RESUMO
Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.
Assuntos
Neurônios , Propriocepção , Animais , Propriocepção/fisiologia , Neurônios/fisiologia , Encéfalo/fisiologia , Movimento/fisiologia , Primatas , Redes Neurais de ComputaçãoRESUMO
Although social interactions are known to drive pathogen transmission, the contributions of socially transmissible host-associated mutualists and commensals to host health and disease remain poorly explored. We use the concept of the social microbiome-the microbial metacommunity of a social network of hosts-to analyze the implications of social microbial transmission for host health and disease. We investigate the contributions of socially transmissible microbes to both eco-evolutionary microbiome community processes (colonization resistance, the evolution of virulence, and reactions to ecological disturbance) and microbial transmission-based processes (transmission of microbes with metabolic and immune effects, inter-specific transmission, transmission of antibiotic-resistant microbes, and transmission of viruses). We consider the implications of social microbial transmission for communicable and non-communicable diseases and evaluate the importance of a socially transmissible component underlying canonically non-communicable diseases. The social transmission of mutualists and commensals may play a significant, under-appreciated role in the social determinants of health and may act as a hidden force in social evolution.
Assuntos
Microbiota , Fatores Sociais , Simbiose , Animais , Humanos , Doenças não Transmissíveis , VirulênciaRESUMO
Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma cells forms a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs). Other subpopulations appear unconnected, and their biological role remains unclear. Here, we demonstrate that whole-brain colonization is fueled by glioblastoma cells that lack connections with other tumor cells and astrocytes yet receive synaptic input from neurons. This subpopulation corresponds to neuronal and neural-progenitor-like tumor cell states, as defined by single-cell transcriptomics, both in mouse models and in the human disease. Tumor cell invasion resembled neuronal migration mechanisms and adopted a Lévy-like movement pattern of probing the environment. Neuronal activity induced complex calcium signals in glioblastoma cells followed by the de novo formation of TMs and increased invasion speed. Collectively, superimposing molecular and functional single-cell data revealed that neuronal mechanisms govern glioblastoma cell invasion on multiple levels. This explains how glioblastoma's dissemination and cellular heterogeneity are closely interlinked.
Assuntos
Neoplasias Encefálicas , Glioblastoma , Animais , Astrócitos/patologia , Encéfalo/patologia , Neoplasias Encefálicas/patologia , Glioblastoma/genética , Glioblastoma/patologia , Humanos , Camundongos , Invasividade Neoplásica , Neurônios/fisiologiaRESUMO
Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.
Assuntos
Fator de Transcrição GATA4/metabolismo , Cardiopatias Congênitas , Proteínas Nucleares/metabolismo , Oxirredutases/metabolismo , Fatores de Transcrição , Animais , Cardiopatias Congênitas/genética , Camundongos , Mutação , Proteômica , Proteínas com Domínio T/genética , Fatores de Transcrição/genéticaRESUMO
Olfactory sensory neurons (OSNs) convert the stochastic choice of one of >1,000 olfactory receptor (OR) genes into precise and stereotyped axon targeting of OR-specific glomeruli in the olfactory bulb. Here, we show that the PERK arm of the unfolded protein response (UPR) regulates both the glomerular coalescence of like axons and the specificity of their projections. Subtle differences in OR protein sequences lead to distinct patterns of endoplasmic reticulum (ER) stress during OSN development, converting OR identity into distinct gene expression signatures. We identify the transcription factor Ddit3 as a key effector of PERK signaling that maps OR-dependent ER stress patterns to the transcriptional regulation of axon guidance and cell-adhesion genes, instructing targeting precision. Our results extend the known functions of the UPR from a quality-control pathway that protects cells from misfolded proteins to a sensor of cellular identity that interprets physiological states to direct axon wiring.
Assuntos
Axônios/metabolismo , Estresse do Retículo Endoplasmático , Receptores Odorantes , Animais , Camundongos , Bulbo Olfatório , Neurônios Receptores Olfatórios/metabolismo , Receptores Odorantes/genética , Receptores Odorantes/metabolismo , Fatores de Transcrição/metabolismoRESUMO
In 1961, Jacob and Monod proposed the operon model of gene regulation. At the model's core was the modular assembly of regulators, operators, and structural genes. To illustrate the composability of these elements, Jacob and Monod linked phenotypic diversity to the architectures of regulatory circuits. In this review, we examine how the circuit blueprints imagined by Jacob and Monod laid the foundation for the first synthetic gene networks that launched the field of synthetic biology in 2000. We discuss the influences of the operon model and its broader theoretical framework on the first generation of synthetic biological circuits, which were predominantly transcriptional and posttranscriptional circuits. We also describe how recent advances in molecular biology beyond the operon model-namely, programmable DNA- and RNA-binding molecules as well as models of epigenetic and posttranslational regulation-are expanding the synthetic biology toolkit and enabling the design of more complex biological circuits.
