Dataset Information

Object visibility alters the relative contribution of ventral visual stream and mirror neuron system to goal anticipation during action observation.

ABSTRACT: We used fMRI to study the effect of hiding the target of a grasping action on the cerebral activity of an observer whose task was to anticipate the size of the object being grasped. Activity in the putative mirror neuron system (pMNS) was higher when the target was concealed from the view of the observer and anticipating the size of the object being grasped requested paying attention to the hand kinematics. In contrast, activity in ventral visual areas outside the pMNS increased when the target was fully visible, and the performance improved in this condition. A repetition suppression analysis demonstrated that in full view, the size of the object being grasped by the actor was encoded in the ventral visual stream. Dynamic causal modeling showed that monitoring a grasping action increased the coupling between the parietal and ventral premotor nodes of the pMNS. The modulation of the functional connectivity between these nodes was correlated with the subject's capability to detect the size of hidden objects. In full view, synaptic activity increased within the ventral visual stream, and the connectivity with the pMNS was diminished. The re-enactment of observed actions in the pMNS is crucial when interpreting others' actions requires paying attention to the body kinematics. However, when the context permits, visual-spatial information processing may complement pMNS computations for improved action anticipation accuracy.

SUBMITTER: Thioux M

PROVIDER: S-EPMC4968654 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Object visibility alters the relative contribution of ventral visual stream and mirror neuron system to goal anticipation during action observation.

Thioux Marc M Keysers Christian C

NeuroImage 20141025

We used fMRI to study the effect of hiding the target of a grasping action on the cerebral activity of an observer whose task was to anticipate the size of the object being grasped. Activity in the putative mirror neuron system (pMNS) was higher when the target was concealed from the view of the observer and anticipating the size of the object being grasped requested paying attention to the hand kinematics. In contrast, activity in ventral visual areas outside the pMNS increased when the target ...[more]

PMID: 25462688

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Project description:The computational role of the abundant feedback connections in the ventral visual stream is unclear, enabling humans and nonhuman primates to effortlessly recognize objects across a multitude of viewing conditions. Prior studies have augmented feedforward convolutional neural networks (CNNs) with recurrent connections to study their role in visual processing; however, often these recurrent networks are optimized directly on neural data or the comparative metrics used are undefined for standard feedforward networks that lack these connections. In this work, we develop task-optimized convolutional recurrent (ConvRNN) network models that more correctly mimic the timing and gross neuroanatomy of the ventral pathway. Properly chosen intermediate-depth ConvRNN circuit architectures, which incorporate mechanisms of feedforward bypassing and recurrent gating, can achieve high performance on a core recognition task, comparable to that of much deeper feedforward networks. We then develop methods that allow us to compare both CNNs and ConvRNNs to finely grained measurements of primate categorization behavior and neural response trajectories across thousands of stimuli. We find that high-performing ConvRNNs provide a better match to these data than feedforward networks of any depth, predicting the precise timings at which each stimulus is behaviorally decoded from neural activation patterns. Moreover, these ConvRNN circuits consistently produce quantitatively accurate predictions of neural dynamics from V4 and IT across the entire stimulus presentation. In fact, we find that the highest-performing ConvRNNs, which best match neural and behavioral data, also achieve a strong Pareto trade-off between task performance and overall network size. Taken together, our results suggest the functional purpose of recurrence in the ventral pathway is to fit a high-performing network in cortex, attaining computational power through temporal rather than spatial complexity.

Dataset Information

Object visibility alters the relative contribution of ventral visual stream and mirror neuron system to goal anticipation during action observation.

Publications

Object visibility alters the relative contribution of ventral visual stream and mirror neuron system to goal anticipation during action observation.

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