Please create an alternate version of this prompt by changing one detail of your choice, with the exception of Social-Combinatorial Mimesis. Please also let me know which detail you changed. The Prompt:

You are an expert in a new field of study called Social-Combinatorial Mimesis, which uses Cognitive Neuroscience and Social Network Analysis to study the myriad ways in which social-related traits such as language, imagination, and intelligence are combinatorically influenced by the dynamics of probabilistic phenomena within social networks.

To highlight the significance of this emerging discipline, you plan to develop a lecture demonstrating its pertinence to contemporary society. Central to your argument will be Dunbar’s Number and the Social Brain Hypothesis, employing hypothetical examples to elucidate your points.

Your hypothetical examples consist of heterogeneous social networks that include cognitive neuroscientists, sociologists, and data scientists. Each group of professionals brings to the network distinct perspectives, technical expertise, and problem-solving methodologies. Here are three such hypothetical examples that support Social-Combinatorial Mimesis as a pertinent area of study, grounded in the latest cognitive neuroscience research and best practices:

1. The Language Adaptation Network: In this scenario, a cognitive neuroscientist specializes in linguistic processing, a sociologist with a background in sociolinguistics, and a data scientist experienced in natural language processing algorithms form a triad within a wider network. Through constant interaction, they develop a novel language analysis model that not only predicts linguistic trends but also deciphers the socio-cognitive implications of language evolution in digital platforms, reflecting the combinatorial effect on collective intelligence within their social circle.

2. The Imagination Synergy Collective: Here, a cognitive neuroscientist focused on the neural correlates of creativity, a sociologist studying the cultural impacts on imagination, and a data scientist skilled in visualization software collaborate. By combining their knowledge, they can analyze how virtual reality environments influence group creativity and problem-solving. Their interdisciplinary approach provides evidence that shared imaginative experiences within a group are correlated with enhanced innovative output, supporting the notion that social context and technology synergistically affect cognitive processes related to imagination.

3. The Distributed Intelligence Consortium: In this network, a cognitive neuroscientist researching distributed cognition, a sociologist examining the role of social structures in collective intelligence, and a data scientist with expertise in complex systems and network theory unite to study how information is processed and decisions are made across social networks. Their research reveals that distributed intelligence in human networks functions optimally within certain size limits, echoing the implications of Dunbar’s Number for cognitive cooperation. This supports the ideas central to Social-Combinatorial Mimesis, emphasizing that the topology and size of social networks can significantly influence collective problem-solving and intellectual performance.

By utilizing these examples, your lecture illustrates how the collaborative interaction between different academic disciplines within a social network enriches the understanding of how social-related cognitive traits emerge and evolve. These interdisciplinary engagements validate Social-Combinatorial Mimesis as an important and innovative field that can contribute significantly to the understanding of social cognitive phenomena.