Fast-Forward

Playback

of

Recent

Memory

Sequences

in

Prefrontal

Cortex

During

Sleep

David

R.

Euston

et

al.

Science

-LRB-

-RRB-

DOI

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REPORTS

Fast-Forward

Playback

of

Recent

Memory

Sequences

in

Prefrontal

Cortex

During

Sleep

David

R.

Euston

Masami

Tatsuno

Bruce

L.

McNaughton

As

previously

shown

in

the

hippocampus

and

other

brain

areas

patterns

of

firing-rate

correlations

between

neurons

in

the

rat

medial

prefrontal

cortex

during

a

repetitive

sequence

task

were

preserved

during

subsequent

sleep

suggesting

that

waking

patterns

are

reactivated

We

found

that

during

sleep

reactivation

of

spatiotemporal

patterns

was

coherent

across

the

network

and

compressed

in

time

by

a

factor

of

to

Thus

when

behavioral

constraints

are

removed

the

brain

's

intrinsic

processing

speed

may

be

much

faster

than

it

is

in

real

time

Given

recent

evidence

implicating

the

medial

prefrontal

cortex

in

retrieval

of

long-term

memories

the

observed

replay

may

play

a

role

in

the

process

of

memory

consolidation

ccording

to

memory-consolidation

theory

the

hippocampus

is

necessary

for

the

retrieval

of

recently

encoded

episodic

memories

For

remote

memories

in

contrast

the

neocortex

is

sufficient

for

recall

-LRB-

-RRB-

The

transfer

of

memories

from

hippocampal

to

neocortical

control

is

widely

believed

to

involve

replay

during

sleep

of

the

neural

patterns

representing

the

memory

-LRB-

-RRB-

Consistent

with

this

hypothesis

patterns

of

brain

activity

during

a

task

appear

to

be

repeated

during

subsequent

sleep

in

rats

birds

monkeys

and

humans

-LRB-

-RRB-

In

rats

multielectrode

hippocampal

recordings

have

shown

that

the

temporal

order

of

replay

during

sleep

is

preserved

-LRB-

-RRB-

Among

cortical

areas

the

medial

prefrontal

cortex

-LRB-

mPFC

-RRB-

apparently

plays

a

unique

role

in

mediating

retrieval

of

consolidated

remote

memories

In

both

rats

and

humans

activity

in

the

mPFC

is

greater

during

retrieval

of

remote

memories

than

during

retrieval

of

recent

memories

an

opposite

pattern

is

seen

in

the

hippocampus

-LRB-

-RRB-

In

addition

lesions

of

mPFC

lead

to

deficits

in

retrieval

of

remote

memories

-LRB-

-RRB-

One

might

thus

expect

the

mPFC

to

play

a

key

role

in

memory

consolidation

Indeed

disrupting

mPFC

activity

during

consolidation

impairs

subsequent

performance

-LRB-

-RRB-

If

mPFC

does

play

a

role

in

consolidation

task-induced

neural

activity

patterns

in

mPFC

may

replay

during

subsequent

sleep

We

therefore

examined

neural

ensemble

activity

after

performance

of

a

spatial

sequence

task

Two

rats

were

trained

to

run

to

a

series

of

locations

around

the

perimeter

of

a

circular

platform

with

electrical

brain

stimulation

as

a

reward

Sequences

consisting

of

eight

locations

were

repeated

throughout

the

course

of

a

running

session

alternating

in

blocks

of

three

cued

and

three

noncued

-LRB-

i.e.

memory-guided

-RRB-

sequences

A

throughout

the

session

Each

day

a

rat

ran

the

sequence

task

continuously

during

two

blocks

Neural

activity

was

recorded

during

a

pretask

sleep

period

preceding

the

first

task

block

and

Arizona

Research

Laboratories

Division

of

Neural

Systems

Memory

and

Aging

University

of

Arizona

Tucson

AZ

USA

To

whom

correspondence

should

be

addressed

E-mail

bruce@nsma.arizona.edu

Fig.

