlighting the need for further research into interventions for impulsive behaviors. This study aims to evaluate the clinical efficacy of neurofeedback treatment in hospitalized male schizophrenia patients exhibiting impulsive behaviors.

Methods

The study was designed as a single-center, randomized, single-blind, sham-controlled parallel trial. Eighty patients were randomly assigned to either a study group or a control group. The control group received risperidone and sham neurofeedback, while the study group received risperidone and active neurofeedback therapy. Both groups underwent training five times per week, with each session lasting 20 minutes, over a six-week period. Clinical symptoms were assessed at baseline, three weeks and six weeks using the Positive and Negative Syndrome Scale (PANSS), the Modified Overt Aggression Scale (MOAS), and the Rating Scale for Extrapyramidal Side Effects (RSESE). Statistical analyses were conducted to compare the therapeutic effects between the two groups at the study's conclusion.

Results

Initial comparisons showed no significant differences in baseline data, except for the number of prior hospitalizations (P<0.018). By the end of the study, the study group demonstrate significant improvements in MOAS and PANSS scores (including the Excited, Positive, Cognitive, and Depressive/Anxiety Components), with no significant changes in RSESE scores.

Discussion

Both time and group interactions were significant across most outcomes, underscoring the efficacy of neurofeedback in reducing the severity of impulsive behaviors and associated schizophrenia symptoms.

Clinical trial registration

chictr.org.cn, identifier ChiCTR2200063407.

Delayed modulation of alpha band activity increases response inhibition deficits in adolescents with AD(H)D

Deficiencies in inhibitory control are one of the hallmarks of attention-deficit-(hyperactivity) disorder (AD(H)D). Response inhibition demands can become increased through additional conflicts, namely when already integrated representations of perception-action associations have to be updated. Yet, the neural mechanisms of how such conflicts worsen response inhibition in AD(H)D are unknown, but, if identified, could help to better understand the complex nature of AD(H)D-associated impulsivity. We investigated both behavioral performance and EEG activity in the theta and alpha band of adolescents (10-18 years of age) with AD(H)D (n = 28) compared to neurotypical (NT) controls (n = 33) in a conflict-modulated Go/Nogo paradigm. We used multivariate pattern analysis (MVPA) and EEG-beamforming to examine how changes in representational content are coded by oscillatory activity and to delineate the cortical structures involved in it. The presented behavioral and neurophysiological data show that adolescents with AD(H)D are more strongly affected by increased response inhibition demands through additional conflicts than NT controls. Precisely, AD(H)D participants showed higher false alarm rates than NT controls in both, non-overlapping and overlapping Nogo trials, but performed even worse in the latter. This is likely due to an inefficient updating of representations related to delayed modulations of alpha band activity in the ventral stream and orbitofrontal regions. Theta band activity is also modulated by conflict but was not differentially affected in the two groups. By this, the present study provides novel insights into underlying neurophysiological mechanisms of the complex nature of response inhibition deficits in adolescents with AD(H)D, stressing the importance to examine the interplay of theta and alpha band activity more closely to better understand inhibitory control deficits in AD(H)D.

Effect of nanoplastic intake on the dopamine system during the development of male mice

Exposure to environmental microplastics has been demonstrated to impact health. However, its effect on development remains unclear. This study investigated whether consumption of nanoplastics (NPx) during development affects social and cognitive functions in rodents. In this study, we utilized male Institute of Cancer Research mice; they were divided into five subgroups based on the duration of NPx administration. NPx (100 nm) was orally administered via gavage for 6 days from gestational day (GTD) 7, representing the mid-gestation period, and for 5-6 days from GTD13 to birth, representing the late-gestation period; the male offspring were used for experiments. NPx was orally administered for 15 days starting at postnatal day (PND) 21 as the juvenile, PND38 as the adolescent, and PND56 as adulthood. On PND77, offspring were assessed for locomotion, social behavior, and nest-building tests. We observed that NPx administration altered dopamine system responses in GTD13 and PND56 groups. Social behavior was similarly affected by NPx treatment, with GTD13 and PND56 groups displaying decreased familiarity. Additionally, NPx treatment enhanced local field potentials in the prefrontal cortex, nucleus accumbens, and amygdala of GTD7 group and in the striatum of GTD13 group, while amphetamine treatment induced changes of local field potentials compared to saline treatment in the prefrontal cortex and the ventral tegmental area of CTR, GTD7, PND21, and PND56 groups. Taken together, these results showed that NPx treatment induced changes in social behavior partly depending on developmental stage, and these changes are associated with neural circuits innervated by the dopamine system.

A Decade of Dedication: Pioneering Perspectives on Neurological Diseases and Mental Illnesses

Welcome to Biomedicines' 10th Anniversary Special Issue, a journey through the human mind's labyrinth and complex neurological pathways [...].

