運動與身體活動經常被認為能促進認知功能、行為表現及腦部健康，然而此類效益並非在所有認知作業、運動類型、神經指標或時間尺度上皆一致。本論文從三個互補層面探討運動相關的認知與腦部差異，包括行為學習、結構性磁振造影（MRI）及真實運動情境下的腦電圖（EEG）。本研究的核心目的並非單純判斷運動對大腦具有益處或害處，而是探討在不同認知作業、解剖尺度及實際運動情境下，運動相關差異如何表現於行為與神經層面。首先，本研究探討運動相關的認知優勢究竟反應較高的基礎能力，或是較佳的學習可塑性。在隱性動作序列學習作業中，比較田徑、棒球選手與缺乏運動習慣者的表現，結果顯示運動員具有較快的基礎動作反應速度，但在一般動作技能學習及序列特定學習方面並未展現一致優勢。研究進一步利用情境提示（contextual cueing）視覺搜尋作業檢驗學習能力，雖然所有受試者皆呈現穩健的視覺搜尋學習效果，但運動參與程度及體適能並未與較高的學習速率相關。整體而言，研究結果顯示運動所帶來的認知優勢較偏向特定能力，而非支持「整體學習能力提升」的假說。其次，本研究利用多種互補性的MRI分析方法探討運動相關的腦部形態差異。在大學美式足球員、越野田徑選手與非運動員之間，比較體素形態分析（FSL-VBM）、皮質下結構分析（FIRST）及腦組織分割（FAST）結果，發現腦幹、皮質下結構及腦組織組成存在差異，但其型態依比較對象而有所不同，凸顯納入非碰撞性運動員作為對照組的重要性。另一項針對菁英足球選手的研究則發現局部灰質差異、廣泛的皮質下體積變化、局部形狀改變以及較低的絕對腦組織體積。然而，組織比例分析及雙向形狀變化結果顯示，這些差異不宜簡化解釋為廣泛性的神經退化。 最後，本研究利用事件鎖定高密度EEG分析桌球實際擊球時的腦神經動態。相較於與發球機互動，受試者在真人對打情境中呈現不同的擊球前後頻譜活動。殘差頻帶功率分析顯示，發球機條件下的α波與β波功率較低；然而，頻譜參數化分析進一步指出，最穩定且明顯的差異為發球機情境下非週期性頻譜指數（aperiodic exponent）增加，且主要分布於後部及頂葉區域。綜合而言，本研究證實運動相關的認知與神經差異確實存在，但其表現並非單一且普遍一致。無論是在行為學習、結構性MRI或真實情境EEG分析中，研究結果皆支持運動效應具有高度特異性，而非普遍性的提升或損害。運動對大腦與認知的影響應視為訓練經驗、作業需求、解剖尺度、暴露特性、測量方法及即時運動情境等多重因素交互作用的結果。;Sport and physical activity are often associated with cognitive， behavioural， and neural benefits， but these associations are not uniform across tasks， sports， brain measures， or timescales. The present work examined sport-related cognition and brain differences across three complementary levels of analysis: behavioural learning， structural magnetic resonance imaging， and real-world electroencephalography. The central aim was not to determine whether sport is simply beneficial or harmful for the brain， but to ask how sport-related differences are expressed when cognition and neural measures are examined across different tasks， anatomical scales， and performance contexts. The first part of the work investigated whether sport-related cognitive advantages are better understood as altered baseline competence or enhanced trainability. In one study， runners， baseball players， and non-exercising controls completed an implicit motor sequence learning task that separated baseline response speed， general motor skill learning， and sequence-specific learning. Sport-trained participants showed evidence of faster baseline motor performance than sedentary controls， but did not show a consistent advantage in general motor skill learning or sequence-specific learning. A second behavioral study extended this question to visual search using a contextual cueing task. Although robust visual-search learning and contextual cueing were observed， sport and fitness were not associated with a broad increase in learning rate. Together， these findings suggest that sport-related behavioral advantages may be more specific than a general “more trainable brain” account would predict. The second part examined sport-related structural brain morphology using complementary MRI methods. In collegiate American football players， cross-country runners， and non-athletes， FSL-VBM， FIRST， and FAST analyses revealed brainstem， subcortical， and tissue-composition differences， but the pattern depended on the comparison group. This supported the value of including a non-collision athlete group when interpreting morphology is collision sports. In elite soccer players and matched controls， structural analyses identified focal grey-matter differences， widespread subcortical volumetric differences， local shape effects， and lower absolute tissue volumes. However， tissue-fraction and bidirectional shape findings caution against a simple interpretation of diffuse degeneration. The final part examined real-world neural dynamics during table tennis using event-locked high-density EEG. Human-player and ball-machine contexts were associated with systematic peri-hit spectral differences. Residualised bandpower suggested lower ball-machine than human-player alpha and beta power in several comparisons， but spectral parameterisation showed that the clearest context effect was a higher aperiodic exponent during ball-machine trials， especially over posterior and parietal regions. Overall， the findings indicate that sport-related cognitive and neural differences are real but not simple. Across behavioural learning， structural MRI， and real-world EEG， the evidence points towards specificity of effects rather than generality. Sport-related brain and cognition differences should therefore be understood as the product of interacting factors， including training history， task demands， anatomical scale， exposure profile， measurement method， and immediate performance context.
