ABOUT THE SPEAKER
Neil Burgess - Neuroscientist
At University College in London, Neil Burgess researches how patterns of electrical activity in brain cells guide us through space.

Why you should listen

Neil Burgessis is deputy director of the Institute of Cognitive Neuroscience at University College London, where he investigates of the role of the hippocampus in spatial navigation and episodic memory. His research is directed at answering questions such as: How are locations represented, stored and used in the brain? What processes and which parts of the brain are involved in remembering the spatial and temporal context of everyday events, and in finding one's way about?

To explore this space, he and his team use a range of methods for gathering data, including pioneering uses of virtual reality, as well as computational modelling and electrophysiological analysis of the function of hippocampal neurons in the rat, functional imaging of human navigation, and neuropsychological experiments on spatial and episodic memory.

A parallel interest: Investigating our human short-term memory for serial order, or how we know our 123s.

More profile about the speaker
Neil Burgess | Speaker | TED.com
TEDSalon London Spring 2011

Neil Burgess: How your brain tells you where you are

Neil Burgess: Como che di o teu cerebro onde estás

Filmed:
1,458,267 views

Como lembramos onde aparcamos o coche? Como sabemos se nos movemos na dirección correcta? O neurocientífico Neil Burgess estuda os mecanismos neuronais que trazan o mapa do espazo que nos rodea e como se relacionan coa memoria e a imaxinación.
- Neuroscientist
At University College in London, Neil Burgess researches how patterns of electrical activity in brain cells guide us through space. Full bio

Double-click the English transcript below to play the video.

