all experimental procedures were approved by the committee on animal care at the massachusetts institute of technology and were in accordance with the us national research council guide for the care and use of laboratory animals .
sample sizes were chosen based on signal variability estimates from other published studies using fscv .
deeply anaesthetized male long evans rats ( n = 9 ) were implanted under sterile precaution according to approved surgical procedures with headstages carrying 13 independently movable voltammetry microsensor probes targeting the dls ( ap + 0.5 mm , ml 3.5 mm , dv 3.54.0 mm ) , of the right ( n = 3 ) or left ( n = 5 ) hemisphere , or the dls bilaterally ( n = 1 ) , with 13 probes targeting the vms of the same hemispheres ( ap + 1.5 mm , ml 2.1 mm , dv 67 mm ) , and with a unilateral ag / agcl reference electrode in the posterior cortex ( ap 2.3 mm , ml 3.5 mm , dv ~0.5 mm ) .
five rats that underwent maze training and three additional rats for acute stimulation experiments were implanted with tungsten bipolar stimulation electrodes ( fhc inc . ) straddling the ipsilateral medial forebrain bundle ( mfb ; ap 4.6 mm , ml 1.3 mm , dv 78 mm ) to verify striatal dopamine release ( see below ) .
all behavioural training was conducted on a custom built  grid maze  with fully reconfigurable tracks and walls .
approximately 4 weeks after implantation , training began on an associative t - maze task with auditory instruction cues ( figs . 1 , 2 , and 4 ) .
voltammetric recordings began when animals learned to smoothly run down the track to retrieve reward .
early sessions with sporadic maze behaviour , such as wall rearing and sluggish initiation of maze running , were discarded .
each trial began with a brief warning click , followed 0.5 s later by the lowering of a swinging gate , allowing the rat to run down the maze .
half - way down the long - arm , a tone was triggered ( 1 or 8 khz ) , indicating which end - arm to visit in order to retrieve chocolate milk reward ( 0.3 ml ) delivered through automated syringe pumps ( pump systems inc . ) upon the rat s arrival .
the spatial position of each rat was continually monitored via video tracking ( neuralynx inc . ) .
tone delivery and syringe pumps were controlled by in - house behavioural software written in matlab ( mathworks inc . ) .
after 1535 t - maze sessions per rat , a subset of rats ( n = 3 ) received 17 training sessions ( 46 sessions each ) on the m - maze task in which the end - arms of the t - maze were extended ( fig .
these rats received a larger amount of reward ( 0.4 ml ) at one goal site than at the other ( 0.1 ml for 2 rats and 0.2 ml for 1 rat ) .
after 23 sessions with a given set of spatial reward contingencies , the reward amounts at the two goals were reversed .
one rat ( m31 ) was required to make turn choices in response to tones as in the previous t - maze task , whereas the other two rats ( m36 and m47 ) were directed pseudo - randomly to one end - arm of the maze on each trial by removing the track to the opposite arm ( 20 trials to each arm ) without tone presentation .
these rats were required simply to run back and forth to retrieve a large volume of chocolate milk ( 0.4 ml ) at one goal and a small volume ( 0.1 ml ) at the other goal .
waveform generation and data acquisition for voltammetry recordings were done with two pci data acquisition cards and software written in labview ( national instruments ) .
triangular voltage waveforms were applied to chronically implanted carbon fibre electrodes , relative to the reference electrode , at 10 hz .
electrodes were held at 0.4 v between scans , and were ramped to 1.3 v and back to 0.4 v during each scan .
we compiled a library of current vs. applied voltage ( c / v ) templates for dopamine and ph changes of varying magnitudes by stimulating the mfb ( 60 hz , 24 pulses , 300 a ) to induce dopamine release in the striatum in 5 rats maintained under isoflurane anaesthesia .
we used these templates from all 5 rats as a training set to perform chemometric analysis on voltammetry measurements obtained during behaviour with in - house matlab software .
this procedure allowed us to distinguish changes in current due to dopamine release from changes due to ph or to other electroactive substances . in a separate set of rats
, we stimulated the mfb ( 10 hz , 60 pulses , 100120 a ) under urethane anaesthesia to mimic the slower , low amplitude ramping signals that we observed in behaving animals ( extended data fig .
