Browsing by Subject "Biological motion"

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Open Access
Biological motion perception in the theoretical framework of perceptual decision-making: an event-related potential study
(Elsevier Ltd, 2024-05) Oğuz, Osman Çağrı; Aydın, Berfin; Ürgen, Burcu Ayşen
Biological motion perception plays a critical role in various decisions in daily life. Failure to decide accordingly in such a perceptual task could have life-threatening consequences. Neurophysiology and computational modeling studies suggest two processes mediating perceptual decision-making. One of these signals is associated with the accumulation of sensory evidence and the other with response selection. Recent EEG studies with humans have introduced an event-related potential called Centroparietal Positive Potential (CPP) as a neural marker aligned with the sensory evidence accumulation while effectively distinguishing it from motor-related lateralized readiness potential (LRP). The present study aims to investigate the neural mechanisms of biological motion perception in the framework of perceptual decision-making, which has been overlooked before. More specifically, we examine whether CPP would track the coherence of the biological motion stimuli and could be distinguished from the LRP signal. We recorded EEG from human participants while they performed a direction discrimination task of a point-light walker stimulus embedded in various levels of noise. Our behavioral findings revealed shorter reaction times and reduced miss rates as the coherence of the stimuli increased. In addition, CPP tracked the coherence of the biological motion stimuli with a tendency to reach a common level during the response, albeit with a later onset than the previously reported results in random-dot motion paradigms. Furthermore, CPP was distinguished from the LRP signal based on its temporal profile. Overall, our results suggest that the mechanisms underlying perceptual decision-making generalize to more complex and socially significant stimuli like biological motion.
Open Access
Effective connectivity in cortical regions during bottom-up perception of biological motion under attentional load: an FMRI-DCM study
(2024-07) Mert, Sezan
The ability to detect biological motion holds an evolutionarily important role in vital and social functions. However, in our daily lives, we perceive biological motion while we are at a task most of the time. In other words, it is perceived when our attention is directed at another thing. In this aspect, understanding the dynamics of its bottom-up perception is of high importance. Meanwhile, the attentional mechanisms and where their effects occur are a matter of debate in the literature, sparking off various theories, such as early selection, late selection, and attentional load theory. Dynamic causal modeling (DCM) is a suitable tool for investigating the dynamics of attentional effects on the network, enabling the bottom-up perception of biological motion, and comparing the existing theories in the literature with Bayesian graph models. To this end, we utilized the DCM approach with fMRI data collected using an attentional load paradigm and biological motion peripheral distractors [1]. In our model space, we modeled the theories of selective attention along with two complementary models. The Bayesian Model Selection (BMS) showed that the model that explained the data the best was the model where both attentional load conditions modulated all top-down connections rather than the models of existing theories. This showed that attentional effects take part in the bottom-up perception, not in a focused location, such as early or late, but in a more distributed manner throughout the processing pipeline. Further statistical tests on the model parameters yielded no difference between load conditions and between biological motion and scrambled motion in their modulation strengths. Yet, the strengths of biological motion on different connections were different from each other. A similar observation is also made for the low load condition but not for the scrambled motion and high load conditions. The former can be accepted as evidence for the differential processing of biological and scrambled motion. The latter may be explained by a spillover of perceptual resources on biological motion and causing competition in low-load conditions.
