scholarly journals Scale-invariance in brain activity predicts practice effects in cognitive performance

2020 ◽  
Author(s):  
Omid Kardan ◽  
Elliot Layden ◽  
Kyoung Whan Choe ◽  
Muxuan Lyu ◽  
Xihan Zhang ◽  
...  
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Video Clip ◽  
Practice Effect ◽  
Network Activity ◽  
Practice Effects ◽  
Scale Free ◽  
Memory And Attention

AbstractAlthough practicing a task generally benefits later performance on that same task (‘practice effect’), there are large—and mostly unexplained—individual differences in reaping the benefits from practice. One promising avenue to model and predict such differences comes from recent research showing that brain networks can extract functional advantages from operating in the vicinity of criticality, a state in which brain network activity is more scale-free. As such, we hypothesized that individuals with more scale-free fMRI activity, indicated by BOLD time series with a higher Hurst exponent (H), gain more benefits from practice. In this study, participants practiced a test of working memory and attention, the dual n-back task (DNB), watched a video clip as a break, and then performed the DNB again, during MRI. To isolate the practice effect, we divided the participants into two groups based on improvement in performance from the first to second DNB task run. We identified regions and connections in which H and functional connectivity related to practice effects in the last run. More scale-free brain activity in these regions during the preceding runs (either first DNB or video) distinguished individuals who showed greater DNB performance improvements over time. In comparison, functional connectivity (r2) in the identified connections did not reliably classify the two groups in the preceding runs. Finally, we replicated both H and r2 results from study 1 in an independent fMRI dataset of participants performing multiple runs of another working memory and attention task (word completion). We conclude that the brain networks can accommodate further practice effects in individuals with higher scale-free BOLD activity.

scholarly journals Early alterations of social brain networks in young children with autism

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Holger Franz Sperdin ◽  
Ana Coito ◽  
Nada Kojovic ◽  
Tonia Anahi Rihs ◽  
Reem Kais Jan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Social Brain ◽  
Compensatory Mechanisms ◽  
Source Imaging ◽  
Gaze Patterns ◽  
Cortical Regions

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD.

scholarly journals Psilocybin acutely alters the functional connectivity of the claustrum with brain networks that support perception, memory, and attention

NeuroImage ◽  
2020 ◽  
Vol 218 ◽  
pp. 116980 ◽  
Author(s):  
Frederick S. Barrett ◽  
Samuel R. Krimmel ◽  
Roland R. Griffiths ◽  
David A. Seminowicz ◽  
Brian N. Mathur
Keyword(s):  
Functional Connectivity ◽  
Brain Networks ◽  
Memory And Attention

scholarly journals Neurofunctional Components of Simple Calculation: A Magnetoencephalography Study

2020 ◽  
Author(s):  
Elena Salillas ◽  
Francesco Piccione ◽  
Silvia di Tomasso ◽  
Sara Zago ◽  
Giorgio Arcara ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Simple Calculation ◽  
Correct Solution ◽  
Opposite Hemisphere ◽  
Causal Loop ◽  
Frontoparietal Network ◽  
Source Estimation ◽  
Electrophysiological Evidence

Abstract Our ability to calculate implies more than the sole retrieval of the correct solution. Essential processes for simple calculation are related to the spreading of activation through arithmetic memory networks. There is behavioral and electrophysiological evidence for these mechanisms. Their brain location is, however, still uncertain. Here, we measured magnetoencephalographic brain activity during the verification of simple multiplication problems. Following the operands, the solutions to verify could be preactivated correct solutions, preactivated table-related incorrect solutions, or unrelated incorrect solutions. Brain source estimation, based on these event-related fields, revealed 3 main brain networks involved in simple calculation: 1) bilateral inferior frontal areas mainly activated in response to correct, matching solutions; 2) a left-lateralized frontoparietal network activated in response to incorrect table-related solutions; and (3) a strikingly similar frontoparietal network in the opposite hemisphere activated in response to unrelated solutions. Directional functional connectivity analyses revealed a bidirectional causal loop between left parietal and frontal areas for table-related solutions, with frontal areas explaining the resolution of arithmetic competition behaviorally. Hence, this study isolated at least 3 neurofunctional networks orchestrated between hemispheres during calculation.

