Dietary sn-2 palmitate influences cognitive behavior by increasing the transport of liver-produced lysophosphatidylcholine VLCPUFAs to the brain.

Investigations indicated that sn-2 palmitate have positive effects on brain development, although its mechanism remains largely unexamined. This research delved into how a diet abundant in sn-2 palmitate influenced the cognitive behavior of mice and elucidated the associated mechanisms using metabolomics and lipidomics. The study demonstrated that dietary sn-2 palmitate led to improved working memory and cognition in mice, as well as an increase in brain BDNF concentration when compared to those fed blend vegetable oil (BVO). This was because sn-2 palmitate feeding promoted the synthesis of very long-chain fatty acids (VLCPUFAs) for the lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) in the liver. This led to more efficient delivery of VLCPUFAs to the brain, as indicated by elevated concentration of LPC/LPE-VLCPUFAs in the liver and heightened expression of the major facilitator superfamily domain containing 2a (MFSD2A). In essence, this paper offered a potential mechanism by which sn-2 palmitate enhanced mouse neurodevelopment.

LC-MS/MS Quantification of Endocannabinoids in Tissues.

Endocannabinoids (ECBs) are lipid-derived endogenous molecules with important physiological roles such as regulation of energy balance, immunity, or neural development. Quantitation of ECBs helps better understand their physiological role and modulation of biological processes. This chapter presents the simultaneous quantification of 14 ECBs and related molecules in the brain, liver, and muscle, as well as white and brown adipose tissue using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The dynamic range of the method has been tuned to cover the endogenous concentrations of these analytes given the fact that they are endogenously present at different orders of magnitude. Specifically, three groups are established: 0.5-5000 ng/mL for 2-oleoyl- and 2-linoleoylglycerol and arachidonic acid, 0.05-500 ng/mL for 2-arachidonoylglycerol, and 0.0005-0.5 ng/mL for anandamide, palmitoyl-, palmitoleoyl-, stearoyl-, oleoyl-, linoleoyl-, alpha-linolenoyl-, dihomo-gamma-linolenoyl-, docosahexaenoyl-, and pentadecanoylethanolamide.

Application of electroencephalogram (EEG) in the study of the influence of different contents of alcohol and Baijiu on brain perception.

Alcoholic beverages flavour is complex and unique with different alcohol content, and the application of flavour perception could improve the objectivity of flavour evaluation. This study utilized electroencephalogram (EEG) to assess brain reactions to alcohol percentages (5 %-53 %) and Baijiu's complex flavours. The findings demonstrate the brain's proficiency in discerning between alcohol concentrations, evidenced by increasing physiological signal strength in tandem with alcohol content. When contrasted with alcohol solutions of equivalent concentrations, Baijiu prompts a more significant activation of brain signals, underscoring EEG's capability to detect subtleties due to flavour complexity. Additionally, the study reveals notable correlations, with δ and α wave intensities escalating in response to alcohol stimulation, coupled with substantial activation in the frontal, parietal, and right temporal regions. These insights verify the efficacy of EEG in charting the brain's engagement with alcoholic flavours, setting the stage for more detailed exploration into the neural encoding of these sensory experiences.

Comparing spatial distributions of ALA-PpIX and indocyanine green in a whole pig brain glioma model using 3D fluorescence cryotomography.

