請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7349完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 葉俊毅(Chun-I Yeh) | |
| dc.contributor.author | Chin-Yi Ji | en |
| dc.contributor.author | 紀欽益 | zh_TW |
| dc.date.accessioned | 2021-05-19T17:41:55Z | - |
| dc.date.available | 2021-07-02 | |
| dc.date.available | 2021-05-19T17:41:55Z | - |
| dc.date.copyright | 2019-07-02 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-06-14 | |
| dc.identifier.citation | References
Adesnik, H., & Scanziani, M. (2010). Lateral competition for cortical space by layer-specific horizontal circuits. Nature, 464, 1155. Ahissar, E., Sosnik, R., Bagdasarian, K., & Haidarliu, S. (2001). Temporal frequency of whisker movement. II. Laminar organization of cortical representations. Journal of Neurophysiology, 86, 354-367. Barth, A. L., & Poulet, J. F. (2012). Experimental evidence for sparse firing in the neocortex. Trends in Neurosciences, 35, 345-355. Boloori, A. R., & Stanley, G. B. (2006). The dynamics of spatiotemporal response integration in the somatosensory cortex of the vibrissa system. Journal of Neuroscience, 26, 3767-3782. Brecht, M. (2007). Barrel cortex and whisker-mediated behaviors. Current Opinion in Neurobiology, 17, 408-416. Brecht, M., & Sakmann, B. (2002). Dynamic representation of whisker deflection by synaptic potentials in spiny stellate and pyramidal cells in the barrels and septa of layer 4 rat somatosensory cortex. The Journal of Physiology, 543, 49-70. Brumberg, J. C., Pinto, D. J., & Simons, D. J. (1996). Spatial gradients and inhibitory summation in the rat whisker barrel system. Journal of Neurophysiology, 76, 130-140. Carvell, G. E., & Simons, D. J. (1988). Membrane potential changes in rat SmI cortical neurons evoked by controlled stimulation of mystacial vibrissae. Brain Research, 448, 186-191. Chander, D., & Chichilnisky, E. J. (2001). Adaptation to temporal contrast in primate and salamander retina. Journal of Neuroscience, 21, 9904-9916. Chichilnisky, E. J. (2001). A simple white noise analysis of neuronal light responses. Network: Computation in Neural Systems, 12, 199-213. DeAngelis, G. C., Ohzawa, I., & Freeman, R. D. (1993). Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. I. General characteristics and postnatal development. Journal of Neurophysiology, 69, 1091-1117. De Kock, C. P. J., Bruno, R. M., Spors, H., & Sakmann, B. (2007). Layer‐and cell‐type‐specific suprathreshold stimulus representation in rat primary somatosensory cortex. The Journal of Physiology, 581, 139-154. DiCarlo, J. J., Johnson, K. O., & Hsiao, S. S. (1998). Structure of receptive fields in area 3b of primary somatosensory cortex in the alert monkey. Journal of Neuroscience, 18, 2626-2645. DiCarlo, J. J., & Johnson, K. O. (2000). Spatial and temporal structure of receptive fields in primate somatosensory area 3b: Effects of stimulus scanning direction and orientation. Journal of Neuroscience, 20, 495-510. Diamond, M. E. (1995). Somatosensory thalamus of the rat. The Barrel Cortex of Rodents (pp. 189-219). Boston, MA: Springer. Ego-Stengel, V., Mello E Souza, T., Jacob, V., & Shulz, D. E. (2005). Spatiotemporal characteristics of neuronal sensory integration in the barrel cortex of the rat. Journal of Neurophysiology, 93, 1450-1467. Estebanez, L., El Boustani, S., Destexhe, A., & Shulz, D. E. (2012). Correlated input reveals coexisting coding schemes in a sensory cortex. Nature Neuroscience, 15, 1691. Fisher, N. I. (1995). Statistical analysis of circular