A jolt to the field: a self‐generating and self‐propagating ephaptically mediated slow spontaneous network activity pattern in the hippocampus
Notice bibliographique
Résumé
Neural activity has been traditionally studied in terms of a sensory-motor (or input-output) function. That is to say, the operation of the nervous system has been typically viewed as an intermediary between actively sensing the environment and then actively producing a response. This framework unfortunately ignores the propensity of the brain to generate its own patterned and synchronized activity in the absence of any active input or output – most notably during states of sleep, or even anaesthesia. A major pattern in this regard is the slow oscillation, a ≤1 Hz network rhythm that appears across vast expanses of the forebrain and which entrains other local patterns of population activity (Steriade et al. 1993). The functional relevance of this input- and output-decoupled slow network rhythm remains a mystery, but one that will probably be solved by an elucidation of both the cellular and the inter-cellular mechanisms giving rise to it in the first place. While the study of spontaneous network neural rhythms is probably best done in situ (Steriade, 2001), certain ex vivo preparations, like brain slices, better lend themselves to experimental probing. Even more compelling for this field of study is that these types of preparations, even with the minimal amount of dissociated neural circuitry contained within, are capable of generating emergent forms of slow spontaneous network activity that bear more than a passing resemblance to the slow-wave patterns observed during sleep (Sanchez-Vives & McCormick, 2000; Dickson et al. 2003). Advantageously, ex vivo preparations are also highly useful to experimentally evaluate both the cellular and the network mechanisms giving rise to spontaneous population neural activity. Traditionally, it had been thought that spontaneous brain rhythms were a result of the interaction between the intrinsic properties of individual neurons and their extrinsic interactions via classical chemical or electrical synaptic transmission. While non-synaptic influences via exogenous or even endogenous electric fields (i.e. ephaptic mechanisms) have been suggested to play a role in modulating ongoing activity, these effects were thought to be reasonably limited, at least during physiologically relevant activity (Anastassiou & Koch, 2015). In this issue of The Journal of Physiology, Chiang, Shivacharan, Wei, Gonzalez-Reyes and Durand (Chiang et al. 2019) show that slow periodic activity in a horizontal hippocampal slice preparation occurs through dendritic NMDA receptor-dependent Ca2+ spiking, which is itself self-generating and self-propagating, via ephaptic interactions across neurons. Consistent with purely ephaptic transmission, this activity and its active propagation across the slice were resistant to pharmacological blockers of fast ionotropic chemical neurotransmission, as well as pharmacological blockade of electrical transmission via gap junctions. What is particularly compelling is that the activity could be not only modulated, but also eliminated or even regenerated by imposed electrical fields. Most shockingly, this activity could be transmitted from one side of a surgically severed slice to the other when the two cut edges were simply placed in close proximity. These surprising findings were further supported by a computer model of hippocampal circuitry. The role of endogenous electric fields generated by the brain (as well as those exogenously imposed on the brain) in neural synchronization is still a matter of investigation (Anastassiou & Koch, 2015). However, the implications of ephaptic mechanisms are certainly relevant to both physiological and pathological states, not to mention therapeutic possibilities. While it remains to be seen if the findings of Chiang et al (2019) are relevant to spontaneous slow rhythms that occur in both cortical and hippocampal tissue in situ during sleep and sleep-like states (Wolansky et al. 2006), they should probably (and quite literally) electrify the field. None declared. None declared. I would like to acknowledge Drs Silvia Pagliardini and Claire Scavuzzo, as well as Dr-to-be Brandon Hauer, for reviewing, editing, and commenting on a previous version of this Perspectives article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».