00:15
When we park in a big parking lot,
0
0
2000
Cando aparcamos nun estacionamento grande,
00:17
how do we remember where we parked our car?
1
2000
2000
como lembramos onde deixamos o coche?
00:19
Here's the problem facing Homer.
2
4000
3000
Este é o problema que ten Homer.
00:22
And we're going to try to understand
3
7000
2000
E imos tratar de comprender
00:24
what's happening in his brain.
4
9000
2000
o que ocorre no seu cerebro.
00:26
So we'll start with the hippocampus, shown in yellow,
5
11000
2000
Comezaremos co hipocampo,
en amarelo,
00:28
which is the organ of memory.
6
13000
2000
que é o órgano da memoria.
00:30
If you have damage there, like in Alzheimer's,
7
15000
2000
Se se dana, como no alzhéimer,
00:32
you can't remember things including where you parked your car.
8
17000
2000
non se lembran cousas
como onde aparcamos.
00:34
It's named after Latin for "seahorse,"
9
19000
2000
É o nome en latín para 'cabaliño de mar',
00:36
which it resembles.
10
21000
2000
ao que se asemella.
00:38
And like the rest of the brain, it's made of neurons.
11
23000
2000
E como o resto do cerebro,
componse de neuronas.
00:40
So the human brain
12
25000
2000
O cerebro humano
ten uns cen mil millóns de neuronas.
00:42
has about a hundred billion neurons in it.
13
27000
2000
00:44
And the neurons communicate with each other
14
29000
3000
As neuronas comunícanse entre si
00:47
by sending little pulses or spikes of electricity
15
32000
2000
con pequenos impulsos ou picos eléctricos
00:49
via connections to each other.
16
34000
2000
a través das súas conexións.
00:51
The hippocampus is formed of two sheets of cells,
17
36000
3000
O hipocampo componse
de dúas capas de células
00:54
which are very densely interconnected.
18
39000
2000
densamente conectadas.
00:56
And scientists have begun to understand
19
41000
2000
Os científicos comezaron a entender
00:58
how spatial memory works
20
43000
2000
como funciona a memoria espacial
01:00
by recording from individual neurons
21
45000
2000
rastrexando neuronas individuais
01:02
in rats or mice
22
47000
2000
de ratas ou ratos
01:04
while they forage or explore an environment
23
49000
2000
ao alimentárense ou exploraren un medio
01:06
looking for food.
24
51000
2000
en busca de comida.
01:08
So we're going to imagine we're recording from a single neuron
25
53000
3000
Imaxinemos que rexistramos
unha neurona individual
01:11
in the hippocampus of this rat here.
26
56000
3000
do hipocampo desta rata.
01:14
And when it fires a little spike of electricity,
27
59000
2000
Cando dispara un impulso eléctrico,
01:16
there's going to be a red dot and a click.
28
61000
3000
aparece un punto vermello e un clic.
01:19
So what we see
29
64000
2000
O que vemos é
01:21
is that this neuron knows
30
66000
2000
que esta neurona sabe
01:23
whenever the rat has gone into one particular place in its environment.
31
68000
3000
se a rata foi a un lugar
específico do seu medio.
01:26
And it signals to the rest of the brain
32
71000
2000
E dálle un sinal ao resto do cerebro
01:28
by sending a little electrical spike.
33
73000
3000
enviando un pequeno impulso eléctrico.
01:31
So we could show the firing rate of that neuron
34
76000
3000
Así que podemos ver a taxa
de disparos desa neurona
01:34
as a function of the animal's location.
35
79000
2000
como unha función localizadora do animal.
01:36
And if we record from lots of different neurons,
36
81000
2000
E se rastrexamos
moitas neuronas diferentes,
01:38
we'll see that different neurons fire
37
83000
2000
vemos que diferentes neuronas dan sinais
01:40
when the animal goes in different parts of its environment,
38
85000
2000
cando o animal vai a sitios diferentes,
01:42
like in this square box shown here.
39
87000
2000
como nesta caixa cadrada.
01:44
So together they form a map
40
89000
2000
Todas xuntas forman un mapa
01:46
for the rest of the brain,
41
91000
2000
para o resto do cerebro,
01:48
telling the brain continually,
42
93000
2000
dicíndolle continuamente:
01:50
"Where am I now within my environment?"
43
95000
2000
"Onde estou agora no meu contorno?"
01:52
Place cells are also being recorded in humans.
44
97000
3000
As células de lugar
tamén se rexistran en persoas.
01:55
So epilepsy patients sometimes need
45
100000
2000
Os pacientes de epilepsia
ás veces precisan
01:57
the electrical activity in their brain monitoring.
46
102000
3000
que se vixíe a súa actividade
eléctrica cerebral.
02:00
And some of these patients played a video game
47
105000
2000
Algúns pacientes xogaron a un videoxogo
02:02
where they drive around a small town.
48
107000
2000
no que conducían ao redor dunha vila.
02:04
And place cells in their hippocampi would fire, become active,
49
109000
3000
