Abstract

Action decisions are considered an emergent property of competitive response activations. As such, decision mechanisms are embedded in, and therefore may differ between, different response modalities. Despite this, the saccadic eye movement system is often promoted as a model for all decisions, especially in the fields of electrophysiology and modelling. Other research traditions predominantly use manual button presses, which have different response distribution profiles and are initiated by different brain areas. Here we tested whether core concepts of action selection models (decision and non-decision times, integration of automatic and selective inputs to threshold, interference across response options, noise, etc.) generalise from saccadic to manual domains. Using two diagnostic phenomena, the remote distractor effect (RDE) and ‘saccadic inhibition', we find that manual responses are also sensitive to the interference of visual distractors but to a lesser extent than saccades and during a shorter time window. A biologically-inspired model (DINASAUR, based on non-linear input dynamics) can account for both saccadic and manual response distributions and accuracy by simply adjusting the balance and relative timings of transient and sustained inputs, and increasing the mean and variance of non-decisional delays for manual responses. This is consistent with known neurophysiological and anatomical differences between saccadic and manual networks. Thus core decision principles appear to generalise across effectors, consistent with previous work, but we also conclude that key quantitative differences underlie apparent qualitative differences in the literature, such as effects being robustly reported in one modality and unreliable in another.

Highlights

  • The problem of how brains make decisions is central to cognitive psychology and neuroscience

  • In previous work (Bompas & Sumner, 2011), we described a competitive leaky accumulator with highly non-linear dynamics based on a model derived from neurophysiological recordings in the superior colliculus (Trappenberg et al, 2001), simulating a one dimensional saccade map with 200 nodes as a simplified representation of left and right superior colliculi

  • If we make the sensible assumption that extra time and extra variance are coupled, i.e. that the extra variance occurs at the same stage as the extra delay, our results suggest that the variability associated with the decision process is similar in saccades and manual responses

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Summary

Introduction

The problem of how brains make decisions is central to cognitive psychology and neuroscience. The key principle emerging from research on basic behavioural decisions is that sensory information and endogenous goals are thought to partially activate various response options, and the decision emerges through competition or interaction between the representations (populations of neurons) for each option (Kopecz, 1995; Leach & Carpenter, 2001; Usher & McClelland, 2001; Van Gisbergen, Van Opstal, & Tax, 1987) This conceptualisation assumes a strong coupling between decision processes and action planning. The brain areas devoted to different modalities are organised in different ways and receive information at different rates from a different balance of pathways (Bompas & Sumner, 2008) This underlying anatomy and physiology has potentially important consequences for action decision dynamics throughout the process. The word decision reflects the process resulting in the selection of action, while decision mechanisms reflects the necessary circuitry underlying this selection process

Manual versus eye movement decisions
A basic phenomenon for investigating competition dynamics
Overview of the present article
Stimuli and procedure
Reaction time analysis
Behavioural results – Experiment 1
Baseline RTs across modalities
Distraction effects in manual responses
Dip Amplitude
Modelling results: decision versus non-decision time
Previous modelling of saccadic behaviour with the 200N-DINASAUR
Constraining non-decision time with 2N-DINASAUR
Rationale and predictions for SOAs 20 and 40 ms
Methods
Distraction effects from Experiment 2
Modelling results: the balance of input signals
Lateral inhibition and winner-takes-all behaviour
General discussion
A manual distractor effect found here but not previously
Why should a model of superior colliculus work for manual decisions?
Are manual and saccadic decision times similar?
Modality-specific versus amodal decision area?
From differences across effectors to differences across sensory modalities
Limitations
Alternative accounts
Findings
Conclusion

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