Significance: ALA-PpIX and second-window indocyanine green (ICG) have been studied widely for guiding the resection of high-grade gliomas. These agents have different mechanisms of action and uptake characteristics, which can affect their performance as surgical guidance agents. Elucidating these differences in animal models that approach the size and anatomy of the human brain would help guide the use of these agents. Herein, we report on the use of a new pig glioma model and fluorescence cryotomography to evaluate the 3D distributions of both agents throughout the whole brain. Aim: We aim to assess and compare the 3D spatial distributions of ALA-PpIX and second-window ICG in a glioma-bearing pig brain using fluorescence cryotomography. Approach: A glioma was induced in the brain of a transgenic Oncopig via adeno-associated virus delivery of Cre-recombinase plasmids. After tumor induction, the pro-drug 5-ALA and ICG were administered to the animal 3 and 24 h prior to brain harvest, respectively. The harvested brain was imaged using fluorescence cryotomography. The fluorescence distributions of both agents were evaluated in 3D in the whole brain using various spatial distribution and contrast performance metrics. Results: Significant differences in the spatial distributions of both agents were observed. Indocyanine green accumulated within the tumor core, whereas ALA-PpIX appeared more toward the tumor periphery. Both ALA-PpIX and second-window ICG provided elevated tumor-to-background contrast (13 and 23, respectively). Conclusions: This study is the first to demonstrate the use of a new glioma model and large-specimen fluorescence cryotomography to evaluate and compare imaging agent distribution at high resolution in 3D.

Recording of Age-Related Changes on Murine and Human Brain Slices.

Preparation of brain slices for electrophysiological and imaging experiments has been developed several decades ago, and the method is still widely used due to its simplicity and advantages over other techniques. It can be easily combined with other well established and recently developed methods as immunohistochemistry and morphological analysis or opto- and chemogenetics. Several aspects of this technique are covered by a plethora of excellent and detailed review papers, in which one can gain a deep insight of variations in it. In this chapter, I briefly describe the solutions, equipment, and preparation techniques routinely used in our laboratory. I also aim to present how certain "old school" brain slice lab devices can be made in a cost-efficient way. These devices can be easily adapted for the special needs of the experiments. I also aim to present some differences in the preparatory techniques of acutely isolated human brain tissue.

Modified Ce/Zr-MOF Nanoparticles Loaded with Curcumin for Alzheimer's Disease via Multifunctional Modulation.

Introduction: Alzheimer's disease (AD), a neurodegenerative condition, stands as the most prevalent form of dementia. Its complex pathological mechanisms and the formidable blood-brain barrier (BBB) pose significant challenges to current treatment approaches. Oxidative stress is recognized as a central factor in AD, underscoring the importance of antioxidative strategies in its treatment. In this study, we developed a novel brain-targeted nanoparticle, Ce/Zr-MOF@Cur-Lf, for AD therapy. Methods: Layer-by-layer self-assembly technology was used to prepare Ce/Zr-MOF@Cur-Lf. In addition, the effect on the intracellular reactive oxygen species level, the uptake effect by PC12 and bEnd.3 cells and the in vitro BBB permeation effect were investigated. Finally, the mouse AD model was established by intrahippocampal injection of Aß1-42, and the in vivo biodistribution, AD therapeutic effect and biosafety of the nanoparticles were researched at the animal level. Results: As anticipated, Ce/Zr-MOF@Cur-Lf demonstrated efficient BBB penetration and uptake by PC12 cells, leading to attenuation of H2O2-induced oxidative damage. Moreover, intravenous administration of Ce/Zr-MOF@Cur-Lf resulted in rapid brain access and improvement of various pathological features of AD, including neuronal damage, amyloid-ß deposition, dysregulated central cholinergic system, oxidative stress, and neuroinflammation. Conclusion: Overall, Ce/Zr-MOF@Cur-Lf represents a promising approach for precise brain targeting and multi-target mechanisms in AD therapy, potentially serving as a viable option for future clinical treatment.

Brain-machine convergent evolution: Why finding parallels between brain and artificial systems is informative.

Central nervous system neurons manifest a rich diversity of selectivity profiles-whose precise role is still poorly understood. Following the striking success of artificial networks, a major debate has emerged concerning their usefulness in explaining neuronal properties. Here we propose that finding parallels between artificial and neuronal networks is informative precisely because these systems are so different from each other. Our argument is based on an extension of the concept of convergent evolution-well established in biology-to the domain of artificial systems. Applying this concept to different areas and levels of the cortical hierarchy can be a powerful tool for elucidating the functional role of well-known cortical selectivities. Importantly, we further demonstrate that such parallels can uncover novel functionalities by showing that grid cells in the entorhinal cortex can be modeled to function as a set of basis functions in a lossy representation such as the well-known JPEG compression. Thus, contrary to common intuition, here we illustrate that finding parallels with artificial systems provides novel and informative insights, particularly in those cases that are far removed from realistic brain biology.

