scholarly journals Rethinking brain-wide interactions through multi-region “network of networks” models

2020 ◽  
Author(s):  
Matthew Perich ◽  
Kanaka Rajan
Keyword(s):  
Recent Work ◽  
Neural Control ◽  
Large Scale ◽  
Brain Regions ◽  
Interconnected Network ◽  
Neural Basis ◽  
Theoretical Approaches ◽  
Neural Populations ◽  
The Brain ◽  
Network Of Networks

The neural control of behavior is distributed across many functionally and anatomically distinct brain regions even in small nervous systems. While classical neuroscience models treated these regions as a set of hierarchically isolated nodes, the brain comprises a recurrently interconnected network in which each region is intimately modulated by many others. Uncovering these interactions is now possible through experimental techniques that access large neural populations from many brain regions simultaneously. Harnessing these large-scale datasets, however, requires new theoretical approaches. Here, we review recent work to understand brain-wide interactions using multi-region "network of networks" models and discuss how they can guide future experiments. We also emphasize the importance of multi-region recordings, and posit that studying individual components in isolation will be insufficient to understand the neural basis of behavior.

scholarly journals The Neural Basis of Motivational Influences on Cognitive Control

2017 ◽  
Author(s):  
Cameron Parro ◽  
Matthew L Dixon ◽  
Kalina Christoff
Keyword(s):  
Cognitive Control ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Premotor Cortex ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Control Mechanisms ◽  
Neural Basis ◽  
The Brain

AbstractCognitive control mechanisms support the deliberate regulation of thought and behavior based on current goals. Recent work suggests that motivational incentives improve cognitive control, and has begun to elucidate the brain regions that may support this effect. Here, we conducted a quantitative meta-analysis of neuroimaging studies of motivated cognitive control using activation likelihood estimation (ALE) and Neurosynth in order to delineate the brain regions that are consistently activated across studies. The analysis included functional neuroimaging studies that investigated changes in brain activation during cognitive control tasks when reward incentives were present versus absent. The ALE analysis revealed consistent recruitment in regions associated with the frontoparietal control network including the inferior frontal sulcus (IFS) and intraparietal sulcus (IPS), as well as consistent recruitment in regions associated with the salience network including the anterior insula and anterior mid-cingulate cortex (aMCC). A large-scale exploratory meta-analysis using Neurosynth replicated the ALE results, and also identified the caudate nucleus, nucleus accumbens, medial thalamus, inferior frontal junction/premotor cortex (IFJ/PMC), and hippocampus. Finally, we conducted separate ALE analyses to compare recruitment during cue and target periods, which tap into proactive engagement of rule-outcome associations, and the mobilization of appropriate viscero-motor states to execute a response, respectively. We found that largely distinct sets of brain regions are recruited during cue and target periods. Altogether, these findings suggest that flexible interactions between frontoparietal, salience, and dopaminergic midbrain-striatal networks may allow control demands to be precisely tailored based on expected value.

scholarly journals Emergence of the Affect from the Variation in the Whole-Brain Flow of Information

2019 ◽  
Vol 10 (1) ◽  
pp. 8
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hiroshi Ishiguro
Keyword(s):  
Information Flow ◽  
Cortical Neurons ◽  
Large Scale ◽  
Brain Activation ◽  
Brain Regions ◽  
Neural Basis ◽  
Whole Brain ◽  
Affect States ◽  
Flow Of Information ◽  
The Brain

Over the past few decades, the quest for discovering the brain substrates of the affect to understand the underlying neural basis of the human’s emotions has resulted in substantial and yet contrasting results. Whereas some point at distinct and independent brain systems for the Positive and Negative affects, others propose the presence of flexible brain regions. In this respect, there are two factors that are common among these previous studies. First, they all focused on the change in brain activation, thereby neglecting the findings that indicate that the stimuli with equivalent sensory and behavioral processing demands may not necessarily result in differential brain activation. Second, they did not take into consideration the brain regional interactivity and the findings that identify that the signals from individual cortical neurons are shared across multiple areas and thus concurrently contribute to multiple functional pathways. To address these limitations, we performed Granger causal analysis on the electroencephalography (EEG) recordings of the human subjects who watched movie clips that elicited Negative, Neutral, and Positive affects. This allowed us to look beyond the brain regional activation in isolation to investigate whether the brain regional interactivity can provide further insights for understanding the neural substrates of the affect. Our results indicated that the differential affect states emerged from subtle variation in information flow of the brain cortical regions that were in both hemispheres. They also showed that these regions that were rather common between affect states than distinct to a specific affect were characterized with both short- as well as long-range information flow. This provided evidence for the presence of simultaneous integration and differentiation in the brain functioning that leads to the emergence of different affects. These results are in line with the findings on the presence of intrinsic large-scale interacting brain networks that underlie the production of psychological events. These findings can help advance our understanding of the neural basis of the human’s emotions by identifying the signatures of differential affect in subtle variation that occurs in the whole-brain cortical flow of information.

scholarly journals Decoding the future from past experience: learning shapes predictions in early visual cortex

