scholarly journals How the human brain introspects about one’s own episodes of cognitive control

2017 ◽  
Author(s):  
David Soto ◽  
Mona Theodoraki ◽  
Pedro M. Paz-Alonso
Keyword(s):  
Cognitive Control ◽  
Human Brain ◽  
Internal Model ◽  
Large Scale ◽  
Brain Activity ◽  
Temporal Correlation ◽  
Control Networks ◽  
Control Functions ◽  
Cognitive States ◽  
Behavioural Performance

AbstractMetacognition refers to our capacity to reflect upon our experiences, thoughts and actions. Metacognition processes are linked to cognitive control functions that allow keeping our actions on-task. But it is unclear how the human brain builds an internal model of one’s cognition and behaviour. We conducted 2 fMRI experiments in which brain activity was recorded ‘online’ as participants engaged in a memory-guided search task and then later ‘offline’ when participants introspected about their prior experience and cognitive states during performance. In Experiment 1 the memory cues were task-relevant while in Experiment 2 they were irrelevant. Across Experiments, the patterns of brain activity, including frontoparietal regions, were similar during on-task and introspection states. However the connectivity profile amongst frontoparietal areas was distint during introspection and modulated by the relevance of the memory cues. Introspection was also characterized by increased temporal correlation between the default-mode network (DMN), frontoparietal and dorsal attention networks and visual cortex. We suggest that memories of one’s own experience during task performance are encoded in large-scale patterns of brain activity and that coupling between DMN and frontoparietal control networks may be crucial to build an internal model of one’s behavioural performance.

scholarly journals Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

2016 ◽  
Author(s):  
Timothy N. Rubin ◽  
Oluwasanmi Koyejo ◽  
Krzysztof J. Gorgolewski ◽  
Michael N. Jones ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Brain Activity ◽  
Human Cognition ◽  
Brain Images ◽  
Whole Brain ◽  
Context Sensitive ◽  
Cognitive States ◽  
Small Set

AbstractA central goal of cognitive neuroscience is to decode human brain activity--i.e., to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive--i.e., capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a Bayesian decoding framework based on a novel topic model---Generalized Correspondence Latent Dirichlet Allocation---that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text--enabling researchers, for the first time, to generative quantitative, context-sensitive interpretations of whole-brain patterns of brain activity.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals Monolingual and bilingual infants rely on the same brain networks: Evidence from resting-state functional connectivity

2020 ◽  
Author(s):  
Borja Blanco ◽  
Monika Molnar ◽  
Manuel Carreiras ◽  
Liam H. Collins-Jones ◽  
Ernesto Vidal ◽  
...  
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Near Infrared ◽  
Functional Organization ◽  
Brain Activity ◽  
Functional Brain Imaging ◽  
Resting State Functional Connectivity ◽  
Functional Near Infrared Spectroscopy ◽  
Behavioural Research ◽  
Infant Brain

AbstractThis study examines whether bilingual exposure has a profound effect on the functional organization of the developing human brain during infancy. Recent behavioural research attests that monolingual vs. bilingual experience affects cognitive and linguistic processes already during the first months of life. However, to what extent the intrinsic organization of the infant human brain adapts to monolingual vs. bilingual environments is unclear. We measured spontaneous hemodynamic brain activity using functional near-infrared spectroscopy (fNIRS) in a large cohort (N=99) of 4-month-old monolingual and bilingual infants. We implemented well-established analysis approaches of functional brain imaging that enabled us to reveal the functional organization of the infant brain in large-scale cortical networks, and to perform group-level comparisons (i.e., monolingual vs. bilingual groups) in a reliable manner. Our results revealed no differences between the intrinsic functional organization of the developing monolingual and bilingual infant brain at 4 months of age.

scholarly journals Combining Noninvasive Electromagnetic and Hemodynamic Measures of Human Brain Activity

2020 ◽  
pp. 179-193
Author(s):  
Fa-Hsuan Lin ◽  
Thomas Witzel ◽  
Matti S. Hämäläinen ◽  
Aapo Nummenmaa
Keyword(s):  
Human Brain ◽  
Neuronal Activity ◽  
Large Scale ◽  
Brain Activity ◽  
High Sensitivity ◽  
Minimum Norm ◽  
Source Modeling ◽  
Physiological Basis ◽  
Fusion Technique ◽  
Minimum Norm Estimate

AbstractMagnetoencephalography (MEG) is directly sensitive to postsynaptic neuronal activity with the millisecond temporal resolution. MEG is ideally to complement functional MRI (fMRI), which measures hemodynamic responses secondary to neuronal activity with the millimeter spatial resolution, for noninvasive imaging of human brain function. Here, using the Minimum-Norm Estimate as an example, we review how fMRI can be integrated with MEG (and electroencephalography, EEG) source modeling and summarize potential advantages and pitfalls of this data fusion technique. Neurovascular coupling as the physiological basis for MEG/EEG/fMRI integration is also discussed. Ultimately, we expect to develop multimodal MEG/EEG/fMRI neuroimaging methodology for characterizing spatiotemporal functional connectivity in large-scale neural networks of the human brain with high sensitivity and accuracy.