GLP-1 programs the neurovascular landscape.

Readily available nutrient-rich foods exploit our inherent drive to overconsume, creating an environment of overnutrition. This transformative setting has led to persistent health issues, such as obesity and metabolic syndrome. The development of glucagon-like peptide-1 receptor (GLP-1R) agonists reveals our ability to pharmacologically manage weight and address metabolic conditions. Obesity is directly linked to chronic low-grade inflammation, connecting our metabolic environment to neurodegenerative diseases. GLP-1R agonism in curbing obesity, achieved by impacting appetite and addressing associated metabolic defects, is revealing additional benefits extending beyond weight loss. Whether GLP-1R agonism directly impacts brain health or does so indirectly through improved metabolic health remains to be elucidated. In exploring the intricate connection between obesity and neurological conditions, recent literature suggests that GLP-1R agonism may have the capacity to shape the neurovascular landscape. Thus, GLP-1R agonism emerges as a promising strategy for addressing the complex interplay between metabolic health and cognitive well-being.

Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.

Understanding the brain requires studying its multiscale interactions from molecules to networks. The increasing availability of large-scale datasets detailing brain circuit composition, connectivity, and activity is transforming neuroscience. However, integrating and interpreting this data remains challenging. Concurrently, advances in supercomputing and sophisticated modeling tools now enable the development of highly detailed, large-scale biophysical circuit models. These mechanistic multiscale models offer a method to systematically integrate experimental data, facilitating investigations into brain structure, function, and disease. This review, based on a Society for Neuroscience 2024 MiniSymposium, aims to disseminate recent advances in large-scale mechanistic modeling to the broader community. It highlights (1) examples of current models for various brain regions developed through experimental data integration; (2) their predictive capabilities regarding cellular and circuit mechanisms underlying experimental recordings (e.g., membrane voltage, spikes, local-field potential, electroencephalography/magnetoencephalography) and brain function; and (3) their use in simulating biomarkers for brain diseases like epilepsy, depression, schizophrenia, and Parkinson's, aiding in understanding their biophysical underpinnings and developing novel treatments. The review showcases state-of-the-art models covering hippocampus, somatosensory, visual, motor, auditory cortical, and thalamic circuits across species. These models predict neural activity at multiple scales and provide insights into the biophysical mechanisms underlying sensation, motor behavior, brain signals, neural coding, disease, pharmacological interventions, and neural stimulation. Collaboration with experimental neuroscientists and clinicians is essential for the development and validation of these models, particularly as datasets grow. Hence, this review aims to foster interest in detailed brain circuit models, leading to cross-disciplinary collaborations that accelerate brain research.

Emerging Functions of Neuromodulation during Sleep.

Neuromodulators act on multiple timescales to affect neuronal activity and behavior. They function as synaptic fine-tuners and master coordinators of neuronal activity across distant brain regions and body organs. While much research on neuromodulation has focused on roles in promoting features of wakefulness and transitions between sleep and wake states, the precise dynamics and functions of neuromodulatory signaling during sleep have received less attention. This review discusses research presented at our minisymposium at the 2024 Society for Neuroscience meeting, highlighting how norepinephrine, dopamine, and acetylcholine orchestrate brain oscillatory activity, control sleep architecture and microarchitecture, regulate responsiveness to sensory stimuli, and facilitate memory consolidation. The potential of each neuromodulator to influence neuronal activity is shaped by the state of the synaptic milieu, which in turn is influenced by the organismal or systemic state. Investigating the effects of neuromodulator release across different sleep substates and synaptic environments offers unique opportunities to deepen our understanding of neuromodulation and explore the distinct computational opportunities that arise during sleep. Moreover, since alterations in neuromodulatory signaling and sleep are implicated in various neuropsychiatric disorders and because existing pharmacological treatments affect neuromodulatory signaling, gaining a deeper understanding of the less-studied aspects of neuromodulators during sleep is of high importance.

Beyond Birth Control: The Neuroscience of Hormonal Contraceptives.

Hormonal contraceptives (HCs) are one of the most highly prescribed classes of drugs in the world used for both contraceptive and noncontraceptive purposes. Despite their prevalent use, the impact of HCs on the brain remains inadequately explored. This review synthesizes recent findings on the neuroscience of HCs, with a focus on human structural neuroimaging as well as translational, nonhuman animal studies investigating the cellular, molecular, and behavioral effects of HCs. Additionally, we consider data linking HCs to mood disorders and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and stress response as a potential mediator. The review also addresses the unique sensitivity of the adolescent brain to HCs, noting significant changes in brain structure and function when HCs are used during this developmental period. Finally, we discuss potential effects of HCs in combination with smoking-derived nicotine on outcomes of ischemic brain damage. Methodological challenges, such as the variability in HC formulations and user-specific factors, are acknowledged, emphasizing the need for precise and individualized research approaches. Overall, this review underscores the necessity for continued interdisciplinary research to elucidate the neurobiological mechanisms of HCs, aiming to optimize their use and improve women's health.

Frustrative Nonreward: Behavior, Circuits, Neurochemistry, and Disorders.

The surprising omission or reduction of vital resources (food, fluid, social partners) can induce an aversive emotion known as frustrative nonreward (FNR), which can influence subsequent behavior and physiology. FNR is an integral mediator of irritability/aggression, motivation (substance use disorders, depression), anxiety/fear/threat, learning/conditioning, and social behavior. Despite substantial progress in the study of FNR during the twentieth century, research lagged in the later part of the century and into the early twenty-first century until the National Institute of Mental Health's Research Domain Criteria initiative included FNR and loss as components of the negative valence domain. This led to a renaissance of new research and paradigms relevant to basic and clinical science alike. The COVID-19 pandemic's extensive individual and social restrictions were correlated with increased drug and alcohol use, social conflict, irritability, and suicide, all potential consequences of FNR. This article highlights animal models related to these psychiatric disorders and symptoms and presents recent advances in identifying the brain regions and neurotransmitters implicated.

Neural Encoding of Bodies for Primate Social Perception.

Primates, as social beings, have evolved complex brain mechanisms to navigate intricate social environments. This review explores the neural bases of body perception in both human and nonhuman primates, emphasizing the processing of social signals conveyed by body postures, movements, and interactions. Early studies identified selective neural responses to body stimuli in macaques, particularly within and ventral to the superior temporal sulcus (STS). These regions, known as body patches, represent visual features that are present in bodies but do not appear to be semantic body detectors. They provide information about posture and viewpoint of the body. Recent research using dynamic stimuli has expanded the understanding of the body-selective network, highlighting its complexity and the interplay between static and dynamic processing. In humans, body-selective areas such as the extrastriate body area (EBA) and fusiform body area (FBA) have been implicated in the perception of bodies and their interactions. Moreover, studies on social interactions reveal that regions in the human STS are also tuned to the perception of dyadic interactions, suggesting a specialized social lateral pathway. Computational work developed models of body recognition and social interaction, providing insights into the underlying neural mechanisms. Despite advances, significant gaps remain in understanding the neural mechanisms of body perception and social interaction. Overall, this review underscores the importance of integrating findings across species to comprehensively understand the neural foundations of body perception and the interaction between computational modeling and neural recording.

Challenges and Approaches in the Study of Neural Entrainment.

