A New Type of Neuroplasticity Rewires the Brain After a Single Experience

The brain stays incredibly plastic throughout our lives, allowing us to learn and adapt to changing environments.

大脑在我们的一生中都保持着令人难以置信的可塑性，使我们能够学习和适应不断变化的环境。

Mark Belan, Yasemin Saplakoglu/ Quanta Magazine

Mark Belan、Yasemin Saplakoglu/Quanta 杂志

Every experience we have changes our brain, the way a ceramicist reshapes a slab of clay.

我们的每一次经历都会改变我们的大脑，就像陶艺家重塑一块粘土的方式一样。

Every corner we turn, every conversation we have, every shudder we feel causes cascading effects: Chemicals are released, electricity surges, the connections between brain cells tighten, and our mental models update.

我们转弯的每一个角落、我们进行的每一次谈话、我们感到的每一次颤抖都会引起连锁反应：化学物质被释放，电流激增，脑细胞之间的连接收紧，我们的心理模型更新。

The brain is “incredibly plastic, and it stays that way throughout the lifespan of a human,” said Christine Grienberger , a neuroscientist at Brandeis University.

布兰代斯大学的神经科学家克里斯汀·格林伯格说，大脑“具有令人难以置信的可塑性，并且在人的一生中都会保持这种状态”。

This plasticity, the quality of being easily reshaped, makes the brain really good at learning — a quintessential process that allows us to remember the plotline of a novel, navigate a new city, pick up a new language, and avoid touching a hot stove.

这种可塑性，即容易重塑的品质，使大脑真正擅长学习——这是一个典型的过程，让我们能够记住小说的情节，在新的城市中航行，学习新的语言，并避免接触热炉。

But neuroscientists are still uncovering fundamental rules that describe how neuroplasticity reshapes brain connections.

但神经科学家仍在揭示描述神经可塑性如何重塑大脑连接的基本规则。

Recently, neuroscientists described a new form of neuroplasticity that might be helping the brain learn across a timescale of several seconds — long enough to capture the behavioral process of learning from a single experience.

最近，神经科学家描述了一种新形式的神经可塑性，它可能有助于大脑在几秒钟的时间内学习——足够长的时间来捕捉从单一经历中学习的行为过程。

In two recent reviews, published in The Journal of Neuroscience and Nature Neuroscience , they describe “behavioral timescale synaptic plasticity,” or BTSP.

在最近发表在《神经科学杂志》和《自然神经科学》上的两篇评论中，他们描述了“行为时间尺度突触可塑性”（BTSP）。

This type of learning in the hippocampus, the brain’s memory hub, is caused by an electrical change that affects multiple neurons at once and unfolds across several seconds.

海马体（大脑的记忆中心）的这种类型的学习是由同时影响多个神经元并在几秒钟内展开的电变化引起的。

Researchers suspect that it may help the brain learn in a single attempt.

研究人员怀疑它可能有助于大脑在一次尝试中学习。

“It’s pretty clear that [BTSP is] a strong, powerful mechanism that can lead to immediate memory formation,” said Daniel Dombeck , a neuroscientist at Northwestern University who was not involved with the theory’s development.

“很明显，[BTSP] 是一种强大的机制，可以导致立即形成记忆，”西北大学神经科学家丹尼尔·多姆贝克 (Daniel Dombeck) 说，他没有参与该理论的发展。

“It’s something that has been missing in the field for a long time.”

“这是该领域长期以来缺失的东西。”

By uncovering BTSP, neuroscientists have unraveled more of the story of how the brain changes with experience, bringing us closer to understanding how learning happens.

通过揭示 BTSP，神经科学家更多地揭示了大脑如何随经验而变化的故事，使我们更接近于理解学习是如何发生的。

“Neuroplasticity is …

“神经可塑性是……

one of the last frontiers of the brain,” said Attila Losonczy , a neuroscientist at the University of Texas Southwestern Medical Center who studies BTSP.