current changes were converted to estimated dopamine concentration by using calibration factors obtained from in - vitro measurements of fixed dopamine concentrations .
behavioural video tracking was synchronized with voltammetry recordings by marker ttl signals sent to the voltammetry data acquisition system . for each trial ,
voltammetry data were normalized by subtracting average background current at each potential measured during the 1-s baseline period before warning click .
session averaged traces ( figs . 1 and 3 and extended figs . 3 and 10 ) were computed by averaging the dopamine signals recorded in a single session across 40 trials , and then averaging these traces to obtain global averages across all rats and electrodes . each session - averaged trace ( 1 from each probe from each session )
concatenation of dopamine and proximity signals ( see below ) was performed by scaling the peri - event windows using the median inter - event intervals between consecutive events across all trials ( figs .
traces between two consecutive events were plotted by taking data from each event to half of the median inter - event interval . maze arm selectivity ( fig .
10 ) was computed by the following equation : 
 dopamineselectivityindex=([da]left[da]right)/([da]left+[da]right ) where [ da]left and [ da]right represent dopamine concentration during trials to the left and right arms of the maze , respectively .
session - averaged dopamine traces were identified as having positive or negative ramping characteristics ( extended data fig .
3 ) if they exhibited a significantly positive or negative linear regression coefficient ( pearson s , r > 0.5 or r < 0.5 and p < 0.01 ) over the entire trial period . trials with phasic responses around trial start ( extended data fig .
4 ) were identified by calculating the relative difference between consecutive time points ( 100 ms / sample ) in a 1-s window with its centre sliding in 0.1-s steps for a 1-s period from 0.5 s to 1.5 s after warning click .
for a given window position , if the differences were all positive values across the first half of the window ( 0.5 s ) and negative across the second half , we determined that a significant inflection point was present in that trial .
2 ) was done by selecting trials that fell in the bottom third ( short trials ) and in the top third ( long trials ) of the trial - time distribution for each rat that displayed a dopamine peak within 0.5 s of goal - reaching .
trials with noisy video tracking data were discarded from this analysis . the simulations for the time - elapsed model ( fig .
2b , f ) were made by calculating the average slope of the ramping signals across all trials on each session and by using linear extrapolation to predict the peak dopamine values on each trial within that session .
peak values were normalized to the median peak value for each session individually and averaged for short and long trials to generate the predictions in fig .
6 ) was implemented in matlab and tested using a range of physiologically realistic estimates for the slope and decay times for previously observed transient signals in vivo .
6a and c , simulations were run 100 times , and temporal offset times for the transients were determined by drawing randomly ( normrnd function in matlab ) from a normal distribution with means of 0.8 s ( with standard deviation of 0.5 s ) and 1.4 s ( with standard deviation of 7 s ) for short and long trials , respectively ( extended data fig .
7b , e ) was calculated by summing the pixel differences in the  x  and  y  spatial dimensions for each recorded rat s position .
these traces were averaged across all short and long trials separately to generate the traces shown in fig 2c .
session - by - session estimations of peak dopamine concentration were made by randomly generating peak trial values using the mean and standard deviation of peak values present in the experimental data .
6b , d ) were normalized to the mean dopamine concentration for each session for both simulated and experimental data .
the presence of population selectivity in the dopamine signals on the associative t - maze task ( fig .
4 ) was determined by comparing the variance of selectivity indices from the t - maze recordings to the distribution of variances obtained by shuffling the dopamine concentrations on the two end - arms and bootstrapping 10,000 times ( z - test comparing variance of the data to the variances of the bootstrapped distributions , p < 0.00001 ) . to identify changes in selectivity and ramping magnitude across training , z - scores of selectivity indices ( fig .
4f ) were computed for each rat by taking the absolute values of all selectivity indices , then by normalizing across sessions before combining all values across rats .
10 ) was computed similarly to the selectivity score for dopamine : 
 behaviouralselectivityindex=(leftarmchoices - rightarmchoices)/(leftarmchoices+rightarmchoices ) run time biases and percent correct biases ( extended data fig .
correlations between peak dopamine magnitude and percent correct performance were calculated by normalizing the average peak dopamine values on each trial to the average peak value across all trials within that session .
brains were fixed by transcardial perfusion with 4% paraformaldehyde in 0.1 m nakpo4 buffer , post - fixed , washed in the buffer solution , and cut transversely at 30 m on a freezing microtome , and they were stained with cresylecht violet to allow reconstruction of the recording sites ( extended data fig .