E as células de lugar do hipocampo
dispararían, activaríanse,
02:07
start sending electrical impulses
50
112000
3000
comezarían a enviar impulsos eléctricos
02:10
whenever they drove through a particular location in that town.
51
115000
3000
cada vez que pasaban
por un punto determinado da vila.
02:13
So how does a place cell know
52
118000
2000
Como pode saber unha célula de lugar
02:15
where the rat or person is within its environment?
53
120000
3000
onde está a rata ou a persoa
dentro do seu contorno?
02:18
Well these two cells here
54
123000
2000
Pois ben, estas dúas células
02:20
show us that the boundaries of the environment
55
125000
2000
indícannos que os límites do contorno
02:22
are particularly important.
56
127000
2000
son especialmente importantes.
02:24
So the one on the top
57
129000
2000
A que está arriba
02:26
likes to fire sort of midway between the walls
58
131000
2000
dispara nalgún punto entre as paredes
02:28
of the box that their rat's in.
59
133000
2000
da caixa onde está a rata.
02:30
And when you expand the box, the firing location expands.
60
135000
3000
E se ampliamos a caixa,
amplíase tamén o lugar destes disparos.
02:33
The one below likes to fire
61
138000
2000
A da parte inferior dispara
02:35
whenever there's a wall close by to the south.
62
140000
3000
cando atopa unha parede cara ao sur.
02:38
And if you put another wall inside the box,
63
143000
2000
E se pomos outra parede na caixa,
02:40
then the cell fires in both place
64
145000
2000
a célula dispara a ambos os lados
02:42
wherever there's a wall to the south
65
147000
2000
cada vez que haxa unha parede ao sur
02:44
as the animal explores around in its box.
66
149000
3000
mentres o animal explora a caixa.
02:48
So this predicts
67
153000
2000
Así que isto predí a percepción
02:50
that sensing the distances and directions of boundaries around you --
68
155000
2000
das distancias e direccións
dos límites ao redor,
02:52
extended buildings and so on --
69
157000
2000
edificios grandes e así...,
02:54
is particularly important for the hippocampus.
70
159000
3000
é especialmente importante
para o hipocampo.
02:57
And indeed, on the inputs to the hippocampus,
71
162000
2000
E, de feito, nas entradas do hipocampo,
02:59
cells are found which project into the hippocampus,
72
164000
2000
hai células que se proxectan no hipocampo,
03:01
which do respond exactly
73
166000
2000
que responden exactamente
03:03
to detecting boundaries or edges
74
168000
3000
á detección de límites ou bordos
03:06
at particular distances and directions
75
171000
2000
en distancias específicas e direccións
03:08
from the rat or mouse
76
173000
2000
desde onde a rata ou o rato
03:10
as it's exploring around.
77
175000
2000
explora o contorno.
03:12
So the cell on the left, you can see,
78
177000
2000
Así que a célula á esquerda, como vedes,
03:14
it fires whenever the animal gets near
79
179000
2000
dispara cando o animal se achega
03:16
to a wall or a boundary to the east,
80
181000
3000
a unha parede ou límite no leste,
03:19
whether it's the edge or the wall of a square box
81
184000
3000
sexa o bordo ou a parede
dun espazo cadrado
03:22
or the circular wall of the circular box
82
187000
2000
ou a parede dun espazo circular,
03:24
or even the drop at the edge of a table, which the animals are running around.
83
189000
3000
ou mesmo o bordo dunha mesa
cando o animal a percorre.
03:27
And the cell on the right there
84
192000
2000
E a célula da dereita
03:29
fires whenever there's a boundary to the south,
85
194000
2000
dispara sempre que hai un bordo ao sur,
03:31
whether it's the drop at the edge of the table or a wall
86
196000
2000
sexa o bordo dunha mesa ou unha parede
03:33
or even the gap between two tables that are pulled apart.
87
198000
3000
ou mesmo o baleiro
entre dúas mesas que se separan.
03:36
So that's one way in which we think
88
201000
2000
Esa é unha forma en que pensamos
03:38
place cells determine where the animal is as it's exploring around.
89
203000
3000
que as células de lugar determinan
onde está o animal mentres explora.
03:41
We can also test where we think objects are,
90
206000
3000
Podemos probar tamén
onde cremos que están os obxectos,
03:44
like this goal flag, in simple environments --
91
209000
3000
como esta bandeira, en medios simples,
03:47
or indeed, where your car would be.
92
212000
2000
ou mesmo, onde deberiamos ter o coche.
03:49
So we can have people explore an environment
93
214000
3000
Pode haber xente que explore un medio
03:52
and see the location they have to remember.
94
217000
3000
e observe a posición que ten que lembrar.
03:55
And then, if we put them back in the environment,
95
220000
2000
E, se os levamos outra vez ao medio,
