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是腦力激盪還是腦波震盪?用波型解開學習的面紗



  不同的神經特徵使科學家們進一步瞭解:無論是動作技巧、或更複雜的認知操作學習中,其神經生物的基礎是什麼。神經元被觸發時會製造電訊號,並產生各式頻率的腦波。Miller希望發現刺激腦部的方法、或可減輕傷害的訓練技巧,進而協助學習或記憶能力受損的患者。
  Roman F. Loonis表示,神經特徵可幫助我們透過學習策略的變化,及早發現阿茲海默患者、或強化其學習的方式,以期患者能與疾病和平相處。

學習,有感嗎?──顯性學習與隱性學習

  科學家曾將所有的「學習」等同視之。1953年,曾透過手術移除部分腦組織的癲癇患者──Henry Molaison ,在術後無法記得幾分鐘才吃過早餐、動作技巧學習與能力保存卻正常;且Miller也發現:與Henry一樣的健忘患者雖無法記得自己做過的事,但在技巧的學習上都與他人無異。自此,科學家們對學習開始有了不同的看法。
  有關大腦的學習與記憶可粗分為「顯性」與「隱性」兩類。在顯性學習(Explicit Learninig中,我們能清楚知道自己在做什麼,並能解釋詳細的活動內容,無論是文章段落的記憶、或解開複雜棋局的策略……等都屬於顯性學習;而隱性學習(Implicit Learning較為內化、無意識,多為動作技巧學習或肌肉記憶,如學會騎腳踏車或雜耍技巧……等。「當然,也有如音樂與樂器演奏等特殊內容,必須同時仰賴兩種不同屬性的學習方式。」Miller強調。

波段下的秘密──不同學習型態下的腦波

  麻省理工學院(MIT)的學者研究動物學習不同操作任務時的行為發現,有些會用到顯性學習、有些則需使用隱性學習。實驗的任務為比較並配對兩個物品:如果答案正確與否會影響下次的決定,學習較傾向顯性;反之,若只要稍移動眼神或做出其他視覺反應即可達成目的,越優化、越正確的表現就有關鍵影像,此為隱性學習的型態。
  在顯性學習中,腦中的α2-β波(振盪頻率為10-30赫茲)與「正確的決定」有關,但會隨學習到一定的階段後開始減少生產。研究亦發現,神經活動的尖峰僅出現在行為出錯之後,此為被動事件相關現象(event-related negativity),僅出現在需要顯性學習的活動中。而隱性學習獨有的δ-θ波(振盪頻率為3-7赫茲)則是在做了錯誤的決定後生成,其反映心智如何建立操作模式,若已習得操作任務,此波段即會慢慢消失,此模式可讓神經在動作技巧學習的過程裡不斷「重新連結」並加以編碼。

冰冷冷的數字,活生生的策略。──關於學習的未來展望

  Loonis表示:「若能偵測不同種類學習下的各式腦波,我們便能強化並提供更好的回饋給學習者。比方說若學習者長於隱性學習法,這意味著他們仰賴過程中的正向回饋,如此一來我們便能從中協助、讓他們學習得更好。」此外,這些神經特徵也有助於判斷早期阿茲海默。阿茲海默症患者得顯性學習因子雖消失,但也許能在隱性學習的過程中找到相類似的方式,畢竟東牆倒了、西牆還是得撐住啊!
  早期研究顯示腦部某些部分如海馬迴(hippocampus)與顯性學習較密切,而基底核(basal ganglia)則與隱性學習較相關。然而腦波研究更進一步指出,兩個學習系統亦有重疊的部分,且享有相同的神經網絡資源。
 
新聞來源:Brain waves reflect different types of learning, Science Daily.

Brain Waves Reflect Different Types of Learning

Figuring out how to pedal a bike and memorizing the rules of chess require two different types of learning, and now for the first time, researchers have been able to distinguish each type of learning by the brain-wave patterns it produces.