scholarly journals Increased amygdala volume and functional connectivity with cognitive control networks in chronic migraine

2020 ◽  
Author(s):  
Danielle D DeSouza ◽  
Samuel R Krimmel ◽  
Bharati M Sanjanwala ◽  
Addie Peretz ◽  
Vinod Menon ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Chronic Migraine ◽  
Resting State ◽  
Large Scale ◽  
Pain Catastrophizing ◽  
Headache Frequency ◽  
Control Networks ◽  
Affective Symptoms ◽  
Amygdala Volume

Objective: To characterize the role of the amygdala in episodic (EM) and chronic (CM) migraine, we evaluated amygdala volumes, functional connectivity (FC), and associations with clinical and affective measures. Methods: Eighty-eight patients (44 with EM and 44 age- and sex-matched patients with CM) completed anatomical and resting-state functional MRI scans. Amygdala volumes and resting-state FC to three core large-scale cognitive control networks (default mode (DMN), salience (SN), central executive (CEN)) were compared between groups. Associations between amygdala volume and FC, measures of headache severity (frequency and intensity), and cognitive-affective measures (depression, anxiety, pain catastrophizing) were evaluated. Results: Compared to EM, patients with CM had larger amygdala volume bilaterally. Headache frequency and intensity were associated with increased left and right amygdala volume, and depression was associated with increased right amygdala volume. Patients with CM also demonstrated increased left amygdala FC with the DMN, which across patients was related to headache frequency. Left amygdala FC to the SN was correlated with headache intensity while right amygdala FC to the CEN was correlated with pain catastrophizing. Conclusion: Our findings reveal increased amygdala volume and FC with large-scale neurocognitive networks in patients with CM compared to EM. Aberrant amygdala volume and FC measures were associated with increased migraine severity, depression, and pain catastrophizing, pointing to a link between emotion and pain in migraine. Our findings provide novel insights into amygdala involvement in chronic migraine and may inform future interventions aimed at preventing the progression of both headache and its negative cognitive-affective symptoms.

Integrative Visuomotor Behavior Is Associated With Interregionally Coherent Oscillations in the Human Brain

1998 ◽  
Vol 79 (3) ◽  
pp. 1567-1573 ◽  
Author(s):  
Joseph Classen ◽  
Christian Gerloff ◽  
Manabu Honda ◽  
Mark Hallett
Keyword(s):  
Motor Cortex ◽  
Human Brain ◽  
Large Scale ◽  
Isometric Force ◽  
Brain Activity ◽  
Motor Task ◽  
Low Frequency ◽  
Visuomotor Behavior ◽  
Electrical Brain Activity ◽  
Eeg Recordings

Classen, Joseph, Christian Gerloff, Manabu Honda, and Mark Hallett. Integrative visuomotor behavior is associated with interregionally coherent oscillations in the human brain. J. Neurophysiol. 79: 1567–1573, 1998. Coherent electrical brain activity has been demonstrated to be associated with perceptual events in mammals. It is unclear whether or not it is also a mechanism instrumental in the performance of sensorimotor tasks requiring the continuous processing of information between primarily executive and receptive brain areas. In particular it is unknown whether or not interregional coherent activity detectable in electroencephalographic (EEG) recordings on the scalp reflects interareal functional cooperativity in humans. We studied patterns of changes in EEG-coherence associated with a visuomotor force-tracking task in seven subjects. Interregional coherence of EEG signals recorded from scalp regions overlying the visual and the motor cortex increased in comparison to a resting condition when subjects tracked a visual target by producing an isometric force with their right index finger. Coherence between visual and motor cortex decreased when the subjects produced a similar motor output in the presence of a visual distractor and was unchanged in a purely visual and purely motor task. Increases and decreases of coherence were best differentiated in the low beta frequency range (13–21 Hz). This observation suggests a special functional significance of low frequency oscillations in information processing in large-scale networks. These findings substantiate the view that coherent brain activity underlies integrative sensorimotor behavior.

scholarly journals Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

2019 ◽  
Author(s):  
Thomas H. Alderson ◽  
Arun L.W. Bokde ◽  
J.A.Scott. Kelso ◽  
Liam Maguire ◽  
Damien Coyle
Keyword(s):  
Cognitive Control ◽  
Cognitive Performance ◽  
Resting State ◽  
Network Architecture ◽  
Large Scale ◽  
Fluid Intelligence ◽  
Coordination Dynamics ◽  
Resting State Networks ◽  
Control Networks ◽  
Local Areas