德克萨斯大学西南医学中心研究 BTSP 的神经科学家 Attila Losonczy 说：“这是大脑最后的前沿领域之一。”

“If we understand this, I think we take a major step towards understanding how the brain works.”

“如果我们理解了这一点，我认为我们就朝着理解大脑如何工作迈出了重要一步。”

Today, neuroplasticity is taken as fact, but for much of the 150-year history of neuroscience, the adult brain was thought to be static.

如今，神经可塑性已被视为事实，但在神经科学 150 年历史的大部分时间里，成人大脑被认为是静态的。

“The idea that the adult brain can change wasn’t actually widely accepted until very late [in] the history of modern neuroscience,” said Moheb Costandi , a trained neuroscientist and author of Neuroplasticity , a primer from MIT Press.

受过训练的神经科学家、麻省理工学院出版社的入门读本《神经可塑性》一书的作者莫赫布·科斯坦迪 (Moheb Costandi) 说：“成人大脑可以改变的想法实际上直到现代神经科学史上很晚才被广泛接受。”

“It was taken for granted that the adult human brain can’t change.” In 1928, Santiago Ramón y Cajal , the oft-cited founder of modern neuroscience, wrote that “in adult centers the nerve paths are something fixed, ended, immutable.” This idea would prevail well into the middle of the 20th century.

“人们理所当然地认为成年人的大脑无法改变。” 1928 年，经常被引用的现代神经科学创始人圣地亚哥·拉蒙·卡哈尔 (Santiago Ramón y Cajal) 写道，“在成人中心，神经路径是固定的、结束的、不可改变的。”这种想法一直盛行到20世纪中叶。

Santiago Ramón y Cajal’s drawings of neurons, such as this Purkinje cell with branching dendrites, led to his theory that the nervous system contains many interacting cells.

圣地亚哥·拉蒙·卡哈尔 (Santiago Ramón y Cajal) 绘制的神经元图（例如带有分支树突的浦肯野细胞）得出了他的理论：神经系统包含许多相互作用的细胞。

Santiago Ramón y Cajal/Public Domain

圣地亚哥·拉蒙·卡哈尔/公共领域

We now know that the brain is constantly remolding itself, both functionally and structurally, across many scales — from the molecules that flow between neurons to the connections that stretch across the brain and beyond.

我们现在知道，大脑在功能和结构上不断重塑自身，跨越多个尺度——从神经元之间流动的分子到横跨大脑内外的连接。

The power of neuroplasticity is perhaps best demonstrated by case studies.

神经可塑性的力量也许可以通过案例研究得到最好的证明。

One patient born without an olfactory bulb could smell because other parts of her brain remolded to serve as substitutes.

一名出生时没有嗅球的患者之所以能闻到气味，是因为她大脑的其他部分被重塑为替代品。

Another patient had the entire left side of her brain removed as a baby; after her right side reorganized to take on the left’s former roles, today she has a functional life.

另一位患者在婴儿时期就被切除了整个左侧大脑。在她的右侧身体重组以承担左侧身体以前的角色后，今天她过上了正常的生活。

When a stroke or an accident damages the brain, other neurons fill in to recover patients’ everyday functions such as speaking and walking.

当中风或事故损害大脑时，其他神经元就会填补以恢复患者的日常功能，例如说话和行走。

Neuroplasticity also drives everyday learning.

神经可塑性也推动日常学习。

This process is mainly thought to result from synaptic plasticity, or changes to the trillions of connections between neurons.

这个过程主要被认为是由突触可塑性或神经元之间数万亿个连接的变化引起的。

And although the brain learns in various ways, one particular idea has dominated for more than 70 years.

尽管大脑以多种方式学习，但 70 多年来，一种特定的观念一直占据主导地位。

In 1949, Donald Hebb, a Canadian psychologist, articulated a theory of learning now known as Hebbian plasticity.

1949 年，加拿大心理学家唐纳德·赫布 (Donald Hebb) 阐述了一种学习理论，现在被称为赫布可塑性。

According to this model, when neurons are activated within milliseconds of each other, the connection between them is physically strengthened , so that in the future they are more likely to fire together.

