Biology subjects

Seger, C. A.

Publications and source records attributed to Seger, C. A..

4 recordsLinked to original sources

bioRxiv2025

Temporal Dynamics of Flexible Cognitive Control

In dynamic environments, flexible cognitive control adaptively adjusts processing through proactive mechanisms deployed in advance and reactive mechanisms engaged upon conflict. Previous studies have primarily focused on identifying neural networks supporting specific control components, while less is known about how multiple components interact over time to support adaptive control. To characterize these temporal dynamics, we combined EEG recordings with a face-word Stroop paradigm under changing conflict environment. A hierarchical Bayesian model was used to estimate trial-wise learning rate, predicted conflict level, and prediction error, providing computational indices of cognitive control flexibility. Neural correlation analysis revealed that these variables correlated with Theta, Alpha, and Beta oscillations in distinct brain regions. Connectivity analysis among these regions indicated enhanced cross-frequency directional interactions triggered by stimuli. Furthermore, connections reflecting updates to predicted conflict level prior to stimulus onset indexed individual strength in proactive control, while connections reflecting learning rate updates after stimulus onset indexed reactive control. These findings highlight how oscillatory dynamics coordinate multiple control components and provide new insight into how proactive and reactive control emerge as distinct modes within this interconnected neural architecture of flexible cognitive control.

neuroscience↗

bioRxiv2023

Alpha Oscillations Encode Bayesian Belief Updating Underlying Attentional Allocation in Dynamic Environments

In a dynamic environment, expectations of the future constantly change based on updated evidence and affect the dynamic allocation of attentional resources.To further investigate the neural mechanisms underlying efficient allocation of attention, we employed a modified Central Cue Posner paradigm in which the probability of cues being valid (that is, accurately indicated the upcoming target location) was manipulated. The proportion of attentional resources allocated to the cued location (), which was sensitive to precision of predictions on previous trials, was estimated using a hierarchical Bayesian model and was included as a regressor in the analyses of electrophysiological (EEG) data. Our results revealed that before the target appeared, the attentional modulation of alpha oscillations (8[~]13Hz) for high-certainty cues (88% valid) were significantly predicted by the attentional resources measure (). This relationship was not observed under low-certainty conditions (69% and 50% valid cues). After the target appeared, the attentional resources measure () correlated with alpha band oscillations only in the valid cue condition and not in the invalid condition. These results provide new insights on how trial-by-trial Bayesian belief updating relates to alpha band encoding environmentally-sensitive allocation of visual spatial attention.

neuroscience↗

bioRxiv2022

Category-induced global effects of feature-based attention in human visual system

Global effects of FBA are generally limited to stimuli sharing the same or similar features, as hypothesized in the "feature-similarity gain model". Visual perception, however, often reflects categories acquired via experience; whether the global-FBA effect can be induced by the categorized features remains unclear. Here human subjects were trained to classify motion-directions into two discrete categories and performed a classical motion-based attention task. We found a category-induced global-FBA effect in both the MT+ and frontoparietal areas, where attention to a motion-direction globally spread to unattended motion-directions within the same category, but not to those in a different category. Effective connectivity analysis showed that the category-induced global-FBA effect in MT+ was derived by feedback from the IFJ. Altogether, our results reveal for the first time a category-induced global-FBA effect and identify a source for this effect in human prefrontal cortex, implying that FBA is of greater ecological significance than previously thought.

neuroscience↗

bioRxiv2018

In model-based fMRI significant is less than specific

By comparing computational model output to BOLD signal changes model-based fMRI has the potential to offer profound insight into what neural computations occur when. If this potential is to be fully realized, statistically significant outcomes must imply specific outcomes. That is, we must have a clear idea of how often a model not present in the BOLD signal but present in the predictor set will reach significance. We ran Monte Carlo simulations of reinforcement learning to examine this kind of specificity, focusing in on two aspects. One, to what degree can we tell related but theoretically distinct predictors apart. About 40% of the time the studied predictors were indistinguishable. Two, how well can we separate out different parameterizations of the same reinforcement learning terms. Nearly all parameter settings were indistinguishable. The lack of specificity between models and between parameters suggests a uncertain relation between significance and specificity. Follow up analyses suggest the temporally slow and prototyped nature of the haemodynamic response (HRF) can substantially increase correlations, ranging from -0.16 to 0.73 with an average of 0.27. Though we focused on a single case study, i.e., reinforcement learning, specificity concerns are potentially present in any design which does not account for the slow prototyped nature of the HRF. We suggest more specific conclusions can be reached by moving from null hypothesis testing approach to a model selection or model comparison framework.

neuroscience↗