Cross-correlations

between

mPFC

cell

pairs

during

task

and

sleep

-LRB-

A

-RRB-

Example

cross-correlations

from

four

cell

pairs

Each

column

shows

data

from

one

cell

pair

during

pre-task

sleep

task

and

post-task

sleep

The

y

axis

shows

the

number

of

coincident

spikes

per

second

within

each

bin

-LRB-

B

-RRB-

Sorted

cross-correlations

from

simultaneously

recorded

cell

pairs

Each

row

in

each

subpanel

shows

the

crosscorrelation

between

a

single

pair

of

cells

scaled

so

that

peak

and

valley

range

from

zero

to

one

The

rows

are

sorted

according

to

the

temporal

offset

of

the

maximum

peak

during

the

task

In

addition

only

cell

pairs

showing

a

peak

z

score

exceeding

during

the

task

were

included

-LRB-

to

see

Supporting

Online

Material

for

details

-RRB-

Red

indicates

the

highest

coincidence

rate

and

blue

the

lowest

The

time

axis

during

sleep

epochs

is

magnified

SCIENCE

VOL

NOVEMBER

Downloaded

from

on

May

in

two

post-task

sleep

periods

following

each

task

block

Each

sleep

session

was

to

min

in

duration

Both

rats

were

implanted

with

microdrives

containing

independently

manipulable

four-conductor

electrodes

-LRB-

tetrodes

-RRB-

-LRB-

-RRB-

allowing

simultaneous

recording

of

to

neurons

within

the

anterior

cingulate

and

prelimbic

cortices

Memory

reactivation

was

assessed

during

periods

of

motionlessness

during

the

sleep

session

The

reactivation

of

the

task-related

neural

patterns

was

initially

assessed

with

a

measure

called

explained

variance

-LRB-

EV

-RRB-

based

on

the

firing

rate

correlation

matrix

for

all

pairs

of

concurrently

recorded

cells

-LRB-

-RRB-

Explained

variance

measures

the

proportion

of

variability

in

the

cellpair

firing-rate

correlations

during

task

performance

that

can

be

accounted

for

by

correlations

during

subsequent

sleep

taking

into

account

the

correlations

that

existed

in

the

initial

sleep

session

For

this

measure

would

mean

that

cell-pair

correlations

during

task

and

subsequent

sleep

were

identical

Previous

reactivation

studies

have

found

average

EV

values

of

REPORTS

in

rat

hippocampus

in

rat

ventral

striatum

and

between

and

in

monkey

cortex

-LRB-

-RRB-

Average

EV

in

the

current

study

was

across

two

rats

and

a

total

of

sessions

The

distribution

of

values

was

strongly

skewed

the

average

of

EV

values

within

the

lower

quartile

was

and

that

in

the

upper

quartile

Reactivation

was

significantly

stronger

in

the

sleep

following

the

second

task

period

than

in

the

sleep

following

the

first

-LRB-

versus

Student

's

t

test

P

-RRB-

At

least

in

some

sessions

reactivation

in

mPFC

was

as

strong

as

if

not

stronger

than

that

reported

in

the

hippocampus

or

other

parts

of

the

brain

Cross-correlations

of

spike

trains

from

pairs

of

cells

were

used

to

examine

the

temporal

structure

of

replaying

patterns

in

mPFC

Analyses

were

limited

to

the

second

post-task

sleep

which

is

the

period

showing

strongest

EV

Cells

in

mPFC

tend

to

fire

at

specific

locations

along

a

segment

with

the

majority

firing

selectively

during

either

approach

to

or

departure

from

at

least

some

reward

zones

These

response

characteristics

combined

with

the

repetitive

nature

of

the

task

led

to

distinct

peaks

and

valleys

in

many

of

the

cross-correlation

plots

-LRB-

Fig.

