When we park in a big parking lot, how do we remember where we parked our car? Here's the problem facing Homer.
当我们在大型停车场停车后，如何回忆起将车停在了哪个车位呢？这就是现在困扰荷马的问题。
And we're going to try to understand what's happening in his brain.
接下来我们将尝试了解此时他脑中正开展何种“运动”。
So we'll start with the hippocampus, shown in yellow, which is the organ of memory.
我们先着眼于大脑海马区，即黄色的区域，这是我们的记忆器官。
If you have damage there, like in Alzheimer's, you can't remember things including where you parked your car.
如果海马区出现损伤，像老年痴呆症患者一样，你将丧失记忆力，乃至记不起将车停在了何处。
It's named after Latin for "seahorse," which it resembles.
hippocampus这个词源自拉丁语，有“海马”之意，因为其形状看上去有点像“海马”。
And like the rest of the brain, it's made of neurons.
海马区和大脑其它区域的组成相似，都由神经元构成。
So the human brain has about a hundred billion neurons in it.
人的大脑由大约一千亿个神经元细胞组成。
And the neurons communicate with each other by sending little pulses or spikes of electricity via connections to each other.
每个神经元细胞之间通过一些连接中介互相发送小的电脉冲或者尖峰电压来进行“交流”。
The hippocampus is formed of two sheets of cells, which are very densely interconnected.
海马区由两层片状的细胞群构成，这两层细胞群紧密相连。
And scientists have begun to understand how spatial memory works
科学家们已经开始了解“空间记忆”的工作原理
by recording from individual neurons in rats or mice while they forage or explore an environment looking for food.
他们通过的是记录老鼠在某环境中搜罗食物时其脑中单个神经元细胞的反应。
So we're going to imagine we're recording from a single neuron in the hippocampus of this rat here.
现在想象一下，我们正在为这只老鼠的海马区中的一个神经元细胞“录像”。
And when it fires a little spike of electricity, there's going to be a red dot and a click.
每当这个细胞发出小型尖峰电压，随后会出现一个红点以及咔哒的一声。
So what we see is that this neuron knows whenever the rat has gone into one particular place in its environment.
我们可以看出，每当老鼠进入环境中某一特定位置，这个神经元细胞便会有反应。
And it signals to the rest of the brain by sending a little electrical spike.
然后这个细胞再通过小型尖峰电压，将以上信息传递给大脑的其它区域。
So we could show the firing rate of that neuron as a function of the animal's location.
这么一来，我们可以凭借这个细胞发送信号的频率，推知老鼠经过的相应位置。
And if we record from lots of different neurons,
倘若我们记录的是很多不同的神经元细胞，
we'll see that different neurons fire when the animal goes in different parts of its environment, like in this square box shown here.
就会发现当老鼠处于不同的位置上时，不同的神经元细胞会产生各自的电信号，正如我们在这些方形中看到的那样。
So together they form a map for the rest of the brain, telling the brain continually, "Where am I now within my environment?"
这些信号为大脑中的其它区域勾勒出一张地图，持续地向大脑指示出，“我现在位于环境中的哪个具体点上？”
Place cells are also being recorded in humans.
我们也记录人脑中的“定位神经元细胞”。
So epilepsy patients sometimes need the electrical activity in their brain monitoring.
癫痫病患者有时需要监测他们的脑电活动情况。
And some of these patients played a video game where they drive around a small town.
一些患者玩一种电子游戏，游戏中他们在一个小镇上自由开车。
And place cells in their hippocampi would fire, become active,
然后当他们驱车驶过镇上的某一处时，
start sending electrical impulses whenever they drove through a particular location in that town.
他们大脑海马区中的“定位神经元细胞”便会被激活，发出信号。
So how does a place cell know where the rat or person is within its environment?
那么这“定位细胞”是怎么知道老鼠或人处于某个位置的呢？
Well these two cells here show us that the boundaries of the environment are particularly important.
这里有两个神经元细胞，它们告诉我们，在定位时，环境的边界是至关重要的。
So the one on the top likes to fire sort of midway between the walls of the box that their rat's in.
上面的这个细胞倾向于在老鼠向盒子中部走去时产生信号。
And when you expand the box, the firing location expands.
因此当你将盒子扩大，相应的信号活跃区也随之扩大。
The one below likes to fire whenever there's a wall close by to the south.
下面的这个喜欢在老鼠紧邻南面屏障时作出反应。
And if you put another wall inside the box,
因此当你在盒中放入另一屏障时，
then the cell fires in both place wherever there's a wall to the south as the animal explores around in its box.
不论老鼠在盒中何处，只要它的南面有屏障，该细胞中的相应位置便会同时产生信号。
So this predicts that sensing the distances and directions of boundaries around you
这表明，了解到达边界需要的距离和方向，
extended buildings and so on -- is particularly important for the hippocampus.
比如周边的建筑物等，对于海马区的“工作”而言至关重要。
And indeed, on the inputs to the hippocampus, cells are found which project into the hippocampus,
而且确实，在老鼠搜罗环境时，我们在海马区的输入信号中，
which do respond exactly to detecting boundaries or edges at particular distances and directions from the rat or mouse as it's exploring around.
