Reviews in the Neurosciences最新文献

Decision making is frequently influenced by factors such as an individual's emotional state, cognitive biases, social influences, and environmental constraints. Understanding how these factors influence the way decisions are made is essential for optimizing and improving this cognitive process. Therefore, this review examines the theoretical basis of emotion-influenced decision making. Here, we integrate insights from eye-tracking, electroencephalography (EEG), and magnetic resonance imaging (MRI) evidence, as well as behavioral findings. We specifically review evidence from studies applying the Wheel of Fortune Gambling Task paradigm. Through critical and reflective synthesis, we (1) present suggestions for distinguishing between emotion types in decision-making theoretical models, (2) identify key research gaps, and (3) explore innovative applications of emerging technologies. In essence, our review highlights the role of diverse emotions in decision making across theoretical models and neural mechanisms, utilizing the Wheel of Fortune Gambling Task paradigm to link clinical disorders with decision-making impairments. This knowledge may have implications for predicting and intervening in behavioral addictions and cognitive disorders through strategies such as the neuromodulation. Additionally, by synthesizing existing knowledge and proposing new avenues for research, this review aims to deepen understanding of emotion-driven decision making and inspire further exploration into this vital area of cognitive science.

Since the 19th century, the study of brain mechanisms of language has depended on available tools: the clinical study of language-impaired patients, with neuropathological correlates, in the style of Broca and Wernicke; imaging techniques including MRI, functional MRI, and MRI tractography; and direct stimulation of, and recording from, the brains of conscious patients performing language tasks. These tasks can be directed or spontaneous and occur typically in the course of evaluations prior to surgery or intraoperatively. The study of brain and language occurs in the context of classical linguistics, with its (relative) distinctions between semantics and syntax, and its requirements for formal analysis in the latter. A consequence has been the effort to parcellate regions of the left hemisphere (of most individuals) in terms of distinct linguistic functions, and to characterize the anatomical connections between parcels: the various fascicles. In parallel, invasive brain recordings of activity at the level of networks or multiple single cells have allowed correlation of localized electrical signals with linguistic parameters. Recently, however, a paradigm shift has begun concerning the proper framework for interpreting language-related brain measurements. Partly this has occurred because of the success of large language models (LLMs), which do not include explicit dependence on formal syntactic/semantic distinctions. As a result, electrical brain measurements are now examined with a focus on interactions between multiple small cortical "modules." In this paper, we examine the cellular physiology underlying the activities of modules and their interactions, with emphasis on the mechanisms and functions of fast brain oscillations.

Elucidating the factors that influence the recovery of impaired consciousness in patients with prolonged disorders of consciousness (pDoC) is essential for guiding neurorehabilitation strategies and improving prognostic accuracy. This review synthesizes evidence from multiple studies that investigated prognostic factors in pDoC using various approaches, including clinical and demographic characteristics, biomarkers, behavioral assessments, pharmacological treatments, neuromodulation techniques, neuroimaging, and electroencephalography. Results indicate that several indicators show significant correlations with functional outcomes at follow-up intervals ranging from 2 months to several years. These findings assist in selecting appropriate assessment tools and support clinical decision-making for pDoC patients. However, limitations such as small sample sizes, absence of control groups, and heterogeneity in follow-up durations were noted across studies. The development of large-scale, multimodal prognostic models is warranted to enhance clinical applicability and predictive power.

Epilepsy is a neurological condition that affects around 50 million people globally. While the underlying mechanism of epilepsy is not fully understood, emerging evidence demonstrates that inflammation is a key player in the pathogenesis of epilepsy. MicroRNAs are involved in the pathogenesis of epilepsy, particularly through regulating oxidative stress, apoptosis, and inflammation. In this systematic review, we analyzed and summarized data from the literature regarding the role of inflammatory miRNAs in the pathophysiology of epilepsy, through human and animal studies. Twenty one reports on humans and 44 reports on animals were included in the current analysis. Kainic acid (KA) and pilocarpine were broadly used approaches in inducing epilepsy in animal models. Among upregulated microRNAs, miR-146a, miR-155, and miR-132 were more emphasized for their inflammatory role involved in epilepsy. MiR-221, miR-222, and miR-29a were downregulated and were associated with anti-inflammatory effects. Notably, microRNAs demonstrated tissue-specific expression patterns in different samples, including brain cortex, hippocampus, and body fluids, which is considerable in further investigations in the pathophysiologic and diagnostic roles of inflammatory microRNAs in epilepsy. Furthermore, inflammatory miRNAs regulate critical signaling pathways like TLR4/NF-κB, PI3K/Akt, and IL-1β-mediated neuroinflammation. Conclusively, these findings highlight the possibility of using inflammatory miRNAs as diagnostic biomarkers and therapeutic targets of epilepsies.

For several decades, the modeling of brain diseases in experimental animals has remained one of the key components of studying the pathogenesis of central nervous system pathology and searching for new methods of prevention and therapy. In recent years, new approaches to modeling pathological conditions in vitro have been in active development; these approaches will not only reduce the number of animal studies but also allow us to take a step toward reproducing the human-specific mechanisms of brain pathology. In this review, we characterize the most common rodent models of cerebral ischemia and reperfusion, as well as neuroinflammation inherent to neurodegeneration (in particular, Parkinson's disease), which are reproduced in vivo. This review addresses engineering and technical challenges and the prospects for the development of brain pathology models in vitro, e.g., vascularized and microglia-containing/neuroimmune cerebral organoids, which may be useful in overcoming the shortcomings and limitations of the current in vivo models.

