In an NSF-supported study, @talsharf.bsky.social and collaborators will investigate the capacity of human brain organoids to learn and adapt, with implications for #organoid research, #bioethics, and science education.

news.ucsc.edu/2025/10/lear...

Our work demonstrates that the emergence of intrinsic computational architectures, defined by low- and high-dimensional activity patterns and neuronal sequences, is an emergent property of neuronal self-assembly and achievable in brain organoid models.

Phenomena such as "preplay," pre-existing sequence motifs are thought to encode novel experiences and underlie episodic memory retrieval in the human cortex. These motifs have recently been shown to encode non-redundant information beyond latency and rate encoding.

The use of neuronal sequences to encode sensory input and motor output has been widely studied. However, whether these sequences arise innately through neurogenesis and synaptogenesis (nature) or emerge through sequential experience (nurture) remains unresolved.

This conclusion can be made most powerfully in a brain organoid that does not have the intimate developmental interaction with other organ systems and thus excludes an internal setting due to cardiac signals, for example, of brain rhythms.

Employing human and murine brain organoids alongside ex vivo neonatal murine brain slices, we demonstrate that intrinsic neuronal sequences, which delineate low- and high-dimensional latent subspaces for information encoding, emerge independently of sensory experience.

In our updated manuscript we present strong evidence supporting the pre-configured brain hypothesis. Separating the effects of experience from intrinsic network dynamics has historically been challenging due to experimental limitations.