Assuntos
Epigenômica/métodos , Óperon , Proteínas/genética , Biologia Sintética/métodos , Sistemas CRISPR-Cas , Retroalimentação Fisiológica , Regulação da Expressão Gênica , Biologia Molecular/métodos , Proteínas/metabolismo , RNA Mensageiro/genética , Transcrição GênicaRESUMO
Neural activity underlying short-term memory is maintained by interconnected networks of brain regions. It remains unknown how brain regions interact to maintain persistent activity while exhibiting robustness to corrupt information in parts of the network. We simultaneously measured activity in large neuronal populations across mouse frontal hemispheres to probe interactions between brain regions. Activity across hemispheres was coordinated to maintain coherent short-term memory. Across mice, we uncovered individual variability in the organization of frontal cortical networks. A modular organization was required for the robustness of persistent activity to perturbations: each hemisphere retained persistent activity during perturbations of the other hemisphere, thus preventing local perturbations from spreading. A dynamic gating mechanism allowed hemispheres to coordinate coherent information while gating out corrupt information. Our results show that robust short-term memory is mediated by redundant modular representations across brain regions. Redundant modular representations naturally emerge in neural network models that learned robust dynamics.
Assuntos
Lobo Frontal/fisiologia , Rede Nervosa/fisiologia , Envelhecimento/fisiologia , Animais , Comportamento Animal , Cérebro/fisiologia , Comportamento de Escolha , Feminino , Luz , Masculino , Camundongos , Modelos Neurológicos , Córtex Motor/fisiologia , Neurônios/fisiologiaRESUMO
Clear cell renal carcinoma (ccRCC) is a heterogeneous disease with a variable post-surgical course. To assemble a comprehensive ccRCC tumor microenvironment (TME) atlas, we performed single-cell RNA sequencing (scRNA-seq) of hematopoietic and non-hematopoietic subpopulations from tumor and tumor-adjacent tissue of treatment-naive ccRCC resections. We leveraged the VIPER algorithm to quantitate single-cell protein activity and validated this approach by comparison to flow cytometry. The analysis identified key TME subpopulations, as well as their master regulators and candidate cell-cell interactions, revealing clinically relevant populations, undetectable by gene-expression analysis. Specifically, we uncovered a tumor-specific macrophage subpopulation characterized by upregulation of TREM2/APOE/C1Q, validated by spatially resolved, quantitative multispectral immunofluorescence. In a large clinical validation cohort, these markers were significantly enriched in tumors from patients who recurred following surgery. The study thus identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential prognostic biomarker for ccRCC recurrence, as well as a candidate therapeutic target.
Assuntos
Carcinoma de Células Renais/metabolismo , Recidiva Local de Neoplasia/genética , Macrófagos Associados a Tumor/metabolismo , Adulto , Apolipoproteínas E/genética , Apolipoproteínas E/metabolismo , Biomarcadores Tumorais/genética , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/patologia , Estudos de Coortes , Feminino , Expressão Gênica/genética , Regulação Neoplásica da Expressão Gênica/genética , Humanos , Rim/metabolismo , Neoplasias Renais/patologia , Linfócitos do Interstício Tumoral/patologia , Macrófagos/metabolismo , Masculino , Glicoproteínas de Membrana/genética , Glicoproteínas de Membrana/metabolismo , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/metabolismo , Prognóstico , Receptores de Complemento/genética , Receptores de Complemento/metabolismo , Receptores Imunológicos/genética , Receptores Imunológicos/metabolismo , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Microambiente Tumoral , Macrófagos Associados a Tumor/fisiologiaRESUMO
Cell surface receptors and their interactions play a central role in physiological and pathological signaling. Despite its clinical relevance, the immunoglobulin superfamily (IgSF) remains uncharacterized and underrepresented in databases. Here, we present a systematic extracellular protein map, the IgSF interactome. Using a high-throughput technology to interrogate most single transmembrane receptors for binding to 445 IgSF proteins, we identify over 500 interactions, 82% previously undocumented, and confirm more than 60 receptor-ligand pairs using orthogonal assays. Our study reveals a map of cell-type-specific interactions and the landscape of dysregulated receptor-ligand crosstalk in cancer, including selective loss of function for tumor-associated mutations. Furthermore, investigation of the IgSF interactome in a large cohort of cancer patients identifies interacting protein signatures associated with clinical outcome. The IgSF interactome represents an important resource to fuel biological discoveries and a framework for understanding the functional organization of the surfaceome during homeostasis and disease, ultimately informing therapeutic development.