Innovation at the Intersection: Emerging Translational Research in Neurology and Psychiatry

Translational research in neurological and psychiatric diseases is a rapidly advancing field that promises to redefine our approach to these complex conditions [...].

Minimum spanning tree analysis of EEG resting-state functional networks in schizophrenia

Schizophrenia is a serious and complex mental disease, known to be associated with various subtle structural and functional deviations in the brain. Recently, increased attention is given to the analysis of brain-wide, global mechanisms, strongly altering the communication of long-distance brain areas in schizophrenia. Data of 32 patients with schizophrenia and 28 matched healthy control subjects were analyzed. Two minutes long 64-channel EEG recordings were registered during resting, eyes closed condition. Average connectivity strength was estimated with Weighted Phase Lag Index (wPLI) in lower frequencies: delta and theta, and Amplitude Envelope Correlation with leakage correction (AEC-c) in higher frequencies: alpha, beta, lower gamma and higher gamma. To analyze functional network topology Minimum Spanning Tree (MST) algorithms were applied. Results show that patients have weaker functional connectivity in delta and alpha frequency bands. Concerning network differences, the result of lower diameter, higher leaf number, and also higher maximum degree and maximum betweenness centrality in patients suggest a star-like, and more random network topology in patients with schizophrenia. Our findings are in accordance with some previous findings based on resting-state EEG (and fMRI) data, suggesting that MST network structure in schizophrenia is biased towards a less optimal, more centralized organization.

Individual Alpha Frequency Contributes to the Precision of Human Visual Processing

Brain oscillatory activity within the alpha band has been associated with a wide range of processes encompassing perception, memory, decision-making, and overall cognitive functioning. Individual alpha frequency (IAF) is a specific parameter accounting for the mean velocity of the alpha cycling activity, conventionally ranging between ∼7 and ∼13 Hz. One influential hypothesis has proposed a fundamental role of this cycling activity in the segmentation of sensory input and in the regulation of the speed of sensory processing, with faster alpha oscillations resulting in greater temporal resolution and more refined perceptual experience. However, although several recent theoretical and empirical studies would support this account, contradictory evidence suggests caution and more systematic approaches in the assessment and interpretation of this hypothesis. For example, it remains to be explored to what degree IAF shapes perceptual outcomes. In the present study, we investigated whether inter-individual differences in bias-free visual contrast detection threshold in a large sample of individuals in the general population (n = 122) could be explained by inter-individual differences in alpha pace. Our results show that the contrast needed to correctly identify target stimuli (individual perceptual threshold) is associated with alpha peak frequency (not amplitude). Specifically, individuals who require reduced contrast show higher IAF than individuals requiring higher contrasts. This suggests that inter-individual differences in alpha frequency contribute to performance variability in low-level perceptual tasks, supporting the hypothesis that IAF underlies a fundamental temporal sampling mechanism that shapes visual objective performance, with higher frequencies promoting enhanced sensory evidence per time unit.

Improving Neuroplasticity through Robotic Verticalization Training in Patients with Minimally Conscious State: A Retrospective Study

In disorders of consciousness, verticalization is considered an effective type of treatment to improve motor and cognitive recovery. Our purpose is to investigate neurophysiological effects of robotic verticalization training (RVT) in patients with minimally conscious state (MCS). Thirty subjects affected by MCS due to traumatic or vascular brain injury, attending the intensive Neurorehabilitation Unit of the IRCCS Neurolesi (Messina, Italy), were included in this retrospective study. They were equally divided into two groups: the control group (CG) received traditional verticalization with a static bed and the experimental group (EG) received advanced robotic verticalization using the Erigo device. Each patient was evaluated using both clinical scales, including Levels of Cognitive Functioning (LCF) and Functional Independence Measure (FIM), and quantitative EEG pre (T0) and post each treatment (T1). The treatment lasted for eight consecutive weeks, and sessions were held three times a week, in addition to standard neurorehabilitation. In addition to a notable improvement in clinical parameters, such as functional (FIM) (p < 0.01) and cognitive (LCF) (p < 0.01) outcomes, our findings showed a significant modification in alpha and beta bands post-intervention, underscoring the promising effect of the Erigo device to influence neural plasticity and indicating a noteworthy difference between pre-post intervention. This was not observed in the CG. The observed changes in alpha and beta bands underscore the potential of the Erigo device to induce neural plasticity. The device's custom features and programming, tailored to individual patient needs, may contribute to its unique impact on brain responses.