-RRB-

indicating

consistent

temporal

relationships

in

neuronal

firing

For

some

cell

pairs

the

increased

number

of

central

peaks

and

valleys

seen

during

the

task

were

evident

again

in

the

post-task

sleep

but

highly

compressed

in

time

suggesting

that

temporal

patterns

playing

during

the

task

were

replaying

during

sleep

at

an

accelerated

rate

Peaks

and

valleys

were

small

or

nonexistent

during

pre-task

sleep

suggesting

that

the

replaying

patterns

were

induced

by

taskrelated

activity

Similar

results

were

obtained

when

data

from

multiple

cell

pairs

within

the

same

session

were

compared

together

-LRB-

Fig.

-RRB-

To

quantify

the

extent

to

which

neural

patterns

during

sleep

evolved

at

a

faster

rate

than

those

during

the

task

times

of

cross-correlation

peaks

during

task

and

sleep

were

automatically

extracted

and

compared

-LRB-

Fig.

-RRB-

For

peaks

nearest

the

origin

a

strong

linear

relation

was

found

between

task

and

sleep

peak

times

with

slopes

indicating

that

replay

during

sleep

is

compressed

relative

to

the

task

Because

this

analysis

requires

many

cell

pairs

with

matching

task

and

sleep

cross-correlations

compression

rates

were

only

computed

for

sessions

where

the

explained

variance

exceeded

a

total

of

sessions

-LRB-

rat

rat

-RRB-

Compression

rates

varied

between

and

with

a

mean

of

-LRB-

Fig.

-RRB-

The

temporal

extent

of

replay

is

limited

The

attenuation

of

a

given

peak

during

sleep

seems

to

be

proportional

to

the

offset

of

the

corresponding

peak

during

the

task

with

peaks

beyond

about

s

being

almost

completely

lost

-LRB-

Fig.

-RRB-

To

quantify

the

duration

of

the

replay

window

we

compared

sleep

and

compressed

task

cross-correlations

at

different

offset

times

-LRB-

Fig.

-RRB-

The

correlation

between

sleep

and

task

cross-correlations

was

strongest

near

zero

and

then

dropped

off

rapidly

reaching

near

chance

levels

around

ms

-LRB-

Fig.

-RRB-

This

suggested

that

replaying

patterns

were

on

average

coherent

for

a

duration

of

s

-LRB-

ms

-RRB-

during

sleep

Assuming

times

compression

the

mPFC

was

evidently

replaying

behavioral

events

spanning

s

during

the

task

-LRB-

about

half

of

a

complete

eight-element

sequence

-RRB-

Template

matching

-LRB-

-RRB-

was

used

to

assess

whether

the

replay

evident

in

pairwise

activity

was

coherent

across

ensembles

of

cells

For

each

of

the

eight

sequence

segments

we

created

a

template

by

averaging

binned

firing

rates

of

a

group

of

cells

across

multiple

repetitions

of

the

sequence

-LRB-

Fig.

left

-RRB-

As

expected

many

strong

matches

to

each

template

were

observed

during

the

task

Strong

matches

were

also

observed

during

post-task

sleep

but

only

when

sleep

bin

size

was

reduced

effectively

compressing

the

template

relative

to

sleep

-LRB-

Fig.

right

-RRB-

Indeed

the

highest

number

of

strong

matches

occurred

for

compression

factors

of

to

-LRB-

Fig.

-RRB-

in

accord

with

estimates

based

on

matching

cross-correlation

peaks

Few

matches

were

observed

when

the

template

column

order

was

reversed

indicating

that

replay

occurs

in

the

forward

direction

Whether

the

observed

mPFC

replay

during

the

first

hour

of

sleep

represents

off-line

rehearsal

needed

for

memory

recoding

remains

an

open

question

however

the

time

frame

coincides

with

what

other

research

suggests

is

a

critical

window

for

memory

processing

Studies

in

humans

have

shown

that

memory

is

tied

to

slowwave

activity

within

the

first

few

hours

of

sleep

-LRB-

-RRB-

In

rats

local

injection

of

drugs

disruptive

to

mPFC

function

leads

to

learning

deficits

when

given

within

hours

after

a

task

but

not

after

this

time

-LRB-

-RRB-

The

hippocampus

reportedly

replays

events

at

to

times

their

behavioral

rate

-LRB-

-RRB-

Fig.

