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1.
Yakugaku Zasshi ; 140(10): 1207-1212, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-32999199

RESUMO

T-type calcium channels are low-threshold voltage-gated calcium channel and characterized by unique electrophysiological properties such as fast inactivation and slow deactivation kinetics. All subtypes of T-type calcium channel (Cav3.1, 3.2 and 3.3) are widely expressed in the central nerve system, and they have an important role in homeostasis of sleep, pain response, and development of epilepsy. Recently, several reports suggest that T-type calcium channels may mediate neuronal plasticity in the mouse brain. We succeeded to develop T-type calcium channel enhancer ethyl 8'-methyl-2',4-dioxo-2-(piperidin-1-yl)-2'H-spiro[cyclopentane-1,3'-imidazo[1,2-a]pyridine]-2-ene-3-carboxylate (SAK3) which enhances Cav3.1 and 3.3 currents in each-channel expressed neuro2A cells. SAK3 can promote acetylcholine (ACh) release in the mouse hippocampus via enhancing T-type calcium channel. In this review, we have introduced the role of T-type calcium channel, especially Cav3.1 channel in the mouse hippocampus based on our previous data using SAK3 and Cav3.1 knockout mice.


Assuntos
Canais de Cálcio Tipo T/efeitos dos fármacos , Canais de Cálcio Tipo T/fisiologia , Imidazóis/farmacologia , Neurônios/fisiologia , Compostos de Espiro/farmacologia , Acetilcolina/metabolismo , Animais , Encéfalo/fisiologia , Canais de Cálcio Tipo T/genética , Canais de Cálcio Tipo T/metabolismo , Células Cultivadas , Sistema Nervoso Central/metabolismo , Fenômenos Eletrofisiológicos , Epilepsia/etiologia , Expressão Gênica/efeitos dos fármacos , Hipocampo/metabolismo , Homeostase , Camundongos , Plasticidade Neuronal , Dor/etiologia , Ratos , Sono/fisiologia
2.
Nat Commun ; 11(1): 4669, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938940

RESUMO

The prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that populations of neurons encoding choice outcomes, outcome prediction errors, and outcome history in their firing rates also carry significant information in their phase-of-firing at a 10-25 Hz band-limited beta frequency at which they synchronize across lateral prefrontal cortex, anterior cingulate cortex and anterior striatum when outcomes were processed. The phase-of-firing code exceeds information that can be obtained from firing rates alone and is evident for inter-areal connections between anterior cingulate cortex, lateral prefrontal cortex and anterior striatum. For the majority of connections, the phase-of-firing information gain is maximal at phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document enhanced information of three important learning variables at specific phases of firing in the beta cycle at an inter-areally shared beta oscillation frequency during goal-directed behavior.


Assuntos
Corpo Estriado/fisiologia , Giro do Cíngulo/fisiologia , Aprendizagem/fisiologia , Neurônios/fisiologia , Córtex Pré-Frontal/fisiologia , Animais , Análise por Conglomerados , Corpo Estriado/citologia , Sincronização de Fases em Eletroencefalografia , Eletrofisiologia/métodos , Eletrofisiologia/estatística & dados numéricos , Giro do Cíngulo/citologia , Macaca mulatta , Masculino , Rede Nervosa , Córtex Pré-Frontal/citologia , Recompensa
3.
Nat Commun ; 11(1): 4632, 2020 09 15.
Artigo em Inglês | MEDLINE | ID: mdl-32934230

RESUMO

Mapping neuroanatomy is a foundational goal towards understanding brain function. Electron microscopy (EM) has been the gold standard for connectivity analysis because nanoscale resolution is necessary to unambiguously resolve synapses. However, molecular information that specifies cell types is often lost in EM reconstructions. To address this, we devise a light microscopy approach for connectivity analysis of defined cell types called spectral connectomics. We combine multicolor labeling (Brainbow) of neurons with multi-round immunostaining Expansion Microscopy (miriEx) to simultaneously interrogate morphology, molecular markers, and connectivity in the same brain section. We apply this strategy to directly link inhibitory neuron cell types with their morphologies. Furthermore, we show that correlative Brainbow and endogenous synaptic machinery immunostaining can define putative synaptic connections between neurons, as well as map putative inhibitory and excitatory inputs. We envision that spectral connectomics can be applied routinely in neurobiology labs to gain insights into normal and pathophysiological neuroanatomy.