Alzheimer's disease (AD), a progressive neurodegenerative disorder, is marked by cognitive decline, neuroinflammation, and neuronal loss. MicroRNAs (miRNAs) have emerged as critical regulators of gene expression, influencing key pathways involved in neuroinflammation and neurodegeneration in AD. This review delves into the multifaceted role of exercise in modulating miRNA expression and its interplay with the gut microbiome, proposing a comprehensive framework for neuroprotection in AD. By synthesizing current research, we elucidate how exercise-induced changes in miRNA profiles can mitigate inflammatory responses, promote neurogenesis, and reduce amyloid-beta and tau pathologies. Additionally, we explore the gut-brain axis, highlighting how exercise-driven alterations in gut microbiota composition can further influence miRNA expression, thereby enhancing cognitive function and reducing neuroinflammatory markers. This holistic approach underscores the potential of targeting exercise-regulated miRNAs and gut microbiome interactions as a novel, noninvasive therapeutic strategy to decelerate AD progression and improve quality of life for patients. This approach aims to decelerate disease progression and improve patient outcomes, offering a promising avenue for enhancing the effectiveness of AD management.

We constructed a computational thalamocortical network model for study of the neocortical slow oscillation. It incorporated a number of neuronal types, both excitatory and inhibitory, each model neuron simulated as a multicompartment entity with numerous membrane conductances. As in previous experimental and modeling studies, simulated slow oscillations primarily depended on recurrently connected deep intrinsic bursting (IB) pyramidal cells, with NMDA receptors being critical as well as intrinsic membrane conductances (e.g. persistent Na⁺); and with repolarization to the Down state dependent on intrinsic (slow Ca²⁺-dependent K⁺) and synaptic (GABA_B receptor mediated) conductances. Furthermore, however, we now can account for additional features of the slow oscillation: the frequent occurrence of spikelets, the presence of very fast ripple-like oscillations, and the transition to so-called fast runs (10 to ∼20 Hz bursty oscillations). These latter phenomena depended in our model on electrical coupling via gap junctions between pyramidal neurons. The importance of gap junctions is supported by previous experimental data on the ripple-blocking effect of halothane, as well as by data from the in vitro hippocampus.

Depression remains one of the most common and debilitating neuropsychiatric conditions, with little consistency in treatment efficacy. Some of the lack of success in developing effective treatments has been the absence of a reliable biomarker of depression, despite many attempts. One such potential biomarker is the electrical activity of the brain that occurs in the gamma band (30-200 Hz). To evaluate the state of research into gamma as a biomarker of depression, a review of recent research literature was conducted. A total of 31 relevant papers was identified, 22 of which used resting-state studies, and nine included a stimulus-task. These studies were examined here in terms of their definition of gamma, sample sizes, research focus, brain region examined, and EEG methodologies used. Due to the range of methodologies, some inconsistent results emerged but several valuable findings remained, including that depressed patients usually had higher gamma power than their healthy controls (HC), that the imposition of a perceptual task into the research protocol also introduced a strong element of confound to the results, and that studies that sought to evaluate the role of gamma in treatment were yet to be established as reliable. Key issues for future research are discussed, and the potential for gamma as a biomarker of depression is evaluated as emerging.

Epilepsy encompasses a group of chronic brain disorders characterized by recurrent, hypersynchronous activity of neuronal clusters, with epileptic seizures being the primary manifestation of these disorders. The objective of epilepsy treatment is to prevent seizures with minimum adverse side effects. However, approximately 30 % of patients do not respond to available medications. One proposed mechanism of epileptogenesis is glutamate excitotoxicity. When released in excess or not appropriately removed from the synaptic cleft, glutamate hyperactivates receptors, causing a biochemical cascade, which culminates in seizures and cell death. The use of animal models is essential for uncovering potential epileptogenic pathways, understanding the role of receptors and transporters in excitotoxicity, and screening effective antiepileptic treatments. This review examines studies that investigate the role of glutamate transporters and receptors in excitotoxicity and epileptogenesis using animal models. For this, we searched through both PubMed/Medline and ScienceDirect databases. After applying the inclusion and exclusion criteria, 26 (twenty-six) studies were selected for analysis. The studies addressed key glutamate transporter family of excitatory amino acid transporters (EAATs) EAAT1, EAAT2, and EAAT3, responsible for glutamate clearance, as well as AMPA receptor subunits GluA1 and GluA2, NMDA receptor subunits GluN1, GluN2a, and GluN2b, and the metabotropic receptors mGluR5 and mGluR2/3. Results showed that the dysregulation of these transporters and receptors is associated to seizure induction and excitotoxic damage, pointing to their fundamental role in the mechanisms of excitotoxicity and epileptogenesis. These findings highlight the potential of targeting glutamate transporters and receptors to stabilize glutamate homeostasis as an intervention in epilepsy management.

Diabetic peripheral neuropathy (DPN) is a serious complication of diabetes mellitus, which is a common cause of disability in individuals with diabetes mellitus. Multiple mechanisms may be involved in the development of DPN. Neuroinflammation is a critical factor contributing to nerve damage during diabetes. Inflammation can induce the development of diabetes mellitus, and long-term hyperglycemia also causes increased oxidative stress and promotes the release of inflammatory cytokines. After reading through the literature, the association of inflammation with the induction of diabetes and DPN was discussed in the review. Inflammation induces nerve damage and nerve conduction impairment. The neuropathic pain in diabetes-induced DPN is also closely associated with the inflammatory response. Given the important roles of inflammation in diabetes-induced DPN, explicit elucidation of neuroinflammation during diabetes mellitus and DPN should hold the potential for developing novel therapeutic strategies for DPN. Experimental studies and limited clinical trials support the value of anti-inflammatory reagents in treating DPN, and the positive outcomes of these investigations warrant further clinical trials.