1 ) . for a subset of the probes , a constant current ( 20 ma , 20 s )
was passed through the probe prior to fixation to make micro - lesions at probe - tip locations .
deeply anaesthetized male long evans rats ( n = 9 ) were implanted under sterile precaution according to approved surgical procedures with headstages carrying 13 independently movable voltammetry microsensor probes targeting the dls ( ap + 0.5 mm , ml 3.5 mm , dv 3.54.0 mm ) , of the right ( n = 3 ) or left ( n = 5 ) hemisphere , or the dls bilaterally ( n = 1 ) , with 13 probes targeting the vms of the same hemispheres ( ap + 1.5 mm , ml 2.1 mm , dv 67 mm ) , and with a unilateral ag / agcl reference electrode in the posterior cortex ( ap 2.3 mm , ml 3.5 mm , dv ~0.5 mm ) . five rats that underwent maze training and three additional rats for acute stimulation experiments
were implanted with tungsten bipolar stimulation electrodes ( fhc inc . ) straddling the ipsilateral medial forebrain bundle ( mfb ; ap 4.6 mm , ml 1.3 mm , dv 78 mm ) to verify striatal dopamine release ( see below ) .
all behavioural training was conducted on a custom built  grid maze  with fully reconfigurable tracks and walls .
approximately 4 weeks after implantation , training began on an associative t - maze task with auditory instruction cues ( figs . 1 , 2 , and 4 ) .
voltammetric recordings began when animals learned to smoothly run down the track to retrieve reward .
early sessions with sporadic maze behaviour , such as wall rearing and sluggish initiation of maze running , were discarded .
each trial began with a brief warning click , followed 0.5 s later by the lowering of a swinging gate , allowing the rat to run down the maze .
half - way down the long - arm , a tone was triggered ( 1 or 8 khz ) , indicating which end - arm to visit in order to retrieve chocolate milk reward ( 0.3 ml ) delivered through automated syringe pumps ( pump systems inc . ) upon the rat s arrival .
the spatial position of each rat was continually monitored via video tracking ( neuralynx inc . ) .
tone delivery and syringe pumps were controlled by in - house behavioural software written in matlab ( mathworks inc . ) .
after 1535 t - maze sessions per rat , a subset of rats ( n = 3 ) received 17 training sessions ( 46 sessions each ) on the m - maze task in which the end - arms of the t - maze were extended ( fig .
3 ) . these rats received a larger amount of reward ( 0.4 ml ) at one goal site than at the other ( 0.1 ml for 2 rats and 0.2 ml for 1 rat ) .
after 23 sessions with a given set of spatial reward contingencies , the reward amounts at the two goals were reversed .
one rat ( m31 ) was required to make turn choices in response to tones as in the previous t - maze task , whereas the other two rats ( m36 and m47 ) were directed pseudo - randomly to one end - arm of the maze on each trial by removing the track to the opposite arm ( 20 trials to each arm ) without tone presentation .
these rats were required simply to run back and forth to retrieve a large volume of chocolate milk ( 0.4 ml ) at one goal and a small volume ( 0.1 ml ) at the other goal .
waveform generation and data acquisition for voltammetry recordings were done with two pci data acquisition cards and software written in labview ( national instruments ) .
triangular voltage waveforms were applied to chronically implanted carbon fibre electrodes , relative to the reference electrode , at 10 hz .
electrodes were held at 0.4 v between scans , and were ramped to 1.3 v and back to 0.4 v during each scan .
we compiled a library of current vs. applied voltage ( c / v ) templates for dopamine and ph changes of varying magnitudes by stimulating the mfb ( 60 hz , 24 pulses , 300 a ) to induce dopamine release in the striatum in 5 rats maintained under isoflurane anaesthesia .
we used these templates from all 5 rats as a training set to perform chemometric analysis on voltammetry measurements obtained during behaviour with in - house matlab software .
this procedure allowed us to distinguish changes in current due to dopamine release from changes due to ph or to other electroactive substances . in a separate set of rats
, we stimulated the mfb ( 10 hz , 60 pulses , 100120 a ) under urethane anaesthesia to mimic the slower , low amplitude ramping signals that we observed in behaving animals ( extended data fig .
