Neuroelectrics Barcelona, Barcelona, Spain.
Starlab Barcelona, Barcelona, Spain.
PLoS Comput Biol. 2023 Feb 3;19(2):e1010811. doi: 10.1371/journal.pcbi.1010811. eCollection 2023 Feb.
A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.
计算神经科学中一个日益受到关注的话题是发现大脑全局动力学和自组织的基本原理。特别是,大脑在临界点附近运作的概念已经得到了相当多的支持,最近的研究表明,不同大脑状态的动力学可以通过在相变(即临界点)附近的成对最大熵伊辛模型来建模。在这里,我们的目标是通过功能磁共振成像(fMRI)来描述两种大脑状态(迷幻剂诱导的和安慰剂),其特征来自伊辛自旋模型形式主义(系统温度、临界点、磁化率)和算法复杂度。根据熵脑假说,我们假设迷幻剂会使大脑在更高的伊辛温度和更高的复杂度下进入更无序的状态。我们分析了在先前的一项研究中从十五名受试者在对照条件(安慰剂)和摄入麦角酸二乙基酰胺(LSD)期间收集的静息状态血氧水平依赖(BOLD)fMRI 数据。我们使用自动解剖标记(AAL)大脑分割,首先为整个数据集(全局)和每个条件的数据创建“原型”伊辛模型。值得注意的是,我们发现这样的原型与从 dMRI 获得的平均结构连接体模板具有很强的相关性(r = 0.6)。我们比较了两种条件下的原型,并发现 LSD 条件下的伊辛连接性低于安慰剂条件,特别是在同型连接(半球间连接)中,反映了 LSD 条件下同型功能连接的显著下降。然后,我们通过调整系统温度为每个个体和条件个性化全局原型。所得温度均接近但高于模型顺磁(无序)相的临界点。LSD 条件下的个体伊辛温度高于安慰剂条件(p = 9×10-5)。接下来,我们使用基于马尔可夫算法的个性化模型为每个参与者和条件估计了二进制 BOLD 数据和合成数据的 Lempel-Ziv-Welch(LZW)复杂度。从实验数据中计算出的 LZW 复杂度与条件呈弱统计学关系(单侧 Wilcoxon 检验,p = 0.04),与伊辛温度无关(r(13) = 0.13,p = 0.65),可能是因为 BOLD 时间序列的长度有限。同样,我们使用块分解方法(BDM)探索复杂度,这是一种估计算法复杂度的更先进的方法。实验数据的 BDM 复杂度与伊辛温度呈显著相关性(r(13) = 0.56,p = 0.03),与条件呈弱但显著的相关性(p = 0.04,单侧 Wilcoxon 检验)。这项研究表明,LSD 的作用通过放松大脑半球间的连接,特别是同型连接,增加了大脑动力学的复杂性。与使用 BOLD 数据的伊辛形式主义的早期工作一致,我们发现安慰剂条件下的大脑状态已经高于临界点,而 LSD 则导致进一步远离临界点进入更无序的状态。