這篇論文提出了一個適合研究螯蝦CPR細胞網路的超大型積體電路。我們從生物量測的資料分析開始，依序建立細胞網路模型、利用Matlab模擬驗證並萃取參數範圍、設計超大型積體電路，最後進行積體電路的量測。這個超大型積體電路不僅能大幅縮減模擬的時間，而且能夠與生物細胞溝通而形成一個混合型系統。此外，由於CPR網路的參數彼此間差距甚大，這個積體電路的架構也可以應用於其他小型的異質細胞網路。

細胞網路是由細胞以及突觸組成。透過分析細胞網路中的動作電位圖形(spiking pattern)，神經科學家可以了解細胞網路對刺激的反應。CPR網路是具有兩種感覺細胞的細胞網路，這兩種細胞分別是CPR細胞以及毛細胞(hair neuron)。CPR細胞接受光的刺激而毛細胞接受力學刺激，例如水的波動。CPR細胞在接受長時間、固定大小的刺激時，動作電位頻率一開始會先增加，然後隨著時間慢慢減少。因此，我們將CPR細胞建置成具有兩個額外離子通道的FS細胞(具有鈉鉀離子通道的基本細胞)。這兩個額外的離子通道，一個會慢慢增加細胞的興奮程度，而另外一個則具有更大的時間常數，它會慢慢減少細胞的興奮程度。此外，CPR細胞網路的網路動態具備有四種現象。前兩種現象-水波強化(wave enhancement)以及由電擊產生的抑制，指得是當我們對毛細胞施予強弱不同的刺激時，CPR細胞所產生的不同反應。若是給予毛細胞弱的刺激，則CPR細胞的動作電位頻率會上升，因而產生水波強化現象。反之，給予毛細胞強刺激時，CPR細胞則會受到抑制，我們稱之為由電擊產生的抑制現象。切除傳入神經現象(the afferent-cut phenomenon)指得是切除傳入神經後，CPR細胞的動作電位頻率上升的現象。互相抑制及振盪現象(mutual inhibition and oscillation)則存在於兩顆CPR細胞之間。在這個現象中，他們會彼此的抑制對方而產生周期性、連串的動作電位(bursting)。

模型在經過Matlab模擬的驗證後，接著進行的是超大型積體電路的設計。這個超大型積體電路的參數範圍是參考由Matlab模擬中萃取出的參數範圍。它包含了類比記憶體陣列以及細胞網路兩部份。類比記憶體陣列包含64個記憶體單元並且操作在100kHz的時脈之下。在每個時脈當中，位址計數器指到的記憶體單元的值會被讀出、與目標值比較，並且更新。記憶體在儲存值0.25V到1.35V間的解析度為0.01V。細胞網路的主要考量為兼顧面積的使用效率以及產生精確動作電位的能力。因此，我們採用了具備第一型興奮性(type-I excitability)，以nullcline方式所設計出的矽細胞。這個矽細胞不只節省面積還可以產生與生物細胞相當振幅的動作電位(0.2V 0.3V)。電路中提供五個參數來調整單一動作電位的持續時間(spike duration)、靜止電位，以及閾值。我們也提出一個可以與離子通道共用架構的突觸電路，如此一來設計的複雜度會變得更簡單。這個電路提供了四個參數來控制最大輸出電流以及時間常數。

我們所製造的晶片面積為1.45mm * 1.45mm，包含半個CPR細胞網路、64個類體記憶體單元的陣列，以及一個包含16個細胞的陣列。完整的CPR網路可以透過將兩顆晶片相連來達成。在這之中，矽神經細胞的面積為49mm * 48mm而功耗為139nW，優於以Hodking-Huxley模型設計的電路的834mm * 870mm以及超過1mW。量測的結果顯示出動作電位的可調性、突觸電路的正確運作，以及一些CPR網路的現象，包含了CPR細胞的動作電位曲線、水波強化，以及由電擊產生的抑制現象。切除傳入神經以及互相抑制及振盪的現象將在未來量測。

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