fMRI Repetition Suppression for Familiar But Not Arbitrary Actions with Tools

Valyear, Kenneth F.; Gallivan, Jason P.; McLean, D. Adam; Culham, Jody C.

doi:10.1523/jneurosci.5270-11.2012

Cited by 72 publications

(51 citation statements)

References 75 publications

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“…The subjects in the present study may have recruited the left posterior SMG area to simulate and adjust communicative speech, thereby compensating for their lack of communicative skills in L2. Our interpretation is supported by several previous studies suggesting that the sensorimotor area, including the left posterior SMG, is shaped by past experience and practice (Iacoboni and Dapretto, 2006;Valyear et al, 2012). Compared with L1, which is acquired through socially interactive experiences in the long term, L2 is learned primarily in classroom settings in the short term.…”

Section: L2 Communication-specific Area: the Left Posterior Smgsupporting

confidence: 87%

Neural correlates of second-language communication and the effect of language anxiety

et al. 2015

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Communicative speech is a type of language use that involves goal-directed action targeted at another person based on social interactive knowledge. Previous studies regarding one's first language (L1) have treated the theory of mind system, which is associated with understanding others, and the sensorimotor system, which is associated with action simulation, as important contributors to communication. However, little is known about the neural basis of communication in a second language (L2), which is limited in terms of its use as a communication tool. In this fMRI study, we manipulated the type of speech (i.e., communication vs. description) and the type of language (L1 vs. L2) to identify the specific brain areas involved in L2 communication. We also attempted to examine how the cortical mechanisms underlying L2 speech production are influenced by oral proficiency and anxiety regarding L2. Thirty native Japanese speakers who had learned English as an L2, performed communicative and descriptive speech-production tasks in both L1 and L2 while undergoing fMRI scanning. We found that the only the L2 communication task recruited the left posterior supramarginal gyrus (pSMG), which may be associated with the action simulation or prediction involved in generating goal-directed actions. Furthermore, the neural mechanisms underlying L2 communication, but not L2 description, were sensitive to both oral proficiency and anxiety levels; (a) activation in the left middle temporal gyrus (MTG) increased as oral proficiency levels increased, and (b) activation in the orbitofrontal cortex (OFC), including the left insula, decreased as L2 anxiety levels increased. These results reflect the successful retrieval of lexical information in a pragmatic context and an inability to monitor social behaviors due to anxiety. Taken together, the present results suggest that L2 communication relies on social skills and is mediated by anxiety and oral proficiency.

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Section: L2 Communication-specific Area: the Left Posterior Smgsupporting

confidence: 87%

Neural correlates of second-language communication and the effect of language anxiety

et al. 2015

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“…The parcels are colored to reflect the magnitude of the towers > color contrast from experiment 1. The subset of the MD network most strongly engaged by physical inference resembles the brain regions discussed in the literatures on motor planning (39-43) and tool use (44)(45)(46) [ figure 1 in the work by Gallivan and Culham (40) shows a meta-analysis]. This overlap points to the intriguing possibility of shared functional neuroanatomy for physical scene understanding and action planning.…”

Section: Experiments 1: Physical and Nonphysical Judgments With Visuallymentioning

confidence: 74%

Functional neuroanatomy of intuitive physical inference

Fischer

Mikhael

Tenenbaum

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

150

159

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To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.physical scene understanding | mental simulation | fMRI | premotor cortex | action planning U nderstanding, predicting, and acting on the world requires an intuitive grasp of physics ( Fig. 1). We see not just a table and a coffee cup, but a table supporting a coffee cup. We see not just a ping pong ball moving after contact with a paddle, but the paddle causing the ball to move by exerting a force through that contact. We use physical intuitions to not just understand the world but predict what will happen next-that a stack of dishes is unstable and likely to fall or that a squash ball is on a trajectory to ricochet off the wall and head in our direction. We also need rich physical knowledge to plan our own actions. Before we pick up an object, we must assess its material and weight and prepare our muscles accordingly. To navigate our environment, we need to determine which surfaces will support us (e.g., a linoleum floor but maybe not the surface of a frozen stream; this tree branch but probably not that one) and what barriers are penetrable (e.g., a beaded curtain but not a glass wall). How do we compute these everyday physical inferences with such apparent ease and speed?Battaglia et al.(1) recently proposed a computational mechanism for how humans can make a wide range of physical inferences in natural scenes via a mental simulation engine akin to the "physics engines" used in many video games. Physics engines are software systems that support efficient but approximate simulations of rigid body, soft body, or fluid mechanics for the purpose of generating realistic interactive gameplay in a virtual physical world. Rather than striving for fine-grained physical accuracy, game physics engines make shortcu...

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“…This function is distributed across multiple parietal and frontal regions, where also action-relevant object properties, therefore affordances, are represented (Valyear et al, 2012), which would provide an evolutionary advantage. The regions activated by planned tool use, but not common hand actions, belongs to the anterior IPL group in the SMG (Gallivan et al, 2013) and to the middle temporal gyrus (MTG).…”

Section: The Inferior Parietal Lobulementioning

confidence: 99%