Handbook of clinical neurology最新文献

{"title":"Hemispheric asymmetries in episodic memory.","authors":"Gian Daniele Zannino, Giovanni Augusto Carlesimo","doi":"10.1016/B978-0-443-15646-5.00023-3","DOIUrl":"https://doi.org/10.1016/B978-0-443-15646-5.00023-3","url":null,"abstract":"<p><p>The term \"episodic memory\" refers to our ability to remember past personal experiences. This ability is severely disrupted following bilateral damage to a dedicated neural substrate located symmetrically in the mesial temporal lobes. Milder deficits are also observed following unilateral damage to the same structures. In this chapter, we contrast memory deficits after left and right mesiotemporal damage and review some of the hypotheses proposed to account for the observed differences. As proposed by other authors (e.g., Binder et al., 2010), the observed lesion side effects in memory profiles after unilateral brain damage do not directly reflect specialization across the two symmetric memory substrates. Rather, they depend on the different kinds of information each of the two mesiotemporal structures receives from the ipsilateral hemisphere where other non-memory-specific cognitive systems are asymmetrically housed. In particular, this chapter outlines the role of language, working memory, and visuospatial processes in accounting for side effects in memory profiles. This is because all these systems greatly contribute to the functioning of episodic memory and also show a variable extent of lateralization in the human brain.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"208 ","pages":"449-460"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The lateralization of reading.","authors":"Jason J S Barton, Andrea Albonico, Randi Starrfelt","doi":"10.1016/B978-0-443-15646-5.00012-9","DOIUrl":"https://doi.org/10.1016/B978-0-443-15646-5.00012-9","url":null,"abstract":"<p><p>Reports in the 1890s described reading disorders from left hemisphere damage. Subsequent work converging from a variety of research approaches have confirmed a strong dependence of reading on the left ventral occipitotemporal cortex, though there is also evidence for some reading capacity of the right hemisphere. The development of this leftward bias parallels reading acquisition in children and adults and is blunted in developmental dyslexia. Several structural and functional hypotheses have been advanced to explain why reading lateralizes to the left. In the second half of this review we explore the extension of these findings to other forms of reading. Most reading studies used the alphabetic scripts of Europe but there are many writing systems. Comparisons with logographic scripts such as Chinese and kanji have revealed subtle differences. Also, while we often think of reading as the extraction of verbal language from written text, it can be broadened to other types of information extraction from symbols. Reading can occur with visual stimuli that are not written text, as with sign language in the deaf and lip-reading, and with non-visual stimuli that are textual, as with Braille. Musical notation and number reading are other text-based visual forms of reading that do not involve words. Overall, most studies show that the left ventral occipitotemporal cortex is involved in processing these diverse types of reading, with variable contributions from the right hemisphere.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"208 ","pages":"301-325"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurologic prognostication in coma and disorders of consciousness.","authors":"Shubham Biyani, Henry Chang, Vishank A Shah","doi":"10.1016/B978-0-443-13408-1.00017-8","DOIUrl":"https://doi.org/10.1016/B978-0-443-13408-1.00017-8","url":null,"abstract":"<p><p>Coma and disorders of consciousness (DoC) are clinical syndromes primarily resulting from severe acute brain injury, with uncertain recovery trajectories that often necessitate prolonged supportive care. This imposes significant socioeconomic burdens on patients, caregivers, and society. Predicting recovery in comatose patients is a critical aspect of neurocritical care, and while current prognostication heavily relies on clinical assessments, such as pupillary responses and motor movements, which are far from precise, contemporary prognostication has integrated more advanced technologies like neuroimaging and electroencephalogram (EEG). Nonetheless, neurologic prognostication remains fraught with uncertainty and significant inaccuracies and is impacted by several forms of prognostication biases, including self-fulfilling prophecy bias, affective forecasting, and clinician treatment biases, among others. However, neurologic prognostication in patients with disorders of consciousness impacts life-altering decisions including continuation of treatment interventions vs withdrawal of life-sustaining therapies (WLST), which have a direct influence on survival and recovery after severe acute brain injury. In recent years, advancements in neuro-monitoring technologies, artificial intelligence (AI), and machine learning (ML) have transformed the field of prognostication. These technologies have the potential to process vast amounts of clinical data and identify reliable prognostic markers, enhancing prediction accuracy in conditions such as cardiac arrest, intracerebral hemorrhage, and traumatic brain injury (TBI). For example, AI/ML modeling has led to the identification of new states of consciousness such as covert consciousness and cognitive motor dissociation, which may have important prognostic significance after severe brain injury. This chapter reviews the evolving landscape of neurologic prognostication in coma and DoC, highlights current pitfalls and biases, and summarizes the integration of clinical examination, neuroimaging, biomarkers, and neurophysiologic tools for prognostication in specific disease states. We will further discuss the future of neurologic prognostication, focusing on the integration of AI and ML techniques to deliver more individualized and accurate prognostication, ultimately improving patient outcomes and decision-making process in neurocritical care.