Quantification

of

temporal

compression

during

reactivation

-LRB-

A

-RRB-

Task

cross-correlation

peak

times

plotted

against

post-task

sleep

peak

times

In

each

case

two

peaks

are

extracted

from

each

crosscorrelation

one

on

the

left

of

zero

and

one

on

the

right

Matches

in

the

upper

left

and

lower

right

quadrants

of

the

graph

are

thus

precluded

Estimating

compression

rate

depended

upon

finding

corresponding

peaks

Therefore

cell

pairs

were

limited

to

those

showing

strong

similarity

between

task

and

sleep

cross-correlations

after

accounting

for

compression

-LRB-

i.e.

cell

pairs

exhibiting

strong

reactivation

-RRB-

The

best-fit

regression

line

was

found

with

robust

regression

a

technique

less

sensitive

to

outliers

than

normal

regression

-LRB-

B

-RRB-

Histogram

of

compression

rates

extracted

with

the

analysis

shown

in

-LRB-

A

-RRB-

Fig.

Temporal

extent

of

replay

window

-LRB-

A

-RRB-

Cross-correlations

from

post-task

sleep

-LRB-

dashed

line

-RRB-

and

task

-LRB-

solid

line

-RRB-

were

compared

with

the

use

of

a

sliding

window

-LRB-

gray

bar

-RRB-

In

this

example

the

task

cross-correlation

has

been

compressed

by

a

factor

of

-LRB-

B

-RRB-

Strength

of

the

correlation

between

task

and

sleep

cross-correlations

in

each

window

plotted

against

time

-LRB-

as

measured

with

the

sleep

time

frame

-RRB-

Data

shown

were

averaged

across

all

high

reactivation

sessions

with

vertical

bars

indicating

the

SEM

Data

from

negative

time

windows

were

averaged

with

the

corresponding

positive

time

windows

NOVEMBER

VOL

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REPORTS

Fig.

Template

matching

-LRB-

A

-RRB-

-LRB-

Left

-RRB-

Template

from

one

segment

of

the

sequence

showing

firing

rate

-LRB-

spikes/bin

-RRB-

from

multiple

cells

-LRB-

y

axis

-RRB-

sorted

by

time

of

peak

firing

-LRB-

x

axis

-RRB-

-LRB-

Middle

-RRB-

Examples

of

good

matches

to

the

template

from

sleep

-LRB-

bottom

-RRB-

and

task

-LRB-

top

-RRB-

periods

Bin

size

for

the

task

and

sleep

examples

are

ms

and

ms

respectively

the

latter

representing

a

compression

factor

of

-LRB-

Right

-RRB-

The

two

graphs

show

histograms

of

match

strength

-LRB-

z

scores

-RRB-

between

templates

and

target

data

within

sequentially

ordered

windows

Z

scores

were

derived

via

random

shuffling

of

template

columns

Color

indicates

the

number

of

matches

In

the

top

graph

template

and

target

bin

size

are

the

same

In

the

bottom

graph

target

bin

size

is

a

factor

of

smaller

than

in

the

template

The

time

axis

is

discontinuous

because

first

task

and

second

sleep

period

were

omitted

-LRB-

B

-RRB-

Match

strength

between

template

and

a

portion

of

post-task

sleep

data

at

different

compression

factors

-LRB-

indicating

the

extent

to

which

sleep

replay

is

compressed

relative

to

the

task

-RRB-

Most

of

the

strong

matches

-LRB-

i.e.

