# Learnable latent embeddings for joint behavioral and neural analysis

@article{Schneider2022LearnableLE, title={Learnable latent embeddings for joint behavioral and neural analysis}, author={Steffen Schneider and Jin Hwa Lee and Mackenzie W. Mathis}, journal={ArXiv}, year={2022}, volume={abs/2204.00673} }

Mapping behavioral actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioral data increases, there is growing interest in modeling neural dynamics during adaptive behaviors to probe neural representations. In particular, neural latent embeddings can reveal underlying correlates of behavior, yet, we lack non-linear techniques that can explicitly and ﬂexibly leverage joint behavior and neural data. Here, we ﬁll this gap with a novel…

## 6 Citations

### Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles

- Computer ScienceArXiv
- 2022

This work proposes feature sharing across neural tuning curves, which significantly improves performance and leads to better-behaved optimization and a solution to the problem of ensemble detection, whereby different groups of neurons, i.e., ensembles, can be modulated by different latent manifolds.

### A model-free approach to link neural activity to behavioral tasks

- Biology, PsychologybioRxiv
- 2022

“Model-free identification of neural encoding (MINE)” is developed using convolutional neural networks (CNN) to relate aspects of tasks to neural activity and identifies a new class of neurons that integrate thermosensory and behavioral information which eluded us previously when using traditional clustering and regression-based approaches.

### Neural manifold analysis of brain circuit dynamics in health and disease

- Computer Science
- 2022

A number of linear and non-linear approaches to neural manifold learning are reviewed, including principal component analysis (PCA), multi-dimensional scaling (MDS), Isomap, locally linear embedding (LLE), Laplacian eigenmaps (LEM), t-SNE, and uniform manifold approximation and projection (UMAP), and are outlined under a common mathematical nomenclature.

### Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs

- Psychology, Computer SciencebioRxiv
- 2022

A class of warped ARHMMs (WARHMM) is introduced in which the warping variable affects the dynamics of each syllable either linearly or nonlinearly, and achieves similar performance to the standard ARHMM while using fewer behavioral syllables.

### Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE

- Computer Science
- 2022

Though the identiﬁability is appealing, it is shown that iVAEs could have local minimum solution where observations and the approximated ICs are independent given covariates.

### Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

- Psychology, BiologybioRxiv
- 2022

Evidence is provided that the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter.

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