Action Observation Network Research Journals

Question: Discuss about theAction Observation Networkfor Research Journals. Answer: Introduction This essay aims to elucidate a clear idea regarding the Action-observation Network in humans and review three research journals that deal with AON and the several factors influencing it. The action observation network has been widely studied in humans as well as animal models and it refers to the neural network of the brain associated with perception and prediction of human and non-human movements. This network remains active while perceiving actions and movements of others and also while recalling that information to predict performed actions and movements in the future. This network has implications in performing simple daily life tasks such as giving a high five to someone to or holding a door open for someone. On the contrary it participates in complex tasks such as socialization (Oberman, Pineda Ramachandran, 2007) or prediction skills required while driving a car or movements not possible for a person to execute or to those they are not familiar with (Ertelt et al., 2007). Bot h visual and motor cues are used to understand actions, however more brain activity has been found for actions that the person has frequently performed him/herself (Calvo-Merino et al., 2006). The brain regions that are associated with this bilateral neural pathway are premotor, parietal and temporo-occipetal cortex (Caspers et al., 2010) and the cerebellum (Sokolov et al., 2009). Cross et al. (2013) in their study aim to determine the influence of visual cues on action observation network for certain actions that the subjects are unable to perform on their own physically. They observed and compared behavioral performance and neural activity of the concerned brain regions while perceiving as well predicting visually trained and untrained actions. The sensorimotor regions of the brain are benefited both from observational and physical experiences. However, the present study was focused to evaluate the influence of visual training solely on perception and prediction of the actions of complex gymnastic sequences (biological action) and wind-up toy sequences (non-biological action). For the purpose of the study 24 participants were selected based on certain selection criteria such as participants had no neurological or psychological issues and not under any kind of medication during the experiments. A 4-days behavioral training and two functional neuroimaging scans were performed. Initially, 32 videos were shown, which acted as stimuli, 16 of them were of a biological action of three female gymnasts performing complex sequences, and the other three videos contained a non-biological action featuring wind-up toys with autonomous motions. First both were presented on a neutral background for perception of the movements and then by video editing occlusions were constructed for the participants to predict when the stimuli reappear. Neuroimages were produced for all the participants to reveal which parts of the brain remains active during perception and prediction before and after the training. Results reveal that inferior parietal, superior temporal and cerebellar cortices were more active during prediction compared to perception. Greater activity of the occipitotemporal cortices were found in untrained participants and further the occipitotemporal activity was more specialized for human movements compared to non-biological movement. The results reveal that selected portions of the AON were activated while predicting complex motions and movements and for unfamiliar movements more regions of the AON are recruited. The purpose of the study conducted by Cross et al. (2012) is to compare how the AON regions of the brain respond to human-like motion and that to robot-like motion. They used neuroimaging techniques to observe the activity of premotor, parietal and occipital regions while responding to the stimuli. They conducted two experiment, of which the first one had 22 right-handed participats and the second one 23 right-handed participants. They were selected based on absence of any neurological or psychological disorders or any medication. 36 free videos of professional break-dancers who were asked to dance wither freestyle or in a robot like fashion were used in the first experiment. In half the videos the dancer wore masks and in the other half they did not. In the second experiment, 16 of the previous videos, 8 in which the dancer dancing in a robotic manner without the mask and 16 videos prepared from software with actual robot like figures, were used. The results show the response of the AON regions were stronger for robot like motion compared to human like motion in experiment 1, and no impact of facial stimuli was observed. In the second experiment the same pattern of response was observed. The study results clearly prove that the AON is preferentially active in response to robot like compared to human like motions. It further signifies that the AON responds more robustly to unfamiliar action figure motion compared to familiar ones. The study by Gardner, Goulden Croos (2015), aims to better predict the relationship between movement familiarity and AON activity using dynamic models. Previous studies suggests than the AON is more active for familiar movements compared to unfamiliar movements. 21 adult volunteers were selected of which 17 were right-handed, 2 left-handed and the rest ambidextrous. A video of dancers performing choreographed movements that ranged from simple and predictable to complex and much less predictable steps was used as stimuli. A prediction task was designed were the participants had to choose from two still frame the following movement after 0.6s of occlusion. An attention control task was designed in which participants were shown dots (5mm) randomly appearing dots at an interval of 1s, and were asked to specify the color of the last do it after the end of the clip. The participants underwent a fMRI scan during the viewing of the movements. The familiarity of individuals to the videos was obtained by the participants rating them. The results reveal more activity in left middle temporal gyrus, inferior parietal lobule, and inferior frontal gyrus for videos with more familiarity. It further showed decrease in bidirectional activity between the parietal and temporal nodes. From the study results it can be concluded that AON activity is higher when moments were found to be more familiar to the participants. However the neural connectivity between the inferior parietal lobe and the middle temporal gyrus were decreases in case of more familiar movements which decreases prediction error. References Calvo-Merino, B., Grzes, J., Glaser, D. E., Passingham, R. E., Haggard, P. (2006). Seeing or doing? Influence of visual and motor familiarity in action observation.Current Biology,16(19), 1905-1910. Caspers, S., Zilles, K., Laird, A. R., Eickhoff, S. B. (2010). ALE meta-analysis of action observation and imitation in the human brain.Neuroimage,50(3), 1148-1167. Cross, E. S., Liepelt, R., de C, H., Antonia, F., Parkinson, J., Ramsey, R., ... Prinz, W. (2012). Robotic movement preferentially engages the action observation network.Human brain mapping,33(9), 2238-2254. Cross, E. S., Stadler, W., Parkinson, J., Schtz?Bosbach, S., Prinz, W. (2013). The influence of visual training on predicting complex action sequences.Human brain mapping,34(2), 467-486. Ertelt, D., Small, S., Solodkin, A., Dettmers, C., McNamara, A., Binkofski, F., Buccino, G. (2007). Action observation has a positive impact on rehabilitation of motor deficits after stroke.Neuroimage,36, T164-T173. Gardner, T., Goulden, N., Cross, E. S. (2015). Dynamic modulation of the action observation network by movement familiarity.The Journal of Neuroscience,35(4), 1561-1572. Oberman, L. M., Pineda, J. A., Ramachandran, V. S. (2007). The human mirror neuron system: a link between action observation and social skills.Social cognitive and affective neuroscience,2(1), 62-66. Sokolov, A. A., Gharabaghi, A., Tatagiba, M. S., Pavlova, M. (2009). Cerebellar engagement in an action observation network.Cerebral cortex, bhp117.