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Journal Article•DOI Spike initiating dynamics of the neuron with different adaptation mechanisms to extracellular electric fields Guosheng Yi, Jiang Wang, Bin Deng, Xile Wei - Show less +3 more 01 May 2015-Communications in Nonlinear Science and Numerical Simulation 10 Citations	It could contribute to uncover the underlying mechanism of how neuron encodes electric field signals.
Open access•Journal Article•DOI Neuronal Modulation in the Prefrontal Cortex in a Transitive Inference Task: Evidence of Neuronal Correlates of Mental Schema Management Emiliano Brunamonti, Valentina Mione, Fabio Di Bello, Pierpaolo Pani, Aldo Genovesio, Stefano Ferraina - Show less +5 more 27 Jan 2016-The Journal of Neuroscience 16 Citations	Our results demonstrated that single-neuron activity supports the construction of an abstract, mental schema of ordered items in solving the task and that this representation is independent of the reward value that is experienced for the single items.
Journal Article•DOI Impulsive pinning complex dynamical networks and applications to firing neuronal synchronization Jin Zhou, Quanjun Wu, Lan Xiang - Show less +2 more 22 Feb 2012-Nonlinear Dynamics 67 Citations	It turns out that the firing activities of a single neuron can induce synchronization of the underlying neuronal networks.
Open access•Journal Article•DOI Simultaneous optical recording of activity from many neurons during feeding in Navanax Jill A. London, Dejan Zecevic, Lawrence B. Cohen - Show less +2 more 01 Mar 1987-The Journal of Neuroscience 72 Citations	Thus, in certain invertebrate ganglia, it is possible to make a reasonably complete recording of the neuron activity responsible for generating relatively complex behaviors.
Open access•Journal Article•DOI A spiking neuron model: applications and learning Chris Christodoulou, Guido Bugmann, T.G. Clarkson - Show less +2 more 01 Sep 2002-Neural Networks 41 Citations	Overall this work illustrates how a hardware-realisable neuron model can capitalise on the unique computational capabilities of biological neurons.

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Emotion influences fast and slow thinking differently. Fast thinking, characterized by rapid and varied thought sequences, tends to induce more positive affect, while slow, repetitive thinking can lead to dejection. On the other hand, negative emotions can slow down movement speed, affecting athletic performance, as seen in studies where participants exhibited slower movements in negative emotional conditions compared to neutral ones. Additionally, emotional processing can impact cognitive control, with concurrent emotion increasing neural activation during high cognitive control conditions, involving regions associated with cognitive control like the prefrontal cortex and basal ganglia. Therefore, emotions play a significant role in shaping the speed and quality of both fast and slow thinking processes.How to compare the physiological data between in neutral state and emotion state?

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