Assuntos
Conectoma/métodos , Microscopia/métodos , Neurônios/fisiologia , Animais , Encéfalo/fisiologia , Camundongos , Camundongos Endogâmicos C57BL , Neuroanatomia , Neurônios/química , Sinapses/química , Sinapses/fisiologia
4.
Nat Commun ; 11(1): 4361, 2020 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-32868773

RESUMO

The sensory responses of cortical neuronal populations following training have been extensively studied. However, the spike firing properties of individual cortical neurons following training remain unknown. Here, we have combined two-photon Ca2+ imaging and single-cell electrophysiology in awake behaving mice following auditory associative training. We find a sparse set (~5%) of layer 2/3 neurons in the primary auditory cortex, each of which reliably exhibits high-rate prolonged burst firing responses to the trained sound. Such bursts are largely absent in the auditory cortex of untrained mice. Strikingly, in mice trained with different multitone chords, we discover distinct subsets of neurons that exhibit bursting responses specifically to a chord but neither to any constituent tone nor to the other chord. Thus, our results demonstrate an integrated representation of learned complex sounds in a small subset of cortical neurons.


Assuntos
Córtex Auditivo/fisiologia , Percepção Auditiva/fisiologia , Neurônios/fisiologia , Estimulação Acústica/métodos , Córtex Auditivo/citologia , Sinalização do Cálcio , Eletrofisiologia/métodos , Aprendizagem/fisiologia , Microscopia de Fluorescência por Excitação Multifotônica/métodos , Neurônios/metabolismo , Análise de Célula Única/métodos
5.
Phys Rev Lett ; 125(8): 088103, 2020 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-32909804

RESUMO

The ability of humans and animals to quickly adapt to novel tasks is difficult to reconcile with the standard paradigm of learning by slow synaptic weight modification. Here, we show that fixed-weight neural networks can learn to generate required dynamics by imitation. After appropriate weight pretraining, the networks quickly and dynamically adapt to learn new tasks and thereafter continue to achieve them without further teacher feedback. We explain this ability and illustrate it with a variety of target dynamics, ranging from oscillatory trajectories to driven and chaotic dynamical systems.


Assuntos
Aprendizagem/fisiologia , Modelos Neurológicos , Neurônios/fisiologia , Animais , Comunicação Celular/fisiologia , Humanos , Rede Nervosa/citologia , Rede Nervosa/fisiologia , Neurônios/citologia
6.
Nat Commun ; 11(1): 4819, 2020 09 23.
Artigo em Inglês | MEDLINE | ID: mdl-32968048

RESUMO

In many parts of the nervous system, experience-dependent refinement of neuronal circuits predominantly involves synapse elimination. The role of sleep in this process remains unknown. We investigated the role of sleep in experience-dependent dendritic spine elimination of layer 5 pyramidal neurons in the visual (V1) and frontal association cortex (FrA) of 1-month-old mice. We found that monocular deprivation (MD) or auditory-cued fear conditioning (FC) caused rapid spine elimination in V1 or FrA, respectively. MD- or FC-induced spine elimination was significantly reduced after total sleep or REM sleep deprivation. Total sleep or REM sleep deprivation also prevented MD- and FC-induced reduction of neuronal activity in response to visual or conditioned auditory stimuli. Furthermore, dendritic calcium spikes increased substantially during REM sleep, and the blockade of these calcium spikes prevented MD- and FC-induced spine elimination. These findings reveal an important role of REM sleep in experience-dependent synapse elimination and neuronal activity reduction.


