The 10 most-cited articles in Nature Neuroscience, 2022

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This…

Autophagy is markedly impaired in Alzheimer's disease (AD). Here we reveal unique autophagy dysregulation within neurons in five AD mouse models in vivo and identify its basis using a neuron-specific transgenic mRFP-eGFP-LC3 probe of autophagy and pH, multiplex confocal imaging and correlative light electron microscopy. Autolysosome acidification declines in neurons well before extracellular amyloid deposition, associated with markedly lowered vATPase activity and build-up of Aβ/APP-βCTF selectively within enlarged de-acidified autolysosomes. In more compromised yet still intact neurons, profuse Aβ-positive autophagic vacuoles (AVs) pack into large membrane blebs forming flower-like perikaryal rosettes. This unique pattern, termed PANTHOS (poisonous anthos (flower)), is also present in AD brains. Additional AVs coalesce into peri-nuclear networks of membrane tubules where fibrillar β-amyloid accumulates intraluminally. Lysosomal membrane permeabilization, cathepsin release and lysosomal cell death ensue, accompanied by microglial invasion. Quantitative analyses confirm that…

Abstract The biological processes that are disrupted in the Alzheimer’s disease (AD) brain remain incompletely understood. In this study, we analyzed the proteomes of more than 1,000 brain tissues to reveal new AD-related protein co-expression modules that were highly preserved across cohorts and brain regions. Nearly half of the protein co-expression modules, including modules significantly altered in AD, were not observed in RNA networks from the same cohorts and brain regions, highlighting the proteopathic nature of AD. Two such AD-associated modules unique to the proteomic network included a module related to MAPK signaling and metabolism and a module related to the matrisome. The matrisome module was influenced by the APOE ε4 allele but was not related to the rate of cognitive decline after adjustment for neuropathology. By contrast, the MAPK/metabolism module was strongly associated with the rate of cognitive decline. Disease-associated modules unique to the proteome are sources of promising therapeutic targets and biomarkers for AD.

The loss of dopamine (DA) neurons within the substantia nigra pars compacta (SNpc) is a defining pathological hallmark of Parkinson's disease (PD). Nevertheless, the molecular features associated with DA neuron vulnerability have not yet been fully identified. Here, we developed a protocol to enrich and transcriptionally profile DA neurons from patients with PD and matched controls, sampling a total of 387,483 nuclei, including 22,048 DA neuron profiles. We identified ten populations and spatially localized each within the SNpc using Slide-seq. A single subtype, marked by the expression of the gene AGTR1 and spatially confined to the ventral tier of SNpc, was highly susceptible to loss in PD and showed the strongest upregulation of targets of TP53 and NR2F2, nominating molecular processes associated with degeneration. This same vulnerable population was specifically enriched for the heritable risk associated with PD, highlighting the importance of cell-intrinsic processes in determining the differential vulnerability of DA neurons to PD-associated degeneration.

Departing from traditional linguistic models, advances in deep learning have resulted in a new type of predictive (autoregressive) deep language models (DLMs). Using a self-supervised next-word prediction task, these models generate appropriate linguistic responses in a given context. In the current study, nine participants listened to a 30-min podcast while their brain responses were recorded using electrocorticography (ECoG). We provide empirical evidence that the human brain and autoregressive DLMs share three fundamental computational principles as they process the same natural narrative: (1) both are engaged in continuous next-word prediction before word onset; (2) both match their pre-onset predictions to the incoming word to calculate post-onset surprise; (3) both rely on contextual embeddings to represent words in natural contexts. Together, our findings suggest that autoregressive DLMs provide a new and biologically feasible computational framework for studying the neural basis of language.

Abstract A key aspect of nearly all single cell experiments is the necessity to dissociate intact tissues into single cell suspensions for processing. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression changes during this process. Microglia, the brain’s resident macrophages, are a highly dynamic population that are extremely sensitive to their microenvironment and have been shown to dramatically alter their transcriptome upon stimulation. We demonstrate that use of enzymatic dissociation methods on mouse central nervous system (CNS) tissue induces an aberrant gene expression signature in microglia that can significantly confound downstream analysis. To minimize this issue, we developed a flexible protocol, that can be used with existing enzymatic protocols for fresh tissue, to eliminate artifactual gene expression while allowing for increased cell type diversity and yield. We demonstrate efficacy of this protocol in analysis of diverse CNS cell types and sorted myeloid…

Iron dysregulation has been implicated in multiple neurodegenerative diseases, including Parkinson's disease (PD). Iron-loaded microglia are frequently found in affected brain regions, but how iron accumulation influences microglia physiology and contributes to neurodegeneration is poorly understood. Here we show that human induced pluripotent stem cell-derived microglia grown in a tri-culture system are highly responsive to iron and susceptible to ferroptosis, an iron-dependent form of cell death. Furthermore, iron overload causes a marked shift in the microglial transcriptional state that overlaps with a transcriptomic signature found in PD postmortem brain microglia. Our data also show that this microglial response contributes to neurodegeneration, as removal of microglia from the tri-culture system substantially delayed iron-induced neurotoxicity. To elucidate the mechanisms regulating iron response in microglia, we performed a genome-wide CRISPR screen and identified novel regulators of ferroptosis, including the vesicle trafficking gene SEC24B. These data suggest a critical…

Neuroscientists today can measure activity from more neurons than ever before, and are facing the challenge of connecting these brain-wide neural recordings to computation and behavior. In the present review, we first describe emerging tools and technologies being used to probe large-scale brain activity and new approaches to characterize behavior in the context of such measurements. We next highlight insights obtained from large-scale neural recordings in diverse model systems, and argue that some of these pose a challenge to traditional theoretical frameworks. Finally, we elaborate on existing modeling frameworks to interpret these data, and argue that the interpretation of brain-wide neural recordings calls for new theoretical approaches that may depend on the desired level of understanding. These advances in both neural recordings and theory development will pave the way for critical advances in our understanding of the brain. Neuroscientists can measure activity from more neurons than ever before, garnering new insights and posing challenges to traditional theoretical…