Biology subjects

Rahnev, D.

Publications and source records attributed to Rahnev, D..

6 recordsLinked to original sources

bioRxiv2018

Overlapping and unique neural circuits support perceptual decision making and confidence

The period of making a perceptual decision is often followed by a period of confidence generation where one rates the likely accuracy of the initial decision. However, it remains unclear whether the same or different neural circuits are engaged during periods of perceptual decision making and confidence generation. To address this question, we conducted two functional MRI experiments in which we dissociated the periods related to perceptual decision making and confidence report by either separating their respective regressors or asking for confidence ratings only in the second half of the experiment. We found that perceptual decision making and confidence reports gave rise to activations in large and mostly overlapping brain circuits including frontal, parietal, posterior, and cingulate regions with the results being remarkably consistent across the two experiments. Further, the confidence report period activated a number of unique regions, whereas there was no evidence for the decision period activating unique regions not involved in the confidence period. We discuss the possible reasons for this overlap and explore their implications about theories of perceptual decision making and confidence generation.

neuroscience↗

bioRxiv2018

Causal evidence for LTP-based interference in visual learning

Training related skills in close succession results in interference but the reasons for this interference are not understood. Here we test the hypothesis that interference occurs due to competition of long-term potentiation (LTP): the LTP induced by one task impedes the LTP induced by the other. Human subjects performed two consecutive training sessions on different Gabor orientations. Immediately after the offset of the first training, we applied continuous theta burst stimulation (cTBS) to interfere with the LTP processes produced by the first training. We found that cTBS to a control site (vertex) resulted in substantial anterograde interference for the second training. Critically, cTBS to the visual cortex not only disrupted learning on the immediately preceding training, but also released the second training from the anterograde interference. These results provide strong support for the LTP-based theory of interference and suggest the possibility of directly manipulating the competition between different learning periods.

neuroscience↗

bioRxiv2018

Distinguishing the roles of dorsolateral and anterior PFC in visual metacognition

Visual metacognition depends on regions within the prefrontal cortex. Two areas in particular have been repeatedly implicated: the dorsolateral prefrontal cortex (DLPFC) and the anterior prefrontal cortex (aPFC). However, it is still unclear what the function of each of these areas is and how they differ from each other. To establish the specific roles of DLPFC and aPFC in metacognition, we employed online transcranial magnetic stimulation (TMS) to causally interfere with their functioning during confidence generation. Human subjects from both sexes performed a perceptual decision-making task and provided confidence ratings. We found a clear dissociation between the two areas: DLPFC TMS lowered confidence ratings, whereas aPFC TMS increased metacognitive ability but only for the second half of the experimental blocks. These results support a functional architecture where DLPFC reads out the strength of the sensory evidence and relays it to aPFC, which makes the confidence judgement by potentially incorporating additional, non-perceptual information. Indeed, simulations from a model that incorporates these putative DLPFC and aPFC functions reproduced our behavioral results. These findings establish DLPFC and aPFC as distinct nodes in a metacognitive network and suggest specific contributions from each of these regions to confidence generation.\n\nSignificance\n\nThe prefrontal cortex (PFC) is known to be critical for metacognition. Two of its sub-regions - dorsolateral PFC (DLPFC) and anterior PFC (aPFC) - have specifically been implicated in confidence generation. However, it is unclear if these regions have distinct functions related to the underlying metacognitive computation. Using a causal intervention with transcranial magnetic stimulation (TMS), we demonstrate that DLPFC and aPFC have dissociable contributions: targeting DLPFC decreased average confidence ratings, while targeting aPFC specifically affected metacognitive scores. Based on these results, we postulated specific functions for DLPFC and aPFC in metacognitive computation and corroborated them using a computational model that reproduced our results. Our causal results reveal the existence of a specialized modular organization in PFC for confidence generation.

animal behavior and cognition↗

bioRxiv2017

Feature-specific awake reactivation in human V1 after visual training

Converging human studies have demonstrated that brain activity patterns observed during task performance reemerge in the following restful awake state. Such \"awake reactivation\" has been demonstrated across higher-order cortex for complex images or associations. However, it remains unclear what specific training components are reactivated in these studies. Here we sought to provide evidence for the reactivation of a particular visual feature - Gabor orientation. Following extensive training on a visual task, we found robust reactivation in human V1 that lasted at least eight minutes. This effect was not present in higher retinotopic areas such as V2, V3, V3A, or V4v, demonstrating that the effects in V1 are not due to top-down processes such as conscious rehearsal. Furthermore, the amount of awake reactivation predicted the amount of performance improvement on the visual task. These results demonstrate that functionally-relevant awake reactivation of specific visual features occurs in early sensory cortex.

neuroscience↗

bioRxiv2017

Sensory noise increases metacognitive efficiency

Visual metacognition is the ability to employ confidence ratings in order to predict the accuracy of ones decisions about visual stimuli. Despite years of research, it is still unclear how visual metacognitive efficiency can be manipulated. Here we show that a hierarchical model of confidence generation makes a counterintuitive prediction: Higher sensory noise should increase metacognitive efficiency. The reason is that sensory noise has a large negative influence on the decision (where it is the only corrupting influence) but a smaller negative influence on confidence (where it is one of two corrupting influences; the other one being metacognitive noise). To test this prediction, we used a perceptual learning paradigm to decrease the amount of sensory noise. In Experiment 1, seven days of training led to significant decrease in noise as well as a corresponding decrease in metacognitive efficiency. Experiment 2 showed the same effect in a brief 97-trial learning for each of two different tasks. Finally, in Experiment 3, we experimentally manipulated stimulus contrast to increase sensory noise and observed a corresponding increase in metacognitive efficiency. Our findings demonstrate the existence of a robust positive relationship between sensory noise and metacognitive efficiency. These results could not be captured by a standard model in which decision and confidence judgments are made based on the same underlying information. Thus, our study provides a novel way to directly manipulate metacognitive efficiency and suggests the existence of metacognitive noise that corrupts confidence but not the perceptual decision.

neuroscience↗

bioRxiv2017

Uncertainty in perceptual representations

How are perceptual decisions made? The answer to this seemingly simple question necessitates that we specify the nature of perceptual representations on which decisions are based. Recent work has taken for granted that the representation at the decision stage consists of a full probability distribution over all possible stimuli. However, to date, no empirical evidence has supported this assumption. Here I present five possible perceptual representation schemes that allow the extraction of different levels of sensory uncertainty. I review the empirical evidence from both continuous and discrete judgments and show that, at present, only the most primitive scheme based on a single point estimate can be rejected. In other words, at least four different representational schemes are consistent with the available data and therefore full probability distributions cannot be assumed. There is an urgent need for empirical research to adjudicate between these theoretical possibilities.

neuroscience↗