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"207 ","pages":"237-264"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroglia and the microbiota-gut-brain axis.","authors":"Hugo J Blair, Lorena Morales, John F Cryan, María R Aburto","doi":"10.1016/B978-0-443-19104-6.00001-2","DOIUrl":"https://doi.org/10.1016/B978-0-443-19104-6.00001-2","url":null,"abstract":"<p><p>Glial cells are key players in the regulation of nervous system functioning in both the central and enteric nervous systems. Glial cells are dynamic and respond to environmental cues to modulate their activity. Increasing evidence suggests that these signals include those originating from the gut microbiota, the community of microorganisms, including bacteria, viruses, archaea, and protozoa, that inhabit the gut. The gut microbiota and the brain communicate in a bidirectional manner across multiple signaling pathways and interfaces that together comprise the microbiota-gut-brain axis. Here, we detail the role of glial cells, including astrocytes, microglia, and oligodendrocytes in the central nervous system, and glial cells in the enteric nervous system along this gut-brain axis. We review what is known regarding the modulation of glia by microbial signals, in particular by microbial metabolites which signal to the brain through systemic circulation and via the vagus nerve. In addition, we highlight what is yet to be discovered regarding the role of other gut microbiota signaling pathways in glial cell modulation and the challenges of research in this area.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"209 ","pages":"171-196"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroglia in the healthy brain.","authors":"Alexei Verkhratsky, Elly M Hol, Lot D de Witte, Eleanora Aronica","doi":"10.1016/B978-0-443-19104-6.00008-5","DOIUrl":"https://doi.org/10.1016/B978-0-443-19104-6.00008-5","url":null,"abstract":"<p><p>The nervous tissue is composed of neurons and neuroglia, which by working in a tightly coordinated manner, define the function of the nervous system. Neuroglia, defined as homeostatic and defensive cells of the nervous system, are highly heterogeneous in form and function and are endowed with a remarkable plasticity that allows life-long adaptation to environmental challenges. Neuroglia of the peripheral nervous system are represented by myelinating, nonmyelinating, perisynaptic, and cutaneous Schwann cells, satellite glia of sensory and sympathetic ganglia and enteric glia of the enteric nervous system. Neuroglia of the central nervous system (CNS) are classified into macroglia and microglia. Macroglia in turn are represented by astroglia and oligodendroglia. Astroglia represent an extended class of homeostatic glial cells, which include astrocytes (protoplasmic, fibrous, velate, and marginal), radial astrocytes (Bergmann glial cells, glia-like nervous stem cells, and tanycytes), and ependymoglia. The oligodendroglial lineage is mainly responsible for myelination and support of central axons and is represented by oligodendrocytes and oligodendrocyte precursor cells. Microglia are the cells of nonneural, myeloid origin that invade the neural tube early in embryonic development. These cells are tissue macrophages adapted to the nervous system requirements. Microglia contribute to physiology of the nervous tissue and to the innate immunity and defense of the CNS.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"209 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell omics and heterogeneity of neuroglial cells.","authors":"Sylvie C Lahaie, Naama Brezner, Keith K Murai","doi":"10.1016/B978-0-443-19104-6.00013-9","DOIUrl":"https://doi.org/10.1016/B978-0-443-19104-6.00013-9","url":null,"abstract":"<p><p>Our bodies contain a rich diversity of cell types with unique physiologic properties. Interestingly, cells within our bodies contain the same DNA content, yet they can vary dramatically with respect to their molecular, structural, and functional properties. The need to better understand cellular complexity and diversity in biologic systems has led to a technical revolution in the field through the development of sophisticated single-cell \"omic\" approaches. This allows the investigation of the genome, epigenome, transcriptome, and proteome of individual cells derived from complex samples or tissues, such as nervous system tissue. These methods are allowing scientists to detect distinct cell populations and cellular states in different species (including rodent and human) and molecular transitions of cell populations across the lifespan. Recent studies have revealed that astrocytes, oligodendrocytes, and microglia exhibit greater molecular and functional heterogeneity than originally thought and innovative single-cell technologies have allowed a more comprehensive and less biased view of this cellular diversity. The chapter begins by providing a primer of single-cell transcriptomic and spatial transcriptomic approaches that have been particularly influential in uncovering single-cell diversity of neuroglial cells in the brain. It then takes a closer look at how these technologies have been pivotal in defining neuroglial cell subtypes and for determining their spatial relationships within the CNS. Then, it concludes with discussion of how the recent technical advances and discoveries have provoked new questions about the origin, organization, and functional purpose of diverse neuroglial cell subtypes.