Assuntos
Córtex Cerebral/fisiologia , Espinhas Dendríticas/fisiologia , Sono REM/fisiologia , Animais , Condicionamento Clássico , Medo/fisiologia , Camundongos , Camundongos Transgênicos , Modelos Animais , Plasticidade Neuronal/fisiologia , Neurônios/fisiologia , Células Piramidais/fisiologia , Privação Sensorial/fisiologia , Privação do Sono , Sinapses , Córtex Visual/fisiologia
7.
BMC Bioinformatics ; 21(1): 395, 2020 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-32887543

RESUMO

BACKGROUND: Neurons are the basic structural unit of the brain, and their morphology is a key determinant of their classification. The morphology of a neuronal circuit is a fundamental component in neuron modeling. Recently, single-neuron morphologies of the whole brain have been used in many studies. The correctness and completeness of semimanually traced neuronal morphology are credible. However, there are some inaccuracies in semimanual tracing results. The distance between consecutive nodes marked by humans is very long, spanning multiple voxels. On the other hand, the nodes are marked around the centerline of the neuronal fiber, not on the centerline. Although these inaccuracies do not seriously affect the projection patterns that these studies focus on, they reduce the accuracy of the traced neuronal skeletons. These small inaccuracies will introduce deviations into subsequent studies that are based on neuronal morphology files. RESULTS: We propose a neuronal digital skeleton optimization method to evaluate and make fine adjustments to a digital skeleton after neuron tracing. Provided that the neuronal fiber shape is smooth and continuous, we describe its physical properties according to two shape restrictions. One restriction is designed based on the grayscale image, and the other is designed based on geometry. These two restrictions are designed to finely adjust the digital skeleton points to the neuronal fiber centerline. With this method, we design the three-dimensional shape restriction workflow of neuronal skeleton adjustment computation. The performance of the proposed method has been quantitatively evaluated using synthetic and real neuronal image data. The results show that our method can reduce the difference between the traced neuronal skeleton and the centerline of the neuronal fiber. Furthermore, morphology metrics such as the neuronal fiber length and radius become more precise. CONCLUSIONS: This method can improve the accuracy of a neuronal digital skeleton based on traced results. The greater the accuracy of the digital skeletons that are acquired, the more precise the neuronal morphologies that are analyzed will be.


Assuntos
Imageamento Tridimensional/métodos , Neurônios/fisiologia , Algoritmos , Encéfalo/diagnóstico por imagem , Humanos
8.
Nat Commun ; 11(1): 4854, 2020 09 25.
Artigo em Inglês | MEDLINE | ID: mdl-32978383

RESUMO

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.


Assuntos
Rede Nervosa/fisiologia , Neurônios/fisiologia , Imagem Óptica/métodos , Análise de Célula Única/métodos , Animais , Axônios , Encéfalo , Células Cultivadas , Células-Tronco Pluripotentes Induzidas , Camundongos , Microeletrodos , Modelos Animais , Rede Nervosa/diagnóstico por imagem , Imagem Óptica/instrumentação , Ratos , Ratos Wistar , Gravação em Vídeo
9.
PLoS Comput Biol ; 16(9): e1008198, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32931495

RESUMO

Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations. The transform between neural activity and calcium-related fluorescence involves nonlinearities and low-pass filtering, but the effects of the transformation on analyses of neural populations are not well understood. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. We report multiple discrepancies between analyses performed on the two types of data, including changes in single-neuron selectivity and population decoding. These were only partially resolved by spike inference algorithms applied to fluorescence. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. The model recapitulated the differences in analyses. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data.


Assuntos
Cálcio/metabolismo , Fenômenos Eletrofisiológicos/fisiologia , Modelos Neurológicos , Imagem Molecular/métodos , Neurônios , Potenciais de Ação/fisiologia , Animais , Lobo Frontal/citologia , Lobo Frontal/fisiologia , Camundongos , Neurônios/metabolismo , Neurônios/fisiologia , Imagem Óptica
10.
PLoS Comput Biol ; 16(9): e1008165, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32941457

RESUMO

Combining information from multiple sources is a fundamental operation performed by networks of neurons in the brain, whose general principles are still largely unknown. Experimental evidence suggests that combination of inputs in cortex relies on nonlinear summation. Such nonlinearities are thought to be fundamental to perform complex computations. However, these non-linearities are inconsistent with the balanced-state model, one of the most popular models of cortical dynamics, which predicts networks have a linear response. This linearity is obtained in the limit of very large recurrent coupling strength. We investigate the stationary response of networks of spiking neurons as a function of coupling strength. We show that, while a linear transfer function emerges at strong coupling, nonlinearities are prominent at finite coupling, both at response onset and close to saturation. We derive a general framework to classify nonlinear responses in these networks and discuss which of them can be captured by rate models. This framework could help to understand the diversity of non-linearities observed in cortical networks.