data. Location: Cambridge University Press. Feldmeyer, D., Egger, V., Lübke, J., & Sakmann, B. (1999). Reliable synaptic connections between pairs of excitatory layer 4 neurons within a single ‘barrel’ of developing rat somatosensory cortex. The Journal of Physiology, 521, 169-190. Feldmeyer, D., Lübke, J., Silver, R. A., & Sakmann, B. (2002). Synaptic connections between layer 4 spiny neuron‐layer 2/3 pyramidal cell pairs in juvenile rat barrel cortex: physiology and anatomy of interlaminar signalling within a cortical column. The Journal of Physiology, 538, 803-822. Feldmeyer, D., Brecht, M., Helmchen, F., Petersen, C. C., Poulet, J. F., Staiger, J. F., & Schwarz, C. (2013). Barrel cortex function. Progress in Neurobiology, 103, 3-27. Higley, M.J. & Contreras, D. (2003). Nonlinear integration of sensory responses in the rat barrel cortex: An intracellular study in vivo. Journal of Neuroscience,23, 10190–10200. Jacob, V., Le Cam, J., Ego-Stengel, V., & Shulz, D. E. (2008). Emergent properties of tactile scenes selectively activate barrel cortex neurons. Neuron, 60, 1112-1125. Jacobson, L. D., Gaska, J. P., Hai-Wen, C., & Pollen, D. A. (1993). Structural testing of multi-input linear—nonlinear cascade models for cells in macaque striate cortex. Vision Research, 33, 609-626. Katz, Y., Heiss, J. E., & Lampl, I. (2006). Cross-whisker adaptation of neurons in the rat barrel cortex. Journal of Neuroscience, 26, 13363-13372. Kerr, J. N., De Kock, C. P., Greenberg, D. S., Bruno, R. M., Sakmann, B., & Helmchen, F. (2007). Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. Journal of Neuroscience, 27, 13316-13328. Kida, H., Shimegi, S., & Sato, H. (2005). Similarity of direction tuning among responses to stimulation of different whiskers in neurons of rat barrel cortex. Journal of Neurophysiology, 94, 2004-2018. Kim, K. J., & Rieke, F. (2001). Temporal contrast adaptation in the input and output signals of salamander retinal ganglion cells. Journal of Neuroscience, 21, 287-299. Land, P. W., & Simons, D. J. (1985). Cytochrome oxidase staining in the rat SmI barrel cortex. Journal of Comparative Neurology, 238, 225-235. Lee, S. H., & Simons, D. J. (2004). Angular tuning and velocity sensitivity in different neuron classes within layer 4 of rat barrel cortex. Journal of Neurophysiology, 91, 223-229. Lu, S. M., & Lin, R. C. S. (1993). Thalamic afferents of the rat barrel cortex: A light-and electron-microscopic study using Phaseolus vulgaris leucoagglutinin as an anterograde tracer. Somatosensory & Motor Research, 10, 1-16. Markram, H., Lübke, J., Frotscher, M., Roth, A., & Sakmann, B. (1997). Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. The Journal of Physiology, 500, 409-440. Matyas, F., Sreenivasan, V., Marbach, F., Wacongne, C., Barsy, B., Mateo, C., & Petersen, C. C. (2010). Motor control by sensory cortex. Science, 330, 1240-1243. Melzer, P., Sachdev, R. N., Jenkinson, N., & Ebner, F. F. (2006). Stimulus frequency processing in awake rat barrel cortex. Journal of Neuroscience, 26, 12198-12205. O'Connor, D. H., Peron, S. P., Huber, D., & Svoboda, K. (2010). Neural activity in barrel cortex underlying vibrissa-based object localization in mice. Neuron, 67, 1048-1061. Ohno, S., Kuramoto, E., Furuta, T., Hioki, H., Tanaka, Y. R., Fujiyama, F., & Kaneko, T. (2011). A morphological analysis of thalamocortical axon fibers of rat posterior thalamic nuclei: A single neuron tracing study with viral vectors. Cerebral Cortex, 22, 2840-2857. Ozuysal, Y., & Baccus, S. A. (2012). Linking the computational structure of variance adaptation to biophysical mechanisms. Neuron, 73, 1002-1015. Petersen, C. C., & Sakmann, B. (2000). The excitatory neuronal network of rat layer 4 barrel cortex. Journal of Neuroscience, 20, 7579-7586. Pillow, J. W., Paninski, L., Uzzell, V. J., Simoncelli, E. P., & Chichilnisky, E. J. (2005). Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model. Journal of Neuroscience, 25, 11003-11013. Pillow, J., & Latham, P. (2008). Neural characterization in partially observed populations of spiking neurons. Advances in Neural Information Processing Systems, 20, 1161–1168. Ramirez, A., Pnevmatikakis, E. A., Merel, J., Paninski, L., Miller, K. D., & Bruno, R. M. (2014). Spatiotemporal receptive fields of barrel cortex revealed by reverse correlation of synaptic input. Nature Neuroscience, 17, 866. Sachdev, R. N., Krause, M. R., & Mazer, J. A. (2012). Surround suppression and sparse coding in visual and barrel cortices. Frontiers in Neural Circuits, 6, 43. Shimegi, S., Ichikawa, T., Akasaki, T., & Sato, H. (1999). Temporal characteristics of response integration evoked by multiple whisker stimulations in the barrel cortex of rats. Journal of Neuroscience, 19, 10164-10175. Simons, D. J. (1978). Response properties of vibrissa units in rat SI somatosensory neocortex. Journal of Neurophysiology, 41, 798-820. Simons, D. J. (1985). Temporal and spatial integration in the rat SI vibrissa cortex. Journal of Neurophysiology, 54, 615-635. Simons, D. J., & Carvell, G. E. (1989). Thalamocortical response transformation in the rat vibrissa/barrel system. Journal of Neurophysiology, 61, 311-330. Sosnik, R., Haidarliu, S., & Ahissar, E. (2001). Temporal frequency of whisker movement. I. Representations in brain stem and thalamus. Journal of Neurophysiology, 86, 339-353. Sripati, A. P., Yoshioka, T., Denchev, P., Hsiao, S. S., & Johnson, K. O. (2006). Spatiotemporal receptive fields of peripheral afferents and cortical area 3b and 1 neurons in the primate somatosensory system. Journal of Neuroscience, 26, 2101-2114. Thakur, P. H., Fitzgerald, P. J., & Hsiao, S. S. (2012). Second-order receptive fields reveal multidigit interactions in area 3b of the macaque monkey. Journal of Neurophysiology, 108, 243. Van Steveninck, R. D. R., & Bialek, W. (1988). Real-time performance of a movement-sensitive neuron in the blowfly visual system: coding and information transfer in short spike sequences. Proceedings of the Royal Society of London. Series B, Biological Sciences, 379-414. Veinante, P., Lavallée, P., & Deschênes, M. (2000). Corticothalamic projections from layer 5 of the vibrissal barrel cortex in the rat. Journal of Comparative Neurology, 424, 197-204. Welker, C. (1976). Receptive fields of barrels in the somatosensory neocortex of the rat. Journal of Comparative Neurology, 166, 173-189. Wilent, W. B., & Contreras, D. (2004). Synaptic responses to whisker deflections in rat barrel cortex as a function of cortical layer and stimulus intensity. Journal of Neuroscience, 24, 3985-3998. Wimmer, V. C., Bruno, R. M., De Kock, C. P., Kuner, T., & Sakmann, B. (2010). Dimensions of a projection column and architecture of VPM and POm axons in rat vibrissal cortex. Cerebral Cortex, 20, 2265-2276. Woolsey, T. A., & Van der Loos, H. (1970). The structural organization of layer IV in the somatosensory region (SI) of mouse cerebral cortex: The description of a cortical field composed of discrete cytoarchitectonic units. Brain Research, 17, 205-242. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7349 | - |
