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Action observation: the less-explored part of higher-order vision.

ABSTRACT: Little is presently known about action observation, an important perceptual component of high-level vision. To investigate this aspect of perception, we introduce a two-alternative forced-choice task for observed manipulative actions while varying duration or signal strength by noise injection. We show that accuracy and reaction time in this task can be modeled by a diffusion process for different pairs of action exemplars. Furthermore, discrimination of observed actions is largely viewpoint-independent, cannot be reduced to judgments about the basic components of action: shape and local motion, and requires a minimum duration of about 150-200?ms. These results confirm that action observation is a distinct high-level aspect of visual perception based on temporal integration of visual input generated by moving body parts. This temporal integration distinguishes it from object or scene perception, which require only very brief presentations and are viewpoint-dependent. The applicability of a diffusion model suggests that these aspects of high-level vision differ mainly at the level of the sensory neurons feeding the decision processes.

SUBMITTER: Platonov A

PROVIDER: S-EPMC5114682 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Action observation: the less-explored part of higher-order vision.

Platonov Artem A Orban Guy A GA

Scientific reports 20161118

Little is presently known about action observation, an important perceptual component of high-level vision. To investigate this aspect of perception, we introduce a two-alternative forced-choice task for observed manipulative actions while varying duration or signal strength by noise injection. We show that accuracy and reaction time in this task can be modeled by a diffusion process for different pairs of action exemplars. Furthermore, discrimination of observed actions is largely viewpoint-ind ...[more]

PMID: 27857160

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Project description:It is increasingly being recognized that physical interactions between distant chromosomal loci influence the expressivity of the genome. Thus, multiple enhancers may converge on a single gene promoter 1,2 and a single enhancer can stochastically loop to multiple promoters 3. Regulatory elements from neighboring domains or from other chromosomes may interact to generate chromatin structures poised for transcription4-8 or repression 9-11. However, a broader perspective on the formation and function of such networks remains largely unexplored. Using the high-resolution 4C (Circular Chromosome Conformation Capture) analysis, we identify here a genome-wide physical network between genomically imprinted domains impinging H19 imprinting control region (ICR). Sequences interacting with the H19 ICR constitutively map at or within most of known imprinted domains both in mouse embryonic stem cells and in vitro-derived embryoid bodies, despite distinct differences in chromatin environments. Moreover, all-to-all 3D DNA FISH analyses revealed that imprinted domains from 7 different chromosomes co-localize with each other in pair-wise patterns, highlighting the dynamic nature of these interactions. The observed interaction network is dependent on CTCF binding sites within the maternally inherited H19 ICR allele and delays reprogramming of epigenetic features at imprinted domains during male germline development. As other imprinted regions can interact with each other in an H19 ICR-dependent manner, the H19 ICR emerges as an organizer of chromosomal networks by specifically recognizing and reconfiguring imprinted domains. We propose that an ancient key regulatory region, such as the H19 ICR, gradually impacted epigenetic modifications via long-range interactions in the germline to facilitate the recruitment of imprinted genes and their formation in clusters during mammalian radiation. Furthermore, the perspective of epigenetic lesions de-stabilizing such chromosomal networks may advance our understanding of how quantitative traits influence human diseases, such as cancer.

Dataset Information

Action observation: the less-explored part of higher-order vision.

Publications

Action observation: the less-explored part of higher-order vision.

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