Processing of auditory novelty in human cortex during a semantic categorization task

Auditory semantic novelty - a new meaningful sound in the context of a predictable acoustical environment - can probe neural circuits involved in language processing. Aberrant novelty detection is a feature of many neuropsychiatric disorders. This large-scale human intracranial electrophysiology study examined the spatial distribution of gamma and alpha power and auditory evoked potentials (AEP) associated with responses to unexpected words during performance of semantic categorization tasks. Participants were neurosurgical patients undergoing monitoring for medically intractable epilepsy. Each task included repeatedly presented monosyllabic words from different talkers ("common") and ten words presented only once ("novel"). Targets were words belonging to a specific semantic category. Novelty effects were defined as differences between neural responses to novel and common words. Novelty increased task difficulty and was associated with augmented gamma, suppressed alpha power, and AEP differences broadly distributed across the cortex. Gamma novelty effect had the highest prevalence in planum temporale, posterior superior temporal gyrus (STG) and pars triangularis of the inferior frontal gyrus; alpha in anterolateral Heschl's gyrus (HG), anterior STG and middle anterior cingulate cortex; AEP in posteromedial HG, lower bank of the superior temporal sulcus, and planum polare. Gamma novelty effect had a higher prevalence in dorsal than ventral auditory-related areas. Novelty effects were more pronounced in the left hemisphere. Better novel target detection was associated with reduced gamma novelty effect within auditory cortex and enhanced gamma effect within prefrontal and sensorimotor cortex. Alpha and AEP novelty effects were generally more prevalent in better performing participants. Multiple areas, including auditory cortex on the superior temporal plane, featured AEP novelty effect within the time frame of P3a and N400 scalp-recorded novelty-related potentials. This work provides a detailed account of auditory novelty in a paradigm that directly examined brain regions associated with semantic processing. Future studies may aid in the development of objective measures to assess the integrity of semantic novelty processing in clinical populations.

Closed-Loop Brain Stimulation

In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.

From Lab to Life: Exploring Cutting-Edge Models for Neurological and Psychiatric Disorders

Neuroscience, neurology, and psychiatry are rapidly evolving fields that aim to understand the complex mechanisms underlying brain function and dysfunction, as well as to develop effective interventions for various neurological and psychiatric disorders [...].

Targeting Human Glucocorticoid Receptors in Fear Learning: A Multiscale Integrated Approach to Study Functional Connectivity

Fear extinction is a phenomenon that involves a gradual reduction in conditioned fear responses through repeated exposure to fear-inducing cues. Functional brain connectivity assessments, such as functional magnetic resonance imaging (fMRI), provide valuable insights into how brain regions communicate during these processes. Stress, a ubiquitous aspect of life, influences fear learning and extinction by changing the activity of the amygdala, prefrontal cortex, and hippocampus, leading to enhanced fear responses and/or impaired extinction. Glucocorticoid receptors (GRs) are key to the stress response and show a dual function in fear regulation: while they enhance the consolidation of fear memories, they also facilitate extinction. Accordingly, GR dysregulation is associated with anxiety and mood disorders. Recent advancements in cognitive neuroscience underscore the need for a comprehensive understanding that integrates perspectives from the molecular, cellular, and systems levels. In particular, neuropharmacology provides valuable insights into neurotransmitter and receptor systems, aiding the investigation of mechanisms underlying fear regulation and potential therapeutic targets. A notable player in this context is cortisol, a key stress hormone, which significantly influences both fear memory reconsolidation and extinction processes. Gaining a thorough understanding of these intricate interactions has implications in terms of addressing psychiatric disorders related to stress. This review sheds light on the complex interactions between cognitive processes, emotions, and their neural bases. In this endeavor, our aim is to reshape the comprehension of fear, stress, and their implications for emotional well-being, ultimately aiding in the development of therapeutic interventions.

Transcranial Alternating Current Stimulation (tACS) and Its Role in Schizophrenia: A Scoping Review

Transcranial alternating current stimulation (tACS) may modulate neuronal oscillations by applying sinusoidal alternating current, thereby alleviating associated symptoms in schizophrenia. Considering its possible utility in schizophrenia, we reviewed the literature for tACS protocols administered in schizophrenia and their findings. A scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline in databases and clinical trial registers. The search resulted in 59 publications. After excluding review articles unrelated to tACS, trials without published results or not involving patients with schizophrenia, 14 studies were included. Among the included studies/case reports only 5 were randomized controlled therapeutic trials. The studies investigated the utility of tACS for clinical and neurobiological outcomes. All studies reported good tolerability with only transient mild side effects. It was administered mostly during the working memory task (such as computerized n-back task, dual back task, and computerized digit symbol substitution task) for schizophrenia patients with cognitive deficits and during resting state while targeting positive symptoms. A possible reduction in hallucinations and delusions using alpha tACS, and improvement in negative and cognitive deficits with theta and gamma tACS were reported. Nevertheless, one of the randomized controlled trials targeting hallucinations was negative and rigorous large-sample studies are lacking for other domains. The current evidence for tACS in schizophrenia is preliminary though promising. In future, more sham controlled randomized trials assessing the effect of tACS on various domains are needed to substantiate these early findings.

Predictive Biomarkers of Treatment Response in Major Depressive Disorder

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain's electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Logistic regression modeling was used to predict treatment response, defined as at least a 50% improvement on the Beck's Depression Inventory, in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). The results show that both age and baseline symptom severity were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance. These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.

