#dynamicalsystem — Public Fediverse posts

🧠 New work by Codol et al. who show that #MotorCortex dynamics are remarkably conserved across #mice, #monkeys, and #humans. Despite very different #behaviors, #NeuralPopulation activity follows similar dynamical rules on low-dimensional #manifolds. Species differences arise mainly from the geometry of trajectories within this shared #DynamicalSystem.

📄 https://doi.org/10.64898/2026.03.06.709637

#Neuroscience #CompNeuro #NeuralDynamics

🧠 New work by Codol et al. who show that #MotorCortex dynamics are remarkably conserved across #mice, #monkeys, and #humans. Despite very different #behaviors, #NeuralPopulation activity follows similar dynamical rules on low-dimensional #manifolds. Species differences arise mainly from the geometry of trajectories within this shared #DynamicalSystem.

📄 https://doi.org/10.64898/2026.03.06.709637

#Neuroscience #CompNeuro #NeuralDynamics

🧠 New work by Codol et al. who show that #MotorCortex dynamics are remarkably conserved across #mice, #monkeys, and #humans. Despite very different #behaviors, #NeuralPopulation activity follows similar dynamical rules on low-dimensional #manifolds. Species differences arise mainly from the geometry of trajectories within this shared #DynamicalSystem.

📄 https://doi.org/10.64898/2026.03.06.709637

#Neuroscience #CompNeuro #NeuralDynamics

🧠 New work by Codol et al. who show that #MotorCortex dynamics are remarkably conserved across #mice, #monkeys, and #humans. Despite very different #behaviors, #NeuralPopulation activity follows similar dynamical rules on low-dimensional #manifolds. Species differences arise mainly from the geometry of trajectories within this shared #DynamicalSystem.

📄 https://doi.org/10.64898/2026.03.06.709637

#Neuroscience #CompNeuro #NeuralDynamics

🧠 New work by Codol et al. who show that #MotorCortex dynamics are remarkably conserved across #mice, #monkeys, and #humans. Despite very different #behaviors, #NeuralPopulation activity follows similar dynamical rules on low-dimensional #manifolds. Species differences arise mainly from the geometry of trajectories within this shared #DynamicalSystem.

📄 https://doi.org/10.64898/2026.03.06.709637

#Neuroscience #CompNeuro #NeuralDynamics

#simplicialcomplex + #Causality +#Reservoircomputing:
"Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction" https://www.nature.com/articles/s41467-024-46852-1

#dynamicalsystem #ML #AI

#simplicialcomplex + #Causality +#Reservoircomputing:
"Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction" https://www.nature.com/articles/s41467-024-46852-1

#dynamicalsystem #ML #AI

#simplicialcomplex + #Causality +#Reservoircomputing:
"Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction" https://www.nature.com/articles/s41467-024-46852-1

#dynamicalsystem #ML #AI

#simplicialcomplex + #Causality +#Reservoircomputing:
"Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction" https://www.nature.com/articles/s41467-024-46852-1

#dynamicalsystem #ML #AI

#simplicialcomplex + #Causality +#Reservoircomputing:
"Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction" https://www.nature.com/articles/s41467-024-46852-1

#dynamicalsystem #ML #AI

An important step in #ComputationalNeuroscience 🧠💻 was the development of the #HodgkinHuxley model, for which Hodgkin and Huxley received the #NobelPrize in 1963. The model describes the dynamics of the #MembranePotential of a #neuron 🔬 by incorporating biophysiological properties. See here how it is derived, along with a simple implementation in #Python:

🌍 https://www.fabriziomusacchio.com/blog/2024-04-21-hodgkin_huxley_model/

Feel free to share and to experiment with the code.

#CompNeuro #PythonTutorial #NeuralDynamics #DynamicalSystem

An important step in #ComputationalNeuroscience 🧠💻 was the development of the #HodgkinHuxley model, for which Hodgkin and Huxley received the #NobelPrize in 1963. The model describes the dynamics of the #MembranePotential of a #neuron 🔬 by incorporating biophysiological properties. See here how it is derived, along with a simple implementation in #Python:

🌍 https://www.fabriziomusacchio.com/blog/2024-04-21-hodgkin_huxley_model/

Feel free to share and to experiment with the code.

#CompNeuro #PythonTutorial #NeuralDynamics #DynamicalSystem

An important step in #ComputationalNeuroscience 🧠💻 was the development of the #HodgkinHuxley model, for which Hodgkin and Huxley received the #NobelPrize in 1963. The model describes the dynamics of the #MembranePotential of a #neuron 🔬 by incorporating biophysiological properties. See here how it is derived, along with a simple implementation in #Python:

🌍 https://www.fabriziomusacchio.com/blog/2024-04-21-hodgkin_huxley_model/

Feel free to share and to experiment with the code.

