Canonical correlation between LFP network and spike network during working memory task in rat

Working memory refers to a system to temporary holding and manipulation of information. Previous studies suggested that local field potentials (LFPs) and spikes as well as their coordination provide potential mechanism of working memory. Popular methods for LFP-spike coordination only focus on the two modality signals, isolating each channel from multi-channel data, ignoring the entirety of the networked brain. Therefore, we investigated the coordination between the LFP network and spike network to achieve a better understanding of working memory. Multi-channel LFPs and spikes were simultaneously recorded in rat prefrontal cortex via microelectrode array during a Y-maze working memory task. Functional connectivity in the LFP network and spike network was respectively estimated by the directed transfer function (DTF) and maximum likelihood estimation (MLE). Then the coordination between the two networks was quantified via canonical correlation analysis (CCA). The results show that the canonical correlation (CC) varied during the working memory task. The CC-curve peaked before the choice point, describing the coordination between LFP network and spike network enhanced greatly. The CC value in working memory showed a significant higher level than inter-trial interval. Our results indicate that the enhanced canonical correlation between the LFP network and spike network may provide a potential network integration mechanism for working memory.

[1]  GuoLin Wang,et al.  Inhibition of Propofol Anesthesia on Functional Connectivity between LFPs in PFC during Rat Working Memory Task , 2013, PloS one.

[2]  M. Wilson,et al.  Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity , 2005, Neural Computation.

[3]  Lei Ding,et al.  Motor imagery classification by means of source analysis for brain–computer interface applications , 2004, Journal of neural engineering.

[4]  H. Hotelling.  Relations Between Two Sets of Variates , 1936 .

[5]  Vikas Singh,et al.  Canonical Correlation Analysis on Riemannian Manifolds and Its Applications , 2014, ECCV.

[6]  Evgueniy V. Lubenov,et al.  Prefrontal Phase Locking to Hippocampal Theta Oscillations , 2005, Neuron.

[7]  Mark Laubach,et al.  Methods for studying functional interactions among neuronal populations. , 2009, Methods in molecular biology.

[8]  V. Lawhern,et al.  Spike Rate and Spike Timing Contributions to Coding Taste Quality Information in Rat Periphery , 2011, Front. Integr. Neurosci..

[9]  M. Jung,et al.  Dynamics of Population Code for Working Memory in the Prefrontal Cortex , 2003, Neuron.

[10]  Mehdi Khamassi,et al.  Coherent Theta Oscillations and Reorganization of Spike Timing in the Hippocampal- Prefrontal Network upon Learning , 2010, Neuron.

[11]  M. Laubach,et al.  The role of rat dorsomedial prefrontal cortex in spatial working memory , 2009, Neuroscience.

[12]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[13]  Vince D. Calhoun,et al.  Joint Blind Source Separation by Multiset Canonical Correlation Analysis , 2009, IEEE Transactions on Signal Processing.

[14]  Mingzhou Ding,et al.  Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance , 2001, Biological Cybernetics.

[15]  Arthur Gretton,et al.  Inferring spike trains from local field potentials. , 2008, Journal of neurophysiology.

[16]  S. Funahashi.  Prefrontal cortex and working memory processes , 2006, Neuroscience.

[17]  Emery N. Brown,et al.  A Granger Causality Measure for Point Process Models of Ensemble Neural Spiking Activity , 2011, PLoS Comput. Biol..

[18]  D. Contreras,et al.  Spatiotemporal Analysis of Local Field Potentials and Unit Discharges in Cat Cerebral Cortex during Natural Wake and Sleep States , 1999, The Journal of Neuroscience.

[19]  Uri T Eden,et al.  A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. , 2005, Journal of neurophysiology.

[20]  Anil K. Seth,et al.  A MATLAB toolbox for Granger causal connectivity analysis , 2010, Journal of Neuroscience Methods.

