Targeted photostimulation uncovers circuit motifs supporting short-term memory

Daie, Kayvon; Svoboda, Karel; Druckmann, Shaul

doi:10.1101/623785

“…A similar mathematical approach has been used recently to analyze the interaction of drugs and their resulting changes in cell morphologies, in order to shed light on the link between drug combinations and treatment of diseases ( 39 ). Targeted multiple-neuron perturbations of functionally identified neurons have in fact been used recently to shed light on the dynamics of persistent activity and short-term memory in mice ( 40 ). Similar approaches can be recruited to reveal how neurons work in tandem to shape functional processing in sensory cortices, with the possibility that different network perturbomes can dissociate between functional and dysfunctional circuitries ( 41 , 42 ).…”

Section: Discussionmentioning

confidence: 99%

Theory of neuronal perturbome in cortical networks

Sadeh

¹

,

Clopath

²

2020

Proc. Natl. Acad. Sci. U.S.A.

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To unravel the functional properties of the brain, we need to untangle how neurons interact with each other and coordinate in large-scale recurrent networks. One way to address this question is to measure the functional influence of individual neurons on each other by perturbing them in vivo. Application of such single-neuron perturbations in mouse visual cortex has recently revealed feature-specific suppression between excitatory neurons, despite the presence of highly specific excitatory connectivity, which was deemed to underlie feature-specific amplification. Here, we studied which connectivity profiles are consistent with these seemingly contradictory observations, by modeling the effect of single-neuron perturbations in large-scale neuronal networks. Our numerical simulations and mathematical analysis revealed that, contrary to the prima facie assumption, neither inhibition dominance nor broad inhibition alone were sufficient to explain the experimental findings; instead, strong and functionally specific excitatory–inhibitory connectivity was necessary, consistent with recent findings in the primary visual cortex of rodents. Such networks had a higher capacity to encode and decode natural images, and this was accompanied by the emergence of response gain nonlinearities at the population level. Our study provides a general computational framework to investigate how single-neuron perturbations are linked to cortical connectivity and sensory coding and paves the road to map the perturbome of neuronal networks in future studies.

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“…A similar mathematical approach has been recruited recently to analyze the interaction of drugs and their resulting changes in cell morphologies, in order to shed light on the link between drug combinations and treatment of diseases (Caldera et al, 2019). Targeted multiple-neuron perturbations of functionally identified neurons have in fact been used recently to shed light on the dynamics of persistent activity and short-term memory in mice (Daie, Svoboda and Druckmann, 2019). Similar approaches can be recruited to reveal how neurons work in tandem to shape functional processing in sensory cortices, with the possibility that different network perturbomes can dissociate between functional and dysfunctional circuitries.…”

Section: Discussionmentioning

confidence: 99%

Theory of Neuronal Perturbome: Linking Connectivity to Coding via Perturbations

Sadeh

¹

,

Clopath

²

2020

Preprint

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To unravel the functional properties of the brain, we need to untangle how neurons interact with each other and coordinate in large-scale recurrent networks. One way to address this question is to measure the functional influence of individual neurons on each other by perturbing them in vivo. Application of such single-neuron perturbations in mouse visual cortex has recently revealed feature-specific suppression between excitatory neurons, despite the presence of highly specific excitatory connectivity, which was deemed to underlie feature-specific amplification. Here, we studied which connectivity profiles are consistent with these seemingly contradictory observations, by modelling the effect of single-neuron perturbations in large-scale neuronal networks. Our numerical simulations and mathematical analysis revealed that, contrary to the prima facie assumption, neither inhibition-dominance nor broad inhibition alone were sufficient to explain the experimental findings; instead, strong and functionally specific excitatory-inhibitory connectivity was necessary, consistent with recent findings in the primary visual cortex of rodents. Such networks had a higher capacity to encode and decode natural images in turn, which was accompanied by the emergence of response gain nonlinearities at the population level. Our study provides a general computational framework to investigate how single-neuron perturbations are linked to cortical connectivity and sensory coding, and paves the road to map the perturbome of neuronal networks in future studies. amplification and suppression). We found that to obtain feature-specific suppression, strong and functionally-specific subnetworks of E and I were necessary. That is, both E and I neurons with similar receptive fields (RFs) should be connected together more strongly than their non-similar counterparts, which was consistent with recent results in visual cortex (Znamenskiy et al., 2018).Our modelling results shed light on the above mentioned controversy by showing that featurespecific amplification and suppression could both exist in the cortex, depending on the regime of functional similarity between the influencers and the influencees. Our model suggests specific predictions on how to observe this in the cortex. Computational modelling also helped us to formulate further predictions that experiments could not directly assess, for instance regarding the temporal evolution of functional influence. We linked the result of single-neuron perturbations to sensory processing, by studying how our model networks in different regimes encode and decode natural images. More generally, we show that our theory can be extended to study multiple-cell perturbations to map the perturbome of neuronal networks in future. Results Single-Neuron Perturbations in Large-scale Networks of Visual CortexWe studied the effect of single-neuron perturbations on functional properties of neurons in largescale network models of visual cortex (Figure 1A). Individual excitatory and inhibitory neurons were modelled ...

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“…Testing how decoding strength in different brain areas relates to the quality of WM-based decisions will be central to evaluating the anatomical separation hypothesis. Ultimately, causal interventions (e.g., Daie et al, 2019 ) may help determine whether only regions exclusively coding for active WM drive behaviour.…”

Section: Orthogonal Coding Schemes For Active and Latent Wmmentioning

confidence: 99%

Theoretical distinction between functional states in working memory and their corresponding neural states

Stokes

¹

,

Muhle-Karbe

²

,

Myers

³

2020

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Working memory (WM) is important for guiding behaviour, but not always for the next possible action. Here we define a WM item that is currently relevant for guiding behaviour as the functionally "active" item; whereas items maintained in WM, but not immediately relevant to behaviour, are defined as functionally "latent". Traditional neurophysiological theories of WM proposed that content is maintained via persistent neural activity (e.g., stable attractors); however, more recent theories have highlighted the potential role for "activity-silent" mechanisms (e.g., short-term synaptic plasticity). Given these somewhat parallel dichotomies, functionally active and latent cognitive states of WM have been associated with storage based on persistent-activity and activity-silent neural mechanisms, respectively. However, in this article we caution against a one-to-one correspondence between functional and activity states. We argue that the principal theoretical requirement for active and latent WM is that the corresponding neural states play qualitatively different functional roles. We consider a number of candidate solutions, and conclude that the neurophysiological mechanisms for functionally active and latent WM items are theoretically independent of the distinction between persistent activity-based and activity-silent forms of WM storage.

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Targeted photostimulation uncovers circuit motifs supporting short-term memory

Cited by 22 publications

References 42 publications

Theory of neuronal perturbome in cortical networks

Theory of neuronal perturbome in cortical networks

Theory of Neuronal Perturbome: Linking Connectivity to Coding via Perturbations

Theoretical distinction between functional states in working memory and their corresponding neural states

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