03:57
generally they're quite good at putting a marker down
96
222000
2000
xeralmente son bastante bos ao marcar
03:59
where they thought that flag or their car was.
97
224000
3000
onde pensaron que estaría
a bandeira ou o coche.
04:02
But on some trials,
98
227000
2000
Pero nalgunhas probas,
04:04
we could change the shape and size of the environment
99
229000
2000
poderiamos cambiar
a forma e o tamaño do medio
04:06
like we did with the place cell.
100
231000
2000
como fixemos coa célula de lugar.
04:08
In that case, we can see
101
233000
2000
Nese caso, podemos ver
04:10
how where they think the flag had been changes
102
235000
3000
como cambia onde pensan
que estaba a bandeira,
04:13
as a function of how you change the shape and size of the environment.
103
238000
3000
en función de como cambiamos
a forma e o tamaño do medio.
04:16
And what you see, for example,
104
241000
2000
Vemos, por exemplo,
04:18
if the flag was where that cross was in a small square environment,
105
243000
3000
se a bandeira estaba onda a cruz
dun espazo pequeno cadrado
04:21
and then if you ask people where it was,
106
246000
2000
e lle preguntamos á xente onde estaba
04:23
but you've made the environment bigger,
107
248000
2000
pero aumentamos o espazo,
04:25
where they think the flag had been
108
250000
2000
o lugar onde crían que estaba a bandeira
04:27
stretches out in exactly the same way
109
252000
2000
amplíase exactamente da mesma maneira
04:29
that the place cell firing stretched out.
110
254000
2000
que os disparos da célula de lugar.
04:31
It's as if you remember where the flag was
111
256000
2000
É coma se lembrásedes
onde estaba a bandeira
04:33
by storing the pattern of firing across all of your place cells
112
258000
3000
gardando o patrón de disparos
a través das células de lugar
04:36
at that location,
113
261000
2000
nesa posición,
04:38
and then you can get back to that location
114
263000
2000
e puidésedes volver á posición
04:40
by moving around
115
265000
2000
movéndovos
ata facer coincidir o padrón actual
das células de lugar
04:42
so that you best match the current pattern of firing of your place cells
116
267000
2000
04:44
with that stored pattern.
117
269000
2000
co outro padrón almacenado.
04:46
That guides you back to the location that you want to remember.
118
271000
3000
Iso guíanos de volta
á posición que queremos lembrar.
04:49
But we also know where we are through movement.
119
274000
3000
Pero tamén sabemos onde estamos
a través do movemento.
04:52
So if we take some outbound path --
120
277000
2000
Se collemos un camiño de saída,
04:54
perhaps we park and we wander off --
121
279000
2000
quizais aparcamos e damos unha volta,
04:56
we know because our own movements,
122
281000
2000
sabemos polos nosos movementos,
04:58
which we can integrate over this path
123
283000
2000
que podemos integrar nese camiño,
05:00
roughly what the heading direction is to go back.
124
285000
2000
cal é a dirección para volver.
05:02
And place cells also get this kind of path integration input
125
287000
4000
E as células de lugar
tamén integran esa información
05:06
from a kind of cell called a grid cell.
126
291000
3000
a través dun tipo de célula
chamada célula grella.
05:09
Now grid cells are found, again,
127
294000
2000
As células grella tamén se atopan
05:11
on the inputs to the hippocampus,
128
296000
2000
nas entradas ao hipocampo,
05:13
and they're a bit like place cells.
129
298000
2000
son un pouco como as células de lugar.
05:15
But now as the rat explores around,
130
300000
2000
Pero neste caso cando a rata explora,
05:17
each individual cell fires
131
302000
2000
cada célula individual dispara
05:19
in a whole array of different locations
132
304000
3000
a un rango de lugares moi diferentes
05:22
which are laid out across the environment
133
307000
2000
que están espallados polo medio
05:24
in an amazingly regular triangular grid.
134
309000
3000
nunha impresionante rede triangular.
05:29
And if you record from several grid cells --
135
314000
3000
E se rastrexades varias células grella,
05:32
shown here in different colors --
136
317000
2000
aquí en diferentes cores,
05:34
each one has a grid-like firing pattern across the environment,
137
319000
3000
cada unha ten un padrón de disparos
nese medio como unha rede
05:37
and each cell's grid-like firing pattern is shifted slightly
138
322000
3000
e o padrón de disparos
de cada célula rede cambia lixeiramente
05:40
relative to the other cells.
139
325000
2000
en relación coas outras células.
05:42
So the red one fires on this grid
140
327000
2000
Así que a vermella dispara nesta rede
05:44
and the green one on this one and the blue on on this one.
141
329000
3000
e a verde nesta e a azul nesta.
