TY - JOUR
T1 - Model predictions of features in microsaccade-related neural responses in a feedforward network with short-term synaptic depression
AU - Zhou, Jian Fang
AU - Yuan, Wu Jie
AU - Zhou, Zhao
AU - ZHOU, Changsong
N1 - Funding Information:
This work is partially supported by Hong Kong Baptist University (HKBU) Strategic Development Fund, NSFC-RGC Joint Research Scheme HKUST/NSFC/12-13/01 (or N_HKUST 606/12), HKRGC GRF12302914, National Natural Science Foundation of China under Grant Nos. 11275027, 11005047 and 11505075, Natural Science Foundation of Anhui Province under Grant No. 1508085MA04, Great Project of Natural Science in Anhui Provincial Colleges and Universities under Grant No. KJ2015ZD33, Major Project of Outstanding Young Talent Support Program in Anhui Provincial Colleges and Universities under Grant No. gxyqZD2016410, Young Fund of Huaibei Normal University under Grant No. 2013xqz17, and Scientific and Technological Activity Foundations for Preferred Overseas Chinese Scholar in Ministry of Human Resources and Social Security of China and in Department of Human Resources and Social Security of Anhui Province.
PY - 2016/2/8
Y1 - 2016/2/8
N2 - Recently, the significant microsaccade-induced neural responses have been extensively observed in experiments. To explore the underlying mechanisms of the observed neural responses, a feedforward network model with short-term synaptic depression has been proposed [Yuan, W.-J., Dimigen, O., Sommer, W. and Zhou, C. Front. Comput. Neurosci. 7, 47 (2013)]. The depression model not only gave an explanation for microsaccades in counteracting visual fading, but also successfully reproduced several microsaccade-related features in experimental findings. These results strongly suggest that, the depression model is very useful to investigate microsaccade-related neural responses. In this paper, by using the model, we extensively study and predict the dependance of microsaccade-related neural responses on several key parameters, which could be tuned in experiments. Particularly, we provide a significant prediction that microsaccade-related neural response also complies with the property â œ sharper is betterâ observed in many contexts in neuroscience. Importantly, the property exhibits a power-law relationship between the width of input signal and the responsive effectiveness, which is robust against many parameters in the model. By using mean field theory, we analytically investigate the robust power-law property. Our predictions would give theoretical guidance for further experimental investigations of the functional role of microsaccades in visual information processing.
AB - Recently, the significant microsaccade-induced neural responses have been extensively observed in experiments. To explore the underlying mechanisms of the observed neural responses, a feedforward network model with short-term synaptic depression has been proposed [Yuan, W.-J., Dimigen, O., Sommer, W. and Zhou, C. Front. Comput. Neurosci. 7, 47 (2013)]. The depression model not only gave an explanation for microsaccades in counteracting visual fading, but also successfully reproduced several microsaccade-related features in experimental findings. These results strongly suggest that, the depression model is very useful to investigate microsaccade-related neural responses. In this paper, by using the model, we extensively study and predict the dependance of microsaccade-related neural responses on several key parameters, which could be tuned in experiments. Particularly, we provide a significant prediction that microsaccade-related neural response also complies with the property â œ sharper is betterâ observed in many contexts in neuroscience. Importantly, the property exhibits a power-law relationship between the width of input signal and the responsive effectiveness, which is robust against many parameters in the model. By using mean field theory, we analytically investigate the robust power-law property. Our predictions would give theoretical guidance for further experimental investigations of the functional role of microsaccades in visual information processing.
UR - http://www.scopus.com/inward/record.url?scp=84957604389&partnerID=8YFLogxK
U2 - 10.1038/srep20888
DO - 10.1038/srep20888
M3 - Journal article
C2 - 26853547
AN - SCOPUS:84957604389
SN - 2045-2322
VL - 6
JO - Scientific Reports
JF - Scientific Reports
M1 - 20888
ER -