根据这个模型，当神经元在几毫秒内被激活时，它们之间的物理连接就会得到加强，因此将来它们更有可能一起放电。

Over time, they form a network that represents a concept or an experience.

随着时间的推移，它们形成了一个代表概念或体验的网络。

In other words, the more the networks in the brain are used, the stronger they get, an idea often summarized as “neurons that fire together, wire together.”

换句话说，大脑中的网络使用得越多，它们就越强大，这个想法通常被概括为“一起放电、连接在一起的神经元”。

In 1949, Donald Hebb, a Canadian psychologist, articulated neuroscience’s dominant theory of learning, now known as Hebbian plasticity.

1949 年，加拿大心理学家唐纳德·赫布 (Donald Hebb) 阐述了神经科学的主导学习理论，即现在的赫布可塑性。

UBC Archives Photograph Collection; University Archives, University of British Columbia Library.

UBC 档案照片集；大学档案馆，不列颠哥伦比亚大学图书馆。

UBC 41.1/2039-1

UBC 41.1/2039-1

But neuroscientists “always had a sneaking suspicion that Hebbian plasticity wasn’t quite right,” said Jeffrey Magee , a neuroscientist at Baylor College of Medicine.

但贝勒医学院的神经科学家杰弗里·马吉说，神经科学家“总是暗中怀疑赫布可塑性不太正确”。

Or at least, it wasn’t the full story.

或者至少，这不是故事的全部。

It required an experience to be repeated multiple times to imprint the lesson on the brain — a framework that may explain how we learn a new city or language, but not how we learn from a single, highly charged experience, such as touching a hot stove.

它需要重复多次才能将教训铭刻在大脑中——这个框架可以解释我们如何学习新的城市或语言，但不能解释我们如何从单一的、高度紧张的经历（例如触摸热炉子）中学习。

Even so, finding more explanatory mechanisms hasn’t been top of mind for neuroscientists.

即便如此，寻找更多的解释机制并不是神经科学家的首要任务。

“It wasn’t a quest, like in particle physics for missing particles,” Losonczy said.

“这不是一个探索，就像粒子物理学中寻找缺失的粒子一样，”洛松齐说。

Maybe there were a couple of gaps that needed to be filled, but most researchers assumed that the Hebbian framework would require only tweaks.

也许有一些空白需要填补，但大多数研究人员认为赫布框架只需要调整。

Few were thinking that a fuller understanding of neuroplasticity might include a new mechanism.

很少有人认为对神经可塑性的更全面理解可能包括一种新机制。

In 2014, when Magee attached electrodes to rodents to record their neural activity, he wasn’t looking to challenge Hebbian plasticity.

2014 年，当马吉在啮齿类动物身上安装电极来记录它们的神经活动时，他并不是想挑战赫布的可塑性。

Magee, then at the Howard Hughes Medical Institute’s Janelia Research Campus, and his students Grienberger and Katie Bittner were looking to observe the behavior of neurons’ arms, called dendrites, in a living animal.

当时在霍华德休斯医学研究所珍妮莉亚研究园区的马吉和他的学生格林伯格和凯蒂比特纳正在观察活体动物神经元臂（称为树突）的行为。

These branches receive molecular signals at one end of a neuron and induce the cell to rapidly fire an electrical charge that ripples down the cell body, known as an action potential.

这些分支在神经元的一端接收分子信号，并诱导细胞快速发射一种电荷，该电荷在细胞体中产生涟漪，称为动作电位。

This process ends with the neuron releasing its own batch of molecular signals, which latch onto the dendrites of the next neuron in the network, continuing the process.

这个过程以神经元释放自己的一批分子信号结束，这些分子信号锁住网络中下一个神经元的树突，继续这个过程。

Dendrites, the extended branches that receive signals from other neurons, are the star players in a recently described type of neuroplasticity.