Aperiodic neural activity is a biomarker for depression severity

A reliable physiological biomarker for Major Depressive Disorder (MDD) is necessary to improve treatment success rates by shoring up variability in outcome measures. In this study, we establish a passive biomarker that tracks with changes in mood on the order of minutes to hours. We record from intracranial electrodes implanted deep in the brain - a surgical setting providing exquisite temporal and spatial sensitivity to detect this relationship in a difficult-to-measure brain area, the ventromedial prefrontal cortex (VMPFC). The aperiodic slope of the power spectral density captures the balance of activity across all frequency bands and is construed as a putative proxy for excitatory/inhibitory balance in the brain. This study demonstrates how shifts in aperiodic slope correlate with depression severity in a clinical trial of deep brain stimulation for treatment-resistant depression (TRD). The correlation between depression severity scores and aperiodic slope is significant in N=5 subjects, indicating that flatter (less negative) slopes correspond to reduced depression severity, especially in the ventromedial prefrontal cortex. This biomarker offers a new way to track patient response to MDD treatment, facilitating individualized therapies in both intracranial and non-invasive monitoring scenarios.

Emerging Translational Research in Neurological and Psychiatric Diseases: From In Vitro to In Vivo Models

Revealing the underlying pathomechanisms of neurological and psychiatric disorders, searching for new biomarkers, and developing novel therapeutics all require translational research [...].

KRAS/NRAS Mutations Associated with Distant Metastasis and BRAF/PIK3CA Mutations Associated with Poor Tumor Differentiation in Colorectal Cancer

Background

The occurrence, progression, and prognosis of colorectal cancer (CRC) are regulated by EGFR-mediated signaling pathways. However, the relationship between the core genes (KRAS/NRAS/BRAF/PIK3CA) status in the signaling pathways and clinicopathological characteristics of CRC patients in Hakka population remains controversial.

Methods

Patients were genotyped for KRAS (codons 12, 13, 61, 117, and 146), NRAS (codons 12, 61, 117, and 146), BRAF (codons 600), and PIK3CA (codons 542, 545 and 1047) mutations. Clinical records were collected, and clinicopathological characteristic associations were analyzed together with mutations of studied genes.

Results

Four hundred and eight patients (256 men and 152 women) were included in the analysis. At least one mutation in the four genes was detected in 216 (52.9%) patients, while none was detected in 192 (47.1%) patients. KRAS, NRAS, BRAF, and PIK3CA mutation status were detected in 190 (46.6%), 11 (2.7%), 10 (2.5%), 34 (8.3%) samples, respectively. KRAS exon 2 had the highest proportion (62.5%). Age, tumor site, tumor size, lymphovascular invasion, and perineural invasion were not associated with gene mutations. KRAS mutations (adjusted OR 1.675, 95% CI 1.017-2.760, P=0.043) and NRAS mutations (adjusted OR 5.183, 95% CI 1.239-21.687, P=0.024) appeared more frequently in patients with distant metastasis. BRAF mutations (adjusted OR 7.224, 95% CI 1.356-38.488, P=0.021) and PIK3CA mutations (adjusted OR 3.811, 95% CI 1.268-11.455, P=0.017) associated with poorly differentiated tumor.

Conclusion

KRAS/NRAS mutations are associated with distant metastasis and BRAF/PIK3CA mutations are associated with poor tumor differentiation in CRC. And the results provided a better understanding between clinicopathological characteristics and gene mutations in CRC patients.

Neural Signatures of Predictive Strategies Track Individuals Along the Autism-Schizophrenia Continuum

BACKGROUND AND HYPOTHESIS

Humans develop a constellation of different representations of the external environment, even in the face of the same sensory exposure. According to the Bayesian framework, these differentiations could be grounded in a different weight assigned to prior knowledge vs. new external inputs in predictive inference. Since recent advances in computational psychiatry suggest that autism (ASD) and schizophrenia (SSD) lie on the two diametric poles of the same predictive continuum, the adoption of a specific inferential style could be routed by dispositional factors related to autistic and schizotypal traits. However, no studies have directly investigated the role of ASD-SSD dimension in shaping the neuro-behavioral markers underlying perceptual inference.

STUDY DESIGN

We used a probabilistic detection task while simultaneously recording EEG to investigate whether neurobehavioral signatures related to prior processing were diametrically shaped by ASD and SSD traits in the general population (n = 80).

RESULTS

We found that the position along the ASD-SSD continuum directed the predictive strategies adopted by the individuals in decision-making. While proximity to the positive schizotypy pole was associated with the adoption of the predictive approach associated to the hyper-weighting of prior knowledge, proximity to ASD pole was related to strategies that favored sensory evidence in decision-making.

