//

메뉴 건너뛰기




  • Journal Club
  • admin
  • Oct 29, 2021
  • 256

Nature
The orbitofrontal cortex maps future navigational goals

https://www.nature.com/articles/s41586-021-04042-9


 


Science advances
Theta oscillations coordinate grid-like representations between ventromedial prefrontal and entorhinal cortex

https://www.science.org/doi/10.1126/sciadv.abj0200

 

 

 

Nature Neuroscience
Visual and linguistic semantic representations are aligned at the border of human visual cortex

https://www.nature.com/articles/s41593-021-00921-6

 

 

 

Nature communications
Partially overlapping spatial environments trigger reinstatement in hippocampus and schema representations in prefrontal cortex

https://www.nature.com/articles/s41467-021-26560-w

 

Concept neurons in the human medial temporal lobe flexibly represent abstract relations between concepts
https://www.nature.com/articles/s41467-021-26327-3

 

 

 

Communication biology
Visual stimulus features that elicit activity in object-vector cells

https://www.nature.com/articles/s42003-021-02727-5

 

 

 

Journal of neuroscience
A Neurocomputational Model for Intrinsic Reward

https://www.jneurosci.org/content/41/43/8963

 

Cognitive and Neural State Dynamics of Narrative Comprehension
https://www.jneurosci.org/content/41/43/8972

 

 

 

Current Biology
Attention improves information flow between neuronal populations without changing the communication subspace

https://www.cell.com/current-biology/fulltext/S0960-9822(21)01344-0

 

 

 

PNAS
Visual exposure enhances stimulus encoding and persistence in primary cortex

https://www.pnas.org/content/118/43/e2105276118

 

An uncommon neuronal class conveys visual signals from rods and cones to retinal ganglion cells
https://www.pnas.org/content/118/44/e2104884118

 

 

 

Scientific report
Spatial representability of neuronal activity

https://www.nature.com/articles/s41598-021-00281-y

 

 


Neural Networks
LGN-CNN: A biologically inspired CNN architecture

https://www.sciencedirect.com/science/article/pii/S0893608021003865

 

 

 

Journal of Vision
Evaluating the progress of deep learning for visual relational concepts

https://jov.arvojournals.org/article.aspx?articleid=2777974

 

ImageNet-trained deep neural networks exhibit illusion-like response to the Scintillating grid
https://jov.arvojournals.org/article.aspx?articleid=2778014

 

 

 

bioRxiv
Neural knowledge assembly in humans and deep networks

https://www.biorxiv.org/content/10.1101/2021.10.21.465374v1

 

Visual space curves before eye movements
https://www.biorxiv.org/content/10.1101/2021.10.13.464140v3

 

Differential patterns of change in brain connectivity resulting from traumatic brain injury
https://www.biorxiv.org/content/10.1101/2021.10.27.466136v1

 

Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics
https://www.biorxiv.org/content/10.1101/2021.10.25.465583v1

 

The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning
https://www.biorxiv.org/content/10.1101/2021.06.18.448989v3
 

제목 날짜
20.02.14 Journal alert   2020.02.14
20.09.04 Journal alert   2020.09.04
21.08.27 Journal alert   2021.08.30
21.09.06 Journal alert   2021.09.06
21.08.13 Journal alert   2021.08.13
22.07.01 Journal alert   2022.07.02
21.03.05 Journal alert   2021.03.05
20.11.15 Journal alert   2020.11.15
21.10.15 Journal alert   2021.10.22
22.12.09 Journal alert   2022.12.09
21.08.20 Journal alert   2021.08.20
21.10.29 Journal alert   2021.10.29
22.10.07 Journal alert   2022.10.07
[Positions] Recruitment of part-time workers from COGI lab in KAIST (24.08.05~24.08.19)   2024.08.05
20.04.03 Journal alert   2020.04.03
20.08.21 Journal alert   2020.09.03
22.01.07 Journal alert   2022.01.07
21.03.13 Journal alert   2021.03.13
21.04.06 Journal alert   2021.04.06
21.07.30 Journal alert   2021.08.11

Institute for Basic Science KAIST Campus (E22) A202-1,
Department of Brain and Cognitive Sciences, Department of Bio and Brain Engineering, KAIST,
291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Tel: +82-42-350-6513,6573, Fax: +82-42-350-6510

© k2s0o1d4e0s2i1g5n. All Rights Reserved