[21]  Bin He,et al.  Seizure source imaging by means of FINE spatio-temporal dipole localization and directed transfer function in partial epilepsy patients , 2012, Clinical Neurophysiology.

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

[23]  S. Bressler,et al.  Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data , 2006, Journal of Neuroscience Methods.

[24]  Vince D. Calhoun,et al.  Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia , 2008, IEEE Journal of Selected Topics in Signal Processing.

[25]  Evan M. Gordon,et al.  Working memory‐related changes in functional connectivity persist beyond task disengagement , 2014, Human brain mapping.

[26]  Wenwen Bai,et al.  Functional connectivity in a rat model of Alzheimer's disease during a working memory task. , 2014, Current Alzheimer research.

[27]  G. Paxinos,et al.  The Rat Brain in Stereotaxic Coordinates , 1983 .

[28]  J. Pernier,et al.  Oscillatory γ-Band (30–70 Hz) Activity Induced by a Visual Search Task in Humans , 1997, The Journal of Neuroscience.

[29]  G. V. Simpson,et al.  Phase Locking of Single Neuron Activity to Theta Oscillations during Working Memory in Monkey Extrastriate Visual Cortex , 2003, Neuron.

[30]  J. Fuster.  The Prefrontal Cortex—An Update Time Is of the Essence , 2001, Neuron.

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

[32]  G. Buzsáki,et al.  A 4 Hz Oscillation Adaptively Synchronizes Prefrontal, VTA, and Hippocampal Activities , 2011, Neuron.

[33]  Joshua A. Gordon,et al.  Theta Oscillations in the Medial Prefrontal Cortex Are Modulated by Spatial Working Memory and Synchronize with the Hippocampus through Its Ventral Subregion , 2013, The Journal of Neuroscience.

[34]  Katarzyna J. Blinowska,et al.  A new method of the description of the information flow in the brain structures , 1991, Biological Cybernetics.

[35]  Stavros Zanos,et al.  Relationships between spike-free local field potentials and spike timing in human temporal cortex. , 2012, Journal of neurophysiology.

[36]  Laura Astolfi,et al.  Connectome : A MATLAB toolbox for mapping and imaging of brain , 2010 .

[37]  Karl J. Friston,et al.  Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.

[38]  O. Bertrand,et al.  Oscillatory gamma-band (30-70 Hz) activity induced by a visual search task in humans. , 1997, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[39]  F. Battaglia,et al.  Oscillations in the prefrontal cortex: a gateway to memory and attention , 2011, Current Opinion in Neurobiology.

[40]  Bin He,et al.  Neocortical seizure foci localization by means of a directed transfer function method , 2010, Epilepsia.

[41]  J. Maunsell,et al.  Network Rhythms Influence the Relationship between Spike-Triggered Local Field Potential and Functional Connectivity , 2011, The Journal of Neuroscience.

[42]  V. Galhardo,et al.  Prefrontal cortex and mediodorsal thalamus reduced connectivity is associated with spatial working memory impairment in rats with inflammatory pain , 2013, PAIN®.

[43]  Alexander S. Ecker,et al.  Comparing the Feature Selectivity of the Gamma-Band of the Local Field Potential and the Underlying Spiking Activity in Primate Visual Cortex , 2008, Frontiers in systems neuroscience.

[44]  M. Wilson,et al.  Theta Rhythms Coordinate Hippocampal–Prefrontal Interactions in a Spatial Memory Task , 2005, PLoS biology.

[45]  M. D’Esposito.  Working memory. , 2008, Handbook of clinical neurology.

[46]  Jonathan D. Wallis,et al.  Executive control processes underlying multi-item working memory , 2014, Nature Neuroscience.

[47]  Vince D. Calhoun,et al.  A review of multivariate methods for multimodal fusion of brain imaging data , 2012, Journal of Neuroscience Methods.

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

[49]  João Jorge,et al.  EEG–fMRI integration for the study of human brain function , 2014, NeuroImage.