Selfconnections

Selfconnections is a term used across several disciplines to describe the connections a system or a person has with itself. The concept highlights internal links, whether they are psychological, neural, structural, or educational, and emphasizes coherence, feedback, or reflexivity.

In psychology, selfconnections refer to the coherence and continuity of the self across contexts and over time. They involve the integration of memories, emotions, and identity into a stable self-concept. Strong selfconnections are associated with a clear sense of self, resilience, and consistent behavior, while weak or fragmented selfconnections can accompany uncertainty or identity conflicts. Practices such as reflective journaling, mindfulness, and meaning-making are often cited as methods to strengthen selfconnections.

In cognitive neuroscience and psychology, self-referential processing is a related idea, focusing on how information related to the self is processed differently from non-self information. This processing engages brain networks associated with self-related thought and autobiographical memory, contributing to how individuals prioritize, recall, and interpret experiences.

In graph theory and computer science, a self-connection (or self-loop) is an edge that connects a node to itself. Self-loops are used to model internal feedback, recursive behavior, or reflexive relations within a system, and can influence calculations such as growth, convergence, or state transitions in networks and models.

In education and learning design, selfconnections describe the explicit links learners make between new material and their prior knowledge, experiences, or beliefs. Recognizing and articulating these connections can enhance comprehension, retention, and transfer of learning.

Variability exists in how selfconnections are defined and applied across fields, and the term is not universally standardized. Related concepts include self-concept, self-identity, self-referential processing, and reflexive relations.