Assuntos
Imunoglobulinas/metabolismo , Neoplasias/patologia , Mapas de Interação de Proteínas , Antígeno B7-H1/metabolismo , Antígeno Carcinoembrionário/metabolismo , Comunicação Celular , Análise por Conglomerados , Meios de Cultivo Condicionados/química , Células HEK293 , Humanos , Imunoglobulinas/química , Imunoglobulinas/genética , Ligantes , Mutação , Neoplasias/genética , Neoplasias/metabolismo , Ligação Proteica , Receptores de Superfície Celular/química , Receptores de Superfície Celular/genética , Receptores de Superfície Celular/metabolismo , Linfócitos T/citologia , Linfócitos T/imunologia , Linfócitos T/metabolismoRESUMO
The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains, provide a mechanistic understanding of the hippocampal role in generalization, and offer unifying principles underlying many entorhinal and hippocampal cell types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells display diverse properties resembling apparently bespoke spatial responses, such as grid, band, border, and object-vector cells. TEM hippocampal cells include place and landmark cells that remap between environments. Crucially, TEM also aligns with empirically recorded representations in complex non-spatial tasks. TEM also generates predictions that hippocampal remapping is not random as previously believed; rather, structural knowledge is preserved across environments. We confirm this structural transfer over remapping in simultaneously recorded place and grid cells.
Assuntos
Córtex Entorrinal/fisiologia , Generalização Psicológica , Hipocampo/fisiologia , Memória/fisiologia , Modelos Neurológicos , Animais , Conhecimento , Células de Lugar/citologia , Sensação , Análise e Desempenho de TarefasRESUMO
The curse of dimensionality plagues models of reinforcement learning and decision making. The process of abstraction solves this by constructing variables describing features shared by different instances, reducing dimensionality and enabling generalization in novel situations. Here, we characterized neural representations in monkeys performing a task described by different hidden and explicit variables. Abstraction was defined operationally using the generalization performance of neural decoders across task conditions not used for training, which requires a particular geometry of neural representations. Neural ensembles in prefrontal cortex, hippocampus, and simulated neural networks simultaneously represented multiple variables in a geometry reflecting abstraction but that still allowed a linear classifier to decode a large number of other variables (high shattering dimensionality). Furthermore, this geometry changed in relation to task events and performance. These findings elucidate how the brain and artificial systems represent variables in an abstract format while preserving the advantages conferred by high shattering dimensionality.
Assuntos
Hipocampo/anatomia & histologia , Córtex Pré-Frontal/anatomia & histologia , Animais , Comportamento Animal , Mapeamento Encefálico , Simulação por Computador , Hipocampo/fisiologia , Aprendizagem , Macaca mulatta , Masculino , Modelos Neurológicos , Redes Neurais de Computação , Neurônios/fisiologia , Córtex Pré-Frontal/fisiologia , Reforço Psicológico , Análise e Desempenho de TarefasRESUMO
What specific features should visual neurons encode, given the infinity of real-world images and the limited number of neurons available to represent them? We investigated neuronal selectivity in monkey inferotemporal cortex via the vast hypothesis space of a generative deep neural network, avoiding assumptions about features or semantic categories. A genetic algorithm searched this space for stimuli that maximized neuronal firing. This led to the evolution of rich synthetic images of objects with complex combinations of shapes, colors, and textures, sometimes resembling animals or familiar people, other times revealing novel patterns that did not map to any clear semantic category. These results expand our conception of the dictionary of features encoded in the cortex, and the approach can potentially reveal the internal representations of any system whose input can be captured by a generative model.
Assuntos
Rede Nervosa/fisiologia , Lobo Temporal/fisiologia , Percepção Visual/fisiologia , Algoritmos , Animais , Córtex Cerebral/fisiologia , Macaca mulatta/fisiologia , Masculino , Neurônios/metabolismo , Neurônios/fisiologiaRESUMO
Distributing learning across multiple layers has proven extremely powerful in artificial neural networks. However, little is known about how multi-layer learning is implemented in the brain. Here, we provide an account of learning across multiple processing layers in the electrosensory lobe (ELL) of mormyrid fish and report how it solves problems well known from machine learning. Because the ELL operates and learns continuously, it must reconcile learning and signaling functions without switching its mode of operation. We show that this is accomplished through a functional compartmentalization within intermediate layer neurons in which inputs driving learning differentially affect dendritic and axonal spikes. We also find that connectivity based on learning rather than sensory response selectivity assures that plasticity at synapses onto intermediate-layer neurons is matched to the requirements of output neurons. The mechanisms we uncover have relevance to learning in the cerebellum, hippocampus, and cerebral cortex, as well as in artificial systems.
