Behavioural relevance of redundant and synergistic stimulus information between functionally connected neurons in mouse auditory cortex.

Q1 Computer Science Brain Informatics Pub Date : 2023-12-05 DOI:10.1186/s40708-023-00212-9
Loren Koçillari, Marco Celotto, Nikolas A Francis, Shoutik Mukherjee, Behtash Babadi, Patrick O Kanold, Stefano Panzeri
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Abstract

Measures of functional connectivity have played a central role in advancing our understanding of how information is transmitted and processed within the brain. Traditionally, these studies have focused on identifying redundant functional connectivity, which involves determining when activity is similar across different sites or neurons. However, recent research has highlighted the importance of also identifying synergistic connectivity-that is, connectivity that gives rise to information not contained in either site or neuron alone. Here, we measured redundant and synergistic functional connectivity between neurons in the mouse primary auditory cortex during a sound discrimination task. Specifically, we measured directed functional connectivity between neurons simultaneously recorded with calcium imaging. We used Granger Causality as a functional connectivity measure. We then used Partial Information Decomposition to quantify the amount of redundant and synergistic information about the presented sound that is carried by functionally connected or functionally unconnected pairs of neurons. We found that functionally connected pairs present proportionally more redundant information and proportionally less synergistic information about sound than unconnected pairs, suggesting that their functional connectivity is primarily redundant. Further, synergy and redundancy coexisted both when mice made correct or incorrect perceptual discriminations. However, redundancy was much higher (both in absolute terms and in proportion to the total information available in neuron pairs) in correct behavioural choices compared to incorrect ones, whereas synergy was higher in absolute terms but lower in relative terms in correct than in incorrect behavioural choices. Moreover, the proportion of redundancy reliably predicted perceptual discriminations, with the proportion of synergy adding no extra predictive power. These results suggest a crucial contribution of redundancy to correct perceptual discriminations, possibly due to the advantage it offers for information propagation, and also suggest a role of synergy in enhancing information level during correct discriminations.

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小鼠听觉皮层中功能连接神经元之间冗余和协同刺激信息的行为相关性。
功能连通性测量在促进我们了解信息如何在大脑中传输和处理方面发挥了核心作用。传统上,这些研究主要集中在识别冗余功能连通性上,即确定不同部位或神经元的活动何时相似。然而,最近的研究强调了识别协同连通性的重要性,即连通性所产生的信息并不单独包含在任何一个部位或神经元中。在这里,我们测量了小鼠初级听觉皮层神经元之间在声音辨别任务中的冗余和协同功能连接。具体来说,我们测量了同时记录钙成像的神经元之间的定向功能连接。我们使用格兰杰因果关系作为功能连通性的衡量标准。然后,我们使用部分信息分解(Partial Information Decomposition)来量化功能连接或功能未连接的神经元对所携带的关于声音的冗余和协同信息量。我们发现,与未连接的神经元对相比,功能连接的神经元对所呈现的声音冗余信息比例更高,协同信息比例更低,这表明它们的功能连接主要是冗余的。此外,当小鼠做出正确或错误的知觉判别时,协同和冗余都同时存在。然而,与不正确的行为选择相比,正确行为选择中的冗余度要高得多(无论是绝对值还是占神经元对可用信息总量的比例),而正确行为选择中的协同性绝对值要比不正确行为选择中的协同性高,但相对值要比不正确行为选择中的协同性低。此外,冗余比例能可靠地预测知觉分辨,而协同比例则没有额外的预测能力。这些结果表明,冗余对正确的知觉判别有重要贡献,这可能是由于冗余在信息传播方面的优势,同时也表明协同作用在正确判别过程中提高了信息水平。
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来源期刊
Brain Informatics
Brain Informatics Computer Science-Computer Science Applications
CiteScore
9.50
自引率
0.00%
发文量
27
审稿时长
13 weeks
期刊介绍: Brain Informatics is an international, peer-reviewed, interdisciplinary open-access journal published under the brand SpringerOpen, which provides a unique platform for researchers and practitioners to disseminate original research on computational and informatics technologies related to brain. This journal addresses the computational, cognitive, physiological, biological, physical, ecological and social perspectives of brain informatics. It also welcomes emerging information technologies and advanced neuro-imaging technologies, such as big data analytics and interactive knowledge discovery related to various large-scale brain studies and their applications. This journal will publish high-quality original research papers, brief reports and critical reviews in all theoretical, technological, clinical and interdisciplinary studies that make up the field of brain informatics and its applications in brain-machine intelligence, brain-inspired intelligent systems, mental health and brain disorders, etc. The scope of papers includes the following five tracks: Track 1: Cognitive and Computational Foundations of Brain Science Track 2: Human Information Processing Systems Track 3: Brain Big Data Analytics, Curation and Management Track 4: Informatics Paradigms for Brain and Mental Health Research Track 5: Brain-Machine Intelligence and Brain-Inspired Computing
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