Professor of Computational Neuroscience at @ELSCbrain @HebrewU
Israel
Joined February 2018
- Tweets48
- Following121
- Followers1.1K
- Likes73
Idan Segev retweeted
Happy to share my new open source tool for exploring connected neurons in the #MICrONS dataset (thanks @AllenInstitute, again) It's in the browser, online & free. No login or install required. 1/
Idan Segev retweeted
What is the difference between excitatory and inhibitory neurons?
Beyond the obvious difference of neurotransmitter effect on postsynaptic cell, another remarkable difference is the fact that excitatory neurons have lots of spines, while inhibitory neurons have less spines. 1/13
A long-awaited and wonderful breakthrough - as now we finally can ask/get answers to both: “what can a neuron compute?” and also “how it actually do it?” - congratulations Ido.
Idan Segev retweeted
Introducing the “biophysics of connectomics”, bridging 3D EM reconstructions and biophysical modeling.
Ultra-thin spine-neck constrictions act as electrical bottlenecks, driving ultra-fast EPSP dynamics.
Great teamwork with @SapirShapira2 and @Segev_Lab
biorxiv.org/content/10.64898…
Our insights from years of modeling human neurons. Come read our new review, now on @FrontNeurosci
Idan Segev retweeted
Human cortical pyramidal neurons are larger, exhibit more complex branching patterns, and feature distinctly nonlinear biophysical properties compared to rat cortical pyramidal neurons.
Do these unique characteristics make human neurons more functionally complex?
Would that enhance the capability of the human brain to perform complex computational tasks?
Is this what makes us human?
In our new preprint (see below) with @danielayoeli, @DavidBeniaguev, Christiaan de Kock, @mikilon, and @Segev_Lab we use deep learning to tackle these questions by comparing the complexity of neurons’ input-output (I/O) functions using our newly developed Functional Complexity Index (FCI) tool. (1/10)
Idan Segev retweeted
What makes us human? A new review from my colleagues at the @Segev_Lab discusses how neuronal modeling can help answer this question.
frontiersin.org/journals/neu…
Will be interesting to hear Christof Koch on "Beyond physicalism - consciousness, quantum mechanics, and mystical experiences."
Neuroscience Unleashed in Jerusalem July 20–24 2025
An international graduate school on consciousness, NeuroAI, brain-machine interfaces, psychedelics & organoids. Graduate students & postdocs: Apply by April 19 2025 iias.huji.ac.il/29LifeSci
RT to help spread the word 🙏
Idan Segev retweeted
Read the paper- Chindemi et al 2022 - A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex - doi.org/10.1038/s41467-022-3… published in @NatureComms
Find out more - actu.epfl.ch/news/does-one-s…
#plasticity #insilico
Idan Segev retweeted
My band, @SynfireChain, released our first single! Then we played it to a zebrafish under a microscope with
@LilachAvitan @ELSCbrain and put the calcium imaging video of its brain as the background to the lyric video. Because #science.
youtu.be/vbrnnCXSa_M
Join us for an exciting series of talks with @YMalchi, in Beit Ariela featuring @Amiramedi, Prof. Sarit Larish, @YovelBatLab, @MeravAhissar and myself. Details inside -
לא רק בכתב! 📣😀🗨️
הצטרפו אלינו לסדרה של חמישה מפגשים בהנחיית @YMalchi המפגישה את הילדים והילדות שלכם עם החוקרים מאחורי המאמרים (ללא תשלום, דורש רישום) - ariela.today/event/מדע-ללא-גבולות/
@Segev_Lab @Amiramedi פרופ' שרית לריש @YovelBatLab @MeravAhissar
I am heading a fascinating endeavor - @FrontYoung_IL, a scientific journal for kids, written by prominent scientists and reviewed by kids! This exciting and unique format allows direct interaction between scientists and kids, benefiting both sides.
Follow us on twitter!
קצת עלינו -
מי אנחנו? כתב עת בינלאומי מדעי מקוון לילדים. 👩🔬🧪📘🧑💻
הכותבים שלנו הם מדענים מובילים מהארץ והעולם. אנחנו מאמינים שהדרך הטובה ביותר להנגיש תגליות מדעיות לצעירים היא לאפשר להם לעבוד יחד עם המדענים, ולכן כתב העת *נערך על ידי ילדים*.
kids.frontiersin.org/he
1/4
Idan Segev retweeted
In our paper Burst Control, we explore the synaptic input conditions leading to spike burst firing in layer 5 pyramidal cells
doi.org/10.1371/journal.pcbi…
@Segev_Lab
@ELSCbrain
New paper from our lab in collaboration with the BBP.
New paper from Blue Brain & the Hebrew University of Jerusalem.
The study uses one of the most detailed models of a piece of brain tissue & modern network science & systematically studies the impact of cell types on network activity in health and disease
frontiersin.org/article/10.3…
A new paper by @DavidBeniaguev from my lab. and that of @mikilon using machine learning approach to systematically quantify and compare how "computationally deep" are different neuron types.
Out work about "Single Cortical Neurons as Deep Artificial Neural Networks" was finally published in Neuron
With @mikilon and @Segev_Lab
@NeuroCellPress paper: bit.ly/3CJic8E
code: bit.ly/3CJUeKv
data: bit.ly/3xIm6uW
All new results in thread below
Idan Segev retweeted
My and @MMKalmenson's #GradientClusteron paper is out in PLOS CB! Learn how a model #neuron with a single #dendrite can solve #MachineLearning tasks by making synapses attract and repel with a gradient descent rule! With @Segev_Lab and @ELSCbrain.
journals.plos.org/ploscompbi…
Idan Segev retweeted
In our paper Burst Control, we model the L5PC and analyze the conditions of synaptic activation in the apical and basal dendrites for burst generation. We found a novel burst-class, defined inhibitory control and correlated it with limiting plasticity.
biorxiv.org/content/10.1101/…
New paper from the lab. The G-clusteron is a model neuron with a single "dendrite" where synapses exhibit distance-dependent multiplicative interactions with each other. It can learn tasks like MNIST via a gradient descent algorithm which makes synapses attract\repel.
The Gradient Clusteron paper with @MMKalmenson and @Segev_Lab is up on biorXiv!
biorxiv.org/content/10.1101/…
Constructive feedback is appreciated!
Idan Segev retweeted
So, I am Happy to share this central effort from my PhD.
Pop-Rec is a high throughput method for unbiased, completely automated reconstruction of thousands of neurons from cleared mouse brains.
biorxiv.org/content/10.1101/…