The functional properties of neural sensory cells or small neural ensembles are often characterized by analyzing response-conditioned stimulus ensembles. Many widely used analytical methods, like receptive fields (RF), Wiener kernels or spatio-temporal receptive fields (STRF), rely on simple statistics of those ensembles. They also tend to rely on simple noise models for the residuals of the conditional ensembles. However, in many cases the response-conditioned stimulus set has more complex structure. If not taken explicitly into account, it can bias the estimates of many simple statistics, and lead to erroneous conclusions about the functionality of a neural sensory system. In this article, we consider sensory noise in the visual system generated by small stimulus shifts in two dimensions (2 spatial or 1-space 1-time jitter). We model this noise as the action of a set of translations onto the stimulus that leave the response invariant. The analysis demonstrates that the spike-triggered average is a biased estimator of the model mean, and provides a de-biasing method. We apply this approach to observations from the stimulus/response characteristics of cells in the cat visual cortex and provide improved estimates of the structure of visual receptive fields. In several cases the new estimates differ substantially from the classic receptive fields, to a degree that may require re-evaluation of the functional description of the associated cells.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Aldworth, Z. N., Miller, J. P., Gedeon, T., Cummins, G. I., & Dimitrov, A. G. (2005). Dejittered spike-conditioned stimulus waveforms yield improved estimates of neuronal feature sensitivity. Journal of Neuroscience, 25(22), 5323–5332.
Bryant, H. L., & Segundo, J. P. (1976). Spike initiation by transmembrane current: A white-noise analysis. Journal of Physiology, 260, 279–314.
Chang, T.-R., Chung, P.-C., Chiu, T.-W., & Poon, P. W.-F. (2005). A new method for adjusting neural response jitter in the STRF obtained by spike-trigger averaging. BioSystems, 79, 213–222.
DeAngelis, G. C., Ohzawa, I., & Freeman, R. D. (1993). Spatiotemporal organization of simple-cell receptive fields in the cat’s striate cortex. I. General characteristics and postnatal development. Journal of Neuroscience, 69(14), 1091–1117.
Dimitrov, A. G., & Gedeon, T. (2006). Effects of stimulus transformations on the perceived function of sensory neurons. JCNS, 20, 265–283.
Eggermont, J. J., Sersten, A. M., & Johannesma, P. I. (1983). Prediction of the responses of auditory neurons in the midbrain of grass frog based on the spectro-temporal receptive field. Hearing Research, 10, 191–202.
Forte, J., Peirce, J., Kraft, J. M., Krauskopf, J., & Lennie, P. (2002). Residual eye-movements in macaque and their effects on visual responses of neurons. Visual Neuroscience, 19(1), 31–38.
Frey, B. J., & Jojic, N. (2003). Transformation-invariant clustering using the EM algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(1), 1–17.
Gawne, T. J., Kjaer, T. W., Hertz, J. A., & Richmond, B. J. (1996). Adjacent visual cortical complex cells share about 20% of their stimulus-related information. Cerebral Cortex, 6(3), 482–489.
Gollisch, T. (2006). Estimating receptive fields in the presence of spike-time jitter. Network: Computation in Neural Systems, 17, 103–129.
Gur, M., Kagan, I., & Snodderly, D. M. (2005). Orientation and direction selectivity of neurons in V1 of alert monkeys: Functional relationships and laminar distributions. Cerebral Cortex, 15(8), 1207–1221.
Jones, J. P., & Palmer, L. A. (1987). An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. Journal of Neurophysiology, 58, 1233–1258.
Kennedy, H., Martin, K. A., Orban, G. A., & Whitteridge, D. (1985). Receptive field properties of neurones in visual area 1 and visual area 2 in the baboon. Neuroscience, 14(2), 405–415.
Kjaer, T. W., Gawne, T. J., Hertz, J. A., & Richmond, B. J. (1997). Insensitivity of V1 complex cell responses to small shifts in the retinal image of complex patterns. Journal of Neuroscience, 78(6), 3187–3197.
Krzanowski, W. J., & Marriott, F. H. C. (1995). Multivariate analysis part 2: classification, covariance structures and repeated measurements. In Kendall’s Library of Statistics 2. London: Edward Arnold.
Levitt, J. B., Kiper, D. C., & Movshon, J. A. (1994). Receptive fields and functional architecture of macaque V2. Journal of Neuroscience, 71(6), 2517–2542.
Mainen, Z.G., & Sejnowski, T. J. (1995). Reliability of spike timing in neocortical neurons. Science, 268(5216), 1503–1506.
Maldonado, P. E., & Gray, C. M. (1996). Heterogeneity in local distributions of orientation-selective neurons in the cat primary visual cortex. Visual Neuroscience, 13(3), 509–516.
