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Item3D-printed stand, timing interface, and coil localization tools for concurrent TMS-fMRI experiments(Georgia Institute of Technology, 2023-04-03) Goldstein, SamuelConcurrent TMS-fMRI involves administrating TMS while subjects are inside an MRI scanner and allows the study of the effects of neurostimulation on simultaneous brain activity. Despite its high promise, the technique has proven challenging to implement for at least three reasons. First, it is difficult to position and stabilize the TMS coil inside the MRI scanner in a way that precisely targets a pre-specified brain region. Second, standard task-presentation software suffers from imprecise timing, which can lead to TMS causing large image artifacts. Third, it is difficult to verify the exact TMS coil position during scanning. In this paper, we describe solutions to all three of these challenges. First, we develop a 3D-printed TMS stand that is fully adjustable and can reach most areas of the scalp. The stand is compatible with various MR coils and features an adjustable mirror holder. Second, we create an interface that can precisely time the TMS pulses with respect to the fMRI image acquisition with a variance of under 1 ms. Third, we develop software for precisely determining the TMS coil position inside the MRI scanner and computing the location of maximal stimulation. All three tools are either free or inexpensive. We provide detailed instructions for building and implementing these tools to facilitate an efficient and reliable concurrent TMS-fMRI setup.
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ItemCan Equating Perception Also Equate Working Memory Performance in Young Adults? A Stage Report for an Attempt to Resolve Individual Differences in Working Memory(Georgia Institute of Technology, 2023-01-18) Wang, MinzhiWorking memory performances are not the same among different individuals, here we examined the role initial perceptual processing plays in working memory functioning. We sought to examine whether equating subjects on the initial perceptual processing could also equate their working memory performances. We did this by using a standard 2-back test using slanted bars as stimuli. Perception was equated by obtaining subjects’ 79% threshold for discrimination of two slanted bars with different orientation using a 3-down-1-up staircase. At this stage, we found some evidence that subjects equated on perception performance performed similarly in working memory tasks. A large scale experiment is needed to generalize the findings.
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ItemEXPLAINING FEATURES OF SIMPLE HUMAN DECISIONS USING BAYESIAN NEURAL NETWORKS(Georgia Institute of Technology, 2022-07-20) Rafiei, FarshadFeedforward neural networks exhibit excellent object recognition performance and currently provide the best models of biological vision. However, despite their remarkable performance in recognizing unseen images, their decision behavior differs markedly from human decision-making. Standard feedforward neural networks perform an identical number of computations to process a given stimulus and always land on the same response for that stimulus. Human decisions, in contrast, take variable amount of time and are stochastic (i.e., the same stimulus elicits different reaction time, RT, and sometimes different responses on different trials). Here we develop a new neural network, RTNet, that closely approximates all basic features of perceptual decision making. RTNet has noisy weights and processes the same stimulus multiple times until the accumulated evidence reaches a threshold, thus producing both variable RT and stochastic decisions. In addition, RTNet exhibits several features of human perceptual decision-making including speed-accuracy tradeoff, right-skewed RT distributions, lower accuracy and confidence for harder decisions, etc. Finally, data from 60 human subjects on a digit discrimination task demonstrates that RT, accuracy, and confidence produced by RTNet for individual novel images correlate with the same quantities produced by human subjects. Overall, RTNet is the first neural network that exhibits all basic signatures of perceptual decision making.