Assuntos
Potenciais de Ação/fisiologia , Modelos Neurológicos , Rede Nervosa/citologia , Rede Nervosa/fisiologia , Neurônios/fisiologia , Animais , Encéfalo/citologia , Encéfalo/fisiologia , Biologia Computacional , Haplorrinos , Camundongos , Dinâmica não Linear
11.
PLoS Comput Biol ; 16(9): e1008192, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32946433

RESUMO

Balanced excitation and inhibition is widely observed in cortex. How does this balance shape neural computations and stimulus representations? This question is often studied using computational models of neuronal networks in a dynamically balanced state. But balanced network models predict a linear relationship between stimuli and population responses. So how do cortical circuits implement nonlinear representations and computations? We show that every balanced network architecture admits stimuli that break the balanced state and these breaks in balance push the network into a "semi-balanced state" characterized by excess inhibition to some neurons, but an absence of excess excitation. The semi-balanced state produces nonlinear stimulus representations and nonlinear computations, is unavoidable in networks driven by multiple stimuli, is consistent with cortical recordings, and has a direct mathematical relationship to artificial neural networks.


Assuntos
Modelos Neurológicos , Rede Nervosa/fisiologia , Neurônios/fisiologia , Dinâmica não Linear , Animais , Córtex Cerebral/fisiologia , Biologia Computacional , Redes Neurais de Computação , Sinapses/fisiologia
13.
Proc Natl Acad Sci U S A ; 117(32): 19590-19598, 2020 08 11.
Artigo em Inglês | MEDLINE | ID: mdl-32732431

RESUMO

During rapid eye movement (REM) sleep, behavioral unresponsiveness contrasts strongly with intense brain-wide neural network dynamics. Yet, the physiological functions of this cellular activation remain unclear. Using in vivo calcium imaging in freely behaving mice, we found that inhibitory neurons in the lateral hypothalamus (LHvgat) show unique activity patterns during feeding that are reactivated during REM, but not non-REM, sleep. REM sleep-specific optogenetic silencing of LHvgat cells induced a reorganization of these activity patterns during subsequent feeding behaviors accompanied by decreased food intake. Our findings provide evidence for a role for REM sleep in the maintenance of cellular representations of feeding behavior.


Assuntos
Comportamento Alimentar/fisiologia , Região Hipotalâmica Lateral/fisiologia , Sono REM/fisiologia , Animais , Mapeamento Encefálico , Masculino , Camundongos , Rede Nervosa , Inibição Neural , Neurônios/metabolismo , Neurônios/fisiologia , Optogenética , Sono/fisiologia , Proteínas Vesiculares de Transporte de Aminoácidos Inibidores/genética , Proteínas Vesiculares de Transporte de Aminoácidos Inibidores/metabolismo
14.
Nat Commun ; 11(1): 3794, 2020 07 30.
Artigo em Inglês | MEDLINE | ID: mdl-32732906

RESUMO

Defective rhythmic metabolism is associated with high-fat high-caloric diet (HFD) feeding, ageing and obesity; however, the neural basis underlying HFD effects on diurnal metabolism remains elusive. Here we show that deletion of BMAL1, a core clock gene, in paraventricular hypothalamic (PVH) neurons reduces diurnal rhythmicity in metabolism, causes obesity and diminishes PVH neuron activation in response to fast-refeeding. Animal models mimicking deficiency in PVH neuron responsiveness, achieved through clamping PVH neuron activity at high or low levels, both show obesity and reduced diurnal rhythmicity in metabolism. Interestingly, the PVH exhibits BMAL1-controlled rhythmic expression of GABA-A receptor γ2 subunit, and dampening rhythmicity of GABAergic input to the PVH reduces diurnal rhythmicity in metabolism and causes obesity. Finally, BMAL1 deletion blunts PVH neuron responses to external stressors, an effect mimicked by HFD feeding. Thus, BMAL1-driven PVH neuron responsiveness in dynamic activity changes involving rhythmic GABAergic neurotransmission mediates diurnal rhythmicity in metabolism and is implicated in diet-induced obesity.


