Examining cross-modal fMRI adaptation for observed and executed actions in the monkey brain

No Evidence for Cross-Modal fMRI Adaptation in Macaque Parieto-Premotor Mirror Neuron Regions

To probe the presence of mirror neurons in the human brain, cross-modal fMRI adaptation has been suggested as a suitable technique. The rationale behind this suggestion is that this technique allows making more accurate inferences about neural response properties underlying fMRI voxel activations, beyond merely showing shared voxels that are active during both action observation and execution. However, the validity of using cross-modal fMRI adaptation to demonstrate the presence of mirror neurons in parietal and premotor brain regions has been questioned given the inconsistent and weak results obtained in human studies. A better understanding of cross-modal fMRI adaptation effects in the macaque brain is required as the rationale for using this approach is based on several assumptions related to macaque mirror neuron response properties that still need validation. Here, we conducted a cross-modal fMRI adaptation study in macaque monkeys, using the same action execution and action observation tasks that successfully yielded mirror neuron region cross-modal action decoding in a previous monkey MVPA study. We scanned two male rhesus monkeys while they first executed a sequence of either reach-and-grasp or reach-and-touch hand actions and then observed a video of a human actor performing these motor acts. Both whole-brain and region-of-interest analyses failed to demonstrate cross-modal fMRI adaptation effects in parietal and premotor mirror neuron regions. Our results, in line with previous findings in non-human primates, show that cross-modal motor-to-visual fMRI adaptation is not easily detected in monkey brain regions known to house mirror neurons. Thus, our results advocate caution in using cross-modal fMRI adaptation as a method to infer whether mirror neurons can be found in the primate brain.

Categorization learning induced changes in action representations in the macaque STS

Neuroimaging and single cell recordings have demonstrated the presence of STS body category-selective regions (body patches) containing neurons responding to presentation of static bodies and body parts. To date, it remains unclear if these body patches and additional STS regions respond during observation of different categories of dynamic actions and to what extent categorization learning influences representations of observed actions in the STS. In the present study, we trained monkeys to discriminate videos depicting three different actions categories (grasping, touching and reaching) with a forced-choice action categorization task. Before and after categorization training, we performed fMRI recordings while monkeys passively observed the same action videos. At the behavioral level, after categorization training, monkeys generalized to untrained action exemplars, in particular for grasping actions. Before training, uni- and/or multivariate fMRI analyses suggest a broad representation of dynamic action categories in particular in posterior and middle STS. Univariate analysis further suggested action category specific training effects in middle and anterior body patches, face patch ML and posterior STS region MT and FST. Overall, our fMRI experiments suggest a widespread representation of observed dynamic bodily actions in the STS that can be modulated by visual learning, supporting its proposed role in action recognition.

Two-monkey fMRI setup for investigating multifaceted aspects of social cognition and behavior involving a real-live conspecific

While brain research over the past decades has shed light on the neural correlates of social cognition and behavior in human and non-human primates, most of this research has been performed in virtual settings requiring subjects to observe pictures or recorded videos instead of observing or interacting with another real-live individual. Here we present a two-monkey fMRI setup, allowing examining whole brain responses in macaque monkeys while they observe or interact face-to-face with another real-live conspecific. We tested this setup by comparing overall brain responses during observation of conspecific hand actions in a virtual (observation of recorded videos of actions) or live context (observation of a real-live conspecific performing actions). This dyadic monkey fMRI setup allows examining brain-wide responses in macaque monkeys during different aspects of social behavior, including observation of real-live actions and sensations, social facilitation, joint-attention and social interactions.

Model-based dynamic off-resonance correction for improved accelerated fMRI in awake behaving nonhuman primates

Purpose

To estimate dynamic off‐resonance due to vigorous body motion in accelerated fMRI of awake behaving nonhuman primates (NHPs) using the echo‐planar imaging reference navigator, in order to attenuate the effects of time‐varying off‐resonance on the reconstruction.

Methods

In NHP fMRI, the animal’s head is usually head‐posted, and the dynamic off‐resonance is mainly caused by motion in body parts that are distant from the brain and have low spatial frequency. Hence, off‐resonance at each frame can be approximated as a spatially linear perturbation of the off‐resonance at a reference frame, and is manifested as a relative linear shift in k‐space. Using GRAPPA operators, we estimated these shifts by comparing the navigator at each time frame with that at the reference frame. Estimated shifts were then used to correct the data at each frame. The proposed method was evaluated in phantom scans, simulations, and in vivo data.

Results

The proposed method is shown to successfully estimate spatially low‐order dynamic off‐resonance perturbations, including induced linear off‐resonance perturbations in phantoms, and is able to correct retrospectively corrupted data in simulations. Finally, it is shown to reduce ghosting artifacts and geometric distortions by up to 20% in simultaneous multislice in vivo acquisitions in awake‐behaving NHPs.

Conclusion

A method is proposed that does not need sequence modification or extra acquisitions and makes accelerated awake behaving NHP imaging more robust and reliable, reducing the gap between what is possible with NHP protocols and state‐of‐the‐art human imaging.