Understanding the nonlinear physiological and behavioral effects of tDCS through computational neurostimulation

Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models

“…We used an established spiking neural model of decision making implementing an attractor network (Bonaiuto and Arbib, 2014; Wang, 2008; Wong et al, 2007; Wang, 2012, 2002; Deco et al, 2009; Bonaiuto and Bestmann, 2015; Rolls et al, 2010; Wong and Wang, 2006; Lo and Wang, 2006; Machens et al, 2005). This model was initially developed to explain the neural dynamics of perceptual decision making and working memory (Wang, 2002) and has been used to investigate the behavioral and neural correlates of a wide variety of perceptual and value-based decision making tasks at various levels of explanation (Rustichini and Padoa-Schioppa, 2015; Hunt et al, 2012; Bonaiuto and Arbib, 2014; Hämmerer et al, 2016; Wang, 2012, 2002; Furman and Wang, 2008; Jocham et al, 2012; Bonaiuto and Bestmann, 2015; Rolls et al, 2010; Wong and Wang, 2006).…”

“…This model was initially developed to explain the neural dynamics of perceptual decision making and working memory (Wang, 2002) and has been used to investigate the behavioral and neural correlates of a wide variety of perceptual and value-based decision making tasks at various levels of explanation (Rustichini and Padoa-Schioppa, 2015; Hunt et al, 2012; Bonaiuto and Arbib, 2014; Hämmerer et al, 2016; Wang, 2012, 2002; Furman and Wang, 2008; Jocham et al, 2012; Bonaiuto and Bestmann, 2015; Rolls et al, 2010; Wong and Wang, 2006). The model is well suited for computational neurostimulation studies because it is complex enough to simulate network dynamics at the neural level, yet is simple enough to generate population-level (neural and hemodynamic) signals, and the resulting behavior allows for comparison with human data (Hunt et al, 2012; Bonaiuto and Arbib, 2014; Rolls et al, 2010).…”

“…The model is well suited for computational neurostimulation studies because it is complex enough to simulate network dynamics at the neural level, yet is simple enough to generate population-level (neural and hemodynamic) signals, and the resulting behavior allows for comparison with human data (Hunt et al, 2012; Bonaiuto and Arbib, 2014; Rolls et al, 2010). The model also incorporates neurons at a level of detail that allows simulation of tDCS by the addition of extra transmembrane currents with parameter values comparable to previous modeling work (Hämmerer et al, 2016; Bonaiuto and Bestmann, 2015; Molaee-Ardekani et al, 2013), and current understanding of the mechanism of action of tDCS (Rahman et al, 2013; Nitsche and Paulus, 2011; Bikson et al, 2004; Funke, 2013; Radman et al, 2009; Bindman et al, 1964). …”

Does 10-Hz cathodal oscillating current of the parieto-occipital lobe modulate target detection?

“…In the future, computational models might help overcome these inter-individual differences by allowing researchers to select the optimal set of stimulation parameters for each individual based on models of current flow (Truong et al, 2014;Dmochowski et al, 2017). However, the fact that tCS can cause non-linear effects at the neurophysiological and behavioral level (Bonaiuto, 2015), and the difficulty in obtaining data in vivo to validate the computational models (Bai et al, 2013), necessitate further model refinements and development. Furthermore, adjusting stimulation frequency as a function of intrinsic brain oscillations properties could also be more effective at modulating perception.…”

Computational neurostimulation for Parkinson's disease

“…Computational neurostimulation, therefore, is the further expansion of this approach to include stimulation inputs into these models that can then make specific predictions about resultant behavior Bonaiuto and Bestmann, 2015). Extending this approach to the clinical domain will require the reformulation of current, descriptively defined clinical syndromes into computational terms, an understanding of how these aberrant computations are represented in the brain, and then a principled approach to their modulation using stimulation.…”