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Simultaneous training of negatively correlated neural networks in an ensemble

Yong Liu, Xin Yao
1999 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
CELS can create negatively correlated neural networks using a correlation penalty term in the error function to encourage such specialization.  ...  This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles.  ...  CELS extends Rosen's work to simultaneous training of negatively correlated neural networks. Such extension has produced significant improvement in neural network ensembles' performance.  ... 
doi:10.1109/3477.809027 pmid:18252352 fatcat:tpp5toq3yfcdbcn7osh64feh5q

Neural Correlates of Positive and Negative Valence System Dysfunction in Adolescents Revealed by Data-Driven Parcellation and Resting-State Network Modeling [article]

Vilma Gabbay, Qi Liu, Samuel J DeWitt, Lushna M Mehra, Carmen M Alonso, Benjamin A Ely
2020 bioRxiv   pre-print
Across subjects, depression correlated with subgenual cingulate CStr and ELoc, anhedonia correlated with ventromedial prefrontal CStr and lateral amygdala ELoc, and anxiety negatively correlated with parietal  ...  Conclusions: Using a data-driven analysis approach, high-quality parcellation, and clinically diverse adolescent cohort, we found that symptoms within positive and negative valence system constructs differentially  ...  This work was also supported in part through the computational resources and staff expertise provided by ISMMS Scientific Computing, with additional resource support provided by the ISMMS Brain Imaging  ... 
doi:10.1101/2020.03.20.001032 fatcat:kv673bplljbmzficu7asj5uz4e


Neil Y. Yen, Timothy K. Shih, Qun Jin
2013 ACM Transactions on Intelligent Systems and Technology  
In 2013, we successfully organized the 5-th International Conference on Awareness Science and Technology (iCAST2013), which was technically co-sponsored by IEEE Systems, Man, and Cybernetics Society, IEEE  ...  ensembles, • Modular neural networks,  ...  highly negatively correlated neural networks.  ... 
doi:10.1145/2438653.2438665 fatcat:4y6svfqcyff5ddqosxkmheimhm

On the Influence of Structural Connectivity on the Correlation Patterns and Network Synchronization

Parisa Sadat Nazemi, Yousef Jamali
2019 Frontiers in Computational Neuroscience  
In this study, we investigates the cross-correlation and synchronization sensitivity to coupling strength between neural regions for different topological networks.  ...  Several approaches have been applied to measure the role of the structural connectivity in the emergent correlation/synchronization patterns.  ...  In general, cross-correlation matrices do not exhibit any significant negative correlation between neural masses. Thus, maximum correlation achieves for lower couplings.  ... 
doi:10.3389/fncom.2018.00105 pmid:30670958 pmcid:PMC6332471 fatcat:dwik26dfkjcm3ow35vamksblsi

Interspike intervals as a discrete time series with history and randomness

Sharon E Norman, Robert J Butera
2014 BMC Neuroscience  
Neurons are fundamental components of neural systems.  ...  In contrast, sequential values of the change in ISI (delta ISI) show a single prominent negative autocorrelation coefficient; this indicates that delta ISI correlates strongest with one previous delta  ...  Neurons are fundamental components of neural systems.  ... 
doi:10.1186/1471-2202-15-s1-p195 pmcid:PMC4126387 fatcat:xmxxlk75pndifgfgjshkkmgqwa

Population Code, Noise Correlations, and Memory

Frédéric E. Theunissen, Julie E. Elie
2013 Neuron  
Changes in the correlated activity in the population code can increase neural discrimination by facilitating noise suppression.  ...  In this issue, Jeanne et al. (2013) observe learning-dependent changes in high-level avian auditory cortical neurons after a song discrimination task.  ...  noise correlations will decrease neural discriminability while negative noise correlations will increase neural discriminability.  ... 
doi:10.1016/j.neuron.2013.04.012 pmid:23622058 pmcid:PMC3677024 fatcat:ptxsu5qhxrcn5olrem5kugg6zi

Microstates-based resting frontal alpha asymmetry approach for understanding affect and approach/withdrawal behavior

Ardaman Kaur, Vijayakumar Chinnadurai, Rishu Chaujar
2020 Scientific Reports  
Finally, alpha-BOLD desynchronization was observed in neural-underpinning whose HLI correlated significantly with negative affect and BIS.  ...  However, the microstate resting frontal-asymmetry correlated significantly with negative affect and its neural underpinning's HLI significantly correlated with Positive/Negative affect and BIS/BAS measures  ...  Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.  ... 
doi:10.1038/s41598-020-61119-7 pmid:32144318 fatcat:bmjes3emsfekfa2e44qsec545i

Improvement of signal-to-noise ratio in parallel neuron arrays with spatially nearest neighbor correlated noise

Tianquan Feng, Qingrong Chen, Ming Yi, Zhongdang Xiao, Jordi Garcia-Ojalvo
2018 PLoS ONE  
Given the existence of spatially nearest neighbor correlated noise in the neural ensemble, the SNR gain of the collective ensemble response can exceed unity, especially for a negative correlation.  ...  In addition, we show that the SNR can be improved by varying the number of neurons, frequency, and amplitude of the weak periodic signal.  ...  In contrast, we aim to unveil the correlation of noise in a neural ensemble.  ... 
doi:10.1371/journal.pone.0200890 pmid:30021023 pmcid:PMC6051645 fatcat:kehw76hnujdu7o6nhfjcedvjcu