树突是从其他神经元接收信号的延伸分支，是最近描述的神经可塑性类型中的明星参与者。

In this image of stained pyramidal neurons from the cerebral cortex, rootlike dendrites extend from the cell bodies.

在这张大脑皮层锥体神经元染色图像中，根状树突从细胞体延伸出来。

In recent decades, neuroscientists have come to a “slow realization that dendritic activity is super important for plasticity and for neuronal computations in general,” said Antoine Madar , a postdoc at the University of Chicago, who led the 2025 review of a Society for Neuroscience symposium on BTSP in The Journal of Neuroscience .

近几十年来，神经科学家们“慢慢意识到，树突活动对于可塑性和一般神经元计算来说非常重要”，芝加哥大学博士后 Antoine Madar 说，他在《神经科学杂志》上主持了 2025 年神经科学学会 BTSP 研讨会的评审。

There is a “zoo” of different events that take place at dendrites, he said.

他说，树突上发生的不同事件有一个“动物园”。

They can fire their own local or global electrical spikes.

他们可以发射自己的本地或全球电尖峰。

They can cover a larger or smaller area, and they can surge for longer or shorter periods of time.

它们可以覆盖更大或更小的区域，并且可以持续更长或更短的时间。

Neuroscientists have found that these events at dendrites can allow even single neurons to perform complex computations — meaning that dendrites are the reason why a single neuron can have the same amount of computational power as a deep artificial neural network .

神经科学家发现，树突上的这些事件甚至可以让单个神经元执行复杂的计算——这意味着树突是单个神经元可以具有与深度人工神经网络相同的计算能力的原因。

Still, there was much unknown about dendrites’ behavior.

尽管如此，关于树突的行为还有很多未知之处。

Neuroscientists have mainly characterized them in brain slices, where neurons are alive and can be activated but aren’t attached to a living animal.

神经科学家主要在大脑切片中表征它们，其中神经元是活的并且可以被激活，但不附着在活体动物身上。

“We were trying to take that into the actual behaving animal, or the actual behaving brain,” Magee said.

“我们试图将其带入实际行为的动物或实际行为的大脑中，”马吉说。

In 2014, they began to home in on the hippocampus, an especially plastic area of the brain where we form experiential memories.

2014年，他们开始关注海马体，这是大脑中一个特别可塑的区域，我们在这里形成经验记忆。

It’s also home to place cells, which fire when an animal moves through its environment .

它也是放置细胞的地方，当动物在其环境中移动时，细胞就会放电。

Each of these neurons learns to fire at specific locations; later, if the rodent reenters that place, the cell will fire, recalling relevant information stored in the network.

这些神经元中的每一个都学会在特定位置放电；之后，如果啮齿动物重新进入该地方，细胞就会启动，调用存储在网络中的相关信息。

Jeffrey Magee, a neuroscientist at Baylor College of Medicine, led the team that first described behavioral timescale synaptic plasticity in 2017.

贝勒医学院的神经科学家 Jeffrey Magee 领导的团队于 2017 年首次描述了行为时间尺度的突触可塑性。

As the rodents ran on a circular track, Magee and his team recorded what was happening in their hippocampal dendrites.

当啮齿类动物在圆形轨道上奔跑时，马吉和他的团队记录了它们的海马树突中发生的情况。

That’s when they observed something interesting.

就在那时，他们观察到了一些有趣的事情。

Neuroscientists had long known that dendrites can sometimes stay active, with a slightly higher charge than when they’re resting, for long periods of time without firing — creating what’s known as a plateau potential.

神经科学家早就知道，树突有时会保持活跃状态​​，其电荷比静止时稍高，长时间不放电，从而产生所谓的平台电位。

Because a plateau potential increases the odds that the neuron will fire, the activity was considered important to neuroplasticity.

由于平台电位会增加神经元放电的几率，因此该活动被认为对神经可塑性很重要。

But while examining the rodent data, Bittner saw that place cells whose dendrites had produced just a single plateau potential began to fire.