These distinct neural signatures could guide scientists as they study the underlying neurobiology of how we both learn motor skills and work through complex cognitive tasks, says Earl K. Miller, the Picower Professor of Neuroscience at the Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences, and senior author of a paper describing the findings in the Oct. 11 edition of Neuron.
When neurons fire, they produce electrical signals that combine to form brain waves that oscillate at different frequencies. "Our ultimate goal is to help people with learning and memory deficits," notes Miller. "We might find a way to stimulate the human brain or optimize training techniques to mitigate those deficits."
The neural signatures could help identify changes in learning strategies that occur in diseases such as Alzheimer's, with an eye to diagnosing these diseases earlier or enhancing certain types of learning to help patients cope with the disorder, says Roman F. Loonis, a graduate student in the Miller Lab and first author of the paper. Picower Institute research scientist Scott L. Brincat and former MIT postdoc Evan G. Antzoulatos, now at the University of California at Davis, are co-authors.

Explicit versus implicit learning

Scientists used to think all learning was the same, Miller explains, until they learned about patients such as the famous Henry Molaison or "H.M.," who developed severe amnesia in 1953 after having part of his brain removed in an operation to control his epileptic seizures. Molaison couldn't remember eating breakfast a few minutes after the meal, but he was able to learn and retain motor skills that he learned, such as tracing objects like a five-pointed star in a mirror.
"H.M. and other amnesiacs got better at these skills over time, even though they had no memory of doing these things before," Miller says.
The divide revealed that the brain engages in two types of learning and memory -- explicit and implicit.
Explicit learning "is learning that you have conscious awareness of, when you think about what you're learning and you can articulate what you've learned, like memorizing a long passage in a book or learning the steps of a complex game like chess," Miller explains.
"Implicit learning is the opposite. You might call it motor skill learning or muscle memory, the kind of learning that you don't have conscious access to, like learning to ride a bike or to juggle," he adds. "By doing it you get better and better at it, but you can't really articulate what you're learning."
Many tasks, like learning to play a new piece of music, require both kinds of learning, he notes.

Brain waves from earlier studies

When the MIT researchers studied the behavior of animals learning different tasks, they found signs that different tasks might require either explicit or implicit learning. In tasks that required comparing and matching two things, for instance, the animals appeared to use both correct and incorrect answers to improve their next matches, indicating an explicit form of learning. But in a task where the animals learned to move their gaze one direction or another in response to different visual patterns, they only improved their performance in response to correct answers, suggesting implicit learning.
What's more, the researchers found, these different types of behavior are accompanied by different patterns of brain waves.
During explicit learning tasks, there was an increase in alpha2-beta brain waves (oscillating at 10-30 hertz) following a correct choice, and an increase delta-theta waves (3-7 hertz) after an incorrect choice. The alpha2-beta waves increased with learning during explicit tasks, then decreased as learning progressed. The researchers also saw signs of a neural spike in activity that occurs in response to behavioral errors, called event-related negativity, only in the tasks that were thought to require explicit learning.
The increase in alpha-2-beta brain waves during explicit learning "could reflect the building of a model of the task," Miller explains. "And then after the animal learns the task, the alpha-beta rhythms then drop off, because the model is already built."
By contrast, delta-theta rhythms only increased with correct answers during an implicit learning task, and they decreased during learning. Miller says this pattern could reflect neural "rewiring" that encodes the motor skill during learning.
"This showed us that there are different mechanisms at play during explicit versus implicit learning," he notes.

Future Boost to Learning

Loonis says the brain wave signatures might be especially useful in shaping how we teach or train a person as they learn a specific task. "If we can detect the kind of learning that's going on, then we may be able to enhance or provide better feedback for that individual," he says. "For instance, if they are using implicit learning more, that means they're more likely relying on positive feedback, and we could modify their learning to take advantage of that."
The neural signatures could also help detect disorders such as Alzheimer's disease at an earlier stage, Loonis says. "In Alzheimer's, a kind of explicit fact learning disappears with dementia, and there can be a reversion to a different kind of implicit learning," he explains. "Because the one learning system is down, you have to rely on another one."
Earlier studies have shown that certain parts of the brain such as the hippocampus are more closely related to explicit learning, while areas such as the basal ganglia are more involved in implicit learning. But Miller says that the brain wave study indicates "a lot of overlap in these two systems. They share a lot of the same neural networks."

Story Source:
Materials provided by Massachusetts Institute of Technology. Original written by Becky Ham. Note: Content may be edited for style and length.
Journal Reference:
Scott L. Brincat, Evan G. Antzoulatos, Earl K. Miller. A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning Roman F. LoonisNeuron, October 2017 DOI: 10.1016/j.neuron.2017.09.032

 

 
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