05:47
So together, it's as if the rat
142
332000
3000
E xuntas, é coma se a rata
05:50
can put a virtual grid of firing locations
143
335000
2000
fixese unha rede
virtual de posicións de disparos
05:52
across its environment --
144
337000
2000
por todo o medio,
05:54
a bit like the latitude and longitude lines that you'd find on a map,
145
339000
3000
un pouco como as liñas de latitude e
lonxitude que hai nun mapa
05:57
but using triangles.
146
342000
2000
pero con triángulos.
05:59
And as it moves around,
147
344000
2000
E ao moverse,
06:01
the electrical activity can pass
148
346000
2000
a actividade eléctrica pode pasar
06:03
from one of these cells to the next cell
149
348000
2000
desde unha destas células á próxima
06:05
to keep track of where it is,
150
350000
2000
para seguir a pista de onde está,
06:07
so that it can use its own movements
151
352000
2000
para que poida usar os propios movementos
06:09
to know where it is in its environment.
152
354000
2000
e saber onde está no contorno.
06:11
Do people have grid cells?
153
356000
2000
A xente ten células grella?
06:13
Well because all of the grid-like firing patterns
154
358000
2000
Ben, que todos os padróns
que disparan en rede
06:15
have the same axes of symmetry,
155
360000
2000
teñan os mesmos eixes de simetrías,
06:17
the same orientations of grid, shown in orange here,
156
362000
3000
a mesma orientación da rede,
en laranxa aquí,
06:20
it means that the net activity
157
365000
2000
quere dicir que a actividade
06:22
of all of the grid cells in a particular part of the brain
158
367000
3000
de todas as células grella
nun lugar particular do cerebro
06:25
should change
159
370000
2000
debería cambiar
06:27
according to whether we're running along these six directions
160
372000
2000
segundo esteamos correndo
nestas seis direccións
06:29
or running along one of the six directions in between.
161
374000
3000
ou nunha das seis direccións intermedias.
06:32
So we can put people in an MRI scanner
162
377000
2000
Podemos poñer xente nun escáner IRM
06:34
and have them do a little video game
163
379000
2000
e darlle un pequeno videoxogo
06:36
like the one I showed you
164
381000
2000
como o que vos amosei
06:38
and look for this signal.
165
383000
2000
e buscar este sinal.
06:40
And indeed, you do see it in the human entorhinal cortex,
166
385000
3000
E vedes no córtex entorrinal humano,
06:43
which is the same part of the brain that you see grid cells in rats.
167
388000
3000
que está na mesma parte do cerebro
que as células grella das ratas.
06:46
So back to Homer.
168
391000
2000
Así que volvendo a Homer.
06:48
He's probably remembering where his car was
169
393000
2000
Estará lembrando onde puxo o coche
06:50
in terms of the distances and directions
170
395000
2000
en termos de distancias e direccións
06:52
to extended buildings and boundaries
171
397000
2000
cara a edificios extensos e límites
06:54
around the location where he parked.
172
399000
2000
ao redor da posición onde aparcou.
06:56
And that would be represented
173
401000
2000
E iso estará representado
06:58
by the firing of boundary-detecting cells.
174
403000
2000
polos disparos de células
detectoras de límites.
07:00
He's also remembering the path he took out of the car park,
175
405000
3000
Tamén estará lembrando o camiño
que colleu fóra do aparcamento,
07:03
which would be represented in the firing of grid cells.
176
408000
3000
que estará representado
nos disparos de células grella.
07:06
Now both of these kinds of cells
177
411000
2000
Ambos os tipos de células
07:08
can make the place cells fire.
178
413000
2000
poden facer disparar as células.
07:10
And he can return to the location where he parked
179
415000
2000
E el pode volver ao lugar onde aparcou
07:12
by moving so as to find where it is
180
417000
3000
movéndose para atopalo
07:15
that best matches the firing pattern
181
420000
2000
ata que encaixe o padrón de disparos
07:17
of the place cells in his brain currently
182
422000
2000
das células de lugar
07:19
with the stored pattern where he parked his car.
183
424000
3000
co padrón almacenado
de onde aparcou o seu coche.
07:22
And that guides him back to that location
184
427000
2000
E iso guíao de volta á posición
07:24
irrespective of visual cues
185
429000
2000
independentemente das pistas visuais
07:26
like whether his car's actually there.
186
431000
2000
coma se o seu coche estivese alí.
07:28
Maybe it's been towed.
187
433000
2000
Pode que llo levara o guindastre.
07:30
But he knows where it was, so he knows to go and get it.
188
435000
3000
Pero el sabe onde estaba, así
que sabe onde ir e collelo.
07:33
So beyond spatial memory,
189
438000
2000
Máis alá da memoria espacial,
