introduction free, pressured, and forced ... - cognac lab
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Exploring the relationship between motor planning and initiationJ. Teman1, R. Ivry1,2, I. Greenhouse3
Introduction
1 Department of Psychology, 2 Helen Willis Neuroscience Institute, University of California, Berkeley; 3 Department of Human Physiology, University of Oregon
Haith, A. M., Pakpoor, J., & Krakauer, J. W. (2016). Independence of Movement Preparation and Movement Initiation. The Journal of Neuroscience : The O�cial Journal of the Society for Neuroscience, 36(10), 3007–3015. https://doi.org/10.1523/JNEUROSCI.3245-15.2016ipsum
Imposing response deadlines yields faster response times (RTs) at the expense of increased error rates, a speed-accuracy tradeo� (SAT). Sequential sampling models (SSMs) assume that evidence for an action accumulates toward a deci-sion boundary. The SAT would emerge in these models given the assumptions that task instructions modulate the boundary and that a response decision nec-essarily precedes response initiation.
Haith et al. 2016 demonstrated an exception to the traditional SAT by showing that, when forced, people can respond faster than their voluntary (Free) RTs without an increase in errors under certain conditions. This violation of the tradi-tional SAT is consistent with the existence of independent motor preparation and motor initiation processes that can unfold in parallel. Here, we set out to replicate this �nding using a two-alternative forced choice task framework that allowed us to employ a hierarchical drift-di�usion SSM model, one commonly used to separate out decision and non-decision compo-nents of RT.
Free, Pressured, and Forced responses
Acc
urac
y (%
)
80
90
100 Button (top) & EMG (bottom) RT
Free Pressured Forced0
0.1
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RT (s
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Task Conditions
Lorem ipsum
random response
accurate response
Movement planning
Movement planning
motor initiation
movement initiationStimulus encoding
&Neural conduction delays
Stimulus encoding&
Neural conduction delays
Serial
Parallel
Stimulus onset time Response time
movement initiation
Δ
Δ
Δ primary determinant of RT
accuracy?
Time
Model comparisons
Acknowledgments
Hierarchical drift-di�usion model
Pressure but not Forcedecreases movement times
Forcing speeded responsesin�ates RT variance
Motivation in the Pressured task results in a standard speed-accuracy tradeo� favoring speed at the cost of accuracy.
Replicating Haith et al. 2016, participants in the Forced condition demonstrated a higher proportion of accurate responses at lower RTs.
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0.1 0.2 0.3 0.4 0.5 0.6 0.7RT (s)
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0 0.5 0.1 0.15 0.2 0.25 0.30
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RT (s)
Prob
abili
ty D
ensi
ty Haith et al. 2016Free speed? Independence model
Drift rate
Non-decision time
Boundary separation
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drift rate (v)
non decision (t)
boundary (a)
Model �ts
Higher drift rate predicts reduced RT without loss of accura-cy and indicates a faster accumulation of evidence. Drift rate was estimated to be higher according the HDDM re-sults for the Forced condition.
Decreased boundary separation predicts faster and less accurate responses. This is consistent with what was ob-served for the Pressured condition.
Left target not shown.
target
target onset window
timing �xation
“go” cue
coincidence timingthreshold window
failure to respondbefore target disappears
RT
E�ective RT
time (ms)
RT
Free
Pressured
Forced“Too soon!”
“Too late!”
-300 -35 0 35
feedback
feedback
e e
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e Pressure signi�cantly reduced movement time as deadlines became increasingly stringent (0.8 to 0.35, 0.35 to 0.3, 0.3 to 0.2; t-test, p < 0.05).
The mean reduction in movement time was (27 ms, p < 0.05) , while the Forced exhibited no such trend. Pressured movement time also decreased signi�cantly relative to the Forced (~20%, p < 0.05).
Measurements of Forced response times in terms of “e�ective RT” (see Task Conditions) show that savings in accuracy come at the cost of increased RT variability.
An inherent challenge with the Forced design is that e�ective RT measurements are necessarily variable due to the nature of the uniform target presentation; however, the variability within the observed window is higher than theoretical predictions.
Pressured responses had signi�cantly higher between-subject variability relative to the Forced (F-test, p < 0.05).
