Preprints

  • Tsujimura H, Zhang J. Concurrent motor sequence learning and choice preference formation during repetitive action-and stimulus-selections. psyArxXiv. [Main text]
  • Zajkowski W, Zhang J. Within and Cross-Domain Effects of Choice-Induced Bias. bioRxiv. [Main text]
  • Tomassini A, Price D, Zhang J, Rowe JB. On the evolution of neural decisions from uncertain visual input to uncertain actions. BioRxiv 803049. [Main text] [Supplementary material]

Journal articles

  • Bundil I, Baltruschat S, Zhang J. Characterising and differentiating cognitive and motor speed in older adults: structural equation modelling on a UK longitudinal birth cohort. BMJ Open, 14:e083968. [Article]
  • Ozkan A, Zhang J (2024). Information sources and congruency modulate preference-based decision-making processes. Journal of Cognitive Psychology. [Article]
  • Tomassini, A, Cope, TE, Zhang, J, Rowe, JB (2024). Parkinson’s disease impairs cortical sensori-motor decision-making cascades. Brain Communications, 6(2). [Article]
  • Read, ML, Berry SC, Graham KS, Voets NL, Zhang J, Aggleton JP, Lawrence AD, Hodgetts CJ (2024). Scene-selectivity in CA1/subicular complex: Multivoxel pattern analysis at 7T. Neuropsychologia, 108783. [Article]
  • Lopes MA, Hamandi K, Zhang J, Creaser J (2023). The interaction between neural populations: Additive versus diffusive coupling. Scientific Reports, 13(1), 4115. [Article]
  • Karahan E, Tait L, Si R, Özkan A, Szul MJ, Graham KS, Lawrence AD, Zhang J (2022). The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure. Communications Biology 5:1007. [Article] [Code & Data]
  • Tait L, Zhang J (2022) +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG. Neuroimage, 119346. [Article] [Toolbox]
  • Krzemiński D, Zhang J. (2022) Imperfect integration: sensory congruency between multiple sources modulates selective decision-making processes. Attention, Perception, & Psychophysics, 84:1566–1582. [Article] [Data] [Code] [Materials]
  • Lopes MA, Bhatia S, Brimble G, Zhang J, Hamandi K (2022) A computational biomarker of photosensitive epilepsy from interictal EEG. eNeuro, 9(3). [Article]
  • Tait L, Zhang J. (2022) MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses. Neuroimage, 119006. [Article] [Code]
  • Wolpe N, Hezemans FH, Rae CL, Zhang J, Rowe JB (2022). The pre-supplementary motor area achieves inhibitory control by modulating response thresholds. Cortex, 152:98-108. [Article]
  • Si R, Rowe JB, Zhang J (2021). Functional localization and categorization of intentional decisions in humans: a meta-analysis of brain imaging studies. Neuroimage, 118468. [Article] [Data]
  • Tait L, Lopes MA, Stothart G, Baker J, Kazanina N, Zhang J, Goodfellow M (2021). A Large-Scale Brain Network Mechanism for Increased Seizure Propensity in Alzheimer’s Disease. Plos Computational Biology. [Article]
  • Tait L, Ozkan A, Szul MJ, Zhang J (2021). A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: performance, precision, and parcellation. Human Brain Mapping. [Article] [Supplementary material] [Code]
  • Lopes MA, Krzemiński D, Hamandi K, Singh KD, Masuda N, Terry JR, Zhang J (2021). A computational biomarker of juvenile myoclonic epilepsy from resting-state MEG. Clinical Neurophysiology, 132, 922-927. [Article]
  • Lopes MA, Zhang J, Krzemiński D, Hamandi K, Chen Q, Livi L, Masuda N (2021). Recurrence Quantification Analysis of Dynamic Brain Networks. European Journal of Neuroscience, 53:1040-1059. [Article]
  • Zajkowski W, Krzemiński D, Barone J, Evans LH, Zhang J (2021). Breaking Deadlocks: Reward Probability and Spontaneous Preference Shape Voluntary Decisions and Electrophysiological Signals in Humans. Computational Brain & Behavior, 4:191-212 [Article] [Code] [Data]
  • Krzemiński D, Masuda N, Hamandi K, Singh KD, Routley B, Zhang J (2020). Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy. Network Neuroscience, 4:374-396. [Article] [Code]
  • Hodgetts CJ, Stefani M, Williams AN, Kolarik BS, Yonelinas AP, Ekstrom AD, Lawrence AD, Zhang J, Graham KS (2020). The role of the fornix in human navigational learning. Cortex, 124:97-110. [Article]
  • Szul MJ, Bompas A, Sumner P, Zhang J (2020). The validity and consistency of continuous joystick response in perceptual decision-making. Behavior Research Methods, 52:681–693. [Article] [Code & Data]
  • Karahan E, Costigan AG, Graham KS, Lawrence AD, Zhang J (2019). Cognitive and white-matter compartment models reveal selective relations between corticospinal tract microstructure and simple reaction time. Journal of Neuroscience, 39:5910-5921. [Article] [Code]
  • Wolpe N, Zhang J, Nombela C, Ingram JN, Wolpert DM, Rowe JB (2018) Sensory attenuation in Parkinson’s disease is related to disease severity and dopamine dose. Scientific reports 8:15643. [Article]
  • Jia K, Xue X, Lee J, Fang F, Zhang J, Li S. (2018). Visual perceptual learning modulates decision network in the human brain: the evidence from psychophysics, modeling, and functional magnetic resonance imaging. Journal of Vision, 18(12):9, 1–19. [Article]
  • Dima D, Perry G, Messaritaki E, Zhang J, Singh K (2018). Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces. Human Brain Mapping 39:3993–4006. [Article]
  • Phillips HN, Cope TE, Hughes LE, Zhang J, Rowe JB (2018). Monitoring the past and choosing the future: the prefrontal cortical influences on voluntary action. Scientific reports, 8(1):7247.
  • Zhang J, Nombela C, Wolpe N, Barker RA, Rowe JB (2016). Time on timing: Dissociating premature responding from interval sensitivity in Parkinson’s disease. Movement Disorders 31:1163–72.
  • Zhang J, Rittman T, Nombela C, Fois A, Coyle-Gilchrist I, Barker RA, Rowe JB (2016) Different decision deficits impair response inhibition in Progressive Supranuclear Palsy and Parkinson’s disease. Brain 139:161-73. (F1000 recommended)
  • Song Y, Zhang J (2016). Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine. Journal of Neuroscience Methods 57, 45-54.
  • Zhang J, Rowe JB (2015). The neural signature of information regularity in temporally extended event sequences. Neuroimage 107:266-76.
  • Mason S, Zhang J, Begeti F, Guzman NV, Lezar A, Rowe JB, Barker RA, Hampshire A (2015). The role of the amygdala during emotional processing in Huntington’s disease: From pre-manifest to late stage disease. Neuropsychologia 70:80-89.
  • Zhang J, Rowe JB (2014). Dissociable mechanisms of speed-accuracy tradeoff during visual perceptual learning are revealed by a hierarchical drift diffusion model. Frontiers in Neuroscience 8:69.
  • Zhang J, Kriegeskorte N, Carlin JD, Rowe JB (2013). Choosing the rules: distinct and overlapping fronto-parietal representations of chosen and specified task rules for perceptual decisions. Journal of Neuroscience 33:11852-62.
  • Song Y, Zhang J (2013). Automatic recognition of epileptic EEG patterns via extreme learning machine and multiresolution feature extraction. Expert Systems with Applications 40:5477-5489.
  • Zhang J, Hughes LH, Rowe JB (2012). Selection and inhibition mechanisms for human voluntary action decisions. Neuroimage 63:392-402. (F1000 recommended)
  • Zhang J (2012). The effects of evidence bounds on decision-making: theoretical and empirical developments. Frontiers in Psychology 3:263.
  • Song Y, Crowcroft J, Zhang J (2012). Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine. Journal of Neuroscience Methods 210:132-146.
  • Zhang J, Messon A, Welchman A, Kourtzi Z (2010). Learning alters the tuning of functional magnetic resonance imaging patterns for visual forms. Journal of Neuroscience 30:14127-33.
  • Zhang J, Kourtzi Z (2010). Learning-dependent plasticity with and without training in the human brain. Proceedings of the National Academy of Sciences USA 107:13503-8.
  • Zhang J, Bogacz R (2010). Optimal decision making on the basis of evidence represented in spike trains. Neural Computation 22:1113-1148.
  • Zhang J, Bogacz R (2010). Bounded Ornstein-Uhlenbeck models for two-choice time controlled tasks. Journal of Mathematical Psychology 54:322-33.
  • Schwarzkopf DS, Zhang J, Kourtzi Z (2009). Flexible learning of natural statistics in the human brain. Journal of Neurophysiology 102:1854-67.
  • Zhang J, Bogacz R, Holmes P (2009). A comparison of bounded diffusion models for choice in time controlled tasks. Journal of Mathematical Psychology 53:231-41.
  • Bogacz R, Usher M, Zhang J, McClelland JL (2006). Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice. Philosophical Transactions of the Royal Society Series B 362:1655-70.

