RESUMO
Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware.
Assuntos
Aprendizagem , Redes Neurais de Computação , Computadores , Encéfalo/fisiologia , Neurônios/fisiologiaRESUMO
Hyperactivity mediated by synaptotoxic ß-amyloid (Aß) oligomers is one of the earliest forms of neuronal dysfunction in Alzheimer's disease. In the search for a preventive treatment strategy, we tested the effect of scavenging Aß peptides before Aß plaque formation. Using in vivo two-photon calcium imaging and SF-iGluSnFR-based glutamate imaging in hippocampal slices, we demonstrate that an Aß binding anticalin protein (Aß-anticalin) can suppress early neuronal hyperactivity and synaptic glutamate accumulation in the APP23xPS45 mouse model of ß-amyloidosis. Our results suggest that the sole targeting of Aß monomers is sufficient for the hyperactivity-suppressing effect of the Aß-anticalin at early disease stages. Biochemical and neurophysiological analyses indicate that the Aß-anticalin-dependent depletion of naturally secreted Aß monomers interrupts their aggregation to neurotoxic oligomers and, thereby, reverses early neuronal and synaptic dysfunctions. Thus, our results suggest that Aß monomer scavenging plays a key role in the repair of neuronal function at early stages of AD.
Assuntos
Doença de Alzheimer , Peptídeos beta-Amiloides , Modelos Animais de Doenças , Hipocampo , Camundongos Transgênicos , Neurônios , Animais , Feminino , Humanos , Masculino , Camundongos , Doença de Alzheimer/metabolismo , Doença de Alzheimer/patologia , Doença de Alzheimer/genética , Peptídeos beta-Amiloides/metabolismo , Cálcio/metabolismo , Ácido Glutâmico/metabolismo , Hipocampo/metabolismo , Hipocampo/patologia , Camundongos Endogâmicos C57BL , Neurônios/metabolismo , Neurônios/efeitos dos fármacos , Placa Amiloide/metabolismo , Placa Amiloide/patologia , Sinapses/metabolismo , Sinapses/efeitos dos fármacosRESUMO
In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.