Publications

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Journal publications


S P Wilson, H P Saal , R Schmidt, and J V Stone (in preparation, 2022). Evolution should favour phenotypic plasticity in uncertain environments.

Stone, J V (2021). Who's the Daddy? Infidelity Favours Father-Son Facial Dissimilarity. arXiv preprint arXiv:2109.10848.

Stone, J V (2021). Using Information Theory to Measure Psychophysical Performance. arXiv preprint arXiv:2108.04936.

Stone, J V (2015). Independent component analysis, The encyclopedia of statistics in behavioral science, Everitt, B S and Howell, D C (eds.), Wiley StatsRef: Statistics Reference Online. Download (PDF, 282KB)

Stone, J V (2014). Using reaction times and binary responses to estimate psychophysical performance: an information-theoretic analysis. Frontiers in Decision Neuroscience, 8(35), February. Download

Stone, J V (2011). Footprints sticking out of the sand (part II): children's Bayesian priors for lighting direction and convexity. Perception, 40(2), 175-190. Download (PDF, 911KB)

Stone, J V and Pascalis, O (2010). Footprints sticking out of the sand (part I): children's perception of naturalistic and embossed symbol stimuli. Perception, 39, 1254-1260.

Stone, J V, Kerrigan, I R and Porrill, J (2009). Where is the light? Bayesian perceptual priors for lighting direction. Proceedings Royal Society (B), 276(1663), 1797-804.

Jupp, P E and Stone, J V (2008). Free-lunch learning and directional distributions in artificial neural networks. Acta et Commentationes Universitatis Tartuensis de Mathematica, 12, 101-108. Download (PDF, 108KB)

Stone, J V and Jupp, P E (2008). Falling towards forgetfulness: synaptic decay prevents spontaneous recovery of memory. Computational Biology, 4(8), August.

Stone, J V (2007). Distributed representations accelerate evolution of adaptive behaviours. PLOS Computational Biology, August.

Stone, J V and Jupp, P E (2007). Free-lunch learning: modelling spontaneous recovery of memory. Neural Computation, 19, 194-217.

Stone, J V (2005). How the brain lit the fuse to the Cambrian explosion. British Neuroscience Association, 53, 25. Highly commended essay in the National Brain Science Writing Prize (December 2005). Download (PDF, 299KB)

Porrill, J, Dean, P and Stone, J V (2004). Recurrent cerebellar architecture solves the motor-error problem. Proceedings Royal Society (B), 271(1541), 789-796.

Stone, J V (2002). Deconvolution using temporal predictability, Neurocomputing, 49, 1-456. Download (PDF, 103KB)

Dean, P, Porrill, J and Stone, J V (2002). Decorrelation control by the cerebellum achieves oculomotor plant compensation in simulated vestibulo-ocular reflex. Proceedings Royal Society (B), 269(1503), 1895-1904.

Stone, J V and Kotter, R (2002). Making connections about brain connectivity, report on the meeting "Functional brain connectivity", April 2002, Dusseldorf, Germany. Trends in Cognitive Science, 59-64, February. Download (PDF, 22KB)

Stone, J V, Porrill, J, Porter, N R and Wilkinson, I W (2002). Spatiotemporal independent component analysis of event-related fMRI data using skewed probability density functions. NeuroImage, 15(2), 407-421. Download (PDF, 691KB)

Stone, J V (2002). Independent component analysis: an introduction. Trends in Cognitive Sciences, 6(2), 59-64, February. Download (PDF, 714KB)

Stone, J V, Hunkin, N M and Hornby, A (2001). Predicting spontaneous recovery of memory. Nature, 414, 167-168, November. Download (PDF, 410KB)

Stone, J V (2001). Face recognition: when a nod is better than a wink. Current Biology, 11, 663-664, August. Invited commentary. Download (PDF, 36KB)

Stone, J V (2001). Blind source separation using temporal predictability. Neural Computation, 13(7), 1559-1574, July.

Stone, J V, Hunkin, N M, Porrill, J, Wood, R, Keeler, V, Beanland, M, Port, M and Porter, N R (2001). When is now? Perception of simultaneity. Proceedings Royal Society (B), 268, 31-38.

Stone, J V, Buckley, D and Moger, F (2000). Determinants object recognition. Vision Research, 40(20), 2723-2736.

Hunkin, N M, Stone, J V, Isaac, C L, Holdstock, J S, Butterfield, R, Wallis, L I and Mayes, A R (2000). Factor analysis of three standardised tests of memory in a clinical population. British Journal of Clinical Psychology, 39(2), 169-180. View abstract

Stone, J V and Harper, N (1999). Temporal constraints on visual learning: a computational model. Perception, 28, 1089-1104, November.

Stone, J V (1999). Object recognition: view-specificity and motion-specificity. Vision Research, 39(24), 4032-4044, October.