但在检查啮齿动物数据时，比特纳发现树突仅产生单一平台电位的位置细胞开始放电。

In other words, a single burst of activity at the dendrite had tuned that cell to fire in that location.

换句话说，树突上的一次活动爆发已经调整了该细胞在该位置的放电。

It was previously thought that encoding a place cell would take multiple action potentials, via Hebbian learning, which would require the animal to explore the same spot multiple times.

此前人们认为，通过赫布学习，对位置细胞进行编码需要多个动作电位，这需要动物多次探索同一地点。

“So we were like, ‘Wow, what’s going on here?’” Magee said.

“所以我们就想，‘哇，这里发生了什么事？’”马吉说。

When they experimentally triggered these plateaus, the cells fired in that location 99.5% of the time after a single dendritic plateau.

当他们通过实验触发这些平台时，在单个树突平台之后，99.5% 的时间细胞都会在该位置放电。

We were going to be facing up to nearly 100 years’ worth of dogma.

我们将面对长达近 100 年的教条。

Jeffree Magee, Baylor College of Medicine

杰弗里·马吉，贝勒医学院

The researchers were elated.

研究人员很高兴。

“We were kind of running back and forth between offices, like, you know, waving papers around — like, ‘Look at this result,’” said Aaron Milstein , a neuroscientist at Rutgers University, who worked in Magee’s lab at the time.

当时在马吉实验室工作的罗格斯大学神经科学家亚伦·米尔斯坦 (Aaron Milstein) 说：“我们在办公室之间来回奔跑，就像，你知道，到处挥舞着文件，就像‘看看这个结果’。”

It seemed that dendrites weren’t just passively nudging a neuron to fire — they were causing the change themselves, strengthening the synapse in a single, swift step.

树突似乎不仅仅是被动地推动神经元放电——它们本身也在引起变化，一步一步地快速强化突触。

Magee and his team published their findings in 2015.

Magee 和他的团队于 2015 年发表了他们的研究结果。

At that point, they thought they had observed some weird subtype of Hebbian plasticity.

那时，他们认为他们观察到了赫布可塑性的一些奇怪的亚型。

But when they looked more closely at brain recordings of live animals plus brain slices, they recognized the biggest difference between the dendrites’ activity and Hebbian plasticity: time.

但当他们更仔细地观察活体动物的大脑记录和脑切片时，他们认识到树突活动和赫布可塑性之间的最大区别：时间。

In most studies of Hebbian plasticity, neurons can strengthen or weaken their connection if they are activated within milliseconds of each other.

在大多数赫布可塑性研究中，如果神经元在几毫秒内被激活，它们的连接就会增强或减弱。

Dendrites’ plateau potentials, on the other hand, persist for tens to hundreds of milliseconds (sometimes approaching one second), and through BTSP they can strengthen synapses active six to eight seconds before or after the plateau event.

另一方面，树突的平台电位持续数十到数百毫秒（有时接近一秒），并且通过 BTSP，它们可以增强在平台事件之前或之后活跃六到八秒的突触。

“It became pretty obvious that this wasn’t at all the standard kind of Hebbian plasticity,” Magee said.

“很明显，这根本不是标准的赫布可塑性，”马吉说。

“That made it even more interesting, of course, and a little bit intimidating, because then we were going to be facing up to nearly 100 years’ worth of dogma.”

“当然，这让它变得更有趣，也有点令人生畏，因为那时我们将面临近 100 年的教条。”

It also addressed another big question that Hebbian plasticity had left open: how our cells can capture our relatively slow human behaviors.

它还解决了赫布可塑性尚未解决的另一个大问题：我们的细胞如何捕捉我们相对缓慢的人类行为。

“If you imagine even the simplest of the behavioral learning — for example, learning to stop at a red light signal, or to even explore and figure out what are the main parts in a particular room — it will take you at least a few seconds,” said Anant Jain , a neurophysiologist at the Center for High Impact Neuroscience and Translational Applications in India.