| dc.description.abstract | 大鼠桶狀皮質離散的表徵特性,使其成為研究感覺訊息處理及其大腦迴路的重要動物模型。桶狀皮質中的神經會對於一根鬍鬚的刺激有最強的反應,這根鬍鬚就稱為此神經的主要鬍鬚(principle whisker, PW),然而其反應也會受到其他周圍鬍鬚(surround whiskers, SWs)的調節(抑制或促進)。過去對於此周圍調節作用(surround modulation)的研究主要著重在主要鬍鬚和單根周圍鬍鬚,這與大鼠探索環境時同時使用多根鬍鬚的運動有所不同。本研究使用三種不同的多根鬍鬚刺激型態去探索周圍調節作用,分別是隨機單根刺激、多鬍鬚同方向刺激,以及多鬍鬚隨機方向刺激。我們試著去回答下列問題:第一、在不同刺激形態下,周圍鬍鬚調節效果如何影響神經反應強度與方向調性。第二、神經反應強度與方向調性是否在不同皮層間有所區別。第三、線性─非線性模型能夠解釋桶狀皮質神經反應的程度。我們發現在記錄到的神經中有近一半的神經有明顯調節效果。多根鬍鬚刺激相較於隨機單根刺激有較低的神經反應以及較強的方向調性(direction selectivity)。我們也發現有顯著側抑制的神經數量為顯著側促進的效果的三倍,顯示側抑制主導桶狀皮質區。在兩種多根鬍鬚刺激中,只有在桶狀皮質的粒上皮層(表層)發現所謂的「情境效果」- 多鬍鬚同方向刺激中神經放電頻率顯著的低於多鬍鬚隨機方向刺激,這個現象可能肇因於同層神經的側向連結。相反的,在前饋輸入主導的顆粒層和粒下皮層都沒有發現情境效果。此外,相較於多根鬍鬚刺激下的桶狀皮質區神經反應,線性─非線性模型在隨機單根刺激下有較好的模擬和描述。總體來說,我們的結果顯示在大鼠桶狀皮質區側抑制是主要的反應偏好,特別是對於桶狀皮質區粒上皮層(訊號輸出)的神經元,其功能主要在整合來自顆粒層(序號輸入)的神經訊號。相反的,顆粒層的神經受到周圍刺激的影響較小(受視丘訊號主導),其功能主要在偵測外在刺激特徵(方向調性,Brecht, 2007). | zh_TW |
| dc.description.abstract | The discrete architecture modules of the rat barrel cortex are an important animal model in studying cortical coding of sensory information and its circuitry. Neurons within the same barrel tend to respond mainly to the deflection of a single whisker (called ‘principal whisker’, PW). However, their responses also modulated when surrounding whiskers (SWs) are deflected alone with the PW. When studying the surround modulation effect, most previous studies deflect only the PW and a single SW, a scheme differs significantly from the synchronous movement of multi-whiskers when rats are exploring the environment. In this study, we aimed on the effect of surround modulation by deflecting multi-whiskers simultaneously with different stimulus patterns: a single whisker (single condition), multi-whiskers (n = 5, chosen randomly) moving in the same direction (correlated condition), multi-whiskers (n = 5, chosen randomly) moving in different directions (uncorrelated condition). We tried to address three questions. First, how firing rate and directional tuning were affected by surround modulation in different stimulus patterns (the contextual effect). Second, were the effect of surround modulation different across different cortical layers. Third, in what degree the response in barrel cortex could be characterized by the linear-nonlinear model. Half of the recorded neurons showed significant surround modulation effect. Comparing to the single-whisker condition, neurons in the multi-whisker conditions tended to have lower firing rates and higher directional selectivity indices. Neurons with significant surround suppression were three times as many as those with significant surround facilitation, indicating that surround suppression was dominant in barrel field cortex. The contextual effect in multi-whisker conditions was found only in the supragranular layer – the reduction in firing rate was larger in the correlated condition than in the uncorrelated condition, maybe due to abandon lateral connections among neurons with similar properties. In contrast, the contextual effect was not evident in other two layers. Moreover, cortical responses in barrel field under multi-whisker conditions were less characterized by the LN model than those under single whisker condition. Overall, these results indicated that surround suppression was dominant especially for neurons in the supragranular layer of the barrel field cortex, which might serve an important role in integrating inputs from the granular layer. In contrast, neurons in the granular layer were less affected by surround stimulation and might serve as critical feature detectors (Brecht, 2007). | en |
