Radoslaw M Cichy
Biographic Data
| ID | 1833494 |
|---|---|
| NAME | Radoslaw M Cichy |
| GIVEN NAMES | Radoslaw M |
| FAMILY NAME | Cichy |
| SIGNATURE | CICHY R M |
| AFFILIATIONS | Humboldt-Universität zu Berlin |
| ORCID | 0000-0003-4190-6071 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
In silico discovery of representational relationships across visual cortex
Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas acro…
End-to-end topographic networks as models of cortical map formation and human visual behaviour
A prominent feature of the primate visual system is its topographic organization. For understanding its origins, its computational role and its behavioural implications, computational models are of central importance. Yet, vision is commonly modelled using convolutional neural networks, which are hard-wired to learn identical features across space and thus lack topography. Here we overcome this limitation by introducing all-topographic neural net…
Individual differences in internal models explain idiosyncrasies in scene perception
According to predictive processing theories, vision is facilitated by predictions derived from our internal models of what the world should look like. However, the contents of these models and how they vary across people remains unclear. Here, we use drawing as a behavioral readout of the contents of the internal models in individual participants. Participants were first asked to draw typical versions of scene categories, as descriptors of their …
The spatiotemporal neural dynamics of object location representations in the human brain
To interact with objects in complex environments, we must know what they are and where they are in spite of challenging viewing conditions. Here, we investigated where, how and when representations of object location and category emerge in the human brain when objects appear on cluttered natural scene images using a combination of functional magnetic resonance imaging, electroencephalography and computational models. We found location representat…
The spatiotemporal neural dynamics of object location representations in the human brain
To interact with objects in complex environments, we must know what they are and where they are in spite of challenging viewing conditions. Here, we investigated where, how and when representations of object location and category emerge in the human brain when objects appear on cluttered natural scene images using a combination of functional magnetic resonance imaging, electroencephalography and computational models. We found location representat…
The spatiotemporal neural dynamics of object location representations in the human brain
To interact with objects in complex environments, we must know what they are and where they are in spite of challenging viewing conditions. Here, we investigated where, how and when representations of object location and category emerge in the human brain when objects appear on cluttered natural scene images using a combination of functional magnetic resonance imaging, electroencephalography and computational models. We found location representat…
Individual differences in internal models explain idiosyncrasies in scene perception
According to predictive processing theories, vision is facilitated by predictions derived from our internal models of what the world should look like. However, the contents of these models and how they vary across people remains unclear. Here, we use drawing as a behavioral readout of the contents of the internal models in individual participants. Participants were first asked to draw typical versions of scene categories, as descriptors of their …
In silico discovery of representational relationships across visual cortex
Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas acro…
End-to-end topographic networks as models of cortical map formation and human visual behaviour
A prominent feature of the primate visual system is its topographic organization. For understanding its origins, its computational role and its behavioural implications, computational models are of central importance. Yet, vision is commonly modelled using convolutional neural networks, which are hard-wired to learn identical features across space and thus lack topography. Here we overcome this limitation by introducing all-topographic neural net…
Computer Science (4 works) · Artificial Intelligence (3 works) · Face Recognition and Perception (3 works) · Neuroscience (3 works) · Psychology (3 works) · Visual perception and processing mechanisms (3 works) · Biology (2 works) · Cognitive science (2 works) · Visual Attention and Saliency Detection (2 works) · Visual cortex (2 works)