On the road to the brain-on-a-chip: a review on strategies, methods, and applications

J Neural Eng. 2021 Aug 12;18(4). doi: 10.1088/1741-2552/ac15e4.

Abstract

The brain is the most complex organ of our body. Such a complexity spans from the single-cell morphology up to the intricate connections that hundreds of thousands of neurons establish to create dense neuronal networks. All these components are involved in the genesis of the rich patterns of electrophysiological activity that characterize the brain. Over the years, researchers coming from different disciplines developedin vitrosimplified experimental models to investigate in a more controllable and observable way how neuronal ensembles generate peculiar firing rhythms, code external stimulations, or respond to chemical drugs. Nowadays, suchin vitromodels are namedbrain-on-a-chippointing out the relevance of the technological counterpart as artificial tool to interact with the brain: multi-electrode arrays are well-used devices to record and stimulate large-scale developing neuronal networks originated from dissociated cultures, brain slices, up to brain organoids. In this review, we will discuss the state of the art of the brain-on-a-chip, highlighting which structural and biological features a realisticin vitrobrain should embed (and how to achieve them). In particular, we identified two topological features, namely modular and three-dimensional connectivity, and a biological one (heterogeneity) that takes into account the huge number of neuronal types existing in the brain. At the end of this travel, we will show how 'far' we are from the goal and how interconnected-brain-regions-on-a-chip is the most appropriate wording to indicate the current state of the art.

Keywords: biocompatible scaffolds; brain-on-a-chip; connectivity; heterogeneity; modularity; multi-electrode arrays; three-dimensionality.

Publication types

  • Review

MeSH terms

  • Brain
  • Electrophysiological Phenomena
  • Lab-On-A-Chip Devices*
  • Neurons*
  • Oligonucleotide Array Sequence Analysis