PT  - JOURNAL ARTICLE
AU  - Daniel Chicharro
AU  - Stefano Panzeri
AU  - Ralf M. Haefner
TI  - Stimulus dependent relationships between behavioral choice and sensory neural responses
AID  - 10.1101/2019.12.27.889550
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 2019.12.27.889550
4099  - http://biorxiv.org/content/early/2019/12/28/2019.12.27.889550.short
4100  - http://biorxiv.org/content/early/2019/12/28/2019.12.27.889550.full
AB  - Understanding the relationship between trial-to-trial variability in neural responses of sensory areas and behavioral choices is fundamental to elucidate the mechanisms of perceptual decision-making. In two-choice tasks, activity-choice co-variations have traditionally been quantified with choice probabilities (CP). It has been so far commonly assumed that choice-related neural signals are separable from stimulus-driven responses, which has led to characterizing activity-choice covariations only with a single CP value estimated combining trials from all stimulus levels. In this work we provide theoretical and experimental evidence for the stimulus dependence of the relationship between neural responses and behavioral choices. We derived a general analytical CP expression for this dependency under the general assumption that a decision threshold converts an internal stimulus estimate into a binary choice. This expression predicts a stereotyped threshold-induced CP modulation by the stimulus information content. We reanalyzed data from Britten et al. (1996) and found evidence of this modulation in the responses of macaque MT cells during a random dot discrimination task. Moreover, we developed new methods of analysis that allowed us to further identify a richer structure of cell-specific CP stimulus dependencies. Finally, we capitalised on this progress to develop new generalized linear models (GLMs) with stimulus-choice interaction terms, which show a higher predictive power and lead to a more precise assessment of how much each neuron is stimulus- or choice-driven, hence allowing a more accurate comparison across areas or cell types. Our work suggests that characterizing the patterns of stimulus dependence of choice-related signals is essential to properly determine how neurons in different areas contribute to linking sensory representations to perceptual decisions.