red

vertical

bands

-RRB-

had

peaks

corresponding

to

compression

factors

between

and

-LRB-

C

-RRB-

For

each

compression

factor

the

number

of

local

maxima

-LRB-

i.e.

peaks

-RRB-

with

a

z

score

exceeding

was

divided

by

the

total

number

of

peaks

-LRB-

Ratio

of

Peaks

-RRB-

Data

are

averaged

over

all

eight

templates

with

the

SEM

indicated

Neither

post-task

sleep

with

reversed

templates

nor

pre-task

sleep

showed

strong

matches

or

evidence

of

a

peak

compression

rate

however

in

the

hippocampus

spikes

representing

adjacent

place

fields

occur

in

rapid

succession

within

a

single

theta

cycle

during

behavior

-LRB-

-RRB-

Relative

to

this

within

theta

cycle

rate

reactivation

during

sleep

is

not

accelerated

In

contrast

reactivation

in

rat

mPFC

is

clearly

compressed

five

to

eight

times

and

a

similar

effect

may

be

present

in

primary

visual

cortex

-LRB-

-RRB-

Fast

replay

in

neocortex

may

reflect

the

speed

of

the

brain

's

intrinsic

dynamics

-LRB-

e.g.

conduction

speeds

synaptic

delays

etc.

-RRB-

when

not

constrained

by

behavioral

events

However

the

episodes

of

sequential

replay

during

sleep

are

limited

to

windows

of

a

few

hundred

milliseconds

This

may

reflect

a

time

limitation

imposed

by

the

duration

of

cortical

up

states

induced

by

slowwave

oscillations

-LRB-

-RRB-

during

which

replay

presumably

occurs

or

it

may

reflect

cumulative

drift

error

in

the

sequence

replay

In

conclusion

two

independent

analytical

methods

cross-correlation

matching

and

tem

plate

matching

both

clearly

showed

accelerated

replay

of

task-related

neural

activity

patterns

within

the

mPFC

during

sleep

That

this

happens

-LRB-

i

-RRB-

in

an

area

implicated

in

remote

memory

retrieval

and

-LRB-

ii

-RRB-

during

a

time

window

in

which

processes

critical

to

consolidation

are

unfolding

suggests

that

accelerated

replay

may

be

an

important

part

of

the

process

whereby

hippocampus-dependent

memories

become

cortex-dependent

References

and

Notes

W.

B.

Scoville

B.

Milner

J.

Neurol

Neurosurg

Psychiatry

-LRB-

-RRB-

L.

R.

Squire

N.

J.

Cohen

L.

Nadel

in

Memory

Consolidation

G.

Weingartner

E.

Parker

Eds

-LRB-

Erlbaum

Hillsdale

-RRB-

pp.

J.

L.

McGaugh

Science

-LRB-

-RRB-

B.

L.

McNaughton

et

al.

in

Sleep

and

Brain

Plasticity

P.

Maquet

C.

Smith

R.

Stickgold

Eds

-LRB-

Oxford

Univ.

Press

New

York

-RRB-

pp.

D.

Marr

Philos

Trans

R.

Soc

B

Biol

Sci

-LRB-

-RRB-

J.

L.

McClelland

B.

L.

McNaughton

R.

C.

O'Reilly

Psychol

Rev.

-LRB-

-RRB-

G.

Buzsaki

J.

Sleep

Res

-LRB-

suppl

-RRB-

-LRB-

-RRB-

C.

Pavlides

J.

Winson

J.

Neurosci

-LRB-

-RRB-

M.

A.

Wilson

B.

L.

McNaughton

Science

-LRB-

-RRB-

S.

Ribeiro

V.

Goyal

C.

V.

Mello

C.

Pavlides

Learn

Mem

-LRB-

-RRB-

P.

Maquet

et

al.

Nat

Neurosci

-LRB-

-RRB-

A.

S.

Dave

D.

Margoliash

Science

-LRB-

-RRB-

K.

L.

Hoffman

B.

