scholarly journals Hierarchical Cognition causes Task Related Deactivations but not just in Default Mode Regions

2018 ◽  
Author(s):  
Ausaf A Farooqui ◽  
Tom Manly
Keyword(s):  
Attentional Control ◽  
Ongoing Task ◽  
Task Execution ◽  
Default Mode ◽  
Entire Duration ◽  
Fixed Set ◽  
Program Load ◽  
Human Participants ◽  
And Control ◽  
Goal Directed Behavior

AbstractThe well-known deactivation of the Default Mode Network (DMN) during external tasks is usually thought to reflect the suppression of internally directed mental activity during external attention. In 3 experiments with human participants we organized sequences of task events identical in their attentional and control demands into larger task episodes. We found that DMN deactivation across such sequential events was never constant, but was maximum at the beginning of the episode, then decreased gradually across the episode, reaching baseline towards episode completion, with the final event of the episode eliciting an activation. Crucially, this pattern of activity was not limited to a fixed set of DMN regions but, across experiments, was shown by a variable set of regions expected to be uninvolved in processing the ongoing task. This change in deactivation across sequential but identical events showed that the deactivation cannot be related to attentional/control demands which were constant across the episode, instead it has to be related to some episode related load that was maximal at the beginning and then decreased gradually as parts of the episode got executed. We argue that this load resulted from cognitive programs through which the entire episode was hierarchically executed as one unit. At the beginning of task episodes, programs related to their entire duration is assembled, causing maximal deactivation. As execution proceeds, elements within the program related to the completed parts of the episode dismantle, thereby decreasing the program load and causing a decrease in deactivation.Significance StatementWe prepare breakfasts and write emails, and not individually execute their many component acts. The current study suggests that cognitive entities that enable such hierarchical execution of goal-directed behavior may cause the ubiquitously seen deactivation during external task execution. Further, while this deactivation has previously been associated with a defined set of the so called default mode regions, current study demonstrates that deactivation is shown by any region not currently involved in task execution, and in certain task episodes can even include attention related fronto-parietal regions as well as primary sensory and motor regions.

Development of a Jacobian Module for Advanced Pulp and Paper Simulation and Control

TAPPI Journal ◽  
2009 ◽  
Vol 8 (1) ◽  
pp. 4-11
Author(s):  
MOHAMED CHBEL ◽  
LUC LAPERRIÈRE
Keyword(s):  
Control System ◽  
Nonlinear Behavior ◽  
Simulation Software ◽  
Pulp And Paper ◽  
Pid Controllers ◽  
Tuning Parameters ◽  
Pid Tuning ◽  
Fixed Set ◽  
And Control ◽  
Operating Points

Pulp and paper processes frequently present nonlinear behavior, which means that process dynam-ics change with the operating points. These nonlinearities can challenge process control. PID controllers are the most popular controllers because they are simple and robust. However, a fixed set of PID tuning parameters is gen-erally not sufficient to optimize control of the process. Problems related to nonlinearities such as sluggish or oscilla-tory response can arise in different operating regions. Gain scheduling is a potential solution. In processes with mul-tiple control objectives, the control strategy must further evaluate loop interactions to decide on the pairing of manipulated and controlled variables that minimize the effect of such interactions and hence, optimize controller’s performance and stability. Using the CADSIM Plus™ commercial simulation software, we developed a Jacobian sim-ulation module that enables automatic bumps on the manipulated variables to calculate process gains at different operating points. These gains can be used in controller tuning. The module also enables the control system designer to evaluate loop interactions in a multivariable control system by calculating the Relative Gain Array (RGA) matrix, of which the Jacobian is an essential part.

Disrupted Salience and Cingulo-Opercular Network Connectivity During Impaired Rapid Instructed Task Learning in Schizophrenia

2021 ◽  
pp. 216770262095934
Author(s):  
Julia M. Sheffield ◽  
Holger Mohr ◽  
Hannes Ruge ◽  
Deanna M. Barch
Keyword(s):  
A Priori ◽  
Network Connectivity ◽  
Task Learning ◽  
Human Ability ◽  
Functional Brain Networks ◽  
Task Goals ◽  
Multivariate Pattern ◽  
And Control ◽  
Goal Directed Behavior

Rapid instructed task learning (RITL) is the uniquely human ability to transform task information into goal-directed behavior without relying on trial-and-error learning. RITL is a core cognitive process supported by functional brain networks. In patients with schizophrenia, RITL ability is impaired, but the role of functional network connectivity in these RITL deficits is unknown. We investigated task-based connectivity of eight a priori network pairs in participants with schizophrenia ( n = 29) and control participants ( n = 31) during the performance of an RITL task. Multivariate pattern analysis was used to determine which network connectivity patterns predicted diagnostic group. Of all network pairs, only the connectivity between the cingulo-opercular network (CON) and salience network (SAN) during learning classified patients and control participants with significant accuracy (80%). CON-SAN connectivity during learning was significantly associated with task performance in participants with schizophrenia. These findings suggest that impaired interactions between identification of salient stimuli and maintenance of task goals contributes to RITL deficits in participants with schizophrenia.