Malone, B. J., Kumar, V. R., & Ringach, D. L. (2007). Dynamics of receptive field size in primary visual cortex. Journal of Neuroscience, 97(1), 407–414.
Martinez-Conde, S., Macknik, S. L., & Hubel, D. H. (2002). The function of bursts of spikes during visual fixation in the awake primate lateral geniculate nucleus and primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 99(21), 13920–13925.
Mazer, J. A., Vinje, W. E., McDermott, J., Schiller, P. H., & Gallant, J. L. (2002). Spatial frequency and orientation tuning dynamics in area V1. Proceedings of the National Academy of Sciences of the United States of America, 99(3), 1645–1650.
Meister, M., Pine, J., & Baylor, D.A. (1994). Multi-neuronal signals from the retina: Acquisition and analysis. Journal of Neuroscience Methods, 51(1), 95–106.
Michelson, A. (1927). Studies in optics. Chicago: University of Chicago Press.
Olshausen, B. A., Anderson, C. H., & van Essen, D. C. (1993). A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. Journal of Neuroscience, 13(11), 4700–4719.
Olshausen, B. A., & Field, D. J. (2005). What is the other 85% of V1 doing? In J. L. van Hemmen, & T. J. Sejnoski (Eds.), 23 problems in systems neuroscience. Oxford: Oxford University Press.
Poon, P. W.-F., & Yu, P. P. (2000). Spectro-temporal receptive fields of midbrain auditory neurons in the rat obtained with frequency modulated stimulation. Neuroscience Letters, 289, 9–12.
Rao, R., & Ruderman, D. (1999). Learning Lie groups for invariant visual perception. In M. S. Kearns, S. A. Solla, & D. A. Cohn (Eds.), Advances in NIPS, (Vol. 11, pp. 810–816). Cambridge: MIT.
Reich, D. S., Mechler, F., Purpura, K. P., & Victor, J. D. (2000). Interspike intervals, receptive fields, and information encoding in primary visual cortex. Journal of Neuroscience, 20, 1964–1974.
Reid, R. C., & Alonso, J. M. (1995). Specifcity of monosynaptic connections from thalamus to visual cortex. Nature, 378(6554), 281–284.
Reid, R., Victor, J. D., & Shapley, R. M. (1997). The use of m-sequences in the analysis of visual neurons: Linear receptive field properties. Visual Neuroscience, 14(6), 1015–1027.
Rieke, F., Warland, D., de Ruyter van Steveninck, R. R., & Bialek, W. (1997) Spikes: Exploring the neural code. Cambridge: MIT.
Ringach, D. L. (2002) Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex. Journal of Neuroscience, 88(1), 455–463.
Ringach, D. L., Hawken, M., & Shapley, R. (1997). Dynamics of orientation tuning in macaque primary visual cortex. Nature, 387(6630), 281–284.
Ringach, D. L., Shapley, R. L., & Hawken, M. J. (2002). Orientation selectivity in macaque V1: diversity and laminar dependence. Journal of Neuroscience, 22(13), 5639–5651.
Rust, N. C., Schwartz, O., Movshon, J. A., & Simoncelli, E. (2004). Spike-triggered characterization of excitatory and suppressive stimulus dimensions in monkey V1. Neurocomputing, 58–60, 793–799.
Schwartz, O., Pillow, J. W., Rust, N. C., & Simoncelli, E. P. (2006). Spike-triggered neural characterization. Journal of Visualization, 6, 484–507.
Simoncelli, E. P., Paninski, L., Pillow, J., & Schwartz, O. (2004). Characterization of neural responses with stochastic stimuli. In M. Gazzaniga (Ed.), The new cognitive neurosciences (3rd edn.). Cambridge: MIT.
Theunissen, F. E., Woolley, S. M., Hsu, A., & Fremouw, T. (2004). Methods for the analysis of auditory processing in the brain. Annals of the New York Academy of Sciences, 1016, 187–207.
Whittle, P. (1994). The psychophysics of contrast brightness. In A. L. Gilchrist (Ed.), Lightness, brightness, and transparency (pp. 35–110). Hillsdale: Lawrence Erlbaum.
Yen, S., Baker, J., & Gray, C. M. (2007). Heterogeneity in the responses of adjacent neurons to natural stimuli in cat striate cortex. Journal of Neurophysiology, 97(2), 1326–1341.
Action Editor: Jonathan David Victor
About this article
Cite this article
Dimitrov, A.G., Sheiko, M.A., Baker, J. et al. Spatial and temporal jitter distort estimated functional properties of visual sensory neurons. J Comput Neurosci 27, 309–319 (2009). https://doi.org/10.1007/s10827-009-0144-8
- Visual cortex