#Neuroscience as a field is relatively fragmented
..
We propose leveraging shared #neurodata repositories and #compneurosci modelling frameworks to benchmark methodologies, facilitating a more coherent integration of findings across #neuro subfields.

Additionally, we advocate for the creation of a structured “map” of neuroscience, charting relationships between domains to enhance conceptual clarity.

https://doi.org/10.52294/001c.138841

#philosophyofneuroscience #theoreticalneuroscience #neuropsy #cogsci

The lab of Mitya Chklovskii is hiring, at the Flatiron Institute – Simons Foundation, in Manhattan, New York:
https://apply.interfolio.com/173400

#PhDJobs #neuroscience #CompNeurosci

The lab of Jakob Macke (Tuebingen, Germany) is recruiting a research engineer to work on brain models:
https://www.mackelab.org/media/Mackelab_ResearchEngineer.pdf

#neuroscience #CompNeurosci

"Algorithmic dissection of optic flow memory in larval zebrafish", Tanaka & Portgues 2025
https://www.sciencedirect.com/science/article/pii/S0960982225011133

#neuroscience #zebrafish #CompNeurosci

NEURON 9.0 released:
https://nrn.readthedocs.io/en/release-9.0/

#neuroscience #CompNeurosci

How do babies and blind people learn to localise sound without labelled data? We propose that innate mechanisms can provide coarse-grained error signals to boostrap learning.

New preprint from @yang_chu.

https://arxiv.org/abs/2001.10605

Thread below 👇

#neuroscience #computationalneuroscience #compneuro #compneurosci

Latest from Kathy Nagel's lab:

"Inhibitory control explains locomotor statistics in walking Drosophila", Gattuso et al. 2025
https://www.pnas.org/doi/abs/10.1073/pnas.2407626122

"we measure and analyze trajectories evoked by attractive odor in walking Drosophila and develop a biologically plausible computational model of trajectory generation and modulation by sensory input. Our model provides a link between neural architectures and locomotor behavior and highlights the potential role of inhibition in shaping the curvature and speed of trajectories. Inspired by this model, we experimentally identify single neurons and populations that modulate either curvature or speed in the manner predicted by our model."

#neuroscience #Drosophila #locomotion #CompNeurosci #SystemsNeuroscience

"Forecasting Whole-Brain Neuronal Activity from Volumetric Video", Immer et al. 2025 (with Florian Engert, Jeff Lichtman, Misha Ahrens, Viren Jain and Michal Januszewski)
https://www.arxiv.org/abs/2503.00073

"ZAPBench: a benchmark for whole-brain activity prediction in zebrafish", Lueckmann et al. 2025
https://openreview.net/pdf?id=oCHsDpyawq

#ZAPBench #neuroscience #zebrafish #CalciumImaging #CompNeurosci

As a Cuban med school student who will graduate in the near future, and would like to pursue a degree in neuroscience especially in the field of cognitive or computational neuroscience.

I will move to Europe in the next few months but I would like some specific recommendations.

#neuroscience #compneurosci

We have a new preprint on the emergence of orientation selectivity in layers 2/3 and 4 of the mouse. We use data from the Allen Institute's Microns project, which includes structure plus function of thousands of neurons, to constrain network models that account for the observations and hint some key features on the origin of tuning in L2/3. For any feedback, do not hesitate to contact us!

https://www.biorxiv.org/content/10.1101/2024.11.18.624135v1

#neuroscience #compneuro #compneurosci

@eLife Above, Markram et al. with a computational model of a column of the rat barrel cortex, building on their work from 2015. Still no densely reconstructed neurons, so the anatomy is collated largely from sparsely labeled neurons in light microscopy volumes. Synapses are inferred from sparse sampling with ephys and some educated guesswork, based also on data from volume electron microscopy from other brain areas in mouse.

The published reviews are rather on point, make very interesting reading.

#neuroscience #connectomics #CompNeurosci

"Homeostatic synaptic normalization optimizes learning in network models of neural population codes", Mayzel and Schneidman, 2024.
https://elifesciences.org/reviewed-preprints/96566

From the assessment:

"... an important contribution to the development of a biologically plausible theory of statistical modeling of spiking activity. The authors convincingly implemented the statistical inference of input likelihood in a simple neural circuit, demonstrating the relationship between synaptic homeostasis, neural representations, and computational accuracy."

#neuroscience #CompNeurosci #synapses

"Selective consolidation of learning and memory via recall-gated plasticity", Lindsey and Litwin-Kumar, 2024.
https://elifesciences.org/reviewed-preprints/90793

On forming long-term memories:

"The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment."

With a discussion including mammalian and insect brains.

#neuroscience #LearningAndMemory #RecallGatedConsolidation #CompNeurosci

@mariamannone

"We propose a general and abstract definition of disease as an operator altering the weights of the connections between neural agglomerates, that is, the elements of the brain matrix."

"The effect of disease is, thus, an alteration to the communication model."

I will refrain from revealing one of the greatest opening sentences of an introduction to a neuroscience paper – wow!

#neuroscience #CompNeurosci

"Recurrent connections enable point attractor dynamics and dimensionality reduction in a connectome-constrained model of the insect learning center", by Joyce et al. 2024

An exploration with computational modeling of feedback inhibition and recurrent excitation – using the #Drosophila olfactory system and learning and memory centre (the mushroom body), as mapped, as an experimental subject.

https://www.biorxiv.org/content/10.1101/2024.01.10.574960v1

#neuroscience #CompNeurosci #connectomics

New approach to modeling neurons and neural circuits, from Mitya Chklovskii's lab:

"The Neuron as a Direct Data-Driven Controller", Moore et al. 2024
https://www.biorxiv.org/content/10.1101/2024.01.02.573843v1

"... a normative theory that interprets neuronal physiology as optimizing a computational objective."

"novel Direct Data-Driven Control (DD-DC) framework, we model neurons as biologically feasible controllers"

"explains various neurophysiological phenomena: the shift from potentiation to depression in Spike-Timing-Dependent Plasticity (STDP) with its asymmetry, the duration and adaptive nature of feedforward and feedback neuronal filters, the imprecision in spike generation under constant stimulation, and the characteristic operational variability and noise in the brain."

#neuroscience #CompNeurosci

@dsmith @debivort @kordinglab @knutson_brain @tdverstynen @beneuroscience @MolemanPeter @NicoleCRust

» Hodgkin-Huxley model
some worries they raised about their quantitative description seem still to be relevant to current work in ongoing #compneurosci «
JB

http://dx.doi.org/10.1007/s40656-023-00582-7
K et al + exps. needed ;)

https://youtu.be/g85bgHul7Ns

2/2

@PhiloNeuroScie

Filing under #neuroscience and #CompNeurosci:

@flypapers

“The functional logic of odor information processing in the Drosophila antennal lobe", Lazar et al. 2023
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011043

A computational model of olfactory circuits based on #connectomics and functional data, which separates semantic information (which odor; quality) from syntactic (intensity; quantity) using known sensory neurons, projection neurons and local neurons.

#neuroscience #Drosophila #olfaction #CompNeurosci