2015 ◽  
Vol 113 (9) ◽  
pp. 3159-3171 ◽  
Author(s):  
Caroline D. B. Luft ◽  
Alan Meeson ◽  
Andrew E. Welchman ◽  
Zoe Kourtzi
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Sequence Structure ◽  
Neural Populations ◽  
Early Visual Cortex ◽  
Temporal Structures ◽  
Future Events ◽  
Sensory Predictions ◽  
Actual Stimulus ◽  
The Brain

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex.

scholarly journals Message-Elicited Brain Response Moderates the Relationship Between Opportunities for Exposure to Anti-Smoking Messages and Message Recall

2019 ◽  
Vol 69 (6) ◽  
pp. 589-611
Author(s):  
Elissa C Kranzler ◽  
Ralf Schmälzle ◽  
Rui Pei ◽  
Robert C Hornik ◽  
Emily B Falk
Keyword(s):  
Large Scale ◽  
Communication Theory ◽  
Brain Regions ◽  
Message Processing ◽  
Memory Encoding ◽  
Brain Response ◽  
Real Cost ◽  
Social Processing ◽  
The Relationship ◽  
The Brain

Abstract Campaign success is contingent on adequate exposure; however, exposure opportunities (e.g., ad reach/frequency) are imperfect predictors of message recall. We hypothesized that the exposure-recall relationship would be contingent on message processing. We tested moderation hypotheses using 3 data sets pertinent to “The Real Cost” anti-smoking campaign: past 30-day ad recall from a rolling national survey of adolescents aged 13–17 (n = 5,110); ad-specific target rating points (TRPs), measuring ad reach and frequency; and ad-elicited response in brain regions implicated in social processing and memory encoding, from a separate adolescent sample aged 14–17 (n = 40). Average ad-level brain activation in these regions moderates the relationship between national TRPs and large-scale recall (p < .001), such that the positive exposure-recall relationship is more strongly observed for ads that elicit high levels of social processing and memory encoding in the brain. Findings advance communication theory by demonstrating conditional exposure effects, contingent on social and memory processes in the brain.

scholarly journals Neural Correlates of Group Bias During Natural Viewing

2018 ◽  
Vol 29 (8) ◽  
pp. 3380-3389
Author(s):  
Timothy J Andrews ◽  
Ryan K Smith ◽  
Richard L Hoggart ◽  
Philip I N Ulrich ◽  
Andre D Gouws
Keyword(s):  
Time Course ◽  
Social Groups ◽  
Sensory Information ◽  
Brain Regions ◽  
Group Differences ◽  
Neural Basis ◽  
Brain Responses ◽  
The World ◽  
High Level ◽  
The Brain

Abstract Individuals from different social groups interpret the world in different ways. This study explores the neural basis of these group differences using a paradigm that simulates natural viewing conditions. Our aim was to determine if group differences could be found in sensory regions involved in the perception of the world or were evident in higher-level regions that are important for the interpretation of sensory information. We measured brain responses from 2 groups of football supporters, while they watched a video of matches between their teams. The time-course of response was then compared between individuals supporting the same (within-group) or the different (between-group) team. We found high intersubject correlations in low-level and high-level regions of the visual brain. However, these regions of the brain did not show any group differences. Regions that showed higher correlations for individuals from the same group were found in a network of frontal and subcortical brain regions. The interplay between these regions suggests a range of cognitive processes from motor control to social cognition and reward are important in the establishment of social groups. These results suggest that group differences are primarily reflected in regions involved in the evaluation and interpretation of the sensory input.

scholarly journals Medial Orbitofrontal Cortex Is Associated with Fatigue Sensation

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Seiki Tajima ◽  
Shigeyuki Yamamoto ◽  
Masaaki Tanaka ◽  
Yosky Kataoka ◽  
Masao Iwase ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Orbitofrontal Cortex ◽  
Brain Region ◽  
Statistical Parametric Mapping ◽  
Brain Regions ◽  
Mapping Method ◽  
Emission Tomography ◽  
Neural Basis ◽  
Positron Emission ◽  
The Brain

Fatigue is an indispensable bioalarm to avoid exhaustive state caused by overwork or stresses. It is necessary to elucidate the neural mechanism of fatigue sensation for managing fatigue properly. We performedH2O  15positron emission tomography scans to indicate neural activations while subjects were performing 35-min fatigue-inducing task trials twice. During the positron emission tomography experiment, subjects performed advanced trail-making tests, touching the target circles in sequence located on the display of a touch-panel screen. In order to identify the brain regions associated with fatigue sensation, correlation analysis was performed using statistical parametric mapping method. The brain region exhibiting a positive correlation in activity with subjective sensation of fatigue, measured immediately after each positron emission tomography scan, was located in medial orbitofrontal cortex (Brodmann's area 10/11). Hence, the medial orbitofrontal cortex is a brain region associated with mental fatigue sensation. Our findings provide a new perspective on the neural basis of fatigue.

scholarly journals Dynamic connectivity analyses of intracranial EEG during recognition memory reveal various large-scale functional networks