#CompNeuro #PythonTutorial #NeuralDynamics #DynamicalSystem

An important step in #ComputationalNeuroscience 🧠💻 was the development of the #HodgkinHuxley model, for which Hodgkin and Huxley received the #NobelPrize in 1963. The model describes the dynamics of the #MembranePotential of a #neuron 🔬 by incorporating biophysiological properties. See here how it is derived, along with a simple implementation in #Python:

🌍 https://www.fabriziomusacchio.com/blog/2024-04-21-hodgkin_huxley_model/

Feel free to share and to experiment with the code.

#CompNeuro #PythonTutorial #NeuralDynamics #DynamicalSystem

An important step in #ComputationalNeuroscience 🧠💻 was the development of the #HodgkinHuxley model, for which Hodgkin and Huxley received the #NobelPrize in 1963. The model describes the dynamics of the #MembranePotential of a #neuron 🔬 by incorporating biophysiological properties. See here how it is derived, along with a simple implementation in #Python:

🌍 https://www.fabriziomusacchio.com/blog/2024-04-21-hodgkin_huxley_model/

Feel free to share and to experiment with the code.

#CompNeuro #PythonTutorial #NeuralDynamics #DynamicalSystem

Here is another #PhasePlaneAnalysis #tutorial, this time applied to the #VanDerPolOscillator, a non-conservative #oscillator with nonlinear damping:

🌍 https://www.fabriziomusacchio.com/blog/2024-03-24-van_der_pol_oscillator/

#DynamicalSystem #ComputationalScience #PhasePortraits #Python

Here is another #PhasePlaneAnalysis #tutorial, this time applied to the #VanDerPolOscillator, a non-conservative #oscillator with nonlinear damping:

🌍 https://www.fabriziomusacchio.com/blog/2024-03-24-van_der_pol_oscillator/

#DynamicalSystem #ComputationalScience #PhasePortraits #Python

Here is another #PhasePlaneAnalysis #tutorial, this time applied to the #VanDerPolOscillator, a non-conservative #oscillator with nonlinear damping:

🌍 https://www.fabriziomusacchio.com/blog/2024-03-24-van_der_pol_oscillator/

#DynamicalSystem #ComputationalScience #PhasePortraits #Python

Here is another #PhasePlaneAnalysis #tutorial, this time applied to the #VanDerPolOscillator, a non-conservative #oscillator with nonlinear damping:

🌍 https://www.fabriziomusacchio.com/blog/2024-03-24-van_der_pol_oscillator/

#DynamicalSystem #ComputationalScience #PhasePortraits #Python

Here is another #PhasePlaneAnalysis #tutorial, this time applied to the #VanDerPolOscillator, a non-conservative #oscillator with nonlinear damping:

🌍 https://www.fabriziomusacchio.com/blog/2024-03-24-van_der_pol_oscillator/

#DynamicalSystem #ComputationalScience #PhasePortraits #Python

Exploring the behavior of #DynamicalSystems directly through their differential equations can be complex. #PhasePlaneAnalysis offers a clearer and intuitive view by visualizing dynamics with #PhasePortraits, simplifying understanding. Here is a #tutorial along with some #Python code, exploring this method and exemplarily applying it to the simple pendulum.

🌍 https://www.fabriziomusacchio.com/blog/2024-03-17-phase_plane_analysis/

#ChaoticSystems #DynamicalSystem #ComputationalScience

Exploring the behavior of #DynamicalSystems directly through their differential equations can be complex. #PhasePlaneAnalysis offers a clearer and intuitive view by visualizing dynamics with #PhasePortraits, simplifying understanding. Here is a #tutorial along with some #Python code, exploring this method and exemplarily applying it to the simple pendulum.

🌍 https://www.fabriziomusacchio.com/blog/2024-03-17-phase_plane_analysis/

#ChaoticSystems #DynamicalSystem #ComputationalScience

Exploring the behavior of #DynamicalSystems directly through their differential equations can be complex. #PhasePlaneAnalysis offers a clearer and intuitive view by visualizing dynamics with #PhasePortraits, simplifying understanding. Here is a #tutorial along with some #Python code, exploring this method and exemplarily applying it to the simple pendulum.

🌍 https://www.fabriziomusacchio.com/blog/2024-03-17-phase_plane_analysis/

#ChaoticSystems #DynamicalSystem #ComputationalScience

Exploring the behavior of #DynamicalSystems directly through their differential equations can be complex. #PhasePlaneAnalysis offers a clearer and intuitive view by visualizing dynamics with #PhasePortraits, simplifying understanding. Here is a #tutorial along with some #Python code, exploring this method and exemplarily applying it to the simple pendulum.