Assuntos
Peixe Elétrico/fisiologia , Aprendizagem , Rede Nervosa/fisiologia , Potenciais de Ação/fisiologia , Estruturas Animais/citologia , Estruturas Animais/fisiologia , Animais , Axônios/metabolismo , Fenômenos Biofísicos , Peixe Elétrico/anatomia & histologia , Feminino , Masculino , Modelos Neurológicos , Plasticidade Neuronal , Comportamento Predatório , Sensação , Fatores de TempoRESUMO
In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy.
Assuntos
Proteínas Ativadoras de GTPase/genética , Regulação da Expressão Gênica no Desenvolvimento/genética , Redes Reguladoras de Genes/genética , Animais , Padronização Corporal/genética , Diferenciação Celular/genética , Proteínas de Drosophila/genética , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/genética , Drosophila melanogaster/metabolismo , Embrião não Mamífero/metabolismo , Desenvolvimento Embrionário/genética , Proteínas Ativadoras de GTPase/metabolismo , Regulação da Expressão Gênica no Desenvolvimento/fisiologia , Modelos Genéticos , Fatores de Transcrição/metabolismoRESUMO
Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.
Assuntos
Transtorno do Espectro Autista/genética , Locos de Características Quantitativas/genética , Esquizofrenia/genética , Transcriptoma/genética , Transtorno do Espectro Autista/metabolismo , Transtorno do Espectro Autista/patologia , Encéfalo/crescimento & desenvolvimento , Encéfalo/metabolismo , Feminino , Feto/metabolismo , Regulação da Expressão Gênica no Desenvolvimento , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Idade Gestacional , Humanos , Masculino , Neurônios/metabolismo , Polimorfismo de Nucleotídeo Único/genética , Splicing de RNA/genética , Esquizofrenia/metabolismo , Esquizofrenia/patologiaRESUMO
Protein serine/threonine phosphatases (PPPs) are ancient enzymes, with distinct types conserved across eukaryotic evolution. PPPs are segregated into types primarily on the basis of the unique interactions of PPP catalytic subunits with regulatory proteins. The resulting holoenzymes dock substrates distal to the active site to enhance specificity. This review focuses on the subunit and substrate interactions for PPP that depend on short linear motifs. Insights about these motifs from structures of holoenzymes open new opportunities for computational biology approaches to elucidate PPP networks. There is an expanding knowledge base of posttranslational modifications of PPP catalytic and regulatory subunits, as well as of their substrates, including phosphorylation, acetylation, and ubiquitination. Cross talk between these posttranslational modifications creates PPP-based signaling. Knowledge of PPP complexes, signaling clusters, as well as how PPPs communicate with each other in response to cellular signals should unlock the doors to PPP networks and signaling "clouds" that orchestrate and coordinate different aspects of cell physiology.
Assuntos
Fosfoproteínas Fosfatases/metabolismo , Animais , Biologia Computacional , Evolução Molecular , Humanos , Modelos Moleculares , Fosfoproteínas Fosfatases/química , Fosfoproteínas Fosfatases/genética , Mapas de Interação de Proteínas , Processamento de Proteína Pós-Traducional , Subunidades Proteicas , Especificidade por SubstratoRESUMO
Single-cell RNA sequencing technologies suffer from many sources of technical noise, including under-sampling of mRNA molecules, often termed "dropout," which can severely obscure important gene-gene relationships. To address this, we developed MAGIC (Markov affinity-based graph imputation of cells), a method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. We validate MAGIC on several biological systems and find it effective at recovering gene-gene relationships and additional structures. Applied to the epithilial to mesenchymal transition, MAGIC reveals a phenotypic continuum, with the majority of cells residing in intermediate states that display stem-like signatures, and infers known and previously uncharacterized regulatory interactions, demonstrating that our approach can successfully uncover regulatory relations without perturbations.
