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1.
Neuroinformatics ; 21(2): 247-265, 2023 04.
Artigo em Inglês | MEDLINE | ID: mdl-36378467

RESUMO

Functional ultrasound (fUS) indirectly measures brain activity by detecting changes in cerebral blood volume following neural activation. Conventional approaches model such functional neuroimaging data as the convolution between an impulse response, known as the hemodynamic response function (HRF), and a binarized representation of the input signal based on the stimulus onsets, the so-called experimental paradigm (EP). However, the EP may not characterize the whole complexity of the activity-inducing signals that evoke the hemodynamic changes. Furthermore, the HRF is known to vary across brain areas and stimuli. To achieve an adaptable framework that can capture such dynamics of the brain function, we model the multivariate fUS time-series as convolutive mixtures and apply block-term decomposition on a set of lagged fUS autocorrelation matrices, revealing both the region-specific HRFs and the source signals that induce the hemodynamic responses. We test our approach on two mouse-based fUS experiments. In the first experiment, we present a single type of visual stimulus to the mouse, and deconvolve the fUS signal measured within the mouse brain's lateral geniculate nucleus, superior colliculus and visual cortex. We show that the proposed method is able to recover back the time instants at which the stimulus was displayed, and we validate the estimated region-specific HRFs based on prior studies. In the second experiment, we alter the location of the visual stimulus displayed to the mouse, and aim at differentiating the various stimulus locations over time by identifying them as separate sources.


Assuntos
Córtex Visual , Vias Visuais , Camundongos , Animais , Vias Visuais/diagnóstico por imagem , Vias Visuais/fisiologia , Imageamento por Ressonância Magnética/métodos , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Hemodinâmica/fisiologia , Córtex Visual/diagnóstico por imagem , Córtex Visual/fisiologia , Mapeamento Encefálico/métodos
2.
Nat Ecol Evol ; 7(4): 557-569, 2023 04.
Artigo em Inglês | MEDLINE | ID: mdl-36941345

RESUMO

Sweat bees have repeatedly gained and lost eusociality, a transition from individual to group reproduction. Here we generate chromosome-length genome assemblies for 17 species and identify genomic signatures of evolutionary trade-offs associated with transitions between social and solitary living. Both young genes and regulatory regions show enrichment for these molecular patterns. We also identify loci that show evidence of complementary signals of positive and relaxed selection linked specifically to the convergent gains and losses of eusociality in sweat bees. This includes two pleiotropic proteins that bind and transport juvenile hormone (JH)-a key regulator of insect development and reproduction. We find that one of these proteins is primarily expressed in subperineurial glial cells that form the insect blood-brain barrier and that brain levels of JH vary by sociality. Our findings are consistent with a role of JH in modulating social behaviour and suggest that eusocial evolution was facilitated by alteration of the proteins that bind and transport JH, revealing how an ancestral developmental hormone may have been co-opted during one of life's major transitions. More broadly, our results highlight how evolutionary trade-offs have structured the molecular basis of eusociality in these bees and demonstrate how both directional selection and release from constraint can shape trait evolution.


Assuntos
Comportamento Social , Suor , Abelhas , Animais , Reprodução , Fenótipo
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