L.

McNaughton

Science

-LRB-

-RRB-

C.

M.

Pennartz

et

al.

J.

Neurosci

-LRB-

-RRB-

P.

Peigneux

et

al.

Neuron

-LRB-

-RRB-

R.

Huber

M.

F.

Ghilardi

M.

Massimini

G.

Tononi

Nature

-LRB-

-RRB-

A.

K.

Lee

M.

A.

Wilson

Neuron

-LRB-

-RRB-

K.

Louie

M.

A.

Wilson

Neuron

-LRB-

-RRB-

P.

W.

Frankland

B.

Bontempi

L.

E.

Talton

L.

Kaczmarek

A.

J.

Silva

Science

-LRB-

-RRB-

T.

Maviel

T.

P.

Durkin

F.

Menzaghi

B.

Bontempi

Science

-LRB-

-RRB-

A.

Takashima

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

K.

Takehara

S.

Kawahara

Y.

Kirino

J.

Neurosci

-LRB-

-RRB-

K.

Takehara-Nishiuchi

K.

Nakao

S.

Kawahara

N.

Matsuki

Y.

Kirino

J.

Neurosci

-LRB-

-RRB-

SCIENCE

VOL

NOVEMBER

Downloaded

from

on

May

REPORTS

K.

Takehara-Nishiuchi

S.

Kawahara

Y.

Kirino

Learn

Mem

-LRB-

-RRB-

B.

L.

McNaughton

J.

O'Keefe

C.

A.

Barnes

J.

Neurosci

Methods

-LRB-

-RRB-

H.

S.

Kudrimoti

C.

A.

Barnes

B.

L.

McNaughton

J.

Neurosci

-LRB-

-RRB-

R.

Stickgold

D.

Whidbee

B.

Schirmer

V.

Patel

J.

A.

Hobson

J.

Cognit

Neurosci

-LRB-

-RRB-

J.

Przybyslawski

S.

J.

Sara

Behav

Brain

Res

-LRB-

-RRB-

W.

E.

Skaggs

B.

L.

McNaughton

in

Multiple

Channel

Recording

and

Analysis

in

Neuroscience

H.

Eichenbaum

J.

L.

Davis

Eds

-LRB-

Wiley

New

York

-RRB-

pp.

Z.

Nadasdy

H.

Hirase

A.

Czurko

J.

Csicsvari

G.

Buzsaki

J.

Neurosci

-LRB-

-RRB-

D.

Ji

M.

A.

Wilson

Nat

Neurosci

-LRB-

-RRB-

W.

E.

Skaggs

B.

L.

McNaughton

M.

A.

Wilson

C.

A.

Barnes

Hippocampus

-LRB-

-RRB-

M.

Steriade

A.

Nunez

F.

Amzica

J.

Neurosci

-LRB-

-RRB-

We

thank

S.

Cowen

M.

Bower

P.

Musial

and

J.-M

Fellous

for

help

with

design

and

construction

of

the

experimental

apparatus

R.

Roop

G.

Van

Acker

J.

Dees

L.

Ash

A.

Uprety

S.

Van

Rhoads

J.

Wang

and

J.

Meltzer

for

help

with

data

collection

and

analysis

P.

Lipa

for

technical

consulting

on

analyses

and

K.

Iamiceli

and

C.

Stengel

for

support

of

Neuralynx

recording

equipment

and

software

This

work

was

supported

by

grant

from

the

National

Institute

of

Neurological

Disorders

and

Stroke

and

by

grant

from

the

National

Institute

of

Mental

Health

R.