current changes were converted to estimated dopamine concentration by using calibration factors obtained from in - vitro measurements of fixed dopamine concentrations .
behavioural video tracking was synchronized with voltammetry recordings by marker ttl signals sent to the voltammetry data acquisition system . for each trial ,
voltammetry data were normalized by subtracting average background current at each potential measured during the 1-s baseline period before warning click .
session averaged traces ( figs . 1 and 3 and extended figs . 3 and 10 ) were computed by averaging the dopamine signals recorded in a single session across 40 trials , and then averaging these traces to obtain global averages across all rats and electrodes . each session -
averaged trace ( 1 from each probe from each session ) was considered as an independent measurement for computing s.e.m .
concatenation of dopamine and proximity signals ( see below ) was performed by scaling the peri - event windows using the median inter - event intervals between consecutive events across all trials ( figs .
traces between two consecutive events were plotted by taking data from each event to half of the median inter - event interval . maze arm selectivity ( fig . 4 and extended data fig .
10 ) was computed by the following equation : 
 dopamineselectivityindex=([da]left[da]right)/([da]left+[da]right ) where [ da]left and [ da]right represent dopamine concentration during trials to the left and right arms of the maze , respectively .
session - averaged dopamine traces were identified as having positive or negative ramping characteristics ( extended data fig .
3 ) if they exhibited a significantly positive or negative linear regression coefficient ( pearson s , r > 0.5 or r < 0.5 and p < 0.01 ) over the entire trial period . trials with phasic responses around trial start ( extended data fig .
4 ) were identified by calculating the relative difference between consecutive time points ( 100 ms / sample ) in a 1-s window with its centre sliding in 0.1-s steps for a 1-s period from 0.5 s to 1.5 s after warning click . for a given window position ,
if the differences were all positive values across the first half of the window ( 0.5 s ) and negative across the second half , we determined that a significant inflection point was present in that trial .
2 ) was done by selecting trials that fell in the bottom third ( short trials ) and in the top third ( long trials ) of the trial - time distribution for each rat that displayed a dopamine peak within 0.5 s of goal - reaching .
2b , f ) were made by calculating the average slope of the ramping signals across all trials on each session and by using linear extrapolation to predict the peak dopamine values on each trial within that session .
peak values were normalized to the median peak value for each session individually and averaged for short and long trials to generate the predictions in fig .
6 ) was implemented in matlab and tested using a range of physiologically realistic estimates for the slope and decay times for previously observed transient signals in vivo .
6a and c , simulations were run 100 times , and temporal offset times for the transients were determined by drawing randomly ( normrnd function in matlab ) from a normal distribution with means of 0.8 s ( with standard deviation of 0.5 s ) and 1.4 s ( with standard deviation of 7 s ) for short and long trials , respectively ( extended data fig .
7b , e ) was calculated by summing the pixel differences in the  x  and  y  spatial dimensions for each recorded rat s position .
these traces were averaged across all short and long trials separately to generate the traces shown in fig 2c .
session - by - session estimations of peak dopamine concentration were made by randomly generating peak trial values using the mean and standard deviation of peak values present in the experimental data .
6b , d ) were normalized to the mean dopamine concentration for each session for both simulated and experimental data .
the presence of population selectivity in the dopamine signals on the associative t - maze task ( fig .
4 ) was determined by comparing the variance of selectivity indices from the t - maze recordings to the distribution of variances obtained by shuffling the dopamine concentrations on the two end - arms and bootstrapping 10,000 times ( z - test comparing variance of the data to the variances of the bootstrapped distributions , p < 0.00001 ) . to identify changes in selectivity and ramping magnitude across training , z - scores of selectivity indices ( fig .
4f ) were computed for each rat by taking the absolute values of all selectivity indices , then by normalizing across sessions before combining all values across rats .