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"209 ","pages":"265-275"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sleep-wake modulation and pathogenesis of Alzheimer disease: Suggestions for postponement and treatment.","authors":"Ya-Jing Liu, Dick F Swaab, Jiang-Ning Zhou","doi":"10.1016/B978-0-323-90918-1.00001-0","DOIUrl":"https://doi.org/10.1016/B978-0-323-90918-1.00001-0","url":null,"abstract":"<p><p>Sleep-wake disorders are recognized as one of the earliest symptoms of Alzheimer disease (AD). Accumulating evidence has highlighted a significant association between sleep-wake disorders and AD pathogenesis, suggesting that sleep-wake modulation could be a promising approach for postponing AD onset. The suprachiasmatic nucleus (SCN) and the pineal hormone melatonin are major central modulating components of the circadian rhythm system. Cerebrospinal fluid (CSF) melatonin levels are dramatically decreased in AD. Interestingly, the number of neurofibrillary tangles in the hippocampus, which is one of the two major neuropathologic AD biomarkers, increases in parallel with the decrease in CSF melatonin levels. Furthermore, a decrease in salivary melatonin levels in middle-aged persons is a significant risk factor for the onset of the early stages of AD. Moreover, the disappearance of rhythmic fluctuations in melatonin may be one of the best biomarkers for AD diagnosis. Light therapy combined with melatonin supplementation is the recommended first-line treatment for sleep-wake disorders in AD patients and may be beneficial for ameliorating cognitive impairment. Sleep-wake cycle modulation based on AD risk gene presence is a promising early intervention for AD onset postponement.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"206 ","pages":"211-229"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A historical review of consciousness and its disorders.","authors":"G Bryan Young, Loretta Norton","doi":"10.1016/B978-0-443-13408-1.00009-9","DOIUrl":"https://doi.org/10.1016/B978-0-443-13408-1.00009-9","url":null,"abstract":"<p><p>Concepts of consciousness and its disorders begin with the realization that both reside in the brain. Then came the realization that consciousness had various components, with two principal aspects, wakefulness and awareness. Awareness has multiple interconnected components, ranging from perception to abstract thought. These require selection of certain stimuli and processing as well as judgment and motivation, colored by emotion, before a consciously directed action is produced. The brain processes information and can influence behavior at levels below conscious awareness. Deeper insights into underlying neuronal functions and the complex interactions of various brain regions that support conscious experience have been made possible by scientific and technologic advancements. Our understanding of regional and global brain functions has been influenced by studies of various diseases and disorders, ranging from \"brain death\" to delirium. We now recognize that we cannot solely rely on behavioral responses to determine the conscious level, as some \"unresponsive-wakeful,\" previously termed \"vegetative,\" patients retain cognitive capacity, revealed by fMRI and electrophysiologic advances. There is still much to learn, especially as to how full awareness and the awareness of awareness arise from the brain and how to best assess and manage patients with various disorders of consciousness.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"207 ","pages":"15-28"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroglia in eating disorders (obesity, Prader-Willi syndrome and anorexia nervosa).","authors":"Felipe Correa-da-Silva, Chun-Xia Yi","doi":"10.1016/B978-0-443-19102-2.00019-3","DOIUrl":"https://doi.org/10.1016/B978-0-443-19102-2.00019-3","url":null,"abstract":"<p><p>The hypothalamus is widely recognized as one of the most extensively studied brain regions involved in the central regulation of energy homeostasis. Within the hypothalamus, peptidergic neurons play a crucial role in monitoring peripheral concentrations of metabolites and hormones, and they finely adjust the sensing of these factors, leading to the activation of either anorexigenic (appetite-suppressing) or orexigenic (appetite-stimulating) pathways. While cortical innervation of the hypothalamus does influence these processes, it is generally considered of secondary importance. Eating-related disorders, such as obesity and anorexia nervosa, are strongly associated with imbalances in energy intake and expenditure. The phenotypes of these disorders can be attributed to dysfunctions in the hypothalamus. Traditionally, it has been believed that hypothalamic dysfunction in these disorders primarily stems from defects in neural pathways. However, recent evidence challenges this perception, highlighting the active participation of neuroglial cells in shaping both physiologic and behavioral characteristics. This review aims to provide an overview of the latest insights into glial biology in three specific eating disorders: obesity, Prader-Willi syndrome, and anorexia. In these disorders, neural dysfunction coincides with glial malfunction, suggesting that neuroglia actively contribute to the development and progression of various neurologic disorders. These findings underscore the importance of glial cells and open up potential new avenues for therapeutic interventions.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"210 ","pages":"313-324"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orchestrating the neuroglial compartment: Ontogeny and developmental interaction of astrocytes, oligodendrocytes, and microglia.","authors":"Imke M E Schuurmans, Annika Mordelt, Lot D de Witte","doi":"10.1016/B978-0-443-19104-6.00011-5","DOIUrl":"https://doi.org/10.1016/B978-0-443-19104-6.00011-5","url":null,"abstract":"<p><p>Neuroglial cells serve as the master regulators of the central nervous system, making it imperative for glial development to be tightly regulated both spatially and temporally to ensure optimal brain function. In this chapter, we will discuss the origin and development of the three major glia cells such as astrocytes, oligodendrocytes, and microglia in the central nervous system. While much of our understanding of neuroglia development stems from studies using animal models, we will also explore recent insights into human glial development and potential differences from rodent models. Finally, the extensive crosstalk between glia cells will be highlighted, discussing how interactions among astrocyte, oligodendrocyte, and microglial influence their respective developmental pathways.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"209 ","pages":"27-47"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}