Assessing neural activity related to decision‐making through flexible odds ratio curves and their derivatives

Abstract

It is well established that neural activity is stochastically modulated over time. Therefore, direct comparisons across experimental conditions and determination of change points or maximum firing rates are not straightforward. This study sought to compare temporal firing probability curves that may vary across groups defined by different experimental conditions. Odds-ratio (OR) curves were used as a measure of comparison, and the main goal was to provide a global test to detect significant differences of such curves through the study of their derivatives. An algorithm is proposed that enables ORs based on generalized additive models, including factor-by-curve-type interactions to be flexibly estimated. Bootstrap methods were used to draw inferences from the derivatives curves, and binning techniques were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to study premotor ventral cortex neural activity associated with decision-making. The proposed statistical procedures proved very useful in revealing the neural activity correlates of decision-making in a visual discrimination task.

Decision-making in the ventral premotor cortex harbinger of action

“…More conclusive evidence came with the introduction of methodological and technical approaches combining operant conditioning with electrophysiological recordings in monkeys. These studies suggested the involvement of PM in planning and execution of complex movements, motor set, preparation for and sensory guidance of movements, reorganization of movements, and learning (Roland et al, 1980; Halsband and Passingham, 1982; Weinrich et al, 1984; Halsband and Freund, 1990; Mitz et al, 1991; Passingham, 1993; Kurata and Hoffman, 1994; Wise et al, 1997) as well as in complex relations with the immediate extrapersonal space (revised in Rizzolatti and Luppino, 2001) and perceptual decision-making (Romo et al, 2004; Pardo-Vazquez et al, 2008, 2009; Lemus et al, 2009). Additionally, conjunction analysis of fMRi data has suggested the involvement of the PM cortices in processing trigeminal information (Iannilli et al, 2007).…”

“…Although all these findings obtained with the these tasks suggested a role for the PMv in cognitive processes that can range from perception to action the first experimental evidence came from the work of Romo et al in the PMv and PMm cortices (Hernandez et al, 2002; Romo et al, 2004). They used an experimental approach that has proved very fruitful in studying the function of the posterior parietal and frontal cortices (Evarts, 1966; Fuster and Alexander, 1971; Mountcastle et al, 1975) and has allowed an identification of neurons in the PMv cortex that supports both perceptual decisions (Romo et al, 2004; Pardo-Vazquez et al, 2008, 2009; Lemus et al, 2009; Roca-Pardiñas et al, 2011) and correct and error monitoring (Pardo-Vazquez et al, 2008, 2009; Acuña et al, 2010). …”

“…Later, the function of the PM cortex has been studied by recording the activity of single neurons from this area while monkeys ( Macaca mulatta ) performed perceptual discrimination tasks of different sensory modalities, including somatosensory (Romo et al, 2004), visual (Pardo-Vazquez et al, 2008, 2009; Acuña et al, 2010; Roca-Pardiñas et al, 2011), and auditory (Lemus et al, 2009). In these tasks, subjects have to choose between different behavioral responses based on the comparison of two stimuli.…”

Statistical Scale Space Methods

“…), electrophysiology (Roca‐Pardiñas et al. ), experimental psychology (Becker and Elliott, ) and economics (Pittau and Zelli, ; Marron and de Uña‐Álvarez, ). Ganguli and Wand () analyzed fishery data using S 3 for geostatistical data and Godtliebsen and Øigård () used Posterior Smoothing in a pattern recognition application to detect bones in fish fillets.…”