10 ) was computed similarly to the selectivity score for dopamine : 
 behaviouralselectivityindex=(leftarmchoices - rightarmchoices)/(leftarmchoices+rightarmchoices ) run time biases and percent correct biases ( extended data fig .
correlations between peak dopamine magnitude and percent correct performance were calculated by normalizing the average peak dopamine values on each trial to the average peak value across all trials within that session .
brains were fixed by transcardial perfusion with 4% paraformaldehyde in 0.1 m nakpo4 buffer , post - fixed , washed in the buffer solution , and cut transversely at 30 m on a freezing microtome , and they were stained with cresylecht violet to allow reconstruction of the recording sites ( extended data fig .
a constant current ( 20 ma , 20 s ) was passed through the probe prior to fixation to make micro - lesions at probe - tip locations .
coloured dots indicate positions of probe tips as determined by post - experiment probe length measurements and histology ( see methods ) .
a , current measured at each potential during successive scans with electrical mfb stimulation ( red line ) in an anaesthetized rat .
b , current - voltage plot from the 5 scans during 0.5 s period after mfb stimulation .
the large increase in current around 0.6 v ( dotted line , peak ) corresponds to the dopamine redox potential measured in in vitro .
c , time - course of current at the dopamine redox potential around electrical mfb stimulation ( red line ) .
c , illustrating dopamine response in the same rat , now awake , to room lights being turned on .
g , average current vs. voltage ( cv ) plot for all identified ramping trials ( n = 4418 trials ) for the time period ( 3 to 2 s ) indicated by the brackets in the colour plot in h. h , current changes averaged over all identified trials in which ramping occurred ( see methods ) during t - maze running .
i , average cv plot from the bracketed time range ( 10 to 11 s ) in j following tonic mfb stimulation in anaesthetized rats ( n = 3 ) .
j , average current changes from all tonically stimulated rats . a , b , dopamine concentration recorded in the vms ( a , n = 9 rats ) and in the dls ( b , n = 8 rats ) .
data were first averaged across trials to yield session average traces for each probe in each session .
these traces were averaged within rat to obtain 1 average trace per rat , which were then averaged across rats .
1e , f , which considered session averages for each probe to be an independent measure .
c , d , distribution of average peak dopamine values for all recordings in vms ( c ) and dls ( d ) .
each colour corresponds to an average peak dopamine concentration measured by a single probe in different sessions .
e , f , proportion of trial averaged dopamine recordings in the vms ( e , out of 300 ) and dls ( f , out of 262 ) that displayed a positive ( blue ) or negative ( grey ) ramping response during maze running , and an unclassified dopamine profile ( red ) .
g , h , average dopamine concentration in the vms ( g ) and dls ( h ) for the positive ramping traces ( top ) , the negative ramping traces ( middle ) , and the unclassified traces ( bottom ) .
shading represents s.e.m . a , dopamine concentration in a representative trial that included both a phasic response to warning click and a sustained ramping response to goal - reaching .
b , c , average normalized dopamine traces from vms ( b ) and dls ( c ) probes from all trials ( n = 890 and 640 , respectively ) that showed identified transients after warning click ( see methods ) . in the vms , note the sharp increase in dopamine around warning click superimposed on the ramping response that followed the phasic click response .
sharper transient responses are present at the start of maze running ( red ) and after goal - reaching ( cyan ) .
these responses can be superimposed on and modulated independently of the slower ramping signal related to goal proximity ( dark blue ) .
a , average peak dopamine to unexpected chocolate milk delivery outside the task is positively correlated with peak ramping dopamine measured from the same probes during preceding behavioural training in the maze ( n = 146 sessions ; pearson s r = 0.45 , p < 0.0001 ) .
b , average peak dopamine concentration induced by unexpected free reward outside the task ( blue ) and peak amplitude of dopamine ramping during maze performance just prior to reward ( red ; paired t - test , p < 0.001 ) . a , dopamine release modelled as a summation of four weighted transients in response to fixed maze events on short trials ( purple ) and long trials ( orange ) .
the overlap of the transients is reduced on the long trials , resulting in a lower peak dopamine level at the end of the maze run .
thick lines indicate overall average dopamine , and thin lines indicate the averages of each of the 4 transients across 100 simulation runs .
b , relative predicted peak dopamine levels on short and long trials calculated as a linear decay function of trial duration for the simulated model shown in a ( black ) , for the spatial proximity model ( light blue ) , and for the actual experimental data ( dark blue ) .
