Self-organization of information processing in developing neuronal networks
نویسندگان
چکیده
منابع مشابه
Self-Organized Criticality in Developing Neuronal Networks
Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monito...
متن کاملStatistical properties of information processing in neuronal networks.
Information processing and coding were analysed in dissociated hippocampal cultures, grown on multielectrode arrays. Multisite stimulation was used to activate different neurons and pathways of the network. The neural activity was binned into firing rates and the variability of the firing of individual neurons and of the whole population was analysed. In individual neurons, the timing of the fi...
متن کاملOptimizing information processing in neuronal networks beyond critical states
Critical dynamics have been postulated as an ideal regime for neuronal networks in the brain, considering optimal dynamic range and information processing. Herein, we focused on how information entropy encoded in spatiotemporal activity patterns may vary in critical networks. We employed branching process based models to investigate how entropy can be embedded in spatiotemporal patterns. We det...
متن کاملDeveloping neuronal networks: Self-organized criticality predicts the future
Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stage...
متن کاملNeuronal Self-Organization of Motion Percepts
Zusammenfassung A neural network which models multi-stable perception is presented. The network consists of sensor and inner neurons. The dynamics is established by a stochastic neuronal dynamics, a formal Hebb-type coupling dynamics and a resource mechanism that corresponds to saturation eeects in perception. From this a system of coupled diierential equations is derived and analyzed. Single s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Neuroscience
سال: 2015
ISSN: 1471-2202
DOI: 10.1186/1471-2202-16-s1-p221