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1. Learning the hierarchical organization of the frontal lobe with differential causal effects

   https://doi.org/10.1016/j.sctalk.2024.100329  

   Butler, Kurt; Cleveland, Duncan; Mikell, Charles B; Mofakham, Sima; Saalmann, Yuri B; Djurić, Petar M (June 2024, Science Talks)

   In this video article, accompanying the paper “An approach to learning the hierarchical organization of the frontal lobe”, we discuss a data driven approach to learning brain connectivity. Hierarchical models of brain connectivity are useful to understand how the brain can process sensory information, make decisions, and perform other high-level tasks. Despite extensive research, understanding the structure of the prefrontal cortex (PFC) remains a crucial challenge. In this work, we propose an approach to studying brain signals and uncovering characteristics of the underlying neural circuity, based on the mathematics of Gaussian processes and causal strengths. For discovering causations, we propose a metric referred to as double-averaged differential causal effect, which is a variant of the recently proposed differential causal effect, and it can be used as a principled measure of the causal strength between time series. We applied this methodology to study local field potential data from the frontal lobe, where the interest was in finding the causal relationship between the medial and lateral PFC areas of the brain. Our results suggest that the medial PFC causally influences the lateral PFC. 

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2. Temporal dynamics of brain activation during three concept generation techniques

   https://doi.org/10.1017/pds.2021.557  

   Milovanovic, J; Shealy, T; Hu, M. and (October 2021, ICED21 Proceedings of the Design Society)

   The research presented in this paper explores features of temporal design neurocognition by comparing regions of activation in the brain during concept generation. A total of 27 engineering graduate students used brainstorming, morphological analysis, and TRIZ to generate concepts to design problems. Students' brain activation in their prefrontal cortex (PFC) was measured using functional near-infrared spectroscopy (fNIRS). Temporal activations were compared between techniques. When using brainstorming and morphological analysis, highly activated regions are consistently situated in the medial and right part of the PFC over time. For both techniques, the temporal neuro-physiological patterns are similar. Cognitive functions associated to the medial and right part of the PFC suggest an association with divergent thinking and adaptive decision making. In contrast, highly activated regions over time when using TRIZ appear in the medial or the left part of the prefrontal cortex, usually associated with goal directed planning. 

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3. Modulation of prefrontal couplings by prior belief-related responses in ventromedial prefrontal cortex

   https://doi.org/10.3389/fnins.2023.1278096  

   Wang, Bin A.; Drammis, Sabrina; Hummos, Ali; Halassa, Michael M.; Pledger, Burkhard (November 2023, Frontiers in neuroscience)

   Humans and other animals can maintain constant payoffs in an uncertain environment by steadily re-evaluating and flexibly adjusting current strategy, which largely depends on the interactions between the prefrontal cortex (PFC) and mediodorsal thalamus (MD). While the ventromedial PFC (vmPFC) represents the level of uncertainty (i.e., prior belief about external states), it remains unclear how the brain recruits the PFC-MD network to re-evaluate decision strategy based on the uncertainty. Here, we leverage non-linear dynamic causal modeling on fMRI data to test how prior belief-dependent activity in vmPFC gates the information flow in the PFC-MD network when individuals switch their decision strategy. We show that the prior belief-related responses in vmPFC had a modulatory influence on the connections from dorsolateral PFC (dlPFC) to both, lateral orbitofrontal (lOFC) and MD. Bayesian parameter averaging revealed that only the connection from the dlPFC to lOFC surpassed the significant threshold, which indicates that the weaker the prior belief, the less was the inhibitory influence of the vmPFC on the strength of effective connections from dlPFC to lOFC. These findings suggest that the vmPFC acts as a gatekeeper for the recruitment of processing resources to re-evaluate the decision strategy in situations of high uncertainty. 

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4. Detecting confounders in multivariate time series using strength of causation

   Y. Liu, C (January 2023, EUSIPCO)

   One of the most important problems in science is understanding causation. This problem is particularly challenging when causation has to be inferred from observational data only. A further challenge of this problem is if the observed data were generated in the presence of latent confounders. In this paper, we propose a method for detecting confounders in multivariate time series using a recently introduced concept referred to as differential causal effect (DCE). The solution is based on feature-based Gaussian processes that are not only used for estimating the DCE of the observed time series but also for estimating the latent confounders. We demonstrate the performance of the proposed method with several examples. They show that the proposed approach can detect confounders and can accurately estimate causal strengths. 

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5. Brain-in-the-Loop Learning Using fNIR and Simulated Virtual Reality Surgical Tasks: Hemodynamic and Behavioral Effects.

   https://doi.org/10.1007/978-3-319-20816-9_31  

   Shewokis, P.A. (January 2015, Lecture Notes in Computer Science)

   Functional near infrared spectroscopy (fNIR) is a noninvasive, portable optical imaging tool to monitor changes in hemodynamic responses (i.e., oxygenated hemoglobin (HbO)) within the prefrontal cortex (PFC) in response to sensory, motor or cognitive activation. We used fNIR for monitoring PFC activation during learning of simulated laparoscopic surgical tasks throughout 4 days of training and testing. Blocked (BLK) and random (RND) practice orders were used to test the practice schedule effect on behavioral, hemodynamic responses and relative neural efficiency (EFFrel-neural) measures during transfer. Left and right PFC for both tasks showed significant differences with RND using less HbO than BLK. Cognitive workload showed RND exhibiting high EFFrel-neural across the PFC for the coordination task while the more difficult cholecystectomy task showed EFFrel-neural differences only in the left PFC. Use of brain activation, behavioral and EFFrel-neural measures can provide a more accurate depiction of the generalization or transfer of learning. 

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