Advances in neurobiology最新文献

Imagine a world in which damaged parts of the body - an arm, an eye, and ultimately a region of the brain - can be replaced by artificial implants capable of restoring or even enhancing human performance. The associated improvements in the quality of human life would revolutionize the medical world and produce sweeping changes across society. In this chapter, we discuss several approaches to the fabrication of fractal electronics designed to interface with neural networks. We consider two fundamental functions - stimulating electrical signals in the neural networks and sensing the location of the signals as they pass through the network. Using experiments and simulations, we discuss the favorable electrical performances that arise from adopting fractal rather than traditional Euclidean architectures. We also demonstrate how the fractal architecture induces favorable physical interactions with the cells they interact with, including the ability to direct the growth of neurons and glia to specific regions of the neural-electronic interface.

Fear attenuation is an etiologically relevant process for animal survival, since once acquired information needs to be continuously updated in the face of changing environmental contingencies. Thus, when situations are encountered that were originally perceived as fearful but are no longer so, fear must be attenuated, otherwise, it risks becoming maladaptive. But what happens to the original memory trace of fear during fear attenuation? In this chapter, we review the studies that have started to approach this question from an engram perspective. We find evidence pointing to both the original memory trace of fear being suppressed, as well as it being updated towards safety. These seemingly conflicting results reflect a well-established dichotomy in the field of fear memory attenuation, namely whether fear attenuation is mediated by an inhibitory mechanism that suppresses fear expression, called extinction, or by an updating mechanism that allows the fear memory to reconsolidate in a different form, called reconsolidation-updating. Which of these scenarios takes the upper hand is ultimately influenced by the behavioral paradigms used to induce fear attenuation, but is an important area for further study as the precise cell populations underlying fear attenuation and the molecular mechanisms therein can now be understood at unprecedented resolution.

In mammals, the subgranular zone of the dentate gyrus is one of two brain regions (with the subventricular zone of the olfactory bulb) that continues to generate new neurons throughout adulthood, a phenomenon known as adult hippocampal neurogenesis (AHN) (Eriksson et al., Nat Med 4:1313-1317, 1998; García-Verdugo et al., J Neurobiol 36:234-248, 1998). The integration of these new neurons into the dentate gyrus (DG) has implications for memory encoding, with unique firing and wiring properties of immature neurons that affect how the hippocampal network encodes and stores attributes of memory. In this chapter, we will describe the process of AHN and properties of adult-born cells as they integrate into the hippocampal circuit and mature. Then, we will discuss some methodological considerations before we review evidence for the role of AHN in two major processes supporting memory that are performed by the DG. First, we will discuss encoding of contextual information for episodic memories and how this is facilitated by AHN. Second, will discuss pattern separation, a major role of the DG that reduces interference for the formation of new memories. Finally, we will review clinical and translational considerations, suggesting that stimulation of AHN may help decrease overgeneralization-a common endophenotype of mood, anxiety, trauma-related, and age-related disorders.

This second chapter in our trilogy reviews and critically appraises the scientific evidence for the role of endogenous opioid system (EOS) activity in the onset and progression of both obesity and eating disorders. Defining features of normative eating and maladaptive eating behaviors are discussed as a foundation. We review the scientific literature pertaining to the predisposing risk factors and pathophysiology for obesity and eating disorders. Research targeting the association between obesity, disordered eating, and psychiatric comorbidities is reviewed. We conclude by discussing the involvement of endogenous opioids in neurobiological and behavior traits, and the clinical evidence for the role of the EOS in obesity and eating disorders.

Pain, fear, stress, and anxiety are separate yet interrelated phenomena. Each of these concepts has an extensive individual body of research, with some more recent work focusing on points of conceptual overlap. The role of the endogenous opioid system in each of these phenomena is only beginning to be examined and understood. Research examining the ways in which endogenous opioids (e.g., beta-endorphin; βE) may mediate the relations among pain, fear, stress, and anxiety is even more nascent. This chapter explores the extant evidence for endogenous opioid activity as an underpinning mechanism of these related constructs, with an emphasis on research examining βE.

Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention. Additional integration of this information into protein-protein interaction networks and genome-scale metabolic models from the literature has potential to decipher functional modules and affected mechanisms for complex scenarios such as AD. In this chapter, we review the application areas of the multilayer content of RNAseq and associated integrative approaches available, with a special focus on AD.