AbstractDespite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies toward integration and segregation by operating in a metastable regime of their coordination dynamics. One proposal is that metastability confers important behavioural qualities by dynamically binding distributed local areas into large-scale neurocognitive entities. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N=566) and comparing the metastability of the brain’s large-scale resting network architecture at rest and during the performance of several tasks. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving (or fluid intelligence) but was less important in tasks relying on prior experience (or crystallised intelligence). Crucially, subjects with resting architectures similar or ‘pre-configured’ to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a critical linkage between the spontaneous metastability of the large-scale networks of the cerebral cortex and cognition.

scholarly journals Flexible coordinator and switcher hubs for adaptive task control

2019 ◽  
Author(s):  
Carrisa V Cocuzza ◽  
Takuya Ito ◽  
Douglas Schultz ◽  
Danielle S Bassett ◽  
Michael W Cole
Keyword(s):  
Cognitive Control ◽  
Large Scale ◽  
Network Dynamics ◽  
Mental Illnesses ◽  
Global Network ◽  
Connectivity Pattern ◽  
Dependent Manner ◽  
Control Networks ◽  
Processing Resources ◽  
Network Properties

AbstractFunctional connectivity studies have identified at least two large-scale neural systems that constitute cognitive control networks – the frontoparietal network (FPN) and cingulo-opercular network (CON). Control networks are thought to support goal-directed cognition and behavior. It was previously shown that the FPN flexibly shifts its global connectivity pattern according to task goal, consistent with a “flexible hub” mechanism for cognitive control. Our aim was to build on this finding to develop a functional cartography (a multi-metric profile) of control networks in terms of dynamic network properties. We quantified network properties in (male and female) humans using a high-control-demand cognitive paradigm involving switching among 64 task sets. We hypothesized that cognitive control is enacted by the FPN and CON via distinct but complementary roles reflected in network dynamics. Consistent with a flexible “coordinator” mechanism, FPN connections were varied across tasks, while maintaining within-network connectivity to aid cross-region coordination. Consistent with a flexible “switcher” mechanism, CON regions switched to other networks in a task-dependent manner, driven primarily by reduced within-network connections to other CON regions. This pattern of results suggests FPN acts as a dynamic, global coordinator of goal-relevant information, while CON transiently disbands to lend processing resources to other goal-relevant networks. This cartography of network dynamics reveals a dissociation between two prominent cognitive control networks, suggesting complementary mechanisms underlying goal-directed cognition.Significance StatementCognitive control supports a variety of behaviors requiring flexible cognition, such as rapidly switching between tasks. Furthermore, cognitive control is negatively impacted in a variety of mental illnesses. We used tools from network science to characterize the implementation of cognitive control by large-scale brain systems. This revealed that two systems – the frontoparietal (FPN) and cingulo-opercular (CON) networks – have distinct but complementary roles in controlling global network reconfigurations. The FPN exhibited properties of a flexible coordinator (orchestrating task changes), while CON acted as a flexible switcher (switching specific regions to other systems to lend processing resources). These findings reveal an underlying distinction in cognitive processes that may be applicable to clinical, educational, and machine learning work targeting cognitive flexibility.

scholarly journals On the edge of criticality: strength-dependent perturbation unveils delicate balance between fluctuation and oscillation in brain dynamics

2021 ◽  
Author(s):  
Yontatan Sanz Perl ◽  
Anira Escrichs ◽  
Enzo Tagliazucchi ◽  
Morten L Kringelbach ◽  
Gustavo Deco
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Dynamics ◽  
Functional Networks ◽  
Oscillatory Regime ◽  
Delicate Balance ◽  
Local Strength ◽  
Global Strength

Going beyond previous research, we use strength-dependent perturbation to obtain a deeper understanding of the mechanisms underlying the emergence of large-scale brain activity. Despite decades of research, we still have a shallow understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used global strength-dependent perturbation to give a causal mechanistic description of human brain function providing a delicate balance between fluctuation and oscillation on the edge of criticality. After application of precise local strength-dependent perturbations and measuring the well-known perturbative complexity index, we demonstrated that the overall balance is shifted towards a fluctuating regime which is superior in terms of enhancing different functional networks compared to the oscillatory regime. This framework can generate specific, testable empirical predictions to be tested in human stimulation studies with strength-dependent rather than constant perturbation. Overall, our novel strength-dependent perturbation framework demonstrates that the human brain is poised on the edge of criticality, between fluctuations to oscillations, allowing for maximal flexibility.

Behavioral stochastic resonance associated with large-scale synchronization of human brain activity

2004 ◽  
Author(s):  
Keiichi Kitajo ◽  
Kentaro Yamanaka ◽  
Daichi Nozaki ◽  
Lawrence M. Ward ◽  
Yoshiharu Yamamoto
Keyword(s):  
Human Brain ◽  
Stochastic Resonance ◽  
Large Scale ◽  
Brain Activity
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