scholarly journals Brain networks and cognitive impairment in Parkinson′s disease

2020 ◽  
Author(s):  
Rosaria Rucco ◽  
Anna Lardone ◽  
marianna Liparoti ◽  
Emahnuel Troisi Lopez ◽  
Rosa De Micco ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Networks ◽  
Motor Impairment ◽  
Brain Network ◽  
Topological Features ◽  
Delta Band ◽  
Wide Range

Aim The aim of the present study is to investigate the relations between both functional connectivity and brain networks with cognitive decline, in patients with Parkinson′s disease (PD). Introduction PD phenotype is not limited to motor impairment but, rather, a wide range of non-motor disturbances can occur, cognitive impairment being one of the commonest. However, how the large-scale organization of brain activity differs in cognitively impaired patients, as opposed to cognitively preserved ones, remains poorly understood. Methods Starting from source-reconstructed resting-state magnetoencephalography data, we applied the PLM to estimate functional connectivity, globally and between brain areas, in PD patients with and without cognitive impairment (respectively PD-CI and PD-NC), as compared to healthy subjects (HS). Furthermore, using graph analysis, we characterized the alterations in brain network topology and related these, as well as the functional connectivity, to cognitive performance. Results We found reduced global and nodal PLM in several temporal (fusiform gyrus, Heschl′s gyrus and inferior temporal gyrus), parietal (postcentral gyrus), and occipital (lingual gyrus) areas within the left hemisphere, in the gamma band, in PD-CI patients, as compared to PD-NC and HS. With regard to the global topological features, PD-CI patients, as compared to HS and PD-NC patients, showed differences in multi frequencies bands (delta, alpha, gamma) in the Leaf fraction, Tree hierarchy (both higher in PD-CI) and Diameter (lower in PD-CI). Finally, we found statistically significant correlations between the MoCA test and both the Diameter in delta band and the Tree Hierarchy in the alpha band. Conclusion Our work points to specific large-scale rearrangements that occur selectively in cognitively compromised PD patients and correlated to cognitive impairment.

scholarly journals Altered Resting State Brain Networks and Cognition in Familial Adenomatous Polyposis

2020 ◽  
Author(s):  
Ryan J. Cali ◽  
Benjamin C. Nephew ◽  
Constance M. Moore ◽  
Serhiy Chumachenko ◽  
Ana Cecilia Sala ◽  
...  
Keyword(s):  
Neural Network ◽  
Familial Adenomatous Polyposis ◽  
Cognitive Deficits ◽  
Resting State ◽  
Brain Activity ◽  
Brain Networks ◽  
Network Activity ◽  
Adenomatous Polyposis ◽  
Autosomal Dominant Disorder ◽  
Functional Neural Network

AbstractFamilial Adenomatous Polyposis (FAP) is an autosomal dominant disorder caused by mutation of the APC gene presenting with numerous colorectal adenomatous polyps and a near 100% risk of colon cancer. Preliminary research findings from our group indicate that FAP patients experience significant deficits across many cognitive domains. In the current study, fMRI brain metrics in a FAP population and matched controls were used to further the mechanistic understanding of reported cognitive deficits. This research identified and characterized any possible differences in resting brain networks and associations between neural network changes and cognition from 34 participants (18 FAP patients, 16 healthy controls). Functional connectivity analysis was performed using FSL with independent component analysis (ICA) to identify functional networks. Significant differences between cases and controls were observed in 8 well-established resting state networks. With the addition of an aggregate cognitive measure as a covariate, these differences were virtually non-existent, indicating a strong correlation between cognition and brain activity at the network level. The data indicate robust and pervasive effects on functional neural network activity among FAP patients and these effects are likely involved in cognitive deficits associated with this disease.

scholarly journals Network Structure During Encoding Predicts Working Memory Performance

2018 ◽  
Author(s):  
Anirudh Wodeyar ◽  
Ramesh Srinivasan
Keyword(s):  
Working Memory ◽  
Graphical Model ◽  
Structural Characteristics ◽  
Brain Activity ◽  
Memory Performance ◽  
Memory Function ◽  
Brain Networks ◽  
Memory Task ◽  
Functional Clustering ◽  
Network Properties

ABSTRACTWorking memory operates through networks that integrate distributed modular brain activity. We characterize the structure of networks in different electroencephalographic frequency bands while individuals perform a working memory task. The objective was to identify network properties that support working memory function during the encoding, maintenance, and retrieval of memory. In each EEG frequency band, we estimated a complex-valued Gaussian graphical model to characterize the structure of brain networks using measures from graph theory. Critically, the structural characteristics of brain networks that facilitate performance are all established during encoding, suggesting that they reflect the effect of attention on the quality of the representation in working memory. Segregation of networks in the alpha and beta bands during encoding increased with accuracy. In the theta band, greater integration of functional clusters involving the temporal lobe with other cortical areas predicted faster response time, starting in the encoding interval and persisting throughout the task, indicating that functional clustering facilitates rapid memory manipulation.

scholarly journals Application of directed transfer function and network formalism for the assessment of functional connectivity in working memory task

2013 ◽  
Vol 371 (1997) ◽  
pp. 20110614 ◽  
Author(s):  
Katarzyna J. Blinowska ◽  
Maciej Kamiński ◽  
Aneta Brzezicka ◽  
Jan Kamiński
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Transfer Function ◽  
Brain Networks ◽  
Memory Task ◽  
Metabolic Energy ◽  
Modular Structure ◽  
Directed Transfer Function ◽  
Clear Cut ◽  
Strength Of Interaction

The dynamic pattern of functional connectivity during a working memory task was investigated by means of the short-time directed transfer function. A clear-cut picture of transmissions was observed with the main centres of propagation located in the frontal and parietal regions, in agreement with imaging studies and neurophysiological hypotheses concerning the mechanisms of working memory. The study of the time evolution revealed that most of the time short-range interactions prevailed, whereas the communication between the main centres of activity occurred more sparsely and changed dynamically in time. The patterns of connectivity were quantified by means of a network formalism based on assortative mixing—an approach novel in the field of brain networks study. By means of application of the above method, we have demonstrated the existence of a modular structure of brain networks. The strength of interaction inside the modules was higher than between modules. The obtained results are compatible with theories concerning metabolic energy saving and efficient wiring in the brain, which showed that preferred organization includes modular structure with dense connectivity inside the modules and more sparse connections between the modules. The presented detailed temporal and spatial patterns of propagation are in line with the neurophysiological hypotheses concerning the role of gamma and theta activity in information processing during a working memory task.

Short-Term Effects of Binaural Beats on EEG Power, Functional Connectivity, Cognition, Gait and Anxiety in Parkinson’s Disease

2018 ◽  
Vol 28 (05) ◽  
pp. 1750055 ◽  
Author(s):  
Gerardo Gálvez ◽  
Manuel Recuero ◽  
Leonides Canuet ◽  
Francisco Del-Pozo
Keyword(s):  
Parkinson’S Disease ◽  
Working Memory ◽  
Parkinson's Disease ◽  
Functional Connectivity ◽  
Repeated Measures ◽  
Brain Activity ◽  
Controlled Study ◽  
Binaural Beats ◽  
Repeated Measures Design ◽  
Eeg Power

We applied rhythmic binaural sound to Parkinson’s Disease (PD) patients to investigate its influence on several symptoms of this disease and on Electrophysiology (Electrocardiography and Electroencephalography (EEG)). We conducted a double-blind, randomized controlled study in which rhythmic binaural beats and control were administered over two randomized and counterbalanced sessions (within-subjects repeated-measures design). Patients ([Formula: see text], age [Formula: see text], stage I–III Hoehn & Yahr scale) participated in two sessions of sound stimulation for 10[Formula: see text]min separated by a minimum of 7 days. Data were collected immediately before and after both stimulations with the following results: (1) a decrease in theta activity, (2) a general decrease in Functional Connectivity (FC), and (3) an improvement in working memory performance. However, no significant changes were identified in the gait performance, heart rate or anxiety level of the patients. With regard to the control stimulation, we did not identify significant changes in the variables analyzed. The use of binaural-rhythm stimulation for PD, as designed in this study, seems to be an effective, portable, inexpensive and noninvasive method to modulate brain activity. This influence on brain activity did not induce changes in anxiety or gait parameters; however, it resulted in a normalization of EEG power (altered in PD), normalization of brain FC (also altered in PD) and working memory improvement (a normalizing effect). In summary, we consider that sound, particularly binaural-rhythmic sound, may be a co-assistant tool in the treatment of PD, however more research is needed to consider the use of this type of stimulation as an effective therapy.

scholarly journals History of Alcohol Consumption and HIV Status Related to Functional Connectivity Differences in the Brain During Working Memory Performance

2020 ◽  
Vol 18 (3) ◽  
pp. 181-193 ◽  
Author(s):  
Vaughn E. Bryant ◽  
Joseph M. Gullett ◽  
Eric C. Porges ◽  
Robert L. Cook ◽  
Kendall J. Bryant ◽  
...  
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Alcohol Consumption ◽  
Memory Performance ◽  
Memory Function ◽  
Brain Networks ◽  
Memory Task ◽  
Hiv Positive ◽  
Hiv Status ◽  
Using Data

Background: Poorer working memory function has previously been associated with alcohol misuse, Human Immunodeficiency Virus (HIV) positive status, and risky behavior. Poorer working memory performance relates to alterations in specific brain networks. Objective: The current study examined if there was a relationship between brain networks involved in working memory and reported level of alcohol consumption during an individual’s period of heaviest use. Furthermore, we examined whether HIV status and the interaction between HIV and alcohol consumption was associated with differences in these brain networks. Methods: Fifty adults, 26 of whom were HIV positive, engaged in an n-back working memory task (0-back and 2-back trials) administered in a magnetic resonance imaging (MRI) scanner. The Kreek- McHugh-Schluger-Kellogg (KMSK) scale of alcohol consumption was used to characterize an individual’s period of heaviest use and correlates well with their risk for alcohol dependence. Connectivity analyses were conducted using data collected during n-back task. Results: Functional connectivity differences associated with greater alcohol consumption included negative connectivity, primarily from parietal attention networks to frontal networks. Greater alcohol consumption was also associated with positive connectivity from working memory nodes to the precuneus and paracingulate. HIV positive status was associated with more nodes of negative functional connectivity relative to alcohol consumption history alone, particularly in the frontoparietal networks. The HIV positive individuals with heavier drinking history related to negative fronto-parietal connectivity, along with positive connectivity from working memory nodes to mesolimbic regions. Conclusion: Findings allow for a better understanding of brain networks affected by HIV and alcohol and may provide avenues for interventions.

scholarly journals Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity

2020 ◽  
Author(s):  
Danielle L. Kurtin ◽  
Ines R. Violante ◽  
Karl Zimmerman ◽  
Robert Leech ◽  
Adam Hampshire ◽  
...  
Keyword(s):  
White Matter ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Networks ◽  
Brain Network ◽  
Network Activity ◽  
Brain State ◽  
State Dependent ◽  
Cathodal Tdcs ◽  
The Right

AbstractBackgroundTranscranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure.ObjectivesIn this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity.MethodsWe applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n=22) and TBI participants (n=34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure.ResultsWe find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional – in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region.ConclusionsOur results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation.

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