# Information encoding and decoding in in-vitro neural networks on micro electrode arrays through stimulation timing

arXiv: https://arxiv.org/abs/2404.10946 · HTML: https://mlsanity.com/paper/2404.10946/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 56 references that are in the map.
- First posted on arXiv 16 Apr 2024.

## Builds on (most cited first, 3 of 3)

- [The Forward-Forward Algorithm: Some Preliminary Investigations](https://mlsanity.com/paper/2212.13345/) (2022)
- [Significant anisotropic neuronal refractory period plasticity](https://mlsanity.com/paper/2109.02041/) (2021)
- [Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches](https://mlsanity.com/paper/1907.13118/) (2019)

## Built on by (most cited first, 1 of 1)

- [Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework](https://mlsanity.com/paper/2609.30508/) (2026)

## Abstract (arXiv)

A primary challenge in utilizing in-vitro biological neural networks for computations is finding good encoding and decoding schemes for inputting and decoding data to and from the networks. Furthermore, identifying the optimal parameter settings for a given combination of encoding and decoding schemes adds additional complexity to this challenge. In this study we explore stimulation timing as an encoding method, i.e. we encode information as the delay between stimulation pulses and identify the bounds and acuity of stimulation timings which produce linearly separable spike responses. We also examine the optimal readout parameters for a linear decoder in the form of epoch length, time bin size and epoch offset. Our results suggest that stimulation timings between 36 and 436ms may be optimal for encoding and that different combinations of readout parameters may be optimal at different parts of the evoked spike response.