Topic: spiking neural network model

Brain networks have the remarkable ability to adapt to neuron loss; however, little is known about how population spiking activity is affected quantitatively and even less is known about how populations adapt to restore behavior. Here, we analyzed the impact of neuron loss on population correlation structure using numerical simulations, a spiking neural network model, and in vivo spiking data from a lesion technique in which focal neuron loss is created through chronically implanted electrode arrays in awake-behaving animals. This easily-repeated perturbation allows neuroscientists to track t

Brain-on-a-chip, a method for reconstructing neuronal networks with brain-like properties in a cultured environment, has attracted attention for investigating the relationship between connection structure and activity patterns. As fundamental technologies for realizing such devices, bioengineering technologies to reconstruct modular structure and directional connection with living cells have been developed previously, they have not been integrated to realize modular networks with directionality. In this study, we developed a novel microfluidic device to reconstruct such network with cultured c

Understanding how our brain integrates information across the visual space is crucial for understanding how visual information is encoded. In the supragranular and infragranular layers of the primary visual cortex (V1) of higher mammals, orientation-biased horizontal connections span several millimeters and connect neurons that encode different portions of the visual space [1], while connections in the granular layers remain local.We presented disks of varying radii and annuli of varying inner radii to anesthetized cats to investigate laminar differences in spatial integration of the stimuli i