Evolving to be flexible - optimizing task-dependent information processing in the visual system

高度进化的大脑通常在复杂的环境中发育，这些环境为具有广泛认知能力和行为的物种提供了生态位。环境的高度复杂性，以及在面对高环境可变性时保持一致和强大功能的需要，对神经处理提出了各种要求。由于可用的大脑质量，每个可能任务的专门神经通路和网络的优化必须很快达到极限。一个进化的原则和摆脱困境的方法是发展更大的灵活性，将现有的网络重新配置成功能不同的电路。这意味着功能和灵活性的共同进化。我们的项目目标是研究一种假设，即神经系统在处理当前任务时不断优化其灵活操作的能力，以应对随机变异性和感官信号中不相关的竞争刺激。由于大脑中的信息处理是通过不同网络结构的相互作用来实现的，所以灵活性的协调也必须并行进行，一项任务必须分解成适合个体参与者的适当控制信号。哪种网络配置对灵活处理是最优的？在给定的生理约束下，它们是如何产生的？对于给定的灵活性问题是否存在多种解决方案？这些解决方案能否解释实验中观察到的可变性？与基于自发同步的神经元“雪崩”机制相比，基于神经元振荡同步的路由机制的功能意义是什么？它们之间可能的进化关系是什么？为了回答这些基本问题，我们将在理论和实验中研究灵活性的优化，重点是视觉系统。理论方法将正式描述中央处理方面，如并行协调和柔性电路的演变，将灵活性和功能的共同演变视为具有约束的优化问题。建模和实验将研究选择性注意作为视觉系统灵活性的一个中心方面，涉及多个视觉区域的任务依赖协调。我们的实验将描述和比较神经灵活性的潜在机制及其对感觉变异性的稳健性。生物物理上的现实建模将伴随实验，以严格测试形式理论，并确定灵活性和优化的机制，以及它们的控制和协调。

Highly evolved brains typically develop in complex environments that provide ecological niches for species with a wide range of cognitive abilities and behaviours. The high complexity of the environment, as well as the need to function consistently and robustly in the face of high environmental variability, places a variety of demands on neural processing. The optimisation of specialised neural pathways and networks for each possible task must quickly have reached a limit due to the available brain mass alone. An evolutionary principle and way out of the dilemma would be the development of ever greater flexibility in reconfiguring existing networks into functionally varying circuits. This implies a co-evolution of function and flexibility. Our project goal is to investigate the hypothesis that neural systems continuously optimise their ability to operate flexibly while processing the current task robustly against random variability and irrelevant competing stimuli in sensory signals. Since information processing in the brain is realized by the interaction of different network structures, the coordination of flexibility must also be done in parallel and a task must be decomposed into appropriate control signals for the individual players. Which network configurations are optimal for flexible processing, and how do they arise under given physiological constraints? Do multiple solutions exist for given flexibility problems, and can these explain the variability observed in the experiment? What is the functional significance of routing mechanisms based on the synchronisation of neuronal oscillations compared to mechanisms based on neuronal "avalanches" of spontaneous synchronisation - and what is the possible evolutionary relationship between them? To answer these fundamental questions, we will study optimisation of flexibility in theory and experiment with a focus on the visual system. Theoretical approaches will formally describe central processing aspects such as parallel coordination and the evolution of flexible circuits, considering co-evolution of flexibility and function as an optimisation problem with constraints. Modelling and experimentation will investigate selective attention as a central aspect of flexibility in the visual system, involving task-dependent coordination of multiple visual areas. Our experiments will characterise and compare potential mechanisms of neural flexibility and their robustness to sensory variability. Biophysically realistic modelling will accompany the experiments to critically test formal theories and identify mechanisms of flexibility and optimisation, as well as their control and coordination.