As our population continues to age, the search for effective therapeutic strategies to combat neurodegenerative diseases, particularly Alzheimer's disease (AD), has become more pressing than ever. For over a decade, researchers have focused on the amyloid cascade hypothesis in their pursuit of new drugs for AD. However, with numerous drugs targeting this hypothesis failing in clinical trials, it is clear that AD's pathogenesis is complex, and each individual may display significant heterogeneity. Consequently, treatment has shifted to focus on multiple targets and early AD detection. Furthermore, there is an urgent need to develop new models that address the shortcomings of current rodent models, which have species differences. The organoid model, a newly developed model, appears to be the future direction, but it must overcome some system immaturity problems.

The promise of individually tailored care for autism has driven efforts to establish biomarkers. This chapter appraises the state of precision-medicine research focused on biomarkers based on the functional brain connectome. This work is grounded on abundant evidence supporting the brain dysconnection model of autism and the advantages of resting-state functional MRI (R-fMRI) for studying the brain in vivo. After considering biomarker requirements of consistency and clinical relevance, we provide a scoping review of R-fMRI studies of individual prediction in autism. In the past 10 years, responding to the availability of open data through the Autism Brain Imaging Data Exchange, machine learning studies have surged. Nearly all have focused on diagnostic label classification. These efforts have shown that autism prediction is feasible using functional connectome markers, with accuracy reported well above chance. In parallel, emerging approaches more directly addressing autism heterogeneity are paving the way for much-needed biomarkers of longitudinal outcome and treatment response. We conclude with key challenges to be addressed by the next generation of studies.

Schizophrenia is a major mental disorder that affects approximately 0.5% of the population worldwide. Persistent negative symptoms and cognitive impairments associated with schizophrenia (CIAS) are key features of the disorder and primary predictors of long-term disability. At the neurochemical level, both CIAS and negative symptoms are potentially attributable to dysfunction or dysregulation of N-methyl-D-aspartate receptor (NMDAR)-mediated neurotransmission within cortical and subcortical brain regions. At present, there are no approved treatments for either CIAS or persistent negative symptoms. Development of novel treatments, moreover, is limited by the lack of biomarkers that can be used translationally across preclinical and early-stage clinical investigation. The present chapter describes the use of mismatch negativity (MMN) as a pharmacodynamic/response (PD/R) biomarker for early-stage clinical investigation of NMDAR targeted therapies for schizophrenia. MMN indexes dysfunction of early auditory processing (EAP) in schizophrenia. In humans, deficits in MMN generation contribute hierarchically to impaired cognition and functional outcome. Across humans, rodents, and primates, MMN has been linked to impaired NMDAR function and resultant disturbances in excitatory/inhibitory (E/I) balance involving interactions between glutamatergic (excitatory) pyramidal and GABAeric (inhibitory) local circuit neurons. In early-stage clinical trials, MMN has shown sensitivity to the acute effects of novel pharmacological treatments. These findings support use of MMN as a pharmacodynamic/response biomarker to support preclinical drug discovery and early-stage proof-of-mechanisms studies in schizophrenia and other related neuropsychiatric disorders.

Sleep spindles and slow waves are the two main oscillatory activities occurring during nonrapid eye movement (NREM) sleep. Here, we will first describe the electrophysiological characteristics of these sleep oscillations along with the neurophysiological and molecular mechanisms underlying their generation and synchronization in the healthy brain. We will then review the extant evidence of deficits in sleep spindles and, to a lesser extent, slow waves, including in slow wave-spindle coupling, in patients with Schizophrenia (SCZ) across the course of the disorder, from at-risk to chronic stages. Next, we will discuss how these sleep oscillatory deficits point to defects in neuronal circuits within the thalamocortical network as well as to alterations in molecular neurotransmission implicating the GABAergic and glutamatergic systems in SCZ. Finally, after explaining how spindle and slow waves may represent neurophysiological biomarkers with predictive, diagnostic, and prognostic potential, we will present novel pharmacological and neuromodulatory interventions aimed at restoring sleep oscillatory deficits in SCZ, which in turn may serve as target engagement biomarkers to ameliorate the clinical symptoms and the quality of life of individuals affected by this devastating brain disorder.