Cellular Mechanisms of Conscious Processing

Aru, Jaan; Suzuki, Mototaka; Larkum, Matthew E.

doi:10.1016/j.tics.2021.09.008

Cited by 18 publications

(25 citation statements)

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“…NMDA-dependent excitation is affected by various neuromodulators, which can enable (Yang et al 2013), enhance (Arnsten et al 2020; Galvin et al 2020; Vijayraghavan et al 2007), or counteract (Arnsten et al 2020, 2019; Vijayraghavan et al 2007) its effects. NMDA-spikes are relatively localized within pyramidal cell dendrites, but they increase the probability of plateau-like calcium spikes, which propagate a much greater distance towards the soma (Aru et al 2020). This dendrite-soma coupling fades under anaesthesia (Suzuki and Larkum 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Once a stimulus is consciously perceived, an array of cognitive computations can be performed that are not available for unconsciously perceived stimuli (Trübutschek et al 2019). Although this behavioral phenomenon has been consistently observed across species, the network, cellular and synaptic mechanisms of conscious access are hotly debated, and largely unresolved (Aru et al 2020;Baars 2005;Dehaene et al 1998;Lamme and Roelfsema 2000;Lau and Rosenthal 2011;Mashour et al 2020;Tononi 2004).…”

Section: Introductionmentioning

confidence: 99%

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A connectome-based model of conscious access in monkey cortex

Klatzmann

Bliss

Theodoni

et al. 2022

Preprint

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A growing body of evidence suggests that conscious perception of a sensory stimulus triggers an all-or-none activity across multiple cortical areas, a phenomenon called 'ignition'. In contrast, the same stimulus, when undetected, induces only transient activity. In this work, we report a large-scale model of the macaque cortex based on recently quantified structural connectome data. We use this model to simulate a detection task, and demonstrate how a dynamical bifurcation mechanism produces ignition-like events in the model network. Within this framework, the model predicts that feedforward excitatory transmission is primarily mediated by the fast AMPA receptors to ensure rapid signal propagation from sensory to associative areas. In contrast, a large fraction of the inter-areal feedback projections and local recurrent excitation depend on the slow NMDA receptors, to ensure ignition of distributed frontoparietal activity. Our model predicts, counterintuitively, that fast-responding sensory areas contain a higher ratio of NMDA to AMPA receptors compared to association cortical areas that show slow, sustained activity. We validate this prediction using in-vitro receptor autoradiography data. Finally, we show how this model can account for various behavioral and physiological effects linked to consciousness. Together, these findings clarify the neurophysiological mechanisms of conscious access in the primate cortex and support the concept that gradients of receptor densities along the cortical hierarchy contribute to distributed cognitive functions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A connectome-based model of conscious access in monkey cortex

Klatzmann

Bliss

Theodoni

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…Similar to the studies of single compartment models, which indicated that ion channels are optimized for energy-efficient generation of sodium APs in the axon [6][7][8] , our ability to generate a comprehensive set of functionally realistic multi-compartmental models indicates that such optimization generalizes to the calcium APs in the dendrites of cortical neurons. Recent studies linked dendritic calcium APs in L5PTs to perception and consciousness [39][40][41][42] . Thus, our findings might reflect a strategy that allows the cerebral cortex to evolve towards energy-efficient implementations of higher brain functions.…”

Section: Discussionmentioning

confidence: 99%

Ion channel distributions in cortical neurons are optimized for energy-efficient active dendritic computations

Bast

Oberlaender²

2021

Preprint

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The mammalian brain uses more than 20% of the energy consumed by the entire body. This enormous demand for energy is thought to impose strong selective pressure by which neurons evolve in ways that ensure robust function at minimal energy cost. Here we demonstrate that the ion channel expression patterns by which pyramidal tract neurons - the major output cell type of the cerebral cortex - could implement their complex intrinsic physiology is extremely widespread. Surprisingly, this wide spectrum does not reflect morphological variability, but the energy costs for generating dendritic calcium action potentials. We found that energy-efficient calcium action potentials require a low expression of slow inactivating potassium channels in the distal dendrites, an empirical observation whose significance remained unclear for more than a decade. Thus, cortical neurons do not utilize all theoretically possible ways to implement their functions, but instead appear to select those optimized for energy-efficient active dendritic computations.

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“…Notably, their computational analysis identified models that were efficient in terms of energy as well as effective in terms of dendritic computation. The nonlinear dendritic computation was assessed based on BAC firing [80,92] and dendritic calcium spikes, which are thought to be important for conscious perception [93][94][95].…”

Section: Effectiveness-economy Trade-offs May Simplify Conductance Sp...mentioning

confidence: 99%

Pareto optimality, economy–effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

2022

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Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

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Cellular Mechanisms of Conscious Processing

Cited by 18 publications

References 0 publications

A connectome-based model of conscious access in monkey cortex

A connectome-based model of conscious access in monkey cortex

Ion channel distributions in cortical neurons are optimized for energy-efficient active dendritic computations

Pareto optimality, economy–effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

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