检测到能对距环境边界的特定距离与方向作出精确感应的神经元细胞。
So the cell on the left, you can see, it fires whenever the animal gets near to a wall or a boundary to the east,
这里左边的细胞，你可以看出，当老鼠向东靠近边界或屏障时，该细胞都会作出反应，
whether it's the edge or the wall of a square box or the circular wall of the circular box
不论这边界是一个方盒的边，还是一个圆柱盒的边，
or even the drop at the edge of a table, which the animals are running around.
甚至是老鼠绕着转的桌布的垂帘。
And the cell on the right there fires whenever there's a boundary to the south,
而右面的细胞则是在老鼠南面出现边界时响应，
whether it's the drop at the edge of the table or a wall or even the gap between two tables that are pulled apart.
不论这边界是桌布的垂帘还是一堵墙，甚至是两个被隔开的桌子之间的间隙。
So that's one way in which we think place cells determine where the animal is as it's exploring around.
以上是我们所推测的一种“定位细胞”给动物定位的方式。
We can also test where we think objects are, like this goal flag, in simple environments -- or indeed, where your car would be.
我们也可检测，人类在简单环境中，是怎样给--诸如这面旗这样的物体定位的，或者干脆--把这物体想成你的车。
So we can have people explore an environment and see the location they have to remember.
我们先让人们熟悉一下环境，同时记下物体所在的位置。
And then, if we put them back in the environment,
接着，再让他们回到那个环境，
generally they're quite good at putting a marker down where they thought that flag or their car was.
通常他们都能根据记忆准确无误地标出物体所在的位置。
But on some trials, we could change the shape and size of the environment like we did with the place cell.
但在一些试验中，我们会改变环境的形状和尺度，正如我们在“定位细胞”实验中所做的那样。
In that case, we can see how where they think the flag had been changes as a function of how you change the shape and size of the environment.
如此，我们可以通过研究实验者改变环境的形状和尺度，来了解旗帜发生了怎样的位移。

And what you see, for example, if the flag was where that cross was in a small square environment,
比如现在你所看到的，假设这面旗帜在如图中小四方形内的“x”的位置，
and then if you ask people where it was, but you've made the environment bigger,
然后接着你问人们小旗在哪，但实际上你已经将总环境的尺度扩大了，
where they think the flag had been stretches out in exactly the same way that the place cell firing stretched out.
结果他们所认为的旗所在的位置也相应地向外扩张，而这扩张的模式和“定位细胞”的一模一样。
It's as if you remember where the flag was by storing the pattern of firing across all of your place cells at that location,
这就好像你是通过存储被某一特定位置所激发的“定位细胞”产生的信号模式，来记忆小旗的位置的，
and then you can get back to that location by moving around
接着当你回到那个地点的时候，通过四处打量，
so that you best match the current pattern of firing of your place cells with that stored pattern.
便可以将你当前脑中“定位细胞”的信号模式与之前的模式进行匹配。
That guides you back to the location that you want to remember.
这个过程便可让你回到“老地方”。
But we also know where we are through movement.
我们也能通过位移来给自己定位。
So if we take some outbound path -- perhaps we park and we wander off
因此当我们外出时--或许是我们停车后下来随便走走
we know because our own movements, which we can integrate over this path roughly what the heading direction is to go back.
我们可以给自己定位，因为我们可以粗略地将自己的运动路线与大体的返回方向进行整合。
And place cells also get this kind of path integration input from a kind of cell called a grid cell.
“定位细胞”也能从一种叫做“网状细胞”的细胞那儿获得此类线路整合的信息。
Now grid cells are found, again, on the inputs to the hippocampus, and they're a bit like place cells.
目前在向海马区的信号输入中又发现了“网状细胞”，它们与“定位细胞”有点类似。
But now as the rat explores around, each individual cell fires in a whole array of different locations
随着老鼠的“四处探索”，每一个神经元细胞被大量各种位置所激发的信号组合在一起，
which are laid out across the environment in an amazingly regular triangular grid.
贯穿整个环境，构成一个令人惊叹的规整的三角网格。倘
And if you record from several grid cells -- shown here in different colors
若你对一系列“网状细胞”进行记录--这里以不同的颜色区分，
each one has a grid-like firing pattern across the environment,
每一个细胞发出的信号都能形成网状，遍及整个环境，
and each cell's grid-like firing pattern is shifted slightly relative to the other cells.
而且每一个细胞的网状信号集的位置都与其他细胞有一定偏差。
So the red one fires on this grid and the green one on this one and the blue on on this one.
因此红色标注的细胞信号集合在这个网格上，绿色的是这个，而蓝色的是这个。
So together, it's as if the rat can put a virtual grid of firing locations across its environment
因此综合来看，这就好像老鼠可以在它所到达的环境中建立一个虚拟的位置信号网，
a bit like the latitude and longitude lines that you'd find on a map, but using triangles.
