scholarly journals Distractibility and impulsivity neural states are distinct from attention states and modulate the implementation of attention

2021 ◽  
Author(s):  
Julian Amengual ◽  
Fabio Di Bello ◽  
Sameh Ben Hadj Hassen ◽  
Suliann Ben Hamed

In the context of visual attention, it has been classically assumed that missing the response to a target or erroneously selecting a distractor occurs as a consequence of the (miss)allocation of attention in space. In the present paper, we challenge this view and provide evidence that, in addition to encoding spatial attention, prefrontal neurons also encode a distractibility-to-impulsivity state. Using supervised dimensionality reduction techniques, we identify two partially overlapped neuronal subpopulations associated either with attention or overt behaviour. The degree of overlap accounts for the behavioural gain associated with the good allocation of attention. We further describe the neural variability accounting for distractibility-to-impulsivity behaviour by a two dimensional state associated with optimality in task and responsiveness. Overall, we thus show that behavioural performance arises from the integration of task-specific neuronal processes and pre-existing neuronal states describing task-independent behavioural states, shedding new light on attention disorders such as ADHD.

2015 ◽  
Vol 294 ◽  
pp. 553-564 ◽  
Author(s):  
Manuel Domínguez ◽  
Serafín Alonso ◽  
Antonio Morán ◽  
Miguel A. Prada ◽  
Juan J. Fuertes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Van Hoan Do ◽  
Stefan Canzar

AbstractEmerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes.


2019 ◽  
Vol 165 ◽  
pp. 104-111 ◽  
Author(s):  
S. Velliangiri ◽  
S. Alagumuthukrishnan ◽  
S Iwin Thankumar joseph

2016 ◽  
Vol 85 ◽  
pp. 241-248 ◽  
Author(s):  
A. Vinay ◽  
Vikkram Vasuki ◽  
Shreyas Bhat ◽  
K.S. Jayanth ◽  
K.N. Balasubramanya Murthy ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document