CONCLUSIONS

These findings revealed that the weight assigned to prior knowledge is a marker of the ASD-SSD continuum, potentially useful for identifying individuals at-risk of developing mental disorders and for understanding the mechanisms contributing to the onset of symptoms observed in ASD and SSD clinical forms.

The Ripple Effect: Unveiling the Bidirectional Relationship Between Negative Life Events and Depressive Symptoms in Medical Cadets

Background

Previous studies have explored the relationship between negative life events and depression, but little is known about the bidirectional relationship between negative life events and depression, particularly in specific groups of medical cadets.

Purpose

This study aimed to explore the relationship between negative life events and depressive symptoms among medical cadets during their four years of college.

Methods

An analysis of 4-wave longitudinal data collected from 2015-2018 was conducted using a cross-lagged panel network (CLPN) model to explore the complex causal relationship between negative life events and depressive symptoms in medical cadets (N=433).

Results

We found differences in negative life events and depressive symptoms among medical cadets across four network models over four years of university. Nodes A-21, A-20, A-23 and A-24, and depressive symptoms D-6 showed greater lagged effect values.

Conclusion

Our findings suggest that there is a lagged and mutually causal interaction between negative life events and depressive symptoms in medical cadets over 4 years of college, but that the predictability of negative life events is more important. However, more attention needs to be paid to the predictive role of depressive symptoms, especially those in early life which are often overlooked. Our study provides new insights into the relationship between negative life events and depressive symptoms in university students and helps to refine strategies for prevention and intervention of depression.

Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models

The alpha rhythm is often associated with relaxed wakefulness or idling and is altered by various factors. Abnormalities in the alpha rhythm have been linked to several neurological and psychiatric disorders, including Alzheimer's disease. Transcranial alternating current stimulation (tACS) has been proposed as a potential tool to restore a disrupted alpha rhythm in the brain by stimulating at the individual alpha frequency (IAF), although some research has produced contradictory results. In this study, we applied an IAF-tACS protocol over parieto-occipital areas to a sample of healthy subjects and measured its effects over the power spectra. Additionally, we used computational models to get a deeper understanding of the results observed in the experiment. Both experimental and numerical results showed an increase in alpha power of 8.02% with respect to the sham condition in a widespread set of regions in the cortex, excluding some expected parietal regions. This result could be partially explained by taking into account the orientation of the electric field with respect to the columnar structures of the cortex, showing that the gyrification in parietal regions could generate effects in opposite directions (hyper-/depolarization) at the same time in specific brain regions. Additionally, we used a network model of spiking neuronal populations to explore the effects that these opposite polarities could have on neural activity, and we found that the best predictor of alpha power was the average of the normal components of the electric field. To sum up, our study sheds light on the mechanisms underlying tACS brain activity modulation, using both empirical and computational approaches. Non-invasive brain stimulation techniques hold promise for treating brain disorders, but further research is needed to fully understand and control their effects on brain dynamics and cognition. Our findings contribute to this growing body of research and provide a foundation for future studies aimed at optimizing the use of non-invasive brain stimulation in clinical settings.

The Role of Serotonin in Fear Learning and Memory: A Systematic Review of Human Studies

Fear is characterized by distinct behavioral and physiological responses that are essential for the survival of the human species. Fear conditioning (FC) serves as a valuable model for studying the acquisition, extinction, and expression of fear. The serotonin (5-hydroxytryptamine, 5-HT) system is known to play a significant role in emotional and motivational aspects of human behavior, including fear learning and expression. Accumulating evidence from both animal and human studies suggests that brain regions involved in FC, such as the amygdala, hippocampus, and prefrontal cortex, possess a high density of 5-HT receptors, implicating the crucial involvement of serotonin in aversive learning. Additionally, studies exploring serotonin gene polymorphisms have indicated their potential influence on FC. Therefore, the objective of this work was to review the existing evidence linking 5-HT with fear learning and memory in humans. Through a comprehensive screening of the PubMed and Web of Science databases, 29 relevant studies were included in the final review. These studies investigated the relationship between serotonin and fear learning using drug manipulations or by studying 5-HT-related gene polymorphisms. The results suggest that elevated levels of 5-HT enhance aversive learning, indicating that the modulation of serotonin 5-HT2A receptors regulates the expression of fear responses in humans. Understanding the role of this neurochemical messenger in associative aversive learning can provide insights into psychiatric disorders such as anxiety and post-traumatic stress disorder (PTSD), among others.