c , an alternative multi - transient model in which the transients ( 3 , inset ) are heavily weighted toward the goal location , are highly variable in their time of occurrence , and display a long decay time - course . in this model ,
the difference between short and long trials is within the noise range of the data .
the average of individual transients ( inset ) across multiple simulations is a smeared version of the single transients that is weighted towards the goal location .
d , data plotted as in b , for the alternative multi - transient model .
e , f , average run speed ( e ) and acceleration ( f ) during short ( purple ) and long ( orange ) trials , as shown in fig 2 , for all animals and sessions . a  c , video tracker traces ( a ) , relative proximity to reward ( b ) , and dopamine concentration ( c ) measured during a single trial in which a rat paused near the choice point .
f , video tracker traces ( d ) , relative proximity to reward ( e ) and dopamine concentration ( f ) measured during another trial from a different rat .
a  c , average peak dopamine levels for m - maze sessions for 3 individual rats ( m31 , m36 , and m47 ) in the left ( blue ) and right ( red ) end - arms .
blue and red shading indicates sessions in which left and right arm contained the larger reward , respectively .
d , e , average peak dopamine levels , as in a  c , for value bias t - maze sessions for 2 rats ( m36 and m47 ) .
c , for value bias s - maze sessions for 2 rats ( m47 and m35 ) .
h  j , average normalized dopamine levels measured in the high reward arm ( light green ) and low reward arm ( dark green ) as rats performed the m - maze ( h ) , t - maze ( i ) and s - maze ( j ) tasks .
k  l , dopamine concentration relative to left ( k ) and right ( l ) goal - reaching during the first session following a reversal of reward values ( session 17 of m47 , indicated by asterisk in c ) . a , average normalized dopamine concentration measured from vms probes in one rat ( n = 5 sessions ) performing the s - maze task as in fig . 3j .
light green line indicates runs to the higher reward goal , and dark green lines to the lower reward goal .
b , traces , as in a , for the second rat trained on the s - maze task ( n = 4 sessions ) .
4d , for all probes implanted in the left ( a , n = 5 rats ) and right ( b , n = 3 rats ) hemispheres . note the bias in both groups of the selectivity preference towards negative selectivity indices ( right bias , red ) relative to the shuffled data ( blue ) .
c  e , biases in average run time ( c ) , percentage of correct responses ( d ) , and arm choices ( e ) across training blocks .
g , correlation coefficients ( pearson s r ) computed for each training block between arm choice selectivity indices and dopamine selectivity indices .
h , normalized peak magnitudes of dopamine signals averaged in a 0.5-s window prior to goal - reaching in sessions with significant ( mann - whitney u - test , p < 0.05 ) pre - goal increases .
n s for each block are : 48 , 101 , 113 , and 179 trial averaged recordings , respectively .
dopamine concentration from ramping dopamine sessions in which percentage of correct trials fell above ( red , n = 179 ) or below ( blue , n = 92 ) the learning criterion for t - maze task acquisition ( 72.5% correct , chi - square test , p < 0.05 ) .
peak dopamine levels from the sessions plotted in i , showing no significant difference between pre- and post - learning periods ( t - test , p = 0.44 ) .
 predictions about future rewarding events have a powerful influence on behaviour . the phasic spike activity of dopamine - containing neurons , and corresponding dopamine transients in the striatum , are thought to underlie these predictions , encoding positive and negative reward prediction errors15 . 
 many behaviours , however , are directed toward distant goals , for which transient signals might fail to provide sustained drive . here 
 we report a novel , extended mode of reward - predictive dopamine signalling in the striatum that emerged as rats moved toward distant goals . 
 these dopamine signals , which were detected with fast - scan cyclic voltammetry ( fscv ) , gradually increased or -- in rare instances -- decreased as the animals navigated mazes to reach remote rewards , rather than having phasic or steady tonic profiles . 
 these dopamine increases ( ramps ) scaled flexibly with both the distance and size of the rewards . during learning , these dopamine signals exhibited spatial preferences for goals in different locations and readily changed in magnitude to reflect changing values of the distant rewards . 
 such prolonged dopamine signalling could provide sustained motivational drive , a control mechanism that may be important for normal behaviour and that can be impaired in a range of neurologic and neuropsychiatric disorders . 
Methods
Implant procedures
Behavioural training
Voltammetry data acquisition and analysis
Histology
Supplementary Material