Roop

's

participation

in

this

research

was

partially

supported

by

a

grant

to

the

University

of

Arizona

from

the

Howard

Hughes

Medical

Institute

-LRB-

HHMI

-RRB-

Supporting

Online

Material

Methods

SOM

Text

Fig

Table

References

August

accepted

October

science

Yukio

Nishimura

Hirotaka

Onoe

Yosuke

Morichika

Sergei

Perfiliev

Hideo

Tsukada

Tadashi

Transection

of

the

direct

cortico-motoneuronal

pathway

at

the

mid-cervical

segment

of

the

spinal

cord

in

the

macaque

monkey

results

in

a

transient

impairment

of

finger

movements

Finger

dexterity

recovers

within

a

few

months

Combined

brain

imaging

and

reversible

pharmacological

inactivation

of

motor

cortical

regions

suggest

that

the

recovery

involves

the

bilateral

primary

motor

cortex

during

the

early

recovery

stage

and

more

extensive

regions

of

the

contralesional

primary

motor

cortex

and

bilateral

premotor

cortex

during

the

late

recovery

stage

These

changes

in

the

activation

pattern

of

frontal

motor-related

areas

represent

an

adaptive

strategy

for

functional

compensation

after

spinal

cord

injury

N

eurorehabilitation

has

its

basis

in

the

concept

that

training

recruits

the

remaining

neuronal

systems

to

compensate

for

partial

injury

of

the

central

nervous

system

-LRB-

CNS

-RRB-

However

the

neuronal

basis

of

these

compensation

mechanisms

is

poorly

understood

Brain

imaging

studies

in

human

stroke

patients

show

increased

activity

in

various

cortical

regions

including

the

side

ipsilateral

to

the

affected

extremity

-LRB-

-RRB-

However

in

these

case

studies

the

extent

of

the

lesion

varies

between

patients

and

thus

identifying

the

damaged

pathways

is

often

difficult

Moreover

it

is

unclear

whether

the

brain

regions

showing

increased

activity

causally

contribute

to

the

recovery

In

addition

because

the

tests

are

usually

performed

at

a

specific

time

Department

of

Developmental

Physiology

National

Institute

for

Physiological

Sciences

Okazaki

Japan

Research

for

Evolutional

Science

and

Technology

Japan

Science

and

Technology

Agency

Kawaguchi

Japan

Probe

Research

Laboratory

Molecular

Imaging

Research

Program

RIKEN

Kobe

Japan

Department

of

Physiology

University

of

G

teborg

Post

Office

Box

G

teborg

Sweden

Research

Institute

of

Hamamatsu

Photonics

Hamamatsu

Japan

University

for

Advanced

Studies

-LRB-

SOKENDAI

-RRB-

Hayama

Japan

Present

address

Department

of

Physiology

and

Biophysics

and

Washington

National

Primate

Center

University

of

Washington

Seattle

WA

USA

To

whom

correspondence

should

be

addressed

E-mail

tisa@nips.ac.jp

after

the

lesion

longitudinal

information

is

lacking

To

assess

the

neuronal

mechanism

of

functional

compensation

we

need

a

longitudinal

study

that

applies

quantitative

behavioral

evaluation

to

an

animal

model

preferably

macaque

monkeys

-LRB-

-RRB-

with

a

defined

lesion

of

the

particular

neuronal

system

Dexterous

finger

movements

can

be

restored

within

a

few

weeks

to

to

months

after

a

lesion

of

the

direct

corticomotoneuronal

-LRB-

CM

-RRB-

connection

via

the

lateral

corticospinal

tract

-LRB-

l-CST

-RRB-

at

the

border

between

the

and

segments

of

the

spinal

cord

-LRB-

-RRB-

This

lesion

site

-LRB-

l-CST

lesion

-RRB-

is

rostral

to

the

segments

where

motoneurons

of

hand

muscles

are

located

These

results

suggest

that

indirect

cortico-motoneuronal

pathways

mediated

by

subcortical

or

spinal

interneuronal

systems

can

mediate

commands

for

the

control

of