🌍 https://www.fabriziomusacchio.com/blog/2024-03-17-phase_plane_analysis/

#ChaoticSystems #DynamicalSystem #ComputationalScience

Exploring the behavior of #DynamicalSystems directly through their differential equations can be complex. #PhasePlaneAnalysis offers a clearer and intuitive view by visualizing dynamics with #PhasePortraits, simplifying understanding. Here is a #tutorial along with some #Python code, exploring this method and exemplarily applying it to the simple pendulum.

🌍 https://www.fabriziomusacchio.com/blog/2024-03-17-phase_plane_analysis/

#ChaoticSystems #DynamicalSystem #ComputationalScience

Genuary Prompt Nr. 5 is "In the style of Vera Molnàr". When I looked at her works I liked the framing squares with things going on in them. They reminded me at what I saw when investigating Dynamical Systems. This is 8 iterations of the function f(x,y)=( x-(1+y/4)tan(y)-t*y , x )

Full-Res full-length full-size version: https://youtu.be/q8V0KPQRjRM

#genuary #genuary5 #genuary2024 #dynamicalsystem

Genuary Prompt Nr. 5 is "In the style of Vera Molnàr". When I looked at her works I liked the framing squares with things going on in them. They reminded me at what I saw when investigating Dynamical Systems. This is 8 iterations of the function f(x,y)=( x-(1+y/4)tan(y)-t*y , x )

Full-Res full-length full-size version: https://youtu.be/q8V0KPQRjRM

#genuary #genuary5 #genuary2024 #dynamicalsystem

Genuary Prompt Nr. 5 is "In the style of Vera Molnàr". When I looked at her works I liked the framing squares with things going on in them. They reminded me at what I saw when investigating Dynamical Systems. This is 8 iterations of the function f(x,y)=( x-(1+y/4)tan(y)-t*y , x )

Full-Res full-length full-size version: https://youtu.be/q8V0KPQRjRM

#genuary #genuary5 #genuary2024 #dynamicalsystem

Genuary Prompt Nr. 5 is "In the style of Vera Molnàr". When I looked at her works I liked the framing squares with things going on in them. They reminded me at what I saw when investigating Dynamical Systems. This is 8 iterations of the function f(x,y)=( x-(1+y/4)tan(y)-t*y , x )

Full-Res full-length full-size version: https://youtu.be/q8V0KPQRjRM

#genuary #genuary5 #genuary2024 #dynamicalsystem

Genuary Prompt Nr. 5 is "In the style of Vera Molnàr". When I looked at her works I liked the framing squares with things going on in them. They reminded me at what I saw when investigating Dynamical Systems. This is 8 iterations of the function f(x,y)=( x-(1+y/4)tan(y)-t*y , x )

Full-Res full-length full-size version: https://youtu.be/q8V0KPQRjRM

#genuary #genuary5 #genuary2024 #dynamicalsystem

Mapping the complex plane.
Using an image of a flower for coloring.

https://gitlab.com/metagrowing/ana/-/blob/master/visual_server/media/frag/cmplx/cmplx-03.frag

https://gitlab.com/metagrowing/ana/-/blob/master/live_coding/src/demo/cmplx/cmplx-03.clj

#dynamicalsystem #openFrameworks

Mapping the complex plane.
Using an image of a flower for coloring.

https://gitlab.com/metagrowing/ana/-/blob/master/visual_server/media/frag/cmplx/cmplx-03.frag

https://gitlab.com/metagrowing/ana/-/blob/master/live_coding/src/demo/cmplx/cmplx-03.clj

#dynamicalsystem #openFrameworks

Mapping the complex plane.
Using an image of a flower for coloring.

https://gitlab.com/metagrowing/ana/-/blob/master/visual_server/media/frag/cmplx/cmplx-03.frag

https://gitlab.com/metagrowing/ana/-/blob/master/live_coding/src/demo/cmplx/cmplx-03.clj

#dynamicalsystem #openFrameworks

Mapping the complex plane.
Using an image of a flower for coloring.

https://gitlab.com/metagrowing/ana/-/blob/master/visual_server/media/frag/cmplx/cmplx-03.frag

https://gitlab.com/metagrowing/ana/-/blob/master/live_coding/src/demo/cmplx/cmplx-03.clj

#dynamicalsystem #openFrameworks

Mapping the complex plane.
Using an image of a flower for coloring.

https://gitlab.com/metagrowing/ana/-/blob/master/visual_server/media/frag/cmplx/cmplx-03.frag

https://gitlab.com/metagrowing/ana/-/blob/master/live_coding/src/demo/cmplx/cmplx-03.clj

