Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs

A Spike-Based Grammar Underlies Directional Modification in Network Connectivity: Effect on Bursting Activity and Implications for Bio-Hybrids Systems

Developed biological systems are endowed with the ability of interacting with the environment; they sense the external state and react to it by changing their own internal state. Many attempts have been made to build ‘hybrids’ with the ability of perceiving, modifying and reacting to external modifications. Investigation of the rules that govern network changes in a hybrid system may lead to finding effective methods for ‘programming’ the neural tissue toward a desired task. Here we show a new perspective in the use of cortical neuronal cultures from embryonic mouse as a working platform to study targeted synaptic modifications. Differently from the common timing-based methods applied in bio-hybrids robotics, here we evaluated the importance of endogenous spike timing in the information processing. We characterized the influence of a spike-patterned stimulus in determining changes in neuronal synchronization (connectivity strength and precision) of the evoked spiking and bursting activity in the network. We show that tailoring the stimulation pattern upon a neuronal spike timing induces the network to respond stronger and more precisely to the stimulation. Interestingly, the induced modifications are conveyed more consistently in the burst timing. This increase in strength and precision may be a key in the interaction of the network with the external world and may be used to induce directional changes in bio-hybrid systems