dexterous

finger

movements

in

primates

In

the

present

study

we

examined

the

neuronal

mechanism

of

this

functional

recovery

from

spinal

cord

injury

We

hypothesized

that

in

addition

to

the

plasticity

of

neural

circuits

in

the

spinal

cord

-LRB-

-RRB-

adaptive

learning

by

higher

order

structures

may

contribute

to

the

recovery

We

applied

positron

emission

tomography

-LRB-

PET

-RRB-

scanning

using

to

measure

changes

in

brain

activity

during

precision

grip

tasks

at

different

stages

of

recovery

Five

monkeys

were

trained

to

reach

for

a

small

piece

of

food

through

a

narrow

vertical

slit

and

to

grasp

it

between

the

pads

of

the

index

VOL

SCIENCE

NOVEMBER

Downloaded

from

on

May

Time-Dependent

Central

Compensatory

Mechanisms

of

Finger

Dexterity

After

Spinal

Cord

Injury

finger

and

thumb

-LRB-

Fig.

preop

-RRB-

In

the

monkey

shown

in

Fig.

the

precision

grip

was

completely

impaired

immediately

after

the

l-CST

lesion

-LRB-

Fig.

day

-RRB-

On

day

the

monkey

was

able

to

grasp

the

food

with

the

index

finger

and

thumb

but

the

independence

of

the

fingers

remained

impaired

All

abilities

gradually

recovered

-LRB-

Fig.

day

-RRB-

as

previously

reported

-LRB-

-RRB-

Figure

shows

the

time

course

of

recovery

of

the

success

rate

for

precision

grip

The

success

rate

recovered

to

more

than

of

that

before

the

lesion

within

weeks

in

all

five

monkeys

On

the

basis

of

these

observations

we

defined

postoperative

days

to

-LRB-

about

month

postoperative

-RRB-

as

the

early

recovery

stage

and

postoperative

days

to

-LRB-

more

than

months

-RRB-

as

the

late

recovery

stage

We

performed

PET

scanning

and

inactivation

experiments

during

the

following

three

stages

-LRB-

i

-RRB-

preoperative

stage

-LRB-

ii

-RRB-

early

recovery

stage

and

-LRB-

iii

-RRB-

late

recovery

stage

Three

monkeys

-LRB-

monkeys

H

T

and

K

-RRB-

were

examined

in

the

PET

study

In

multiple

comparisons

their

performance

in

the

precision

grip

task

during

the

preoperative

stage

was

associated

with

an

increased

activity

in

visuomotor-related

regions

including

the

sensorimotor

cortex

premotor

cortex

and

intraparietal

sulcus

in

the

contralateral

hemisphere

and

the

early

visual

cortices

putamen

and

the

cerebellum

on

the

ipsilateral

side

as

previously

shown

-LRB-

-RRB-

-LRB-

Fig.

-RRB-

To

identify

the

cortical

regions

that

showed

an

increase

in

activity

during

postoperative

stages

we

compared

the

regional

cerebral

blood

flow

-LRB-

r-CBF

-RRB-

during

the

postoperative

stages

with

that

during

the

preoperative

stage

Activity

increased

in

the

bilateral

primary

motor

cortex

-LRB-

-RRB-

during

early

recovery

-LRB-

Fig.

A

to

C

and

E

and

table

-RRB-

Furthermore

activity

increased

in

the

bilateral

early

visual

cortices

-LRB-

-RRB-

contralateral

contralateral

accumbens

and

the

vermis

of

the

cerebellar

cortex

-LRB-

Fig.

A

to

G

and

table

-RRB-

During

the

late

recovery

stage

increased

activation

was

observed

in

the

contralateral

-LRB-

-RRB-

and

ipsilateral

ventral

premotor

cortex

-LRB-

ip-PMv

-RRB-

-LRB-

Fig.

I

to

M

and

table

-RRB-

Activity

in

the

bilateral

insula

contralesional

accumbens

and

the

cerebellar

vermis

also

increased

-LRB-

Fig.

L

to

O

and

table

-RRB-

The

area

of

with

increased

activity

expanded

during

the

late

recovery

stage

compared

with

that

during

O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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