Characterizing endogenous delta oscillations in human MEG

Rhythmic activity in the delta frequency range (0.5-3 Hz) is a prominent feature of brain dynamics. Here, we examined whether spontaneous delta oscillations, as found in invasive recordings in awake animals, can be observed in non-invasive recordings performed in humans with magnetoencephalography (MEG). In humans, delta activity is commonly reported when processing rhythmic sensory inputs, with direct relationships to behaviour. However, rhythmic brain dynamics observed during rhythmic sensory stimulation cannot be interpreted as an endogenous oscillation. To test for endogenous delta oscillations we analysed human MEG data during rest. For comparison, we additionally analysed two conditions in which participants engaged in spontaneous finger tapping and silent counting, arguing that internally rhythmic behaviours could incite an otherwise silent neural oscillator. A novel set of analysis steps allowed us to show narrow spectral peaks in the delta frequency range in rest, and during overt and covert rhythmic activity. Additional analyses in the time domain revealed that only the resting state condition warranted an interpretation of these peaks as endogenously periodic neural dynamics. In sum, this work shows that using advanced signal processing techniques, it is possible to observe endogenous delta oscillations in non-invasive recordings of human brain dynamics.

Age, Dose, and Locomotion: Decoding Vulnerability to Ketamine in C57BL/6J and BALB/c Mice

Ketamine has been abused as a psychedelic agent and causes diverse neurobehavioral changes. Adolescence is a critical developmental stage but vulnerable to substances and environmental stimuli. Growing evidence shows that ketamine affects glutamatergic neurotransmission, which is important for memory storage, addiction, and psychosis. To explore diverse biological responses, this study was designed to assess ketamine sensitivity in mice of different ages and strains. Male C57BL/6J and BALB/c mice were studied in adolescence and adulthood separately. An open field test assessed motor behavioral changes. After a 30-min baseline habituation, mice were injected with ketamine (0, 25, and 50 mg/kg), and their locomotion was measured for 60 min. Following ketamine injection, the travelled distance and speed significantly increased in C57BL/6J mice between both age groups (p < 0.01), but not in BALB/c mice. The pattern of hyperlocomotion showed that mice were delayed at the higher dose (50 mg/kg) compared to the lower dose (25 mg/kg) of ketamine treatment. Ketamine accentuated locomotor activation in adolescent C57BL/6J mice compared to adults, but not in the BALB/c strain. Here, we show that ketamine-induced locomotor behavior is modulated by dose and age. The discrepancy of neurobehaviors in the two strains of mice indicates that sensitivity to ketamine is biologically determined. This study suggests that individual vulnerability to ketamine's pharmacological responses varies biologically.

Rhythmic TMS as a Feasible Tool to Uncover the Oscillatory Signatures of Audiovisual Integration

Multisensory integration is quintessential to adaptive behavior, with clinical populations showing significant impairments in this domain, most notably hallucinatory reports. Interestingly, altered cross-modal interactions have also been reported in healthy individuals when engaged in tasks such as the Sound-Induced Flash-Illusion (SIFI). The temporal dynamics of the SIFI have been recently tied to the speed of occipital alpha rhythms (IAF), with faster oscillations entailing reduced temporal windows within which the illusion is experienced. In this regard, entrainment-based protocols have not yet implemented rhythmic transcranial magnetic stimulation (rhTMS) to causally test for this relationship. It thus remains to be evaluated whether rhTMS-induced acoustic and somatosensory sensations may not specifically interfere with the illusion. Here, we addressed this issue by asking 27 volunteers to perform a SIFI paradigm under different Sham and active rhTMS protocols, delivered over the occipital pole at the IAF. Although TMS has been proven to act upon brain tissues excitability, results show that the SIFI occurred for both Sham and active rhTMS, with the illusory rate not being significantly different between baseline and stimulation conditions. This aligns with the discrete sampling hypothesis, for which alpha amplitude modulation, known to reflect changes in cortical excitability, should not account for changes in the illusory rate. Moreover, these findings highlight the viability of rhTMS-based interventions as a means to probe the neuroelectric signatures of illusory and hallucinatory audiovisual experiences, in healthy and neuropsychiatric populations.

Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations

Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.

Dissecting Relations between Depression Severity, Antidepressant Use, and Metabolic Syndrome Components in the NHANES 2005-2020

We aimed to dissect the complex relations between depressive symptoms, antidepressant use, and constituent metabolic syndrome (MetS) components in a representative U.S. population sample. A total of 15,315 eligible participants were included from 2005 to March 2020. MetS components were defined as hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, central obesity, and elevated blood glucose. Depressive symptoms were classified as mild, moderate, or severe. Logistic regression was used to evaluate the relationship between depression severity, antidepressant use, individual MetS components and their degree of clustering. Severe depression was associated with the number of MetS components in a graded fashion. ORs for severe depression ranged from 2.08 [95%CI, 1.29-3.37] to 3.35 [95%CI, 1.57-7.14] for one to five clustered components. Moderate depression was associated with hypertension, central obesity, raised triglyceride, and elevated blood glucose (OR = 1.37 [95%CI, 1.09-1.72], 1.82 [95%CI, 1.21-2.74], 1.63 [95%CI, 1.25-2.14], and 1.37 [95%CI, 1.05-1.79], respectively). Antidepressant use was associated with hypertension (OR = 1.40, 95%CI [1.14-1.72]), raised triglyceride (OR = 1.43, 95%CI [1.17-1.74]), and the presence of five MetS components (OR = 1.74, 95%CI [1.13-2.68]) after adjusting for depressive symptoms. The depression severity and antidepressant use were associated with individual MetS components and their graded clustering. Metabolic abnormalities in patients with depression need to be recognized and treated.