Book Chapter

  • Bogacz R, Usher M, Zhang J, McClelland JL (2011). Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice. Seth A, Bryson J, and Prescott T Eds. Modeling Natural Action Selection. Cambridge Press.

Conference Proceedings

  • Morgan ML, Rahat A, Jenkins G, Zhang J. (2024). Explainable Machine Learning: Predicting Clinical Outcomes in Welsh Emergency Departments. In International Conference on AI in Healthcare, 290-301. Lecture Notes in Computer Science, Springer.
  • Aslam S, Chen Q, Zhang J. (2024). DELRecon: Depth Electrode Reconstruction Toolbox for Stereo-EEG. In International Conference on AI in Healthcare, 135-148. Lecture Notes in Computer Science, Springer.
  • Sicurella E, Zhang J (2022). Deep learning for parameter recovery from a neural mass model of perceptual decision-making. Conference on Cognitive Computational Neuroscience, San Francisco, USA.
  • Song Y, Crowcroft J, Zhang J (2012). Epileptic EEG Signal Analysis and Identification Based On Nonlinear Features. IEEE Bioinformatics and Biomedicine, Philadelphia, USA.
  • Zhang J, Bogacz R (2018). Superior colliculus and basal ganglia control the saccadic response in motion discrimination tasks. Advances in Cognitive Neurodynamics ICCN 2007, 475-479.