Inter-Postsynaptic Functional Links for Associative Memory: Feasibility in a Realistic Neuropil Model.

IF 3.3 4区 医学 Q3 NEUROSCIENCES
Kunjumon I Vadakkan
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引用次数: 0

Abstract

Aim: To quantify neuronal input degeneracy and test computationally whether nanoscale (≤30 nm) spine appositions are structurally eligible sites for inter-postsynaptic functional links (IPLs) underlying associative learning, assuming plausible pathway convergence onto abutted spine pairs. Empirical Constraint: Neuronal firing exhibits extreme input degeneracy. Any subset of inputs arriving at ~100-200 out of ~104 spines can trigger an action potential; ~140 inputs yield >10300 possible effective input combinations. This degeneracy introduces ambiguity regarding the specific input combinations that contribute to associative encoding. Testable Mechanism: The semblance hypothesis proposes a spine-level conjunction code between co-active spines forming inter-postsynaptic functional links (IPLs) that operate independently of postsynaptic neuronal firing, and are proposed to maintain the fidelity of original associations during retrieval. Computational Validation: During retrieval, cue-induced reactivation of IPLs is hypothesized to depolarize inter-linked spines and generate semblances. Taking the depolarization of an inter-linked spine in the absence of direct presynaptic input as an "operational semblance" constituting the elemental substrate of associative recall, a computational model was implemented within a biologically realistic 1000 μm3 neuropil volume containing 1600 dendritic spines (density 1.6/μm3; diameter 0.6-0.7 μm) as independent dendritic segments. Of 391 crossing dendritic sites, 151 have abutted spine pairs, using ≤30 nm inter-spine distance as a candidate eligibility criterion, motivated by reported nanoscale appositions. Spine density, diameter, and separation were parameterized from electron microscopy and confocal/super-resolution imaging literature; coupling strength (0.7) was fixed and exploratory. IPL formation was implemented probabilistically across 20 learning trials (formation probability = 0.30 per trial at each of the 49 designated sites; reversal probability = 0.04), producing a gradual acquisition curve and trial-to-trial variance emerging naturally from the two-state Markov dynamics. Across 100 independent simulations, 49 of the 151 abutted pairs were designated as structurally eligible Bell-Food convergence sites; of these, 44.7 ± 2.1 developed active IPLs after 20 trials, generating operational semblances per retrieval (recall accuracy 36.93% ± 1.71%; paired t-test, p < 0.001; Cohen's d = 30.54, illustrative not calibrated). This work demonstrates that given a plausible convergence of associative pathways onto existing abutted spine pairs, the structural relations between spines in the cortical neuropil are compatible with the formation of a spine-level conjunction code as a potential substrate for associative learning.

联想记忆的突触后功能联系:现实神经模型的可行性。
目的:量化神经元输入退化,并计算测试纳米尺度(≤30 nm)脊柱连接是否在结构上符合突触后功能链接(ipl)的条件,假设可能的通路收敛到毗邻的脊柱对。经验约束:神经元放电表现出极端的输入退化。在约104个脊髓中,任何到达约100-200个脊髓的输入子集都可以触发动作电位;140个输入产生10300个可能的有效输入组合。这种退化引入了与有助于关联编码的特定输入组合有关的模糊性。可验证机制:外表假说提出了一种脊柱水平的连接代码,这些连接代码形成突触后功能链接(ipl),独立于突触后神经元放电,并在检索过程中保持原始关联的保真度。计算验证:在检索过程中,假设线索诱导的ipl重新激活可以使相互连接的棘去极化并产生相似性。在没有直接突触前输入的情况下,将相互连接的脊柱的去极化作为构成联想回忆基本基质的“操作相似性”,在生物真实的1000 μm3神经体积中实现了一个计算模型,该体积包含1600个树突棘(密度1.6/μm3,直径0.6-0.7 μm)作为独立的树突节段。在391个交叉树突位点中,151个有相邻的脊柱对,使用≤30nm的脊柱间距离作为候选资格标准,这是由纳米级的附着所驱动的。从电子显微镜和共聚焦/超分辨率成像文献中参数化脊柱密度、直径和分离;耦合强度(0.7)是固定的、探索性的。IPL的形成是在20个学习试验中概率实现的(在49个指定地点的每个试验中,每次试验的形成概率= 0.30;反转概率= 0.04),产生一个渐进的获取曲线和从两态马尔可夫动力学中自然产生的试验间方差。在100个独立模拟中,151个相邻对中有49个被指定为结构合格的Bell-Food融合点;其中,44.7±2.1在20次试验后发展为活动性ipl,每次检索产生操作相似(回忆率36.93%±1.71%;配对t检验,p < 0.001; Cohen’s d = 30.54,说明性未校准)。这项工作表明,在现有的相邻的脊柱对上,联想通路似乎是收敛的,皮层神经中脊柱之间的结构关系与作为联想学习潜在基础的脊柱水平连接代码的形成是相容的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
自引率
5.60%
发文量
173
审稿时长
2 months
期刊介绍: JIN is an international peer-reviewed, open access journal. JIN publishes leading-edge research at the interface of theoretical and experimental neuroscience, focusing across hierarchical levels of brain organization to better understand how diverse functions are integrated. We encourage submissions from scientists of all specialties that relate to brain functioning.
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