这就有点像你在地图上所看到的经线和纬线，只不过要将线替换成“三角形”。
And as it moves around, the electrical activity can pass from one of these cells to the next cell to keep track of where it is,
当老鼠移动的时候，这些电信号能通过这些细胞传递给下一个神经元细胞，从而为老鼠定位，
so that it can use its own movements to know where it is in its environment.
这样老鼠就能在运动时知道自己身在何处。
Do people have grid cells?
那么人类是否有“网状细胞”呢？
Well because all of the grid-like firing patterns have the same axes of symmetry, the same orientations of grid, shown in orange here,
因为所有的网状信号集合体都有相同的对称轴，以及相同的网格朝向，这里以橘红色标识，
it means that the net activity of all of the grid cells in a particular part of the brain should change
这就意味着大脑中特定部位的所有网状细胞的联网行为的变化，
according to whether we're running along these six directions or running along one of the six directions in between.
应该取决于我们是在向着这六个方向运动，还是沿着六个方向之间所夹的某一个方向运动。
So we can put people in an MRI scanner and have them do a little video game like the one I showed you and look for this signal.
我们可以为人们做核磁共振扫描，与此同时让他们玩一个小型电子游戏，还是之前所说的那个游戏，然后来看看当时的信号。
And indeed, you do see it in the human entorhinal cortex, which is the same part of the brain that you see grid cells in rats.
没错，你在人脑中的内嗅皮层上看到了网状细胞，而它们出现的位置和老鼠的网状细胞在大脑中所出现的位置一样。
So back to Homer. He's probably remembering where his car was
现在我们回头看看荷马。他可能回忆起他的车停在哪儿，
in terms of the distances and directions to extended buildings and boundaries around the location where he parked.
凭借的是停车地点与周边建筑以及四周边界的相对距离和方向。
And that would be represented by the firing of boundary-detecting cells.
而那将由专门“检测边界”的神经元细胞发出的信号来执行。
He's also remembering the path he took out of the car park, which would be represented in the firing of grid cells.
他可能也记得自己是怎么从停车场走出来的，而这就有赖于网状细胞发出信号了。
Now both of these kinds of cells can make the place cells fire.
这两种类型的神经元细胞都可以激活“定位细胞”。
And he can return to the location where he parked by moving so as to find
因此荷马成功折返的方法，便是在走动中寻求
where it is that best matches the firing pattern of the place cells in his brain currently with the stored pattern where he parked his car.
与他之前停车时脑中所建立的信号集样式最为匹配的一个脑中即时形成的信号集样式。
And that guides him back to that location irrespective of visual cues like whether his car's actually there.
而那就能将他领回“老地方”了，这个过程与最终的目标视物无关，不论他的车是否还在那儿他都能找到停车点。
Maybe it's been towed. But he knows where it was, so he knows to go and get it.
或许车已经被拖走了，但他仍然知道车原来停在哪儿，因此他会回到原位去取车。
So beyond spatial memory, if we look for this grid-like firing pattern throughout the whole brain,
撇开“空间记忆力”而言，倘若我们单独观察这种网状信号集在整个大脑中的活动情况，
we see it in a whole series of locations which are always active when we do all kinds of autobiographical memory tasks,
就会发现这种信号形式分布广泛，每当我们需要回忆一些自己过去的经历时，这种网状的信号形式就会活跃起来，
like remembering the last time you went to a wedding, for example.
譬如，当你试图回忆上次参加婚礼的情况时。
So it may be that the neural mechanisms for representing the space around us are also used for generating visual imagery
因此有可能，神经元细胞再现空间的功能，也参与视觉画面的呈现，
so that we can recreate the spatial scene, at least, of the events that have happened to us when we want to imagine them.
这样当我们试图回忆一个曾经置身其中的场面时，至少可以借助想象而勾勒出整个场景。
So if this was happening, your memories could start by place cells activating each other via these dense interconnections
倘若事实果真如此，记忆的形成就开始于：“定位细胞”通过这些缜密的连结相互激活，
and then reactivating boundary cells to create the spatial structure of the scene around your viewpoint.
然后“边界感应细胞"被再次激活，从而形成我们视点周围的场景的空间格局。
And grid cells could move this viewpoint through that space.
网状细胞可以使视点穿透那个空间。
Another kind of cell, head direction cells, which I didn't mention yet, they fire like a compass according to which way you're facing.
而另一种“方位细胞”，我之前没有提到它，它们像指南针一样，都是根据你的朝向来作出反应的。
They could define the viewing direction from which you want to generate an image for your visual imagery,
它们可以明确你需要在脑中形成哪个方位的图像，
so you can imagine what happened when you were at this wedding, for example.
就拿回忆婚礼情景来说，以上过程就能让你回想起那一切。
So this is just one example of a new era really in cognitive neuroscience
好了，以上就是在认知神经科学领域所开辟的新纪元，
where we're beginning to understand psychological processes like how you remember or imagine or even think
在这个领域中，我们开始尝试了解人类心理活动产生的过程，比如人们是如何记忆、想象甚至思考的，
in terms of the actions of the billions of individual neurons that make up our brains. Thank you very much.
这是根据大脑中数以亿计的单个神经元细胞的行为得到的。非常感谢各位。