#dynamicalsystem #openFrameworks

@noneuclideandreamer Again, this iterative mapping in the complex plane. This time with adjustable color spectrum and denoised.

for(int l=0; l<9; ++l) {
_xy = vec2(_xy.y + sin(t * _xy.x),
_xy.x);
}

#dynamicalsystem

@noneuclideandreamer Again, this iterative mapping in the complex plane. This time with adjustable color spectrum and denoised.

for(int l=0; l<9; ++l) {
_xy = vec2(_xy.y + sin(t * _xy.x),
_xy.x);
}

#dynamicalsystem

@noneuclideandreamer Again, this iterative mapping in the complex plane. This time with adjustable color spectrum and denoised.

for(int l=0; l<9; ++l) {
_xy = vec2(_xy.y + sin(t * _xy.x),
_xy.x);
}

#dynamicalsystem

@noneuclideandreamer Again, this iterative mapping in the complex plane. This time with adjustable color spectrum and denoised.

for(int l=0; l<9; ++l) {
_xy = vec2(_xy.y + sin(t * _xy.x),
_xy.x);
}

#dynamicalsystem

@noneuclideandreamer Again, this iterative mapping in the complex plane. This time with adjustable color spectrum and denoised.

for(int l=0; l<9; ++l) {
_xy = vec2(_xy.y + sin(t * _xy.x),
_xy.x);
}

#dynamicalsystem

Soapy Function:

(x,y)=(y+tlog|x|,x)

(better resolution on youtube)

#mastoart #codeart #dynamicalsystem

Soapy Function:

(x,y)=(y+tlog|x|,x)

(better resolution on youtube)

#mastoart #codeart #dynamicalsystem

Soapy Function:

(x,y)=(y+tlog|x|,x)

(better resolution on youtube)

#mastoart #codeart #dynamicalsystem

Soapy Function:

(x,y)=(y+tlog|x|,x)

(better resolution on youtube)

#mastoart #codeart #dynamicalsystem

Soapy Function:

(x,y)=(y+tlog|x|,x)

(better resolution on youtube)

#mastoart #codeart #dynamicalsystem

Proudly presenting this month's High-res Render for Patrons of Level Square and up: full size 25600×25600 pixels

If you try to "magic eye" it, it shimmers!

It's my favorite of the iteration functions I explored: (x,y)=(x-t*tan(y),x).
The squares have a side length of pi, due to tan of course.
Squares below each other would actually look the same since it does only depend on y%pi via tan. So I discretely jumped my t-value from 1.1 over 1 to 0.9.

#mathart #codeart #fractal #blackandwhite #dynamicalsystem #mastoart

Proudly presenting this month's High-res Render for Patrons of Level Square and up: full size 25600×25600 pixels

If you try to "magic eye" it, it shimmers!

It's my favorite of the iteration functions I explored: (x,y)=(x-t*tan(y),x).
The squares have a side length of pi, due to tan of course.
Squares below each other would actually look the same since it does only depend on y%pi via tan. So I discretely jumped my t-value from 1.1 over 1 to 0.9.

#mathart #codeart #fractal #blackandwhite #dynamicalsystem #mastoart

Proudly presenting this month's High-res Render for Patrons of Level Square and up: full size 25600×25600 pixels

If you try to "magic eye" it, it shimmers!

It's my favorite of the iteration functions I explored: (x,y)=(x-t*tan(y),x).
The squares have a side length of pi, due to tan of course.
Squares below each other would actually look the same since it does only depend on y%pi via tan. So I discretely jumped my t-value from 1.1 over 1 to 0.9.

#mathart #codeart #fractal #blackandwhite #dynamicalsystem #mastoart

Proudly presenting this month's High-res Render for Patrons of Level Square and up: full size 25600×25600 pixels

If you try to "magic eye" it, it shimmers!

It's my favorite of the iteration functions I explored: (x,y)=(x-t*tan(y),x).
The squares have a side length of pi, due to tan of course.
Squares below each other would actually look the same since it does only depend on y%pi via tan. So I discretely jumped my t-value from 1.1 over 1 to 0.9.

#mathart #codeart #fractal #blackandwhite #dynamicalsystem #mastoart

Proudly presenting this month's High-res Render for Patrons of Level Square and up: full size 25600×25600 pixels

If you try to "magic eye" it, it shimmers!

It's my favorite of the iteration functions I explored: (x,y)=(x-t*tan(y),x).
The squares have a side length of pi, due to tan of course.
Squares below each other would actually look the same since it does only depend on y%pi via tan. So I discretely jumped my t-value from 1.1 over 1 to 0.9.

#mathart #codeart #fractal #blackandwhite #dynamicalsystem #mastoart