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ItemDissociating the brain regions involved in processing objective and subjective performance(Georgia Institute of Technology, 2021-08-02) Yeon, JiwonWhen making perceptual decisions, easier tasks produce higher task accuracy and, naturally, higher confidence levels. We recognize the two distinctive cognitive processes, but it is challenging to judge exactly how decision and confidence processes affect different brain regions. In the current study, I aimed to reveal which brain regions are activated by objective and subjective performance, respectively. The experiment was a 2 x 2 factorial design, where one factor was task difficulty (i.e., Easy and Difficult conditions) and the other was the number dots presented for the visual stimulus (i.e., High and Low conditions). Different from what observed in the pilot test, the main experiment did not dissociate task performance and confidence level in High and Low conditions. Contrast tests revealed different patterns of activation for Easy > Difficult and Low > High comparisons. However, because behavioral responses for decision and confidence were not clearly separated, it is hard to interpret what those activated regions are associated with. Moreover, none of the regions were able to distinguish either task difficulty or confidence level in the planned MVPA analysis. Meanwhile, I found weak dissociation in the behavioral responses between Difficult-High and Difficult-Low conditions. When contrasting the two conditions each other, I found left middle temporal gyrus (MTG) and right SPL were activated more in Difficult-Low condition compared to Difficult-High condition. Importantly, the right SPL cluster was similar to the right SPL observed in Low > High contrast test. The current study was unfortunately not able to draw a strong conclusion about the task performance and confidence level, and the brain regions associated with those cognitive processes. Nevertheless, partial data of the study showed weak dissociation effect. To understand how the brain computes two cognitive processes that are seemingly separable, it is important to create stable conditions where task performance and confidence level are dissociated and investigate how the brain differently associated with those processes.
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ItemDistinguishing the roles of dorsolateral and anterior PFC in visual metacognition(Georgia Institute of Technology, 2021-07-22) Shekhar, MedhaVisual 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.
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ItemHow do humans give confidence? Comparing popular process models of confidence generation(Georgia Institute of Technology, 2021-07-20) Shekhar, MedhaHumans have the metacognitive ability to assess the likelihood of their decisions being correct via estimates of confidence. Several theories have attempted to model the computational mechanisms that generate confidence. Yet, due to little work directly comparing these models using the same data, there is no consensus among these theories. Here, we compare twelve popular process models by fitting them to large datasets from two experiments in which participants completed a perceptual task with confidence ratings. Quantitative comparisons, validated by model recovery analysis, selected the best fitting model as one that postulates a single system for generating both choice and confidence judgments, where confidence is additionally corrupted by signal-dependent noise. These results contradict dual processing theories – according to which confidence and choice arise from coupled or independent systems. Model evidence from these data also failed to support popular notions that confidence is derived from post-decisional evidence, strictly decision-congruent evidence, or posterior probability computations. Further, we explored the link between model performance and the model’s ability to predict different qualitative patterns in the data, in order to determine the reasons why some models fail. These analyses showed that the models that consistently perform the worst fail to capture individual variations in either primary task performance or metacognitive ability. Together, these analyses establish a general framework for model evaluation that also provides qualitative insights into the successes and failures of these models. Most importantly, these results begin to reveal the nature of metacognitive computations.
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ItemRepresenting the Effect of Multiple Alternatives and Information Strength on Confidence in Perceptual Decision Tasks(Georgia Institute of Technology, 2020-12) Crabtree, BrooklynConfidence in perceptual decisions is a baseline for quantitatively measuring metacognitive processes in psychology. Most researchers limit the stimulus to two choices, assuming that the mental process summarizes the likely accuracy of all choices to determine confidence in the decision. The purpose of this study was to determine whether multiple alternative choices, with varying levels of information strength for each choice, follow the same mental statistics as similar two-alternative forced choice (2AFC) tasks. If the differences between information strengths for each of the multiple choices had a direct effect on confidence, then presenting higher and lower differences of information strength between the correct choice and the incorrect choice would result in corresponding higher and lower confidence ratings. Participants were shown multicolor clouds of dots made up of three colors, with one dot color (dominant) being more abundant than the others. Participants decided which color was the dominant color for each cloud, then indicated their confidence in that decision. The overall information strength, dominant-secondary strength difference, and dominant-tertiary strength difference all had significant main effects on both confidence and accuracy. The overall strength had the largest effect size for confidence, with more information strength resulting in higher confidence ratings. The dominant-secondary strength difference had the largest effect size for accuracy, with a larger difference between dominant and secondary color strengths resulting in higher accuracy rates. Further investigation on how the brain defines relevant stimuli in an environment and processing of multiple choices must be conducted before developing computational models for confidence.