07:35
if we look for this grid-like firing pattern
190
440000
2000
se buscamos este padrón rede
07:37
throughout the whole brain,
191
442000
2000
a través de todo o cerebro,
07:39
we see it in a whole series of locations
192
444000
3000
vémolo nunha serie de posicións
07:42
which are always active
193
447000
2000
que están sempre activas
ao facermos tarefas
de memoria autobiográfica,
07:44
when we do all kinds of autobiographical memory tasks,
194
449000
2000
07:46
like remembering the last time you went to a wedding, for example.
195
451000
3000
como lembrar a última vez
que fomos a unha voda.
07:49
So it may be that the neural mechanisms
196
454000
2000
Pode que os mecanismos neuronais
07:51
for representing the space around us
197
456000
3000
para representar o espazo ao noso redor
07:54
are also used for generating visual imagery
198
459000
4000
se usen tamén
para xerar imaxinaría visual,
07:58
so that we can recreate the spatial scene, at least,
199
463000
3000
para que poidamos recrear
a escena espacial, polo menos,
08:01
of the events that have happened to us when we want to imagine them.
200
466000
3000
dos eventos que nos ocorreron
cando os imaxinamos.
08:04
So if this was happening,
201
469000
2000
Se isto ocorrese,
08:06
your memories could start by place cells activating each other
202
471000
3000
as vosas memorias comezarían
activando entre si as células de lugar
08:09
via these dense interconnections
203
474000
2000
a través desas densas conexións
08:11
and then reactivating boundary cells
204
476000
2000
e reactivando células límite
08:13
to create the spatial structure
205
478000
2000
para crear a estrutura espacial
08:15
of the scene around your viewpoint.
206
480000
2000
ao redor da vosa perspectiva.
08:17
And grid cells could move this viewpoint through that space.
207
482000
2000
E as células grella poderían
mover a perspectiva no espazo.
08:19
Another kind of cell, head direction cells,
208
484000
2000
Outro tipo de célula,
as de dirección da cabeza,
08:21
which I didn't mention yet,
209
486000
2000
que aínda non mencionei,
08:23
they fire like a compass according to which way you're facing.
210
488000
3000
disparan como un compás
de acordo co camiño que seguides.
08:26
They could define the viewing direction
211
491000
2000
Poden definir a dirección da vista
08:28
from which you want to generate an image for your visual imagery,
212
493000
3000
desde onde queredes xerar unha imaxe
para a vosa imaxinaría visual,
08:31
so you can imagine what happened when you were at this wedding, for example.
213
496000
3000
así que podedes imaxinar
o que ocorreu nesa voda, por exemplo.
08:34
So this is just one example
214
499000
2000
Isto é só un exemplo
08:36
of a new era really
215
501000
2000
dunha nova era
08:38
in cognitive neuroscience
216
503000
2000
da neurociencia cognitiva,
08:40
where we're beginning to understand
217
505000
2000
cando comezamos a entender
08:42
psychological processes
218
507000
2000
procesos psicolóxicos,
08:44
like how you remember or imagine or even think
219
509000
3000
como o xeito en que lembramos
ou imaxinamos ou mesmo pensamos
08:47
in terms of the actions
220
512000
2000
en termos de accións
08:49
of the billions of individual neurons that make up our brains.
221
514000
3000
dos centos de miles de neuronas
individuais que forman o cerebro.
08:52
Thank you very much.
222
517000
2000
Moitas grazas.
08:54
(Applause)
223
519000
3000
(Aplausos)
Translated by Carme Paz
Reviewed by Xusto Rodriguez

▲Back to top

ABOUT THE SPEAKER
Neil Burgess - Neuroscientist
At University College in London, Neil Burgess researches how patterns of electrical activity in brain cells guide us through space.

Why you should listen

Neil Burgessis is deputy director of the Institute of Cognitive Neuroscience at University College London, where he investigates of the role of the hippocampus in spatial navigation and episodic memory. His research is directed at answering questions such as: How are locations represented, stored and used in the brain? What processes and which parts of the brain are involved in remembering the spatial and temporal context of everyday events, and in finding one's way about?

To explore this space, he and his team use a range of methods for gathering data, including pioneering uses of virtual reality, as well as computational modelling and electrophysiological analysis of the function of hippocampal neurons in the rat, functional imaging of human navigation, and neuropsychological experiments on spatial and episodic memory.

A parallel interest: Investigating our human short-term memory for serial order, or how we know our 123s.

More profile about the speaker
Neil Burgess | Speaker | TED.com