Evolving, training and designing neural network ensembles

Xin Yao
2010 2010 IEEE 14th International Conference on Intelligent Engineering Systems  
Yao, "Negatively correlated neural networks can produce best ensembles," Australian Journal of Intelligent Information Processing Systems, 4(3/4):176-185, 1997.  ...  Yao, "Ensemble learning via negative correlation," Neural Networks, 12(10):1399-1404, December 1999. b E. K. Tang, P. N. Suganthan and X.  ...  Evolve ensembles through hybridisation with negative correlation, so that a population of species are formed. 2. The number of species is determined automatically. 3.  ... 
doi:10.1109/ines.2010.5483861 fatcat:acqqfhojunflbkle5geokqo7ka

Ensemble learning via negative correlation

Y. Liu, X. Yao
1999 Neural Networks  
Unlike previous learning approaches for neural network ensembles, negative correlation learning attempts to train individual networks in an ensemble and combines them in the same learning process.  ...  This paper presents a learning approach, i.e. negative correlation learning, for neural network ensembles.  ...  Table 5 compares the results of negative correlation learning with those produced by other neural and nonneural algorithms, where EPNet is an evolutionary system for designing neural networks (Yao &  ... 
doi:10.1016/s0893-6080(99)00073-8 pmid:12662623 fatcat:jvt3ypar7vh7pef7nzo7eo3m7m

GABA, Glutamate and Neural Activity: A Systematic Review With Meta-Analysis of Multimodal 1H-MRS-fMRI Studies

Amanda Kiemes, Cathy Davies, Matthew J. Kempton, Paulina B. Lukow, Carly Bennallick, James M. Stone, Gemma Modinos
2021 Frontiers in Psychiatry  
Advances in 1H-MRS methodology as well as in the integration of 1H-MRS readouts with other imaging modalities for indexing neural activity hold great potential to reveal key aspects of the pathophysiology  ...  These meta-analyses found evidence of significant negative associations between local GABA levels and (a) fMRI activation to visual tasks in the occipital lobe, and (b) activation to emotion processing  ...  Neural activity in a variety of other regions were also negatively correlated with ACC glutamate levels in this study (see Table 4 ).  ... 
doi:10.3389/fpsyt.2021.644315 pmid:33762983 pmcid:PMC7982484 fatcat:obhexi2rkrfrdh2of2hbtdrtsa

Dynamical correlation patterns and corresponding community structure in neural spontaneous activity at criticality

T. Termsaithong, K. Aihara
2013 Cognitive Neurodynamics  
We examine community structure of the functional connectivity in simulated brain spontaneous activity, which is based on dynamical correlations between neural activity patterns at different positions.  ...  In the critical region, we found some distinctive properties, namely high correlation and correlation switching, high modularity and a low number of modules, high stability of the dynamical functional  ...  In our model, at criticality, a negative activity area in the field tends to correlate with the other negative activity areas, and a positive activity area tends to correlate with the other positive activity  ... 
doi:10.1007/s11571-013-9251-3 pmid:24427213 pmcid:PMC3773324 fatcat:u67wr7xo3vh6pmtdvawufcsgiq

Activity-type dependent conductance relationships in a model neuron database

Amber E Hudson, Astrid A Prinz
2009 BMC Neuroscience  
No conductance pairs showed a positive correlation in one activity type and a negative correlation in another.  ...  Here we use an existing database of generic STG conductance-based model neurons [1] to demonstrate how conductance correlations shape neural activity.  ...  No conductance pairs showed a positive correlation in one activity type and a negative correlation in another.  ... 
doi:10.1186/1471-2202-10-s1-p41 fatcat:fwdwe3jz3vds5igpoxyb7o55qm

Single neural code for blur in subjects with different interocular optical blur orientation

Aiswaryah Radhakrishnan, Lucie Sawides, Carlos Dorronsoro, Eli Peli, Susana Marcos
2015 Journal of Vision  
The neural PSF was found to be highly correlated in both eyes, even for eyes with different ocular PSF orientations (r Pos ¼ 0.95; r Neg ¼ 0.99; p , 0.001).  ...  The ability of the visual system to compensate for differences in blur orientation between eyes is not well understood.  ...  There was strong and significant interocular correlation in the orientations of the positive neural PSF (r ¼ 0.95, p , 0.001) and negative neural PSF (r ¼ 0.99, p , 0.001).  ... 
doi:10.1167/15.8.15 pmid:26114678 pmcid:PMC4484355 fatcat:putx54airzfi7njlockh6qk5s4

Altered dynamics between neural systems sub-serving decisions for unhealthy food

Qinghua He, Lin Xiao, Gui Xue, Savio Wong, Susan L. Ames, Bin Xie, Antoine Bechara
2014 Frontiers in Neuroscience  
Neural systems implicated in decision-making and inhibitory control were engaged by having participants perform the IGT during fMRI scanning.  ...  These results provide preliminary support for our hypotheses that unhealthy food choices in real life are reflected by neuronal changes in key neural systems involved in habits, decision-making and self-control  ...  In contrast, high consumption of snacks negatively correlated with activity in the left frontal pole (a part of the reflective system), but positively correlated with activity in the right ventral striatum  ... 
doi:10.3389/fnins.2014.00350 pmid:25414630 pmcid:PMC4220120 fatcat:oaqbwxh6brhzfp6hti3rssrm5m
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