Stone, J V (1999). Learning perceptually salient visual parameters using spatiotemporal smoothness constraints. In Hinton, G and Sejnowski, T (eds.), Unsupervised learning: foundations of neural computation, 71-100. MIT Press, London, England.

Stone, J V (1998). Object recognition using spatiotemporal signatures (published as a rapid communication). Vision Research, 38(7), 947-951, March.

Stone, J V (1997) Information theory: the holy grail of cortical computation? Brain and Behavioural Science commentary on the article "In search of common foundations for cortical computation" by Phillips, W and Singer, 20(4), 698, December. View article

Eglen, S, Bray, A and Stone, J V (1997). Unsupervised discovery of invariances. Network: Computation in Neural Systems, 441-452, November.

Stone, J V (1996). Learning perceptually salient visual parameters using spatiotemporal smoothness constraints. Neural Computation, 8(7), 1463-1492.

Stone, J V (1996). Learning stereo disparity using temporal smoothness constraints: A computational model,. Spatial Vision: Special issue on learning and adaptation in man and machine, 10(1), 15-29. View abstract

Stone, J V (1996). A canonical microfunction for learning perceptual invariances. Perception, 25, 207-220.

Harvey, I and Stone, J V (1996). Unicycling helps your French: Spontaneous recovery of associations by learning unrelated tasks. Neural Computation, 8, 697-704.

Stone, J V and Isard, S (1995). Adaptive scale filtering: A general method for obtaining shape from texture. IEEE Trans. Pattern Analysis and Machine Intelligence, 17(7), 713-718.

Stone, J V and Bray, A (1995). A learning rule for extracting spatio-temporal invariances. Network, 6(3), 1-8.

Stone, J V (1995). The sinking is green stone: Using spatio-temporal cues in vision. Image Processing, 7(4), 20-25.

Stone, J V and Cliff, D (1994). How to play the creative game, review of the book The garden in the machine by Emmeche, C. New Scientist, 17 September.

Stone, J V (1992). Shape from local and global analysis of texture. Transactions Royal Society London (B), 339:1287, 53-65.

Stone, J V (1990). Shape from texture: A computational analysis. DPhil, Experimental Psychology, University of Sussex, 1990.

Stone, J V (1988). Connectionist models: Theoretical status, form and function. In Artificial Intelligence and Simulation of Behaviour, 15-18, June.

Book chapters

Dean, P, Porrill, J and Stone, J V (2003). Visual awareness and the cerebellum: possible role of decorrelation control. In Blakemore, C, Heywood, C A and Milner, A D (eds.), The roots of visual awareness: A Festschrift in honour of Alan Cowey (Progress in brain research). Elsevier.

Porrill, J, Stone, J V, Berwick, J, Mayhew, J and Coffey, P (2000). Analysis of optical imaging data using weak models and ICA. In Girolami, M (ed.), Advances in independent component analysis. Springer-Verlag.

Stone, J V (1999). Learning perceptually salient visual parameters using spatiotemporal smoothness constraints. In Hinton, G and Sejnowski, T (eds.), Unsupervised learning: Foundations of neural computation, 71-100. MIT Press, London, England. View abstract

Conference publications

Stone, J V (2012). Fat-face-thin illusion predicted by own-face shape. York vision conference. Download poster (PDF, 452KB)

Stone, J V and Pascalis, O (2009). Development of priors for lighting direction in children. Society for research in child development conference, Denver. Download poster (PDF, 1.4MB)

Stone, J V, Kerrigan, I R and Porrill, J (2008). Where is the light? Bayesian perceptual priors for lighting direction. York vision conference. Download poster (PDF, 1.3MB)

Stone, J V (2006). Free-lunch learning: Modelling spontaneous recovery of memory. CNS, Edinburgh, 15-20 July.

Stone, J V (2004). Free-lunch learning, spontaneous recovery of memory, and accelerated evolution. Sheffield machine learning workshop, Sheffield, September 7-10.

Stone, J V, Porter, N R and Porrill, J (2001). The colour-contingent motion after-effect: An Efmri study. Human brain mapping, Brighton, UK, June 10-14.

Porrill, J, Stone, J V, Porter, N R and Hunkin, N M (2001) Recovering spatially localised sources from fMRI data. Human brain mapping, Brighton, UK, June 10-14.

Dean, P, Porrill, J and Stone, J V (2001). Decorrelation control by cerebellum compensates automatically for oculomotor plant in simulated VOR. Society for Neuroscience.

Stone, J V, Hunkin, N M, Porrill, J, Wood, R, Keeler, V, Beanland, M, Port, M and Porter, N R (2000). When is now? Perception of simultaneity. Second annual multisensory research conference, Tarrytown New York, October 6-7.