Assuntos
Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Algoritmos , Linhagem Celular , Epistasia Genética/genética , Redes Reguladoras de Genes/genética , Humanos , Cadeias de Markov , MicroRNAs/genética , RNA Mensageiro/genética , SoftwareRESUMO
Brain-wide fluctuations in local field potential oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional pathology. Using machine learning, we discover a spatiotemporal dynamic network that predicts the emergence of major depressive disorder (MDD)-related behavioral dysfunction in mice subjected to chronic social defeat stress. Activity patterns in this network originate in prefrontal cortex and ventral striatum, relay through amygdala and ventral tegmental area, and converge in ventral hippocampus. This network is increased by acute threat, and it is also enhanced in three independent models of MDD vulnerability. Finally, we demonstrate that this vulnerability network is biologically distinct from the networks that encode dysfunction after stress. Thus, these findings reveal a convergent mechanism through which MDD vulnerability is mediated in the brain.
Assuntos
Encéfalo/fisiologia , Depressão/patologia , Animais , Proteína Quinase Tipo 2 Dependente de Cálcio-Calmodulina/genética , Proteína Quinase Tipo 2 Dependente de Cálcio-Calmodulina/metabolismo , Depressão/fisiopatologia , Modelos Animais de Doenças , Estimulação Elétrica , Eletrodos Implantados , Imunoglobulina G/genética , Imunoglobulina G/metabolismo , Ketamina/farmacologia , Aprendizado de Máquina , Masculino , Proteínas de Membrana/genética , Proteínas de Membrana/metabolismo , Camundongos , Camundongos Endogâmicos C57BL , Fenômenos Fisiológicos/efeitos dos fármacos , Córtex Pré-Frontal/fisiologia , Estresse PsicológicoRESUMO
Many patients with advanced cancers achieve dramatic responses to a panoply of therapeutics yet retain minimal residual disease (MRD), which ultimately results in relapse. To gain insights into the biology of MRD, we applied single-cell RNA sequencing to malignant cells isolated from BRAF mutant patient-derived xenograft melanoma cohorts exposed to concurrent RAF/MEK-inhibition. We identified distinct drug-tolerant transcriptional states, varying combinations of which co-occurred within MRDs from PDXs and biopsies of patients on treatment. One of these exhibited a neural crest stem cell (NCSC) transcriptional program largely driven by the nuclear receptor RXRG. An RXR antagonist mitigated accumulation of NCSCs in MRD and delayed the development of resistance. These data identify NCSCs as key drivers of resistance and illustrate the therapeutic potential of MRD-directed therapy. They also highlight how gene regulatory network architecture reprogramming may be therapeutically exploited to limit cellular heterogeneity, a key driver of disease progression and therapy resistance.
Assuntos
Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Melanoma/tratamento farmacológico , Neoplasia Residual/tratamento farmacológico , Células-Tronco Neoplásicas/efeitos dos fármacos , Células-Tronco Neurais/efeitos dos fármacos , Inibidores de Proteínas Quinases/farmacologia , Receptor X Retinoide gama/antagonistas & inibidores , Animais , Biomarcadores Tumorais , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Feminino , Humanos , MAP Quinase Quinase 1/antagonistas & inibidores , MAP Quinase Quinase 1/genética , Masculino , Melanoma/metabolismo , Melanoma/patologia , Camundongos SCID , Mutação , Neoplasia Residual/metabolismo , Neoplasia Residual/patologia , Células-Tronco Neoplásicas/metabolismo , Células-Tronco Neoplásicas/patologia , Células-Tronco Neurais/metabolismo , Células-Tronco Neurais/patologia , Proteínas Proto-Oncogênicas B-raf/antagonistas & inibidores , Proteínas Proto-Oncogênicas B-raf/genética , Células Tumorais Cultivadas , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
Human brain networks that encode variation in mood on naturalistic timescales remain largely unexplored. Here we combine multi-site, semi-chronic, intracranial electroencephalography recordings from the human limbic system with machine learning methods to discover a brain subnetwork that correlates with variation in individual subjects' self-reported mood over days. First we defined the subnetworks that influence intrinsic brain dynamics by identifying regions that showed coordinated changes in spectral coherence. The most common subnetwork, found in 13 of 21 subjects, was characterized by ß-frequency coherence (13-30 Hz) between the amygdala and hippocampus. Increased variability of this subnetwork correlated with worsening mood across these 13 subjects. Moreover, these subjects had significantly higher trait anxiety than the 8 of 21 for whom this amygdala-hippocampus subnetwork was absent. These results demonstrate an approach for extracting network-behavior relationships from complex datasets, and they reveal a conserved subnetwork associated with a psychological trait that significantly influences intrinsic brain dynamics and encodes fluctuations in mood.