'Tagesspiegel' reports on brain-constrained neural network models

The German newspaper "Tagesspiegel" has reported on the MatCo project. The article addresses our latest findings regarding the processing and memorization of abstract concepts, highlighting why language, particularly words, is adept at tackling this subject. You can read the full article here .

Feb 21, 2024 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New student assistant hired

A new student assistant, Anna Sadlon, has just joined the team. Welcome!

Feb 01, 2024 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New student assistant hired

A new student assistant, Sabrina Nieswand, has just joined the team. Welcome!

Jan 01, 2024 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

What influence does language have on concept learning?

What is a brain-constrained neural network, and how can it shed light on the influence language has on concept learning? Join Technology Networks and Fynn Dobler for an interview answering these questions here !

Nov 28, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

The MatCo project is featured in the 'Project Repository Journal'

The European Dissemination Media Agency (EDMA) reports on the MatCo project in detail in their latest issue of the project repository journal (PRj). You can directly access the article  here , and for more information about the issue, you can find it here .

Nov 28, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Talk at Ringvorlesung at Bernstein Center Freiburg

Friedemann Pulvermüller will present novel research results at the Ringvorlesung  in Freiburg. On Monday, 23.10., he will give a talk on how meaning enters the brain. (german)

Oct 16, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Talk at NeuroExp 2023 in Berlin

Friedemann Pulvermüller will present novel research results at the NeuroExp in Berlin. On Thursday, 12.10., he will give a talk on the formation and explanation of abstract concepts via a brain-constrained neurocomputational mechanism.

Oct 09, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New student assistant hired

A new student assistant, Nikos Antoniadis, has just joined the team. Welcome!

Oct 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New postdoctoral researcher hired

A new postdoctoral researcher, Effrosyni Ntemou, has just joined the team. Welcome!

Oct 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Press Release: Exploring the Brain Basis of Concepts by Using a New Type of Neural Networks

To highlight important aspects of MatCo research, we have written a press release on our newest paper on brain-constrained neural network modelling, which was published in Progress in Neurobiology. You can find the press release  here .

Sep 26, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Key Note and Talk at ESLP2023 in Messina

Friedemann Pulvermüller and Fynn Dober will present novel research results at the ESLP in Messina. On Friday, 29.09., Friedemann Pulvermüller will give a keynote on semantic grounding and brain-constrained neural modelling of symbols and concepts. On Saturady, 30.09., Fynn Dobler will give a talk on evidence from brain-constrained deep neural networks regarding the formation of abstract and concrete concepts.

Sep 22, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New student assistant hired

A new student assistant, Lorenzo Stroppa, has just joined the team. Welcome!

Sep 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New student assistant hired

A new student assistant, Johann Berger, has just joined the team. Welcome!

Sep 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New PhD student hired

A new PhD student, Anna-Thekla Jäger , has just joined the team. Welcome!

Aug 09, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New PhD student hired

A new PhD student, Milena Osterloh , has just joined the team. Welcome!

Aug 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

What chatGPT cannot do for you: Explanation of human symbol processing based on brain-constrained networks

Jul 20, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Guest talk by Prof. Andreas Knoblauch: Learning mechanisms in neural networks and in artificial intelligence

28.07.2023, 16 - 18 c.t. FU Berlin JK 31/102 (Habelschwerdter Allee 45)

Jul 14, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

Guest talk by Phuc Nguyen: A brain-constrained neural network model of proper names and category terms

31.05.2023, 16 -18 c.t. FU Berlin, JK 31/102 (Habelschwerdter Allee 45)

May 19, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New PhD student hired

A new PhD student, Agata Feledyn, has just joined the team. Welcome!

Apr 03, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition

New paper: Brain-constrained neural modeling explains fast mapping of words to meaning

Marika Constant, Friedemann Pulvermüller and Rosario Tomasello have used brain-constrained neural networks to simulate key features of semantic associative learning with only a few simultaneous exposures to objects, actions and corresponding word forms. This corresponds to so-called "fast-mapping": the rapid association of symbols and meaning. Most neural network learning algorithms fail to achieve rapid information storape quickly, raising the question of whether there can be a mechanistic explanation of fast-mapping. The researchers have compared two different networks: one with prior encounters with phonological and conceptual knowledge, as claimed by fast-mapping theory and one without. Simulations showed that word-specific representations emerged in the network modelled after fast-mapping theory after 1-10 learning events, but only after 40-100 learning events in the direct word learning model. These findings provide a better understanding of the critical mechanisms underlying the human brain's unique ability to acquire new words quickly. You can read the full paper published in  Cerebral Cortex   here .

Mar 01, 2023 | ERC Advanced Grant 883811, MatCo: Material Constraints Enabling Human Cognition