by Kristine Heiney (Department of Computer Science, Oslo Metropolitan University, Oslo, Norway)
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The dynamic state of neuronal networks is influenced by a wide range of functional and structural factors, including network connectivity, synaptic function, and the balance of excitation and inhibition in the network. Additionally, it has been shown that only some dissociated networks self-organize into the critical state as they are left to mature in vitro, with many ultimately showing the tightly synchronized behavior indicative of a supercritical state.
To explore the possibility of manipulating dissociated networks into the critical state by chemical intervention, we increased inhibition in the network by adding -aminobutyric acid (GABA) at day in vitro (DIV) 51. Prior to perturbation with GABA, the networks showed large network-wide bursts with close synchrony, and the size distribution of neuronal avalanches was bimodal. After perturbation, the synchrony was broken, and the avalanche distribution followed a power law, one of the hallmarks of criticality.
This finding indicates that it is possible to use chemical perturbation in dissociated networks to manipulate the dynamic state. This will allow for future comparative experimental studies on the characteristics and computational capabilities of networks in different dynamical regimes, shedding light on the mechanisms and benefits of critical and near-critical behavior.
Many factors related to computational function are optimized when systems are in the critical state, including dynamic range, information capacity, and mutual information. Although there has recently been a great deal of evidence that the brain self-organizes into the critical state to optimize its capacity for computation, studies of in vitro networks indicate that not all dissociated networks reach criticality during their maturation. In this work, we examined whether we could manipulate supercritical networks into the critical state by increasing inhibition in the network.
The dynamic state of a network is often determined by evaluating the behavior of cascades of activity called neuronal avalanches. We observed the spontaneous activity of networks of dissociated rat cortical neurons over 51 days in vitro (DIV) using microelectrode arrays (MEAs) and assessed their avalanche scaling behavior. After an initial period of low activity, the networks showed first exponential and then bimodal avalanche scaling, respectively indicative of sub- and supercritical dynamics but notably did not show the power-law scaling observed at criticality.
At DIV 51, the networks showed tightly synchronized behavior indicative of a supercritical state. To disrupt the synchrony, we added -aminobutyric acid (GABA) to increase inhibition in the network. After perturbation, avalanches showed power-law scaling across a wide range of time bin sizes, one of the hallmarks of criticality. This finding indicates that it may be possible to use chemical perturbation in dissociated networks to manipulate the dynamic state. This will allow for future comparative experimental studies on the characteristics and computational capabilities of networks in different dynamical regimes, shedding light on the mechanisms and computational benefits of critical and near-critical behavior.
Hi Christine, thanks for submitting this work. Happy to talk to you about your experimental condition. We didn’t succeed to move cultures that had gone supercritical back to a critical state using GABA but maybe we didn’t titrate well enough. What you show is that GABA allows this to happen and I was wondering whether after helping the network to maintain the critical state in the presence of GABBA whether the network is able to maintain this after you remove GABA?
Hi Dietmar, Thanks for your interest in my poster! The response we saw was transient and dose-dependent. In the case of the culture that is shown in the poster, we were able to achieve power-law avalanche scaling with microliter volumes of 50 uM GABA, and the bimodal distribution returned after the GABA was washed out or metabolized. More details in the conference paper here: https://ieeexplore.ieee.org/document/9002693
As Paolo Massobrio discussed in his talk, many cultures do not self-organize into the critical state, and we’re curious to see if simple interventions can be applied to manipulate them into the critical state. We’re performing some follow-up experiments to relate the avalanche scaling to other features of network function and computation, but I’m still in the early stages of analyzing at the data. I’d be happy to discuss with you in more detail over email or Zoom if you’re interested!