Piercing of Consciousness as a Threshold-Crossing Operation

Abstract

SummaryMany decisions arise through an accumulation of evidence to a terminating threshold. The process, termed bounded evidence accumulation (or drift diffusion), provides a unified account of decision speed and accuracy, and it is supported by neurophysiology in human and animal models. In many situations, a decision maker may not communicate a decision immediately and yet feel that at some point she had made up her mind. We hypothesized that this occurs when an accumulation of evidence reaches a termination threshold, registered, subjectively, as an “aha” moment. We asked human participants to make perceptual decisions about the net direction of dynamic random dot motion. The difficulty and viewing duration were controlled by the experimenter. After indicating their choice, participants adjusted the setting of a clock to the moment they felt they had reached a decision. The subjective decision times (tSDs) were faster on trials with stronger (easier) motion, and they were well fit by a bounded drift-diffusion model. The fits to the tSDs alone furnished parameters that fully predicted the choices (accuracy) of four of the five participants. The quality of the prediction provides compelling evidence that these subjective reports correspond to the terminating process of a decision rather than a post hoc inference or arbitrary report. Thus, conscious awareness of having reached a decision appears to arise when the brain’s representation of accumulated evidence reaches a threshold or bound. We propose that such a mechanism might play a more widespread role in the “piercing of consciousness” by non-conscious thought processes.

The interaction between elapsed time and decision accuracy differs between humans and rats

“…But neither our experiment nor our analysis presumes a drift diffusion model, or that evidence is being accumulated, in either species. The data presented here are consistent with evidence accumulation, but we have not done other tests, such as motion kernel analysis (8) or choice prediction from reaction time (31), to distinguish integration from other strategies, such as extrema detection (32).…”

Decoding the contents of consciousness from prefrontal ensembles

“…Future work aimed at elucidating the causal mechanisms of conscious perception not just in the PFC, but the primate brain in general could greatly benefit from employing direct activation of such perceptually modulated ensembles (75). In combination with carefully designed experimental approaches, it could help us both understand the relationship and disentangling the mechanisms underlying consciousness from other cognitive processes (76) such as introspection (27,77), attention (78), decision making (79,80) or cognitive control (37,81).…”

Differentiating between integration and non-integration strategies in perceptual decision making

“…The integration model with flat bounds has separate, closed-form equations that describe the RT and choice functions given a set of model parameters (see Methods). This allows us to estimate the model parameters that best fit the mean RT data, which can then be plugged into the equation for choice-accuracy to generate a prediction for the choice-data (Shadlen & Kiani, 2013;Kang et al, 2017;Shushruth et al, 2018). Conveniently, the same procedure can be performed using the equations derived for the extrema detection model (also with flat bounds; see Methods).…”