Engrams of Fast Learning

Piette, Charlotte; Touboul, Jonathan; Venance, Laurent

doi:10.3389/fncel.2020.575915

Cited by 14 publications

(13 citation statements)

References 137 publications

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“…Also, a decrease in lactate production mediated by mitochondrial cannabinoid type-1 receptor activation in astrocytes, alters social behavior in a lactate reversible manner (Jimenez-Blasco et al, 2020). In contrast fast learning engrams originating from light activity patterns (Piette et al, 2020), could emerge even in the absence of lactate metabolism, with glucose as the main energy substrate.…”

Section: Inhibition Of Ldh Impaired Oip-induced Ltp But Not Nor-induc...mentioning

confidence: 99%

Lactate Supply Overtakes Glucose When Neural Computational and Cognitive Loads Scale Up

et al. 2022

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Section: Inhibition Of Ldh Impaired Oip-induced Ltp But Not Nor-induc...mentioning

confidence: 99%

Lactate Supply Overtakes Glucose When Neural Computational and Cognitive Loads Scale Up

et al. 2022

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“…Also, a decrease in lactate production mediated by mitochondrial cannabinoid type-1 receptor activation in astrocytes alters social behavior in a lactate-reversible manner ( 47 ). By contrast, fast-learning engrams originating from light activity patterns ( 48 ) could emerge even in the absence of lactate metabolism, with glucose as the main energy substrate.…”

Section: Discussionmentioning

confidence: 99%

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

Dembitskaya

Piette

Pérez

et al. 2022

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

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Neural computational power is determined by neuroenergetics, but how and which energy substrates are allocated to various forms of memory engram is unclear. To solve this question, we asked whether neuronal fueling by glucose or lactate scales differently upon increasing neural computation and cognitive loads. Here, using electrophysiology, two-photon imaging, cognitive tasks, and mathematical modeling, we show that both glucose and lactate are involved in engram formation, with lactate supporting long-term synaptic plasticity evoked by high-stimulation load activity patterns and high attentional load in cognitive tasks and glucose being sufficient for less demanding neural computation and learning tasks. Indeed, we show that lactate is mandatory for demanding neural computation, such as theta-burst stimulation, while glucose is sufficient for lighter forms of activity-dependent long-term potentiation (LTP), such as spike timing–dependent plasticity (STDP). We find that subtle variations of spike number or frequency in STDP are sufficient to shift the on-demand fueling from glucose to lactate. Finally, we demonstrate that lactate is necessary for a cognitive task requiring high attentional load, such as the object-in-place task, and for the corresponding in vivo hippocampal LTP expression but is not needed for a less demanding task, such as a simple novel object recognition. Overall, these results demonstrate that glucose and lactate metabolism are differentially engaged in neuronal fueling depending on the complexity of the activity-dependent plasticity and behavior.

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“…Finally, it is also worth to mention that long-term potentiation may be modulated by homeostatic plasticity 70,71 . Two learning processes also occur when acquiring new skills: a fast learning in a cortical structure is simultaneously slowly learned in a subcortical structure (habit learning for instance) [72][73][74][75] . Thus, according to previous experiences and the nature of inputs, the rate of learning may need to evolve so that neurons adapt more or less quickly to sensory inputs 69,72,76,77 .…”

Section: /20mentioning

confidence: 99%

Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli

Bergoin

Torcini

Deco

et al. 2023

Preprint

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Brain circuits display modular architecture at different scales of organization. Such neural assemblies are typically associated to functional specialization but the mechanisms leading to their emergence and consolidation still remain elusive. In this paper we investigate the role of inhibition in structuring new neural assemblies driven by the entrainment to various inputs. In particular, we focus on the role of partially synchronized dynamics for the creation and maintenance of structural modules in neural circuits by considering a network of excitatory and inhibitory theta-neurons with plastic Hebbian synapses. The learning process consists of an entrainment to temporally alternating stimuli that are applied to separate regions of the network. This entrainment leads to the emergence of modular structures. Contrary to common practice in artificial neural networks - where the acquired weights are typically frozen after the learning session - we allow for synaptic adaptation even after the learning phase. We find that the presence of inhibitory neurons in the network is crucial for the emergence and the post-learning consolidation of the modular structures. Indeed networks made of purely excitatory neurons or of neurons not respecting Dale's principle are unable to form or maintain the modular architecture induced by the entrained stimuli. We also demonstrate that the number of inhibitory neurons in the network is directly related to the maximal number of neural assemblies that can be consolidated, supporting the idea that inhibition has a direct impact on the memory capacity of the neural network.

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Engrams of Fast Learning

Cited by 14 publications

References 137 publications

Lactate Supply Overtakes Glucose When Neural Computational and Cognitive Loads Scale Up

Lactate Supply Overtakes Glucose When Neural Computational and Cognitive Loads Scale Up

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli

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