Stone, J V, Porrill, J, Buchel, C and Friston, K (1999). Spatial, temporal, and spatiotemporal independent component analysis of fMRI data. 18th Leeds statistical research workshop on spatial-temporal modelling and its applications, University of Leeds, July. View abstract

Porrill, J, Stone, J V, Mayhew, J E W, Berwick, J and Coffey, P (1999). Spatio-temporal data analysis using weak linear models. 18th Leeds statistical research workshop on spatial-temporal modelling and its applications, University of Leeds, July. View abstract

Stone, J V and Harper, N. Using temporal constraints to learn visual invariances in an artificial neural network. Presented at ECVP99.

Stone, J V, Buckely, D and Moger, F. Determinants of shape perception and object recognition. Presented at ECVP99.

Stone, J V, Porrill, J, Buchel, C and Friston, K (1999). Spatial and temporal independent component analysis of fMRI data. Human brain mapping, Dusseldorf.

Porrill, J, Stone, J V, Mayhew, J E W, Berwick, J and Coffey, P (1999). Analysis of optical imaging data using weak models. Human brain mapping, Dusseldorf.

Stone, J V (1998). Recognition of rigid Johansson objects mediated by spatiotemporal signatures, ECVP98 abstract. Perception, 27, 119.

Buckley, D and Stone, J V, Brennand, D A A and Davis, H (1998). Predicting individual differences in performance of an object recognition task, ECVP98 abstract. Perception, 27, 1124.

Stone, J V (1996). Characteristic spatiotemporal views and object recognition, invited paper. Rank prize funds symposium on visual motion analysis, 4-7 November.

Lister, R and Stone, J (1995). An empirical study of the time complexity of various error functions with conjugate gradient back propagation. IEEE international conference on artificial neural networks (ICNN95), Perth, Australia.

Stone, J V and Bray, A (1995). Extracting temporal invariances. International workshop on artificial neural networks, Malaga, June.

Stone, J V (1995). Hierarchical learning of spatio-temporal invariances. International conference on artificial neural networks, Cambridge. 110-115.

Stone, J V and Thornton, C (1995). Can artificial neural networks learn useful regularities? International conference on artificial neural networks, Cambridge, June. 201-205.

Lister, R and Stone, J V (1995). Error functions, error signals, and conjugate gradient back propagation. International conference on artificial neural networks, Cambridge, June. 76-81.

Stone, J V (1995). Learning visual invariances through spatio-temporal constraints. Applied Vision Association annual meeting, invariance and constancy in vision workshop, Reading, April.

Lister, R and Stone, J V (1995) Error functions and conjugate gradient back propagation. Australian conference on neural networks, Sydney, February. 130-133.

Stone, J V (1994). Learning spatio-temporal invariances. Proceedings of British Machine Vision conference, York. 681-690.

Stone, J V (1995). Learning spatio-temporal invariances. In Smith, L S and Hancock, P J B (eds.), Neural Computation and Psychology proceedings of the third Neural Computation and Psychology workshop (NCPW3), Stirling, Scotland, 31 August – 2 September. Springer Verlag, Workshops in Computing Series, April.

Stone, J V (1994). Evolutionary robots: Our hands in their brains? Proceedings of the Artificial Life conference, Boston, July. 400-405.

Stone, J V and Lister, R (1994). On the time complexity of conjugate gradient back-propagation. Australian conference on neural networks, Brisbane, February.

Stone, J V and Lister, R (1994). On the relative time complexities of standard and conjugate gradient back-propagation. Proceedings of the IEEE international conference on neural networks, Orlando, June. 84-87.

Stone, J V (1993). Computer vision: What is the object? Prospects for AI, Proceedings of artificial intelligence and simulation of behaviour, Birmingham, April. 199-208. IOS Press, Amsterdam.

Stone, J V (1992). The adaptive bisector method: Separating slant and tilt in obtaining shape from texture. British Machine Vision conference, Leeds. 177-186.

Stone, J V (1992). The optimal elastic net: Finding solutions to the travelling salesman problem. International conference on artificial neural networks, Brighton, September. 170-174.

Stone, J V (1990). Shape from texture: Textural invariance and the problem of scale in perspective images of textured surfaces. CSRP 167, July.

Technical reports

Stone, J V, Porrill, J, Porter, N R and Hunkin, N M (2000). Spatiotemporal ICA of fMRI data. Computational Neuroscience Report 202.

Stone, J V and Porrill, J (1999). Regularisation using spatiotemporal independence and predictability. Computational Neuroscience Report 201.

Stone, J V and Porrill, J (1998). Independent component analysis and projection pursuit: A tutorial introduction.

Note: MATLAB code which implements the methods described in the next two technical reports can be obtained on request.

Stone, J V and Porrill, J (1998). Undercomplete independent component analysis for signal separation and dimension reduction.

Stone, J V and Porrill, J (1998). Independent components analysis for step-wise separation of signals.