Assuntos
Fatores de Transcrição ARNTL/genética , Ritmo Circadiano/fisiologia , Obesidade/patologia , Núcleo Hipotalâmico Paraventricular/metabolismo , Receptores de GABA-A/metabolismo , Animais , Ritmo Circadiano/genética , Dieta Hiperlipídica , Metabolismo Energético/fisiologia , Comportamento Alimentar/fisiologia , Camundongos , Camundongos Knockout , Neurônios/fisiologia , Obesidade/genética , Núcleo Hipotalâmico Paraventricular/citologia
15.
Nat Commun ; 11(1): 3845, 2020 07 31.
Artigo em Inglês | MEDLINE | ID: mdl-32737295

RESUMO

Many experimental studies suggest that animals can rapidly learn to identify odors and predict the rewards associated with them. However, the underlying plasticity mechanism remains elusive. In particular, it is not clear how olfactory circuits achieve rapid, data efficient learning with local synaptic plasticity. Here, we formulate olfactory learning as a Bayesian optimization process, then map the learning rules into a computational model of the mammalian olfactory circuit. The model is capable of odor identification from a small number of observations, while reproducing cellular plasticity commonly observed during development. We extend the framework to reward-based learning, and show that the circuit is able to rapidly learn odor-reward association with a plausible neural architecture. These results deepen our theoretical understanding of unsupervised learning in the mammalian brain.


Assuntos
Condicionamento Clássico/fisiologia , Rede Nervosa , Plasticidade Neuronal/fisiologia , Condutos Olfatórios/fisiologia , Percepção Olfatória/fisiologia , Olfato/fisiologia , Animais , Teorema de Bayes , Simulação por Computador , Mamíferos , Neurônios/citologia , Neurônios/fisiologia , Odorantes/análise , Bulbo Olfatório/fisiologia , Recompensa
16.
PLoS Comput Biol ; 16(8): e1007983, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32745096

RESUMO

Many large-scale functional connectivity studies have emphasized the importance of communication through increased inter-region correlations during task states. In contrast, local circuit studies have demonstrated that task states primarily reduce correlations among pairs of neurons, likely enhancing their information coding by suppressing shared spontaneous activity. Here we sought to adjudicate between these conflicting perspectives, assessing whether co-active brain regions during task states tend to increase or decrease their correlations. We found that variability and correlations primarily decrease across a variety of cortical regions in two highly distinct data sets: non-human primate spiking data and human functional magnetic resonance imaging data. Moreover, this observed variability and correlation reduction was accompanied by an overall increase in dimensionality (reflecting less information redundancy) during task states, suggesting that decreased correlations increased information coding capacity. We further found in both spiking and neural mass computational models that task-evoked activity increased the stability around a stable attractor, globally quenching neural variability and correlations. Together, our results provide an integrative mechanistic account that encompasses measures of large-scale neural activity, variability, and correlations during resting and task states.


Assuntos
Encéfalo/fisiologia , Rede Nervosa/fisiologia , Potenciais de Ação/fisiologia , Adulto , Animais , Encéfalo/diagnóstico por imagem , Feminino , Humanos , Macaca mulatta , Imagem por Ressonância Magnética , Masculino , Rede Nervosa/diagnóstico por imagem , Neurônios/fisiologia , Análise e Desempenho de Tarefas , Adulto Jovem
17.
PLoS Comput Biol ; 16(8): e1008080, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32745134

RESUMO

Neural computation is determined by neurons' dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron's total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.


Assuntos
Modelos Neurológicos , Rede Nervosa , Sinapses/fisiologia , Animais , Drosophila melanogaster , Larva/citologia , Larva/fisiologia , Corpos Pedunculados/citologia , Corpos Pedunculados/fisiologia , Rede Nervosa/citologia , Rede Nervosa/fisiologia , Neurônios/citologia , Neurônios/fisiologia
18.
PLoS Comput Biol ; 16(8): e1008118, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32764742