Outcome Evaluation in Social Comparison: When You Deviate from Others

Individuals often measure their performance through social comparison. With the increase in the deviation degree between the self and others, the outcome evaluation of individuals' abilities in the social comparison context is still unknown. In the current study, we used a two self-outcomes × three others' outcomes within-participant design to investigate the effect of the deviation degree of the self versus others in the social comparison context. Event-related potentials (ERPs) were measured while participants performed a three-person dot estimation task with two other people. When participants received positive results, the amplitudes of feedback-related negativity (FRN) and P300 showed a significant gradient change in the degree of deviation between the self and others (even win vs. better win vs. best win conditions). However, we did not find a similar progressive effect when participants received negative results (even loss vs. worse loss vs. worst loss conditions). These findings suggest that the deviation degree affects the primary and later processing stages of social comparison outcomes only when individuals received positive outcomes, which may reflect how people develop an empathic response to others. In contrast, people tended to avoid deeper social comparison that threatened their self-esteem when they received negative outcomes.

Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review

We review the research progress on noninvasive neural regulatory systems through system design and theoretical guidance. We provide an overview of the development history of noninvasive neuromodulation technology, focusing on system design. We also discuss typical cases of neuromodulation that use modern noninvasive electrical stimulation and the main limitations associated with this technology. In addition, we propose a closed-loop system design solution of the "time domain", "space domain", and "multi-electrode combination". For theoretical guidance, this paper provides an overview of the "digital brain" development process used for noninvasive electrical-stimulation-targeted modeling and the development of "digital human" programs in various countries. We also summarize the core problems of the existing "digital brain" used for noninvasive electrical-stimulation-targeted modeling according to the existing achievements and propose segmenting the tissue. For this, the tissue parameters of a multimodal image obtained from a fresh cadaver were considered as an index. The digital projection of the multimodal image of the brain of a living individual was implemented, following which the segmented tissues could be reconstructed to obtain a "digital twin brain" model with personalized tissue structure differences. The "closed-loop system" and "personalized digital twin brain" not only enable the noninvasive electrical stimulation of neuromodulation to achieve the visualization of the results and adaptive regulation of the stimulation parameters but also enable the system to have individual differences and more accurate stimulation.

Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies

Background

Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease.

Methods

In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM).

Results

Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions.

Conclusion

This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.

Biomarkers of Neurodegeneration in Post-Traumatic Stress Disorder: An Integrative Review

Post-Traumatic Stress Disorder (PTSD) is a chronic psychiatric disorder that occurs following exposure to traumatic events. Recent evidence suggests that PTSD may be a risk factor for the development of subsequent neurodegenerative disorders, including Alzheimer's dementia and Parkinson's disease. Identification of biomarkers known to be associated with neurodegeneration in patients with PTSD would shed light on the pathophysiological mechanisms linking these disorders and would also help in the development of preventive strategies for neurodegenerative disorders in PTSD. With this background, the PubMed and Scopus databases were searched for studies designed to identify biomarkers that could be associated with an increased risk of neurodegenerative disorders in patients with PTSD. Out of a total of 342 citations retrieved, 29 studies were identified for inclusion in the review. The results of these studies suggest that biomarkers such as cerebral cortical thinning, disrupted white matter integrity, specific genetic polymorphisms, immune-inflammatory alterations, vitamin D deficiency, metabolic syndrome, and objectively documented parasomnias are significantly associated with PTSD and may predict an increased risk of subsequent neurodegenerative disorders. The biological mechanisms underlying these changes, and the interactions between them, are also explored. Though requiring replication, these findings highlight a number of biological pathways that plausibly link PTSD with neurodegenerative disorders and suggest potentially valuable avenues for prevention and early intervention.

Paraneoplastic Neurological Syndromes of the Central Nervous System: Pathophysiology, Diagnosis, and Treatment

