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#NeuralPopulation

Fabrizio Musacchiopixeltracker@sigmoid.social
2025-09-07

🧠 New preprint by Ruff, Markman, Kim & Cohen (2025): #NeuralPopulation formatting matters for function. In monkeys combining motion and reward, both middle temporal area (#MT) & dorsolateral prefrontal #cortex (#dlPFC) encode both signals. But MT formats them separately, dlPFC integrates them. A recurrent #RNN model predicted, and microstimulation confirmed, distinct #behavioral impacts.

🌍 biorxiv.org/content/10.1101/20

#Neuroscience #CompNeuro #DecisionMaking #NeuralCoding

Figure 1. Population formatting, task and behavior.
Fabrizio Musacchiopixeltracker@sigmoid.social
2025-07-24

@juangallego just published a review on how #NeuralManifolds go beyond being a convenient data representation – they reflect fundamental constraints on #NeuralPopulation activity. Originating in mammalian BCI work (2014), these low-dimensional trajectories shape what neural patterns are learnable and expressible.

🌍 nature.com/articles/s41583-025

#CompNeuro #SystemsNeuroscience #PopulationDynamics #Neuroscience

Fabrizio Musacchiopixeltracker@sigmoid.social
2024-01-16

Preserved #NeuralPopulation dynamics across animals performing similar #behaviour – #preprint by Safaie et al. (2022)

🌍 biorxiv.org/content/10.1101/20

#CompNeuro #Neuroscience

Figure 1: Hypothesis. Different individuals from the same species performing the same behaviour (Panel A) will generate preserved neural population latent dynamics by instantiating a species-wide ‘neural landscape’ (Panel B). These preserved latent dynamics can be revealed by ‘aligning’ the individual-specific latent dynamics estimated from their neural population recordings (Panel C).
Fabrizio Musacchiopixeltracker@sigmoid.social
2023-12-22

Nonlinear #manifolds underlie #NeuralPopulation activity during #behaviour – new #preprint by Fortunato et al. (2023)

🌍 biorxiv.org/content/10.1101/20

#CompNeuro #Neuroscoence

Figure 1: Hypothesis. A. Due to the nonlinear activity profiles of single neurons and the complex connectivity profiles of neural circuits, we hypothesized that neural manifolds underlying behaviour should be nonlinear. B. We predicted that, if the geometry of neural manifolds indeed reflects circuit properties, neural manifolds from cytoarchitecturally different brain regions would exhibit distinct degrees of nonlinearity. C. We further predicted that more complex behavioural tasks that require a broader range of activity patterns will make the intrinsic nonlinearity of neural manifolds more apparent.

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