Inhibitory neurons are a Central Controlling regulator in the effective cortical microconnectome

Abstract

The brain is a network system in which excitatory and inhibitory neurons keep the activity balanced in the highly non-uniform connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons. So, in general, how the inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question.We observed effective networks, reflecting causal interactions, of ~1000 neurons in cortical acute slices. Surprisingly, we found that inhibitory neurons are not only located at more central positions than excitatory neurons but also have stronger controlling ability of other neurons than excitatory neurons. Besides, we found that the precedence in centrality and controlling ability of inhibitory neurons are well observed in deep cortical layers by comparing with distribution of neurons coloured by NeuN immunostaining data. Preceding the observation, we also found that inhibitory neurons show higher firing rate than excitatory neurons, and that their firing rate also closely obey a log-normal distribution as previously known about excitatory neurons. Additionally, their connectivity strengths also obeyed a log-normal distribution.In summary, within the network interaction of huge numbers of neurons, inhibitory neurons seem to produce a central controlling system that sustains the homeostatic behavior of the brain. A similar evaluation in different life stages and in disease states etc. will not only provide deeper understandings in the homeostasis of the brain, but also will provide a selective and effective way to stimulate individual neurons to modulate neuropsychiatry or neurodegeneration disease states.

Single spikes drive sequential propagation and routing of activity in a cortical network

“…We generated inhibitory connections from a scaled-up copy of the distribution of excitatory conductances, resulting in a skewed distribution, as observed in other systems ( Iascone et al, 2020 ; Kajiwara et al, 2020 ; Rubinski and Ziv, 2015 ). We assumed that strengths for excitatory and inhibitory connections are independent of distance.…”

Inhibition-Dominated Rich-Club Shapes Dynamics in Cortical Microcircuits

“…(Modol et al, 2020). Kajiwara and colleagues (Kajiwara et al, 2021) found that inhibitory neurons were more centrally located within the functional network topology of somato-motor cortex in mouse slices. However, a broader characterization of functional connectivity in cortical circuits is lacking, especially in a higher cortical area such as the orbitofrontal cortex.…”

“…In the past decade, the relationship between neuron types and network structure has received increased research attention. In the developing hippocampus, hub neurons are all inhibitory (Bonifazi et al, 2009); more recent work in mouse somato-motor cortex slices found inhibitory neurons were more topologically central within networks than excitatory neurons (Kajiwara et al, 2021). However, neither of these studies directly examined the rich club and its cell type composition.…”

Early lock-in of structured and specialised information flows during neural development

“…Indeed, to the best of the authors’ knowledge, all previous applications of the discrete-time TE estimator to spiking data from cell cultures used only a single bin in their history embeddings. The bin widths used in those studies were 40 s ( Nigam et al, 2016 ), 0.3 ms ( Garofalo et al, 2009 ), and 1 ms ( Shimono and Beggs, 2015 ; Kajiwara et al, 2020 ). Some studies chose to examine the TE values produced by multiple different bin widths, specifically, 0.6 ms and 100 ms ( Matsuda et al, 2013 ), 1.6 ms and 3.5 ms ( Timme et al, 2016 ), and 10 different widths ranging from 1 ms to 750 ms ( Timme et al, 2014 ).…”