1,721,065 research outputs found
Change of network dynamics in a neuro-robotic system
No full textIn the past, tetanic stimulation has been used in several different instances to induce changes in the firing patterns of neural networks in vitro. In this paper, we ran a new experimental campaign to verify if this protocol induced lasting changes and if those changes were predictable. We found out that our stimulation protocol led to different results in cortical and hippocampal preparations: in the first case, stronger connections were weakened, resulting in a reduction of bursting activity and late evoked response; in the case of hippocampal preparations, single strong connections underwent strong changes but, on average, remained unchanged. In both preparations, the geometry of induced changes remains largely uncorrelated with the actual site of stimulation delivery. © 2014 Springer International Publishing
A self-adapting approach for the detection of bursts and network bursts in neuronal cultures
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Development of excitatory neuronal networks derived from human induced pluripotent stem cells
No full textThe combination of neuronal networks derived from human induced pluripotent stem cells (h-iPSCs) with micro-electrode arrays (MEAs) opened new perspectives in the neuroscience and neuroengineering fields. In this paper, we present the electrophysiological characterization of excitatory h-iPSCs-derived neuronal networks obtained from healthy subjects. We recorded the neural activity from 35 up to 91 days in vitro, and we extrapolated the main features describing both firing and bursting patterns. With this work, we provide a solid baseline for future exploitation of in vitro human-derived experimental models in the field of personalized medicine
Bioartificial neuronal networks: coupling networks of biological neurons to microtransducer arrays
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Dissociated cortical networks show spontaneously correlated activity patterns during in vitro development
No full textInvestigating the impact of electrical stimulation temporal distribution on cortical network responses
No full textBackground: The brain is continuously targeted by a wealth of stimuli with complex spatio-temporal patterns and has presumably evolved in order to cope with those inputs in an optimal way. Previous studies investigating the response capabilities of either single neurons or intact sensory systems to external stimulation demonstrated that stimuli temporal distribution is an important, if often overlooked, parameter. Results: In this study we investigated how cortical networks plated over micro-electrode arrays respond to different stimulation sequences in which inter-pulse intervals followed a 1/f β distribution, for different values of β ranging from 0 to ∞. Cross-correlation analysis revealed that network activity preferentially synchronizes with external input sequences featuring β closer to 1 and, in any case, never for regular (i.e. fixed-frequency) stimulation sequences. We then tested the interplay between different average stimulation frequencies (based on the intrinsic firing/bursting frequency of the network) for two selected values of β, i.e. 1 (scale free) and ∞ (regular). In general, we observed no preference for stimulation frequencies matching the endogenous rhythms of the network. Moreover, we found that in case of regular stimulation the capability of the network to follow the stimulation sequence was negatively correlated to the absolute stimulation frequency, whereas using scale-free stimulation cross-correlation between input and output sequences was independent from average input frequency. Conclusions: Our results point out that the preference for a scale-free distribution of the stimuli is observed also at network level and should be taken into account in designing more efficient protocols for neuromodulation purposes
Profiling of phase-amplitude couplings across sleep for personalized neuroengineering systems
No full textIn this work, we computed sleep-wake cycle (SWC) stage-specific cross-frequency couplings in order to identify patterns of neural synchronization with neurobiological relevance. This may be used for the control of neuroengineering systems capable of delivering personalized therapeutic electrical stimulation according to relevant sleep events
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