印度高影响神经科学和转化应用中心的神经生理学家 Anant Jain 表示：“如果你想象一下，即使是最简单的行为学习——例如，学习在红灯信号处停下来，或者甚至探索并找出特定房间的主要部分是什么——也至少需要几秒钟的时间。”

BTSP explains how the brain can encode behaviors in a single burst of brain activity that unfolds across several seconds.

BTSP 解释了大脑如何在持续数秒的大脑活动爆发中编码行为。

Because this new mechanism seemed more behaviorally relevant than Hebbian learning, Magee named it “ behavioral time scale synaptic plasticity ” in a 2017 Science paper.

由于这种新机制似乎比赫布学习在行为上更相关，Magee 在 2017 年《科学》杂志的一篇论文中将其命名为“行为时间尺度突触可塑性”。

“I’m not very good at naming things,” he admitted.

“我不太擅长命名事物，”他承认。

Then he waited for the response from fellow neuroscientists.

然后他等待神经科学家同行的回应。

Initially, BTSP received pushback within the field.

最初，BTSP 受到了业内的抵制。

There was good reason for that, Magee said, as it challenged the dogma of neuroplasticity that had dominated for decades.

马吉说，这是有充分理由的，因为它挑战了几十年来主导的神经可塑性教条。

But over the past few years, other researchers have started to investigate it themselves.

但在过去的几年里，其他研究人员也开始自行研究。

Attila Losonczy at the University of Texas Southwestern Medical Center said that the BTSP model for single-trial learning could be “useful for artificial intelligence models.”

德克萨斯大学西南医学中心的 Attila Losonczy 表示，单次试验学习的 BTSP 模型可能“对人工智能模型有用”。

This is “a very compelling model for single-shot learning,” said Losonczy, who worked in Magee’s lab prior to the discovery and now studies BTSP at his lab.

这是“一个非常引人注目的单次学习模型”，Losonczy 说，他在这一发现之前在 Magee 的实验室工作，现在在他的实验室研究 BTSP。

Unlike the mechanisms that allow an animal to learn a new skill slowly, BTSP might help it to learn — after just a single exploration of its cage — that food exists in the northwest corner or that a shock exists to its south.

与让动物慢慢学习新技能的机制不同，BTSP 可能会帮助它在对笼子进行一次探索后了解食物存在于西北角或震动存在于其南部。

“Sometimes you need to remember events you only have one chance to remember, [such as] where the predator is,” Losonczy said.

“有时你需要记住只有一次机会记住的事件，例如捕食者在哪里，”洛松齐说。

“Otherwise, you will be taken out of the genetic pool.”

“否则，你就会被从基因库中剔除。”

While it’s a neat explanation, the exact mechanism remains elusive.

虽然这是一个简洁的解释，但确切的机制仍然难以捉摸。

“There are still so many unanswered questions, at least at the level of molecules,” Jain said.

“至少在分子水平上，仍然有很多未解答的问题，”贾恩说。

However, neuroscientists are starting to get some hints.

然而，神经科学家开始得到一些提示。

Early findings suggest that certain experiences cause synapses, the gaps between neurons where dendrites extend, to be tagged with elusive biochemical signatures called eligibility traces.

早期发现表明，某些经历会导致突触（树突延伸的神经元之间的间隙）被标记为难以捉摸的生化特征，称为资格痕迹。

These tags stick around for several seconds and indicate that those neurons were recently active and therefore relevant to a particular experience.

这些标签会保留几秒钟，表明这些神经元最近很活跃，因此与特定的经历相关。

Then, in the next neuron, a dendritic plateau potential causes a widespread voltage change that spreads across the entire dendrite.

然后，在下一个神经元中，树突平台电位会引起广泛的电压变化，并传播到整个树突。

This plateau triggers all the synapses with the eligibility trace to strengthen.

这个平台触发所有具有资格痕迹的突触加强。

Some studies are starting to zoom in on the molecular process.