When exposed to rhythmic stimulation, the human brain displays rhythmic activity across sensory modalities and regions. Given the ubiquity of this phenomenon, how sensory rhythms are transformed into neural rhythms remains surprisingly inconclusive. An influential model posits that endogenous oscillations entrain to external rhythms, thereby encoding environmental dynamics and shaping perception. However, research on neural entrainment faces multiple challenges, from ambiguous definitions to methodological difficulties when endogenous oscillations need to be identified and disentangled from other stimulus-related mechanisms that can lead to similar phase-locked responses. Yet, recent years have seen novel approaches to overcome these challenges, including computational modeling, insights from dynamical systems theory, sophisticated stimulus designs, and study of neuropsychological impairments. This review outlines key challenges in neural entrainment research, delineates state-of-the-art approaches, and integrates findings from human and animal neurophysiology to provide a broad perspective on the usefulness, validity, and constraints of oscillatory models in brain-environment interaction.

The Brain's Best Kept Secret Is Its Degenerate Structure.

Degeneracy is defined as multiple sets of solutions that can produce very similar system performance. Degeneracy is seen across phylogenetic scales, in all kinds of organisms. In neuroscience, degeneracy can be seen in the constellation of biophysical properties that produce a neuron's characteristic intrinsic properties and/or the constellation of mechanisms that determine circuit outputs or behavior. Here, we present examples of degeneracy at multiple levels of organization, from single-cell behavior, small circuits, large circuits, and, in cognition, drawing conclusions from work ranging from bacteria to human cognition. Degeneracy allows the individual-to-individual variability within a population that creates potential for evolution.

The involvement of K+ channels in depression and pharmacological effects of antidepressants on these channels.

Depression is a common and complex psychiatric illness with multiple clinical symptoms, even leading to the disability and suicide. Owing to the partial understanding of the pathogenesis of depressive-like disorders, available pharmacotherapeutic strategies are developed mainly based on the "monoamine hypothesis", resulting in a limited effectiveness and a number of adverse effects in the clinical practice. The concept of multiple pathogenic factors be helpful for clarifying the etiology of depression and developing the antidepressants. It is well documented that K+ channels serve crucial roles in modulating the neuronal excitability and neurotransmitter release in the brain, and abnormality of these channels participated in the pathogenic process of diverse central nervous system (CNS) pathologies, such as seizure and Alzheimer's disease (AD). The clinical and preclinical evidence also delineates that the involvement of several types of K+ channels in depressive-like behaviors appear to be evident, suggesting these channels being one of the multiple factors in the etiology of this debilitating disorder. Emerging data manifest that diverse antidepressants impact distinct K+ channels, such as Kv, Kir and K2P, meaning the functioning of these drug via a "multi-target" manner. On the other hand, the scenario of antidepressants impinging K+ channels could render an alternative interpretation for the pharmacological effectiveness and numerous side effects in clinical trials. Furthermore, these channels serve to be considered as a "druggable target" to develop novel therapeutic compound to antagonize this psychiatry.

Diminished circadian and ultradian rhythms of human brain activity in pathological tissue in vivo.

Chronobiological rhythms, such as the circadian rhythm, have long been linked to neurological disorders, but it is currently unknown how pathological processes affect the expression of biological rhythms in the brain. Here, we use the unique opportunity of long-term, continuous intracranially recorded EEG from 38 patients (totalling 6338 hours) to delineate circadian (daily) and ultradian (minute to hourly) rhythms in different brain regions. We show that functional circadian and ultradian rhythms are diminished in pathological tissue, independent of regional variations. We further demonstrate that these diminished rhythms are persistent in time, regardless of load or occurrence of pathological events. These findings provide evidence that brain pathology is functionally associated with persistently diminished chronobiological rhythms in vivo in humans, independent of regional variations or pathological events. Future work interacting with, and restoring, these modulatory chronobiological rhythms may allow for novel therapies.

Associations between antagonistic SNPs for neuropsychiatric disorders and human brain structure.

A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required.