دورية أكاديمية

Tracking axon initial segment plasticity using high-density microelectrode arrays: A computational study.

التفاصيل البيبلوغرافية
العنوان: Tracking axon initial segment plasticity using high-density microelectrode arrays: A computational study.
المؤلفون: Kumar SS; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Gänswein T; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Buccino AP; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Xue X; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Bartram J; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Emmenegger V; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland., Hierlemann A; Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
المصدر: Frontiers in neuroinformatics [Front Neuroinform] 2022 Oct 03; Vol. 16, pp. 957255.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101477957 Publication Model: Print Cited Medium: Print ISSN: 1662-5196 (Print) Linking ISSN: 16625196 NLM ISO Abbreviation: Front Neuroinform Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: Lausanne, Switzerland : Frontiers Research Foundation, 2007-
مستخلص: Despite being composed of highly plastic neurons with extensive positive feedback, the nervous system maintains stable overall function. To keep activity within bounds, it relies on a set of negative feedback mechanisms that can induce stabilizing adjustments and that are collectively termed "homeostatic plasticity." Recently, a highly excitable microdomain, located at the proximal end of the axon-the axon initial segment (AIS)-was found to exhibit structural modifications in response to activity perturbations. Though AIS plasticity appears to serve a homeostatic purpose, many aspects governing its expression and its functional role in regulating neuronal excitability remain elusive. A central challenge in studying the phenomenon is the rich heterogeneity of its expression (distal/proximal relocation, shortening, lengthening) and the variability of its functional role. A potential solution is to track AISs of a large number of neurons over time and attempt to induce structural plasticity in them. To this end, a promising approach is to use extracellular electrophysiological readouts to track a large number of neurons at high spatiotemporal resolution by means of high-density microelectrode arrays (HD-MEAs). However, an analysis framework that reliably identifies specific activity signatures that uniquely map on to underlying microstructural changes is missing. In this study, we assessed the feasibility of such a task and used the distal relocation of the AIS as an exemplary problem. We used sophisticated computational models to systematically explore the relationship between incremental changes in AIS positions and the specific consequences observed in simulated extracellular field potentials. An ensemble of feature changes in the extracellular fields that reliably characterize AIS plasticity was identified. We trained models that could detect these signatures with remarkable accuracy. Based on these findings, we propose a hybrid analysis framework that could potentially enable high-throughput experimental studies of activity-dependent AIS plasticity using HD-MEAs.
Competing Interests: Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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معلومات مُعتمدة: 188910 Switzerland SNSF_ Swiss National Science Foundation; 694829 International ERC_ European Research Council
فهرسة مساهمة: Keywords: AIS plasticity; HD-MEAs; LTI systems; biophysical modeling; homeostatic plasticity; neighborhood components analysis (NCA); random forest classifier; wide neural networks
تواريخ الأحداث: Date Created: 20221012 Latest Revision: 20221014
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC7613690
DOI: 10.3389/fninf.2022.957255
PMID: 36221258
قاعدة البيانات: MEDLINE
الوصف
تدمد:1662-5196
DOI:10.3389/fninf.2022.957255