Rapid Rebalancing of Excitation and Inhibition by Cortical Circuitry

Moore, Alexandra K.; Weible, Aldis P.; Balmer, Timothy S.; Trussell, Laurence O.; Wehr, Michael

doi:10.1016/j.neuron.2018.01.045

Cited by 93 publications

(113 citation statements)

References 72 publications

(110 reference statements)

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“…In the absence of data that reveal the nature of interlaminar interactions, extending our model to incorporate these is impractical given the large number of parameters to vary. Experiments in ALM and S1 where the optogenetic marker is expressed in only one layer at a time would constraint models which include interlaminar interactions and facilitate their analysis (Moore et al, 2018) .…”

Section: Limitationsmentioning

confidence: 99%

Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

Mahrach¹,

Chen

et al. 2019

Preprint

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GABAergic interneurons can be subdivided into three subclasses: parvalbumin positive (PV), somatostatin positive (SOM) and serotonin positive neurons. With principal cells (PCs) they form complex networks. We examine PCs and PV responses in mouse anterior lateral motor cortex (ALM) and barrel cortex (S1) upon PV photostimulation in vivo . In layer 5, the PV response is paradoxical: photoexcitation reduces their activity. This is not the case in ALM layer 2/3. We combine analytical calculations and numerical simulations to investigate how these results constrain the architecture. Twopopulation models cannot account for the results. Networks with three inhibitory populations and V1like architecture account for the data in ALM layer 2/3. Our data in layer 5 can be accounted for if SOM neurons receive inputs only from PCs and PV neurons. In both fourpopulation models, the paradoxical effect implies not too strong recurrent excitation. It is not evidence for stabilization by inhibition.sufficiently strong, namely ifThe denominator in is the strength of the connection from the SOM population to J EE the VIP population. The numerator is the gain of the pathway which connects these two populations via the PCs. When the negative contribution of the disinhibitory J EE > J EE loop PCVIPSOMPC dominates in the expression of . It is the opposite when χ II . The stability of the balanced state provides other necessary conditions that J EE < J EE the interactions must satisfy (Materials and Methods). In particular, the determinant of the interaction matrix, , must be positive. J of the positive feedback loop, SOMXPCSOM, is sufficiently strong (Supplementary Materials, SMD). Obviously, this condition simplifies and reads J J J EX XS > J XX ES (4) Remarkably, this inequality does not depend on . This is in contrast to what J EE happens in Model 1 where the paradoxical effect occurs only if is small enough J EE (see Eq. (2)). https://docs.google.com/document/d/1UaHERm5J7ZX8fMIoyG42_mFfOzWPZq32QDjE_gxdSgk/edit?ts=5c9dfa46# 24/46 was already substantial for small light intensities, where the PCs were still significantly active. The twopopulation model cannot account for this feature. In Model 1, whether the network exhibits a paradoxical effect depends on the value of the ratio where . Here, , is theThe requirement that at baseline the network state is fully balanced and stable implies that J I0 Therefore, the PC population activity increases upon PC stimulation if J J J J IX XS > IS XX (SM61)

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Section: Limitationsmentioning

confidence: 99%

Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

Mahrach¹,

Chen

et al. 2019

Preprint

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“…Excitation and inhibition are tightly coupled in cortical circuits [33][34][35][36] . Strong inhibition keeps baseline firing rates low, which limits the dynamic range available for decreases in firing rate to encode information.…”

Section: Why Would Cortex Preferentially Decode From Increments In Nementioning

confidence: 99%

Perceptual detection depends on spike count integration

Cone

Bade

Masse

et al. 2019

Preprint

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Whenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking.Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

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“…10 in (Sadeh et al, 2017)). While reducing transplant derived inhibition causes an increase in some excitatory cells' firing rate, this enhanced excitation might activate other inhibitory cells that in turn feedback to suppress other excitatory cells (Moore et al, 2018). Figures 2E and F show that the ratio of firing rates during optogenetic suppression (light on) to control (light off) non-deprived-eye responses are more strongly modulated in both populations.…”

Section: Resultsmentioning

confidence: 95%

“…An alternative approach to determine whether transplantation specifically inhibits deprived-eye responses after MD is to activate the transplanted cells. Since optogenetic activation and inactivation of interneurons need not produce symmetric effects (Phillips and Hasenstaub, 2016;Moore et al, 2018), the outcome of this experiment is not trivial. To activate transplanted cells optogenetically, donor embryos expressing the gene for channelrhodopsin-2 in all of the inhibitory neurons were generated by crossing Gad2-Cre mouse line with Ai32 (RCL-ChR2-EYFP) line.…”

Section: Resultsmentioning

confidence: 99%

Transplanted cells are essential for the induction but not the expression of cortical plasticity

Hoseini¹,

Rakela²,

Flores-Ramirez

et al. 2019

Preprint

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Transplantation of even a small number of embryonic inhibitory neurons from the medial ganglionic eminence (MGE) into postnatal visual cortex makes it lose responsiveness to an eye deprived of vision when the transplanted neurons reach the age of the normal critical period of activity-dependent ocular dominance (OD) plasticity. The transplant might induce OD plasticity in the host circuitry or might instead construct a parallel circuit of its own to suppress cortical responses to the deprived-eye. We transplanted MGE neurons expressing archaerhodopsin, closed one eyelid for 4-5 days, and, as expected, observed transplant-induced OD plasticity. This plasticity was evident even when the activity of the transplanted cells was suppressed optogenetically, demonstrating that the plasticity was produced by changes in the host visual cortex.

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Rapid Rebalancing of Excitation and Inhibition by Cortical Circuitry

Cited by 93 publications

References 72 publications

Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

Perceptual detection depends on spike count integration

Transplanted cells are essential for the induction but not the expression of cortical plasticity

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