Paraneoplastic neurological syndromes (PNS) include any symptomatic and non-metastatic neurological manifestations associated with a neoplasm. PNS associated with antibodies against intracellular antigens, known as "high-risk" antibodies, show frequent association with underlying cancer. PNS associated with antibodies against neural surface antigens, known as "intermediate- or low-risk" antibodies, are less frequently associated with cancer. In this narrative review, we will focus on PNS of the central nervous system (CNS). Clinicians should have a high index of suspicion with acute/subacute encephalopathies to achieve a prompt diagnosis and treatment. PNS of the CNS exhibit a range of overlapping "high-risk" clinical syndromes, including but not limited to latent and overt rapidly progressive cerebellar syndrome, opsoclonus-myoclonus-ataxia syndrome, paraneoplastic (and limbic) encephalitis/encephalomyelitis, and stiff-person spectrum disorders. Some of these phenotypes may also arise from recent anti-cancer treatments, namely immune-checkpoint inhibitors and CAR T-cell therapies, as a consequence of boosting of the immune system against cancer cells. Here, we highlight the clinical features of PNS of the CNS, their associated tumors and antibodies, and the diagnostic and therapeutic strategies. The potential and the advance of this review consists on a broad description on how the field of PNS of the CNS is constantly expanding with newly discovered antibodies and syndromes. Standardized diagnostic criteria and disease biomarkers are fundamental to quickly recognize PNS to allow prompt treatment initiation, thus improving the long-term outcome of these conditions.

Electrophysiological and Behavioral Effects of Alpha-Band Sensory Entrainment: Neural Mechanisms and Clinical Applications

Alpha-band (7-13 Hz) activity has been linked to visuo-attentional performance in healthy participants and to impaired functionality of the visual system in a variety of clinical populations including patients with acquired posterior brain lesion and neurodevelopmental and psychiatric disorders. Crucially, several studies suggested that short uni- and multi-sensory rhythmic stimulation (i.e., visual, auditory and audio-visual) administered in the alpha-band effectively induces transient changes in alpha oscillatory activity and improvements in visuo-attentional performance by synchronizing the intrinsic brain oscillations to the external stimulation (neural entrainment). The present review aims to address the current state of the art on the alpha-band sensory entrainment, outlining its potential functional effects and current limitations. Indeed, the results of the alpha-band entrainment studies are currently mixed, possibly due to the different stimulation modalities, task features and behavioral and physiological measures employed in the various paradigms. Furthermore, it is still unknown whether prolonged alpha-band sensory entrainment might lead to long-lasting effects at a neural and behavioral level. Overall, despite the limitations emerging from the current literature, alpha-band sensory entrainment may represent a promising and valuable tool, inducing functionally relevant changes in oscillatory activity, with potential rehabilitative applications in individuals characterized by impaired alpha activity.

A Convenient All-Cell Optical Imaging Method Compatible with Serial SEM for Brain Mapping

The mammalian brain, with its complexity and intricacy, poses significant challenges for researchers aiming to understand its inner workings. Optical multilayer interference tomography (OMLIT) is a novel, promising imaging technique that enables the mapping and reconstruction of mesoscale all-cell brain atlases and is seamlessly compatible with tape-based serial scanning electron microscopy (SEM) for microscale mapping in the same tissue. However, currently, OMLIT suffers from imperfect coatings, leading to background noise and image contamination. In this study, we introduced a new imaging configuration using carbon spraying to eliminate the tape-coating step, resulting in reduced noise and enhanced imaging quality. We demonstrated the improved imaging quality and validated its applicability through a correlative light-electron imaging workflow. Our method successfully reconstructed all cells and vasculature within a large OMLIT dataset, enabling basic morphological classification and analysis. We also show that this approach can perform effectively on thicker sections, extending its applicability to sub-micron scale slices, saving sample preparation and imaging time, and increasing imaging throughput. Consequently, this method emerges as a promising candidate for high-speed, high-throughput brain tissue reconstruction and analysis. Our findings open new avenues for exploring the structure and function of the brain using OMLIT images.

Hierarchical psychophysiological pathways subtend perceptual asymmetries in Neglect

Stroke patients with left Hemispatial Neglect (LHN) show deficits in perceiving left contralesional stimuli with biased visuospatial perception towards the right hemifield. However, very little is known about the functional organization of the visuospatial perceptual neural network and how this can account for the profound reorganization of space representation in LHN. In the present work, we aimed at (1) identifying EEG measures that discriminate LHN patients against controls and (2) devise a causative neurophysiological model between the discriminative EEG measures. To these aims, EEG was recorded during exposure to lateralized visual stimuli which allowed for pre-and post-stimulus activity investigation across three groups: LHN patients, lesioned controls, and healthy individuals. Moreover, all participants performed a standard behavioral test assessing the perceptual asymmetry index in detecting lateralized stimuli. The between-groups discriminative EEG patterns were entered into a Structural Equation Model for the identification of causative hierarchical associations (i.e., pathways) between EEG measures and the perceptual asymmetry index. The model identified two pathways. A first pathway showed that the combined contribution of pre-stimulus frontoparietal connectivity and individual-alpha-frequency predicts post-stimulus processing, as measured by visual-evoked N100, which, in turn, predicts the perceptual asymmetry index. A second pathway directly links the inter-hemispheric distribution of alpha-amplitude with the perceptual asymmetry index. The two pathways can collectively explain 83.1% of the variance in the perceptual asymmetry index. Using causative modeling, the present study identified how psychophysiological correlates of visuospatial perception are organized and predict the degree of behavioral asymmetry in LHN patients and controls.