Three parameters describe di�usion toward a boundary for a two-alternative choice decision: 1. drift rate (v) 2. non-decision time (t) 3. boundary separation (a).
The non-decision time parameter captures a combination of stimulus perception and response execution time. A decrease in non-decision time suggests reduced RT without loss of accuracy. However, the non-decision parameter estimates for the Forced and Pressured conditions are unreasonable given our movement time data.
Free Pressured Forced
Traditional sequential sampling models assume serial processes determine RT. Alternatively, independent movement planning and movement initiation processes may happen in parallel to permit fast and accurate responses.
Three task conditions were used. The Free condition measured voluntary responses in the absence of any imposed timing constraints. The Pressured condition permitted responses only within a limited response interval. The Forced condition required participants to execute a response at a given time regardless of whether information about which response had been provided.
In the Forced condition accuracy, e�ective RT, and movement time analyses were performed in four selected intervals (-0.3 to -0.2, -0.2 to -0.186, -0.186 to -0.1, -0.1 to 0; in seconds) for comparison against the four harshest deadlines in the Pressured condition (saturated below for emphasis).
Empirical speed-accuracy tradeo� curves were obtained by calculating the moving average of the probability that a response was successful given a 50 ms RT window. Signi�cance was calculated according to a binomial test (p < 0.00001).
Probability of accurate movement over 50ms windows
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4RT (s)
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Prob
abili
ty o
f acc
urat
e m
ovem
ent
Not signi�cant
ns*
*
DiscussionConsistent with Haith et al., 2016, RT data support parallel movement planning andinitiation processes during the performance of a two-alternative choice task.
Movements were executed more quickly when the allowable time for responses decreased (Pres-sured). In contrast, movement time variability increased when a �xed response initiation time was imposed (Forced). This may re�ect a three-way tradeo� between movement speed, response accuracy, and movement time variability.
HDDM may compensate for parallel response processes with unrealistic non-decision time parameter estimates.
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AssumptionsReaction time is determined by an initiation pro-cess independent from motor planning
The underlying preparation distributions gener-ated by Free, Pressured, and Forced conditions are similar
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Pressured included seven blocks of progressively harsher deadlines in seconds (2.0, 0.8, 0.35, 0.3, 0.2, 0.186, 0.1) followed by an eighth block, like the �rst, with e�ectively no deadline (2.0 s), used to separate performance increases due to learning from motivational in�uence. Forced target presentation followed a uniform distribution (-0.3 s, 0 s) relative to a �xed initiation deadline.
In the independence model, TI is a random variable representing the time motor initiation is complete and Tp represents the independent random time motor preparation is complete.
Above: a plot from Haith et al. 2016 showing TI, obtained directly from their Free RT data, and Tp, , which they estimated from their Forced e�ective RT data according to the probability model above, where P(H | RT) stands for the probability of success on a trial given an RT with the preparation parameters that maximize the summed log likelihood of this function across trials.
On the left: TI and estimated Tp distributions obtained with our data according to this model.
Free Pressured Forced
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Acc
urac
y (%
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Response accuracy
Response accuracies were calculated as the proportion of correct responses in each bin.
Free 2 0.8 0.35 0.3 0.2 0.186 0.1 2 0.3 0.2 0.186 0.1 (s)Pressured Forced
nsns *
0.1
0.2
0.3
0.4
RT (s
)
0.020.040.060.080.1
0.12
SD (s
)
*
Response times were calculated as the o�set between target presentation and button presses using the right or left index �nger.
Response times
Free 2 0.8 0.35 0.3 0.2 0.186 0.1 2 0.3 0.2 0.186 0.1 (s)Pressured Forced
Movement times
nsns
ns ns
ns
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Mov
emen
t tim
e SD
(s)
0.06
0.08
0.1
0.12
0.14
0.16
Mov
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t tim
e (s
)* * **
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Movement times were calculated as the di�erence between button press RTs and EMG onset RTs recorded from the FDI of the left and right hands.
Free 2 0.8 0.35 0.3 0.2 0.186 0.1 2 0.3 0.2 0.186 0.1 (s)Pressured Forced
Model
This work was generously funded by NIH grant NS092079. We thank Leah Carrol with the Haas Scholar’s Program for her support and Weixin Liang for assistance with data collection.