2020 ◽  
Author(s):  
Jakub Kopal ◽  
Jaroslav Hlinka ◽  
Elodie Despouy ◽  
Luc Valton ◽  
Marie Denuelle ◽  
...  
Keyword(s):  
Recognition Memory ◽  
Large Scale ◽  
Visual Recognition ◽  
Effective Connectivity ◽  
Memory Task ◽  
Brain Regions ◽  
Neural Basis ◽  
Intracranial Eeg ◽  
Large Scale Networks ◽  
The Right

Recognition memory is the ability to recognize previously encountered events, objects, or people. It is characterized by its robustness and rapidness. Even this relatively simple ability requires the coordinated activity of a surprisingly large number of brain regions. These spatially distributed, but functionally linked regions are interconnected into large-scale networks. Understanding memory requires an examination of the involvement of these networks and the interactions between different regions while memory processes unfold. However, little is known about the dynamical organization of large-scale networks during the early phases of recognition memory. We recorded intracranial EEG, which affords high temporal and spatial resolution, while epileptic subjects performed a visual recognition memory task. We analyzed dynamic functional and effective connectivity as well as network properties. Various networks were identified, each with its specific characteristics regarding information flow (feedforward or feedback), dynamics, topology, and stability. The first network mainly involved the right visual ventral stream and bilateral frontal regions. It was characterized by early predominant feedforward activity, modular topology, and high stability. It was followed by the involvement of a second network, mainly in the left hemisphere, but notably also involving the right hippocampus, characterized by later feedback activity, integrated topology, and lower stability. The transition between networks was associated with a change in network topology. Overall, these results confirm that several large-scale brain networks, each with specific properties and temporal manifestation, are involved during recognition memory. Ultimately, understanding how the brain dynamically faces rapid changes in cognitive demand is vital to our comprehension of the neural basis of cognition.

scholarly journals The Neural Basis of Shared Preference Learning

2019 ◽  
Author(s):  
Harry Farmer ◽  
Uri Hertz ◽  
Antonia Hamilton
Keyword(s):  
Social Interactions ◽  
Computational Modelling ◽  
Brain Regions ◽  
The Self ◽  
Neural Activation ◽  
Neural Basis ◽  
Daily Lives ◽  
Neural Processes ◽  
Specific Manner ◽  
The Brain

AbstractDuring our daily lives, we often learn about the similarity of the traits and preferences of others to our own and use that information during our social interactions. However, it is unclear how the brain represents similarity between the self and others. One possible mechanism is to track similarity to oneself regardless of the identity of the other (Similarity account); an alternative is to track each confederate in terms of consistency of the similarity to the self, with respect to the choices they have made before (consistency account). Our study combined fMRI and computational modelling of reinforcement learning (RL) to investigate the neural processes that underlie learning about preference similarity. Participants chose which of two pieces of artwork they preferred and saw the choices of one confederate who usually shared their preference and another who usually did not. We modelled neural activation with RL models based on the similarity and consistency accounts. Data showed more brain regions whose activity pattern fits with the consistency account, specifically, areas linked to reward and social cognition. Our findings suggest that impressions of other people can be calculated in a person-specific manner which assumes that each individual behaves consistently with their past choices.

scholarly journals Seeking the “beauty center” in the brain: A meta-analysis of fMRI studies of beautiful human faces and visual art

2016 ◽  
Author(s):  
Chuan-Peng Hu ◽  
Yi Huang ◽  
Simon B. Eickhoff ◽  
Kaiping Peng ◽  
Jie Sui
Keyword(s):  
Visual Art ◽  
Ventral Striatum ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Neural Basis ◽  
The Common ◽  
Conjunction Analysis ◽  
Human Faces ◽  
The Brain

AbstractThe existence of a common beauty is a long-standing debate in philosophy and related disciplines. In the last two decades, cognitive neuroscientists have sought to elucidate this issue by exploring the common neural basis of the experience of beauty. Still, empirical evidence for such common neural basis of different forms of beauty is not conclusive. To address this question, we performed an activation likelihood estimation (ALE) meta-analysis on the existing neuroimaging studies of beauty appreciation of faces and visual art by non-expert adults (49 studies, 982 participants, meta-data are available at https://osf.io/s9xds/). We observed that perceiving these two forms of beauty activated distinct brain regions: while the beauty of faces convergently activated the left ventral striatum, the beauty of visual art convergently activated the anterior medial prefrontal cortex (aMPFC). However, a conjunction analysis failed to reveal any common brain regions for the beauty of visual art and faces. The implications of these results are discussed.

scholarly journals Heterogeneity of EEG resting-state brain networks in absolute pitch

2020 ◽  
Author(s):  
Marielle Greber ◽  
Carina Klein ◽  
Simon Leipold ◽  
Silvano Sele ◽  
Lutz Jäncke
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Resting State ◽  
Large Scale ◽  
Absolute Pitch ◽  
Brain Regions ◽  
Brain Network ◽  
Higher Order ◽  
Neural Basis ◽  
Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

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