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  • Intricate connections

    between the Julia and Mandelbrot sets,
    discovered by Marius F. Danca and colleagues

    Find out more
  • The chronotron

    a neuron that learns to fire
    temporally precise spike patterns

    Find out more
  • New metrics

    for quantifying the variability of neural spike trains

    Find out more

News

Digi24 TV showcases the Romanian Institute of Science and Technology

Raul Mureşan and Răzvan Florian have talked about the institute's history and results.  

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Nature, about TENSS: „a rare beacon of research excellence in Romania”

The prestigious weekly journal of science has published an editorial about the Transilvanian Experimental Neuroscience Summer School, co-organized by our institute's Center for Cognitive and Neural Studies.

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A new class of spike train metrics

Cătălin Rusu and Răzvan Florian have developed a series of several new metrics for quantifying the differences between spike trains. The new metrics are inspired by the Pompeiu-Hausdorff distance.

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Intricate connections between the Julia and Mandelbrot sets

RIST's scientist Marius F. Danca and his colleagues have discovered that the Mandelbrot set is not only the set of complex plane points for which Julia sets are connected, but also the set of all parameter values for which alternated Julia sets are disconnected.

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The research of Raul Mureşan's lab is featured on the Max Planck website

The website of the prestigious Max Planck Institute (Germany) features an article on the work of the group led by Raul Mureşan at our institute's Center for Cognitive and Neural Studies.

Nature showcases the research of Florian Engert

The prestigious Nature journal showcases the research of Florian Engert, who is a member of the board of the Romanian Institute of Science and Technology and a professor at Harvard University, USA.

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The chronotron - a neuron that learns to fire temporally precise spike patterns

Răzvan Florian has shown how neurons can learn to process and memorize information that is entirely temporally coded, both as input and as output, in the precise timings of spikes.

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Finding attractors of continuous-time systems by parameter switching

RIST's Marius F. Danca has found that if the control parameter p, of a continuous-time nonlinear system belonging to a large class of systems, is switched within a set of chosen values in a deterministic or even random manner, while the underlying model is numerically integrated, the obtained attractor is a numerical approximation of one of the existing attractors of the considered system.

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The brain's timescale correlates to the timescale of visual stimuli

Our scientists have found that the internal timescale of the brain, i.e., the time window needed by neurons to encode a given aspect of the visual stimulus, is tightly correlated to the external timescale of the visual stimulus, i.e., the speed with which the visual image on the retina changes.

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Visualizing how the brain encodes information

The institute's scientists have developed a special visualization technique for how multiple neurons fire spikes together to encode information, by representing the identity of firing patterns of multiple neurons with color sequences.

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