Decoupling countermands nonselective response inhibition during selective stopping

2021 ◽  
Author(s):  
Corey George Wadsley ◽  
John Cirillo ◽  
Arne Nieuwenhuys ◽  
Winston D Byblow
Keyword(s):  
Response Inhibition ◽  
Interference Effect ◽  
Complex Form ◽  
Functional Coupling ◽  
Response Preparation ◽  
Response Delay ◽  
Healthy Human ◽  
Human Participants ◽  
Goal Directed Behavior ◽  
Effector Response

Response inhibition is essential for goal-directed behavior within dynamic environments. Selective stopping is a complex form of response inhibition where only part of a multi-effector response must be cancelled. A substantial response delay emerges on unstopped effectors when a cued effector is successfully stopped. This stopping-interference effect is indicative of nonselective response inhibition during selective stopping which may, in-part, be a consequence of functional coupling. The present study examined selective stopping of (de)coupled bimanual responses in healthy human participants of either sex. Participants performed synchronous and asynchronous versions of an anticipatory stop-signal paradigm across two sessions while mu (µ) and beta (β) rhythm were measured with electroencephalography. Results showed that responses were behaviorally decoupled during asynchronous go trials and the extent of response asynchrony was associated with lateralized sensorimotor µ and β desynchronization during response preparation. Selective stopping produced a stopping-interference effect and was marked by a nonselective increase and subsequent rebound in prefrontal and sensorimotor β. In support of the coupling account, stopping-interference was smaller during selective stopping of asynchronous responses, and negatively associated with the magnitude of decoupling. However, the increase in sensorimotor β during selective stopping was equivalent between the stopped and unstopped hand irrespective of response synchrony. Overall, the findings demonstrate that decoupling facilitates selective stopping after a global pause process and emphasizes the importance of considering the influence of both the go and stop context when investigating response inhibition.

scholarly journals Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity

2015 ◽  
Vol 36 (7) ◽  
pp. 2719-2731 ◽  
Author(s):  
Luke Hearne ◽  
Luca Cocchi ◽  
Andrew Zalesky ◽  
Jason B. Mattingley
Keyword(s):  
Default Mode ◽  
Control Networks ◽  
Cognitive Reasoning ◽  
And Control

scholarly journals Neurophysiology (fMRI)

2015 ◽  
Vol 42 (S1) ◽  
pp. S38-S38
Author(s):  
ST Lang ◽  
B Goodyear ◽  
J Kelly ◽  
P Federico
Keyword(s):  
Cognitive Functioning ◽  
Default Mode Network ◽  
Resting State ◽  
Attentional Control ◽  
Brain Tumours ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Resting State Networks ◽  
Default Mode ◽  
Eloquent Cortex

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

scholarly journals Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4543 ◽  
Author(s):  
Heekyung Yang ◽  
Jongdae Han ◽  
Kyungha Min
Keyword(s):  
Emotion Recognition ◽  
Eeg Signals ◽  
Human Emotions ◽  
Human Participants ◽  
Valence And Arousal ◽  
And Control

Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove our argument. We also sample several scenes of these emotions from visual contents and control the contrast of the scenes. We manipulate the contrast of the scenes and measure the change of valence and arousal from human participants who watch the contents using a deep emotion recognition module based on electroencephalography (EEG) signals. As a result, we conclude that the enhancement of contrast induces the increase of valence, while the reduction of contrast induces the decrease. Meanwhile, the contrast control affects arousal on a very minute scale.

Age effects on the default mode and control networks in typically developing children

2014 ◽  
Vol 58 ◽  
pp. 89-95 ◽  
Author(s):  
João Ricardo Sato ◽  
Giovanni Abrahão Salum ◽  
Ary Gadelha ◽  
Felipe Almeida Picon ◽  
Pedro Mario Pan ◽  
...  
Keyword(s):  
Age Effects ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Default Mode ◽  
Control Networks ◽  
And Control

scholarly journals Towards a computational phenomenology of mental action: modelling meta-awareness and attentional control with deep parametric active inference

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Lars Sandved-Smith ◽  
Casper Hesp ◽  
Jérémie Mattout ◽  
Karl Friston ◽  
Antoine Lutz ◽  
...  
Keyword(s):  
Attentional Control ◽  
Formal Model ◽  
Hierarchical Level ◽  
Active Inference ◽  
Mental Action ◽  
Perceptual Object ◽  
Cognitive States ◽  
Policy Selection ◽  
Current Content ◽  
And Control

Abstract Meta-awareness refers to the capacity to explicitly notice the current content of consciousness and has been identified as a key component for the successful control of cognitive states, such as the deliberate direction of attention. This paper proposes a formal model of meta-awareness and attentional control using hierarchical active inference. To do so, we cast mental action as policy selection over higher-level cognitive states and add a further hierarchical level to model meta-awareness states that modulate the expected confidence (precision) in the mapping between observations and hidden cognitive states. We simulate the example of mind-wandering and its regulation during a task involving sustained selective attention on a perceptual object. This provides a computational case study for an inferential architecture that is apt to enable the emergence of these central components of human phenomenology, namely, the ability to access and control cognitive states. We propose that this approach can be generalized to other cognitive states, and hence, this paper provides the first steps towards the development of a computational phenomenology of mental action and more broadly of our ability to monitor and control our own cognitive states. Future steps of this work will focus on fitting the model with qualitative, behavioural, and neural data.

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