Using Action-congruent Language Facilitates the Motor Response during Action Observation: A Combined Transcranial Magnetic Stimulation and Eye-tracking Study.

There is evidence that action observation (AO) and the processing of action-related words are associated with increased activity in cortical motor regions. Research has examined the effects of AO and action verb processing on activity in the motor system independently. The aim of this experiment was to investigate, for the first time, the modulation of corticospinal excitability and visual attention during the concurrent processing of action verbs and AO stimuli. Twenty participants took part in an integrated transcranial magnetic stimulation and eye-tracking protocol. Single-pulse transcranial magnetic stimulation was delivered to the hand representation of the left motor cortex during (i) observation of a static hand, (ii) AO of a hand squeezing a sponge, (iii) AO of the same action with an audio recording of the word "squeeze," and (iv) AO of the same action with an audio recording of the word "green". Motor evoked potentials were recorded from the abductor pollicis brevis and abductor digiti minimi muscles of the right hand. Eye gaze was recorded throughout the four conditions as a proxy for visual attention. Interviews were conducted to discuss participants' preferences and imagery use for each condition. The AO and action verb condition resulted in significantly increased motor evoked potential amplitudes in the abductor pollicis brevis; participants also made significantly more fixations on the sponge and reported wanting to move their hand. The inclusion of auditory action verbs, alongside AO stimuli, in movement simulation interventions could have implications for the delivery of AO interventions for motor (re)learning

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives