The dynamic properties of a brain network during working memory based on the algorithm of cross-frequency coupling

Working memory (WM) refers to a memory system with limited energy for short-term maintenance and plays an important role in cognitive functions. At present, research regarding WM mostly focuses on the coordination between neural signals in the signal microelectrode channel. However, how neural signals coordinate the coding of WM at the network level is rarely studied. Cross-frequency coupling (CFC) reflects the coordinated effect between different frequency components (e.g., theta and gamma) of local field potentials (LFPs) during WM. In this study, we try to map the changes that occur in the brain networks during WM at the level of CFC between theta-gamma of LFPs. First, a 16-channel brain network by using the CFC between theta-gamma of LFPs during WM was constructed. Then, the dynamic properties of the brain network during WM were analyzed based on graph theory. Experimental results show that the LFPs power increased at the WM state than at resting stat, but decreased across learning; the CFC between theta-gamma increased with learning days and phase-amplitude coupling (PAC) in the WM state was higher than that in free choice state and rest state; the changes of average degree, average shortest path length and global efficiency had significant difference on learning days. We can indicate that the CFC between theta-gamma in the network plays an important role in the WM formation. Furthermore, correct storage of WM information will not change local information transmission and the small-world attribute, while, it can increase the network connection and efficiency of information transmission.

[1]  Jie Zheng,et al.  Hippocampal CA1 gamma power predicts the precision of spatial memory judgments , 2018, Proceedings of the National Academy of Sciences.

[2]  Yangding Li,et al.  Abnormal brain white matter network in young smokers: a graph theory analysis study , 2018, Brain Imaging and Behavior.

[3]  Hui Chen,et al.  Neuronal activity pattern defects in the striatum in awake mouse model of Parkinson’s disease , 2018, Behavioural Brain Research.

[4]  Yong He,et al.  Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease. , 2015, Cerebral cortex.

[5]  Guizhi Xu,et al.  Changes in Brain Functional Networks of Insomniacs Induced by Magnetic Stimulation at Acupoints , 2019, IEEE Transactions on Applied Superconductivity.

[6]  A. Gouws,et al.  A Direct Demonstration of Functional Differences between Subdivisions of Human V5/MT+ , 2016, Cerebral cortex.

[7]  Yanchun Zhang,et al.  Weighted Visibility Graph With Complex Network Features in the Detection of Epilepsy , 2016, IEEE Access.

[8]  Uwe Friese,et al.  Alterations in oscillatory cortical activity indicate changes in mnemonic processing during continuous item recognition , 2018, Experimental Brain Research.

[9]  Ann M Graybiel,et al.  Oscillations of local field potentials in the rat dorsal striatum during spontaneous and instructed behaviors. , 2007, Journal of neurophysiology.

[10]  Richard Coppola,et al.  Prefrontal high gamma during a magnetoencephalographic working memory task , 2018, Human brain mapping.

[11]  Bora Baskak,et al.  Frontal activity during a verbal emotional working memory task in patients with Alzheimer's disease: A functional near-infrared spectroscopy study , 2017, Psychiatry Research: Neuroimaging.

[12]  Earl K. Miller,et al.  Different Levels of Category Abstraction by Different Dynamics in Different Prefrontal Areas , 2018, Neuron.

[13]  Lamine Mili,et al.  New Robust Estimators of Correlation and Weighted Basis Pursuit , 2015, IEEE Transactions on Signal Processing.

[14]  Wenwen Bai,et al.  Functional connectivity among spike trains in neural assemblies during rat working memory task , 2014, Behavioural Brain Research.

[15]  P. Roelfsema,et al.  The Distributed Nature of Working Memory , 2017, Trends in Cognitive Sciences.

[16]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[17]  Shuangyan Li,et al.  Functional Connectivity among Spikes in Low Dimensional Space during Working Memory Task in Rat , 2014, PloS one.

[18]  Earl K Miller,et al.  Gamma and beta bursts during working memory readout suggest roles in its volitional control , 2017, Nature Communications.

[19]  Rainer Goebel,et al.  The When and Where of Working Memory Dysfunction in Early-Onset Schizophrenia-A Functional Magnetic Resonance Imaging Study. , 2015, Cerebral cortex.

[20]  R. Romo,et al.  Neuronal correlates of parametric working memory in the prefrontal cortex , 1999, Nature.

[21]  Wenwen Bai,et al.  Incoordination between spikes and LFPs in Aβ1−42-mediated memory deficits in rats , 2014, Front. Behav. Neurosci..

[22]  Shuangyan Li,et al.  Increase of spike–LFP coordination in rat prefrontal cortex during working memory , 2014, Behavioural Brain Research.

[23]  David L. Stern,et al.  Correlated Evolution of Two Copulatory Organs via a Single cis-Regulatory Nucleotide Change , 2018, Current Biology.

[24]  I. Fried,et al.  Selective neuronal lapses precede human cognitive lapses following sleep deprivation , 2017, Nature Medicine.

[25]  Yong He,et al.  Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory , 2016, Cerebral cortex.

[26]  Laura Astolfi,et al.  Different Topological Properties of EEG-Derived Networks Describe Working Memory Phases as Revealed by Graph Theoretical Analysis , 2018, Front. Hum. Neurosci..

[27]  Men-Tzung Lo,et al.  Spurious cross-frequency amplitude-amplitude coupling in nonstationary, nonlinear signals. , 2016, Physica A.

[28]  Pascal Antoine,et al.  Describe yourself to improve your autobiographical memory: A study in Alzheimer's disease , 2017, Cortex.

[29]  Thomas J. Davidson,et al.  Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode , 2017, Neuron.

[30]  S. Funahashi.  Working Memory in the Prefrontal Cortex , 2017, Brain sciences.

[31]  Klaus Kessler,et al.  The Detection of Phase Amplitude Coupling during Sensory Processing , 2017, bioRxiv.

[32]  B. Sahakian,et al.  Angular default mode network connectivity across working memory load , 2017, Human brain mapping.

[33]  August B. Smit,et al.  Optogenetic dissection of medial prefrontal cortex circuitry , 2014, Front. Syst. Neurosci..

[34]  R. Zatorre,et al.  Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance , 2017, Neuron.

[35]  Mohammad Reza Daliri,et al.  Decoding of object categories from brain signals using cross frequency coupling methods , 2016, Biomed. Signal Process. Control..

[36]  Mark P. Brandon,et al.  Hippocampal Neural Circuits Respond to Optogenetic Pacing of Theta Frequencies by Generating Accelerated Oscillation Frequencies , 2018, Current Biology.

[37]  Gregor M. Hörzer,et al.  Theta coupling between V4 and prefrontal cortex predicts visual short-term memory performance , 2012, Nature Neuroscience.

[38]  S. Micheloyannis,et al.  Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury. , 2016, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[39]  J. Lisman,et al.  The Theta-Gamma Neural Code , 2013, Neuron.

[40]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[41]  Muriah D. Wheelock,et al.  Psychosocial Stress Reactivity Is Associated With Decreased Whole-Brain Network Efficiency and Increased Amygdala Centrality , 2018, Behavioral neuroscience.

[42]  Lei Wang,et al.  Development of Multiscale Model in Large-Scale HTS Coils With Improved Coupling , 2019, IEEE Transactions on Applied Superconductivity.

[43]  Mathew E. Diamond,et al.  Neuronal Correlates of Tactile Working Memory in Prefrontal and Vibrissal Somatosensory Cortex , 2019, Cell reports.

[44]  J. Gigg,et al.  Water and T-maze protocols are equally efficient methods to assess spatial memory in 3xTg Alzheimer’s disease mice , 2017, Behavioural Brain Research.