Open Access
Neural processing of bottom-up perception of biological motion under attentional load
(Elsevier, 2023-11-04) Nizamoğlu, Hilal; Ürgen, Burcu Ayşen
Considering its importance for one’s survival and social significance, biological motion (BM) perception is assumed to occur automatically. Previous behavioral results showed that task-irrelevant BM in the periphery interfered with task performance at the fovea. Under selective attention, BM perception is supported by a network of regions including the occipito-temporal (OTC), parietal, and premotor cortices. Retinotopy studies that use BM stimulus showed distinct maps for its processing under and away from selective attention. Based on these findings, we investigated how bottom-up perception of BM would be processed in the human brain under attentional load when it was shown away from the focus of attention as a task-irrelevant stimulus. Participants (N = 31) underwent an fMRI study in which they performed an attentionally demanding visual detection task at the fovea while intact or scrambled point light displays of BM were shown at the periphery. Our results showed the main effect of attentional load in fronto-parietal regions and both univariate activity maps and multivariate pattern analysis results support the attentional load modulation on the task-irrelevant peripheral stimuli. However, this effect was not specific to intact BM stimuli and was generalized to motion stimuli as evidenced by the motion-sensitive OTC involvement during the presence of dynamic stimuli in the periphery. These results confirm and extend previous work by showing that task-irrelevant distractors can be processed by stimulus-specific regions when there are enough attentional resources available. We discussed the implications of these results for future studies.
Open Access
Neural underpinnings of biological motion perception under attentional load
(2022-06) Çalışkan, Hilal Nizamoğlu
Humans can detect and differentiate biological motion from non-biological motion stimuli effortlessly, even if the stimuli were shown as simplistic as a composition of moving dots (i.e. point-light displays [PLD]). Considering its survival and social significance, BM perception is assumed to occur automatically. Indeed, Thorn-ton and Vuong [1] showed that task-irrelevant BM in the periphery interfered with task performance at the fovea. However, the neural underpinnings of this bottom-up processing of BM lacks thorough examination in the field. Under selec-tive attention, BM perception is supported by a network of regions including the occipito-temporal, parietal, and premotor cortices. A retinotopy mapping study on BM showed distinct maps for its processing under and away from selective attention [2]. Based on these findings, we investigated how bottom-up percep-tion of BM would be processed under attentional load when it was shown away from the focus of attention as a task-irrelevant stimulus. Participants (N=31) underwent an fMRI study in which they performed an attentionally demand-ing visual detection task at the fovea while intact or scrambled PLDs of BM were shown at the periphery. Our results showed the main effect of attentional load in fronto-parietal regions; as well as, the main effect of peripheral stimuli in occipito-temporal cortex. Both univariate and multivariate pattern analysis results support the attentional load modulation on BM. Lastly, ROI results on each core node of BM processing network expanded these findings by showing that the attentional load modulation on both intact and scrambled BM stimuli were the strongest in bilateral occipito-temporal regions as compared to parietal and premotor cortices. In conclusion, BM was processed within the motion sensi-tive regions in the occipito-temporal cortex when shown away from the selective attention, and was modulated by attentional load.
Open Access
Predictive processing in the cortical network of biological motion perception
(2024-07) Tunca, Murat Batu
The literature on biological motion processing argues that it occurs in occipitotemporal, parietal and frontal regions of the brain. Nevertheless, the literature is currently unable to explain how this processing is affected by expectations. Although models exist to explain how biological motion is perceived, they usually ignore top-down processes. To this end, the current fMRI study presented two point-light displays (embedded in noise) on either side of the screen to the participants (N=29). One of the displays was a biological motion (walking or kicking) whereas the other one was its scrambled version. The participants were asked to report the location of the biological motion. Importantly, before the presentation of motions, the participants were shown a cue about the action type (walking or kicking) which was congruent with the motion 75% of the time. There were also two additional conditions in which the cue was uninformative about the action (neutral condition) or there were no motion stimuli at all. As expected, the action observation network (consisting of pSTS, parietal cortex and IFG) showed a clear and strong activation during the conditions that a motion was present. However, these regions have failed to significantly discriminate between congruent and incongruent conditions. It should be acknowledged that this lack of significant result might be caused by the low number of trials. In order to better investigate the connections within action observation network, a DCM analysis was conducted. The winning DCM model has successfully shown the presence of feedback connections in the biological motion processing. More specifically, the model argues that both feedforward and feedback modulatory connections are present during congruent, incongruent and neutral conditions. In sum, the study highlights the importance of incorporating top-down signals such as expectations in the computational models of biological motion perception.