一些研究开始关注分子过程。

In 2024, Jain and his team reported that dendritic plateaus might cause a cascade of biochemical signals to build up over several seconds and then activate one of the most important proteins for learning, known as CaMKII.

2024 年，Jain 和他的团队报告说，树突平台可能会导致一系列生化信号在几秒钟内建立起来，然后激活对学习最重要的蛋白质之一，即 CaMKII。

This protein directly influences synaptic strength by physically increasing the surface area and the number of receptors on dendrites, allowing more neurotransmitters to bind there the next time the cell fires.

这种蛋白质通过物理增加树突上的表面积和受体数量来直接影响突触强度，从而允许更多的神经递质在下次细胞放电时结合在那里。

BTSP may also address an ongoing conundrum in neuroscience.

BTSP 还可能解决神经科学中一个持续存在的难题。

Because it strengthens only relevant active neurons, as opposed to any active neuron, BTSP may help address the “ credit assignment problem ” — how the brain can tell which neurons should encode a given experience.

因为它只强化相关的活跃神经元，而不是任何活跃的神经元，所以 BTSP 可能有助于解决“信用分配问题”——大脑如何判断哪些神经元应该编码给定的经历。

Now, Magee and others are looking into the role that BTSP might play not only in learning but also in consolidating memories.

现在，Magee 和其他人正在研究 BTSP 不仅在学习方面，而且在巩固记忆方面可能发挥的作用。

However, Dombeck is cautious about overreaching on BTSP’s significance.

然而，Dombeck 对于过度强调 BTSP 的重要性持谨慎态度。

It has been observed in limited circumstances: only in the hippocampus as an animal learns locations (although researchers have found some evidence for BTSP in the neocortex, where the brain’s higher-order processes happen).

它在有限的情况下被观察到：仅在动物学习位置时的海马体中被观察到（尽管研究人员在新皮质中发现了 BTSP 的一些证据，而新皮质是大脑高级过程发生的地方）。

In his lab, Dombeck has found that BTSP occurs in some hippocampal cells, but not in all of them.

在他的实验室中，Dombeck 发现 BTSP 发生在某些海马细胞中，但并非全部发生。

Jain is not even convinced that BTSP should be categorized as a non-Hebbian type of learning.

Jain 甚至不相信 BTSP 应该被归类为非赫布类型的学习。

Hebbian learning is often vaguely defined, and Hebb himself was vague about the timescales upon which it works.

赫布学习的定义通常很模糊，而赫布本人对于其运作的时间尺度也很模糊。

“Donald never really specified that it has to happen within milliseconds,” only that the neurons need to repeatedly fire together, he said.

“唐纳德从未真正指定它必须在几毫秒内发生”，只是神经元需要反复一起放电，他说。

Only later did neuroscientists mechanistically refine it to include millisecond timescales, Jain said.

杰恩说，直到后来，神经科学家才对其进行机械改进，使其包含毫秒时间尺度。

Most neuroscientists agree that BTSP doesn’t replace Hebbian learning, but rather works alongside it.

大多数神经科学家都认为 BTSP 不会取代赫布学习，而是与之并存。

“Hebbian plasticity probably plays a huge role in development, in the initial wiring” of the brain, Grienberger suggested, while BTSP may be more important for forming episodic memories in adults.

格林伯格认为，“赫布可塑性可能在大脑的发育和初始连接中发挥着巨大作用”，而 BTSP 对于成人情景记忆的形成可能更为重要。

There’s still much unknown about BTSP, especially the mechanism, which Madar said is “quite speculative.” However, he also acknowledged that before becoming the archetypal model for learning, “Hebbian plasticity was also a hypothesis.” Our understanding of how the brain learns through endlessly changing is itself endlessly changing.

关于 BTSP 仍有很多未知之处，尤其是其机制，Madar 称其“相当具有推测性”。然而，他也承认，在成为学习的原型模型之前，“赫布可塑性也是一种假设。”我们对大脑如何通过不断变化进行学习的理解本身也在不断变化。

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