| dc.description.provenance | Made available in DSpace on 2021-05-19T17:41:55Z (GMT). No. of bitstreams: 1 ntu-108-R04227109-1.pdf: 3507248 bytes, checksum: b4e84d973dffeeef39f6819c2398661f (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | Table of Contents
Introduction 1 Material and Methods 7 Animal preparation 7 Histology and layer reconstruction 8 Stimulus presentation. 9 Data analysis 10 Peri-stimulus time histogram (PSTH) and firing rate analysis 10 Direction selectivity index and prefer direction analysis 12 Receptive field estimation 13 Estimation of the static nonlinearity 14 Results 15 Strong surround modulation in barrel field cortex 16 Surround suppression is dominant in barrel field cortex 21 Surround modulation of directional selectivity of the PW 24 Surround modulation of the tuning curve and the preferred direction 28 The Linear-Nonlinear (LN) model and reverse correlation 311 Laminar differences in linear-Nonlinear (LN) model 39 Response linearity in barrel field cortex 41 Discussion 43 Barrel cortex vs. barrel field cortex 455 Surround modulation in firing rate 455 Surround modulation in directional selectivity 47 Surround modulation in preferred direction 49 Application of LN model in barrel cortex 49 References .54 Appendix A. Example brain ections………...………………………………………..63 Appendix B. Example single unit waveform and clusters………………….…...…...66 List of Tables and Figures Table1. Suppression and Faciliation interactions quantified by CTR and FI………...22 Figure 1. Stimulus paradigm and an example neuron in the granular layer of the barrel field cortex 19 Figure 2. Comparisons of firing rates based on stimulus types and cortical layers 20 Figure 3. Surround modulation vs. firing rate in PW alone condition 23 Figure 4. Polar plots of responses to different layers and the direction selectivity indices (DI) under three stimulus conditions. 26 Figure 5. Comparisons of direction selective index (DI) based on stimulus types and cortical layers 27 Figure 6. Surround modulation of DIs 29 Figure 7. The tuning curve in three different stimulus conditions. 34 Figure 8. Differences in preferred direction in different stimulus condition 35 Figure 9. The spatiotemporal receptive field was calculated by reverse correlation and was use to estimate the static nonlinearity based on the linear-nonlinear model 36 Figure 10. Comparisons of gains based on stimulus types and cortical layers 37 Figure 11. Comparisons of zero-crossings (offsets) based on stimulus types and cortical layers 38 Figure 12. Histograms of the explained variance (r-square) in three different stimulus conditions. 42 | |
| dc.language.iso | en | |
| dc.title | 大鼠桶狀皮質區不同皮層間的側調節 | zh_TW |
| dc.title | Surround Modulation in Different Cortical Layers of Rat Barrel Field Cortex | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 裴育晟(Yu-Cheng Pei),蔡孟利(Meng-Li Tsai) | |
| dc.subject.keyword | 大鼠,桶狀皮質區,側調節,方向調性,線性─非線性模型,腦皮層, | zh_TW |
| dc.subject.keyword | rat,barrel field cortex,surround modulation,direction selectivity,LN model,cortical layer, | en |
| dc.relation.page | 66 | |
| dc.identifier.doi | 10.6342/NTU201900913 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2019-06-14 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 心理學研究所 | zh_TW |
| 顯示於系所單位: | 心理學系 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf | 3.43 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
