Literature DB >> 24959154

Multisensory integration in action control.

Christine Sutter1, Knut Drewing2, Jochen Müsseler1.   

Abstract

Entities:  

Keywords:  acoustics; haptic; human information processing; perception; recalibration; reference frame; tool use; vision

Year:  2014        PMID: 24959154      PMCID: PMC4051139          DOI: 10.3389/fpsyg.2014.00544

Source DB:  PubMed          Journal:  Front Psychol        ISSN: 1664-1078


× No keyword cloud information.
The integration of multisensory information is an essential mechanism in perception and action control. Research in multisensory integration is concerned with how the information from the different sensory modalities, such as the senses of vision, hearing, smell, taste, touch, and proprioception, are integrated to a coherent representation of objects (for an overview, see e.g., Calvert et al., 2004). The combination of information from the different senses is central for action control. For instance, when you grasp for a rubber duck, you can see its size, feel its compliance and hear the sound it produces. Moreover, identical physical properties of an object can be provided by different senses. You can both see and feel the size of the rubber duck. Even when you grasp for the rubber duck with a tool (e.g., with tongs), the information from the proximal hand, from the effective part of the distal tool and from the eyes are integrated in a manner to act successfully (for limitations of this integration see Sutter et al., 2013). Over the recent decade a surge of interest in multisensory integration and action control has been witnessed, especially in connection with the idea of a statistically optimized integration of multiple sensory sources. The human information processing system is assumed to adjust moment-by-moment the relative contribution of each sense's estimate to a multisensory task. The sense's contribution depends on its variance, so that the total variance of the multisensory estimate is lower than that for each sense alone. Accordingly, the validity of a statistically optimized multisensory integration has been demonstrated by extensive empirical research (e.g., Ernst and Banks, 2002; Alais and Burr, 2004; Reuschel et al., 2010), also in applied setting such as tool-use (e.g., Takahashi et al., 2009; in the present research topic: Takahashi and Watt, 2014). For this perspective to mature it will be helpful to delve deeper into the multisensory information processing mechanisms and their neural correlates, asking about the range and constraints of these mechanisms, about its localization and involved networks. The contributions to the present research topic range from how information from different senses and action control are linked and modulated by object affordances (Garrido-Vásquez and Schubö, 2014), by task-irrelevant information (Juravle et al., 2013; Wendker et al., 2014; for a review see Wesslein et al., 2014), by temporal and spatial coupling within and between senses (Cameron et al., 2014; Mueller and Fiehler, 2014; Rieger et al., 2014; Sugano et al., 2014) to childhood development of multisensory mechanisms (Jovanovic and Drewing, 2014). Correspondences between the information from different senses play an important role for multisensory integration. Integration does, for instance, not take place when vision and touch are spatially separated (e.g., Gepshtein et al., 2005). However, cognitive approaches on action effect control assume that information from different senses is still coded and represented within the same cognitive domain, when the information concerns the same action (e.g., Müsseler, 1999; Hommel et al., 2001). The present research topic also addresses the corresponding issue of modality-specific action control (Boutin et al., 2013; Grunwald et al., 2014). Overall, the present research topic broadens our view on how multisensory mechanisms add to action control. We thank all authors and all reviewers for their valuable contributions.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  18 in total

1.  The ventriloquist effect results from near-optimal bimodal integration.

Authors:  David Alais; David Burr
Journal:  Curr Biol       Date:  2004-02-03       Impact factor: 10.834

Review 2.  The Theory of Event Coding (TEC): a framework for perception and action planning.

Authors:  B Hommel; J Müsseler; G Aschersleben; W Prinz
Journal:  Behav Brain Sci       Date:  2001-10       Impact factor: 12.579

3.  The combination of vision and touch depends on spatial proximity.

Authors:  Sergei Gepshtein; Johannes Burge; Marc O Ernst; Martin S Banks
Journal:  J Vis       Date:  2005-12-28       Impact factor: 2.240

4.  Humans integrate visual and haptic information in a statistically optimal fashion.

Authors:  Marc O Ernst; Martin S Banks
Journal:  Nature       Date:  2002-01-24       Impact factor: 49.962

5.  Optimal integration of visual and proprioceptive movement information for the perception of trajectory geometry.

Authors:  Johanna Reuschel; Knut Drewing; Denise Y P Henriques; Frank Rösler; Katja Fiehler
Journal:  Exp Brain Res       Date:  2009-12-02       Impact factor: 1.972

6.  Visual target distance, but not visual cursor path length produces shifts in motor behavior.

Authors:  Nike Wendker; Oliver S Sack; Christine Sutter
Journal:  Front Psychol       Date:  2014-03-17

7.  The role of differential delays in integrating transient visual and proprioceptive information.

Authors:  Brendan D Cameron; Cristina de la Malla; Joan López-Moliner
Journal:  Front Psychol       Date:  2014-02-03

8.  The influence of intersensory discrepancy on visuo-haptic integration is similar in 6-year-old children and adults.

Authors:  Bianca Jovanovic; Knut Drewing
Journal:  Front Psychol       Date:  2014-01-30

9.  Gaze-dependent spatial updating of tactile targets in a localization task.

Authors:  Stefanie Mueller; Katja Fiehler
Journal:  Front Psychol       Date:  2014-02-10

10.  Visual-haptic integration with pliers and tongs: signal "weights" take account of changes in haptic sensitivity caused by different tools.

Authors:  Chie Takahashi; Simon J Watt
Journal:  Front Psychol       Date:  2014-02-14
View more
  1 in total

1.  Trust in haptic assistance: weighting visual and haptic cues based on error history.

Authors:  Tricia L Gibo; Winfred Mugge; David A Abbink
Journal:  Exp Brain Res       Date:  2017-05-22       Impact factor: 1.972

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.