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研究生:紀欽益
研究生(外文):Chin-Yi Ji
論文名稱:大鼠桶狀皮質區不同皮層間的側調節
論文名稱(外文):Surround Modulation in Different Cortical Layers of Rat Barrel Field Cortex
指導教授:葉俊毅葉俊毅引用關係
指導教授(外文):Chun-I Yeh
口試委員:裴育晟蔡孟利
口試委員(外文):Yu-Cheng PeiMeng-Li Tsai
口試日期:2019-04-09
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:心理學研究所
學門:社會及行為科學學門
學類:心理學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:英文
論文頁數:66
中文關鍵詞:大鼠桶狀皮質區側調節方向調性線性─非線性模型腦皮層
DOI:10.6342/NTU201900913
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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).
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).
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
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