RESUMO

Hebbian plasticity, a mechanism believed to be the substrate of learning and memory, detects and further enhances correlated neural activity. Because this constitutes an unstable positive feedback loop, it requires additional homeostatic control. Computational work suggests that in recurrent networks, the homeostatic mechanisms observed in experiments are too slow to compensate instabilities arising from Hebbian plasticity and need to be complemented by rapid compensatory processes. We suggest presynaptic inhibition as a candidate that rapidly provides stability by compensating recurrent excitation induced by Hebbian changes. Presynaptic inhibition is mediated by presynaptic GABA receptors that effectively and reversibly attenuate transmitter release. Activation of these receptors can be triggered by excess network activity, hence providing a stabilising negative feedback loop that weakens recurrent interactions on sub-second timescales. We study the stabilising effect of presynaptic inhibition in recurrent networks, in which presynaptic inhibition is implemented as a multiplicative reduction of recurrent synaptic weights in response to increasing inhibitory activity. We show that networks with presynaptic inhibition display a gradual increase of firing rates with growing excitatory weights, in contrast to traditional excitatory-inhibitory networks. This alleviates the positive feedback loop between Hebbian plasticity and network activity and thereby allows homeostasis to act on timescales similar to those observed in experiments. Our results generalise to spiking networks with a biophysically more detailed implementation of the presynaptic inhibition mechanism. In conclusion, presynaptic inhibition provides a powerful compensatory mechanism that rapidly reduces effective recurrent interactions and thereby stabilises Hebbian learning.


Assuntos
Modelos Neurológicos , Inibição Neural/fisiologia , Plasticidade Neuronal/fisiologia , Sinapses/fisiologia , Animais , Biologia Computacional , Homeostase , Aprendizagem , Memória , Neurônios/fisiologia
19.
Nat Commun ; 11(1): 3980, 2020 08 07.
Artigo em Inglês | MEDLINE | ID: mdl-32769969

RESUMO

Recent research has highlighted a role for the hippocampus and a Posterior Medial cortical network in signaling event boundaries. However, little is known about whether or how these neural processes change over the course of healthy aging. Here, 546 cognitively normal participants 18-88 years old viewed a short movie while brain activity was measured using fMRI. The hippocampus and regions of the Posterior Medial network show increased activity at event boundaries, but these boundary-evoked responses decrease with age. Boundary-evoked activity in the posterior hippocampus predicts performance on a separate test of memory for stories, suggesting that hippocampal activity during event segmentation may be a broad indicator of individual differences in episodic memory ability. In contrast, boundary-evoked responses in the medial prefrontal cortex and middle temporal gyrus increase across the age range. These findings suggest that aging may alter neural processes for segmenting and remembering continuous real-world experiences.


Assuntos
Envelhecimento/fisiologia , Hipocampo/fisiologia , Neurônios/fisiologia , Núcleos Ventrais do Tálamo/fisiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Oxigênio/sangue , Fatores de Tempo , Adulto Jovem
20.
Nat Commun ; 11(1): 3983, 2020 08 07.
Artigo em Inglês | MEDLINE | ID: mdl-32770078

RESUMO

Frontal top-down cortical neurons projecting to sensory cortical regions are well-positioned to integrate long-range inputs with local circuitry in frontal cortex to implement top-down attentional control of sensory regions. How adolescence contributes to the maturation of top-down neurons and associated local/long-range input balance, and the establishment of attentional control is poorly understood. Here we combine projection-specific electrophysiological and rabies-mediated input mapping in mice to uncover adolescence as a developmental stage when frontal top-down neurons projecting from the anterior cingulate to visual cortex are highly functionally integrated into local excitatory circuitry and have heightened activity compared to adulthood. Chemogenetic suppression of top-down neuron activity selectively during adolescence, but not later periods, produces long-lasting visual attentional behavior deficits, and results in excessive loss of local excitatory inputs in adulthood. Our study reveals an adolescent sensitive period when top-down neurons integrate local circuits with long-range connectivity to produce attentional behavior.


Assuntos
Envelhecimento/fisiologia , Atenção/fisiologia , Comportamento Animal/fisiologia , Neurônios/fisiologia , Potenciais de Ação/fisiologia , Animais , Channelrhodopsins/metabolismo , Giro do Cíngulo/fisiologia , Masculino , Camundongos Endogâmicos C57BL , Modelos Neurológicos , Inibição Neural/fisiologia , Terminações Pré-Sinápticas/fisiologia , Raiva/fisiopatologia , Sinapses/fisiologia , Visão Ocular/fisiologia
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