A minimal mechanistic model for temporal signal processing in the lateral geniculate nucleus
Tóm tắt
The receptive fields of cells in the lateral geniculate nucleus (LGN) are shaped by their diverse set of impinging inputs: feedforward synaptic inputs stemming from retina, and feedback inputs stemming from the visual cortex and the thalamic reticular nucleus. To probe the possible roles of these feedforward and feedback inputs in shaping the temporal receptive-field structure of LGN relay cells, we here present and investigate a minimal mechanistic firing-rate model tailored to elucidate their disparate features. The model for LGN relay ON cells includes feedforward excitation and inhibition (via interneurons) from retinal ON cells and excitatory and inhibitory (via thalamic reticular nucleus cells and interneurons) feedback from cortical ON and OFF cells. From a general firing-rate model formulated in terms of Volterra integral equations, we derive a single delay differential equation with absolute delay governing the dynamics of the system. A freely available and easy-to-use GUI-based MATLAB version of this minimal mechanistic LGN circuit model is provided. We particularly investigate the LGN relay-cell impulse response and find through thorough explorations of the model’s parameter space that both purely feedforward models and feedback models with feedforward excitation only, can account quantitatively for previously reported experimental results. We find, however, that the purely feedforward model predicts two impulse response measures, the time to first peak and the biphasic index (measuring the relative weight of the rebound phase) to be anticorrelated. In contrast, the models with feedback predict different correlations between these two measures. This suggests an experimental test assessing the relative importance of feedforward and feedback connections in shaping the impulse response of LGN relay cells.
Tài liệu tham khảo
Andolina IM, Jones HE, Wang W, Sillito AM (2007) Corticothalamic feedback enhances stimulus response precision in the visual system. Proc Natl Acad Sci 104:1685–1690
Bhattacharya BM, Coyle D, Maguire LP (2011) A thalamo-cortico-thalamic neural mass model to study alpha rhythms in Alzheimer’s disease. Neural Netw 24:631–645
Blomquist P, Devor A, Indahl UG, Einevoll GT, Dale AM (2009) Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminar-electrode recordings in the rat barrel system. PLoS Comput Biol 5:e1000328
Briggs F, Usrey WM (2005) Temporal properties of feedforward and feedback pathways between the thalamus and visual cortex in ferret. Thalamus Relat Syst 3:133–139
Briggs F, Usrey WM (2007) A fast, reciprocal pathway between the lateral geniculate nucleus and visual cortex in the macaque monkey. J Neurosci 27:5431–5436
Briggs F, Usrey WM (2008) Emerging views of corticothalamic function. Curr Opin Neurobiol 18:403–407
Briggs F, Usrey WM (2011) Corticogeniculate feedback and visual processing in the primate. J Physiol 589(1):33–40
Cai D, Deangelis G, Freeman R (1997) Spatiotemporal receptive field organization in the lateral geniculate nucleus of cats and kittens. J Neurophysiol 78:1045–1061
Carandini M, Horton JC, Sincich LC (2007) Thalamic filtering of retinal spike trains by postsynpatic summation. J Vision 7:1–11
Casti A, Xiao Y, Kaplan E (2004) Effects of cortical feedback on LGN dynamics. Soc Neurosci Abstracts 409(7)
Casti A, Hayot F, Xiao Y, Kaplan E (2008) A simple model of retina-LGN transmission. J Comp Neurosci 24:235–252
Cruse H (1997) Neural networks as cynernetic systems. Thieme Verlag, Stuttgart
Cudeiro J, Sillito AM (1996) Spatial frequency tuning of orientation-discontinuity-sensitive corticofugal feedback to the cat lateral geniculate nucleus. J Physiol 490:481–492
Dayan P, Abbott L (2001) Theoretical Neuroscience. The MIT Press, Cambridge, MA
DeAngelis GC, Ohzawa I, Freeman RD (1995) Receptive-field dynamics in the central visual pathways. Trends Neurosci 18:451–458
Derrington AM, Fuchs AF (1979) Spatial and temporal properties of x and y cells in the cat lateral geniculate nucleus. J Physiol 293:347–364
Destexhe A, Contreras D, Steriade M (1998) Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells. J Neurophysiol 79:999–1016
Destexhe A (2000) Modelling corticothalamic feedback and the gating of the thalamus by the cerebral cortex. J Physiol (Paris) 94:391–410
Einevoll G, Heggelund P (2000) Mathematical models for the spatial receptive-field organization of nonlagged X cells in dorsal lateral geniculate nucleus of cat. Vis Neurosci 17:871–885
Einevoll GT, Plesser HE (2002) Linear mechanistic models for the dorsal lateral geniculate nucleus of cat probed using drifting grating stimuli. Netw Comp Neural 13:503–530
Einevoll GT, Plesser HE (2011) Extended difference-of-Gaussians model incorporating cortical feedback for relay cells in the lateral geniculate nucleus of cat. Cogn Neurodyn. doi:10.1007/s11571-011-9183-8
Enroth-Cugell C, Robson J (1966) The constrast sensitivity of retinal ganglion cells of the cat. J Physiol 181:517–552
Ermentrout B (1998) Neural networks as spatio-temporal pattern-forming systems. Rep Prog Phys 61:353–430
Gazères N, Borg-Graham LJ, Frégnac Y (1998) A phenomenological model of visually evoked spike trains in cat geniculate nonlagged x-cells. Vis Neurosci 15:1157–1174
Geisert EE, Langsetmo A, Spear PD (1981) Influence of the cortico-geniculate pathway on response properties of cat lateral geniculate neurons. Brain Res 208(2):409–415
Gerstner W (2000) Population dynamics of spiking neurons: fast transients, asynchronous states, and locking. Neural Comp 12:43–89
Godwin DW, Vaughan JW, Sherman SM (1996) Metabotropic glutamate receptors switch visual response mode of lateral geniculate nucleus cells from burst to tonic. J Neurophysiol 76(3):1800–1816
Guido W, Sherman SM (1998) Response latencies of cells in the cat’s lateral geniculate nucleus are less variable during burst than tonic firing. Vis Neurosci 15:231–237
Hayot F, Tranchina D (2001) Modeling corticofugal feedback and the sensitivity of lateral geniculate neurons to orientation discontinuity. Vis Neurosci 18:865–877
Heeger D (1991) Nonlinear model of neural responses in cat visual cortex. In: MS Landy, JA Movshon (eds) Computational models of visual processing, MIT Press, Cambridge, MA, pp 119–133
Hillenbrand U, van Hemmen LJ (2000) Spatiotemporal adaptation through corticothalamic loops: a hypothesis. Vis Neurosci 17:107–118
Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol 160:106–154
Jin J, Weng C, Yeh CI, Gordon JA, Ruthazer ES, Stryker MP, Swadlow HA, Alonso JM (2008) On- and off-domains of geniculate afferents in cat primary visual cortex. Nat Neurosci 11:88–94
Jing W, Liu W-Z, Gong X-W, Gong H-Q, Liang P-J (2010) Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities. Cogn Neurodyn 3:179–188
Kaplan E, Marcus S, So YT (1979) Effects of dark adaptation on spatial and temporal properties of receptive fields in cat lateral geniculate nucleus. J Physiol 294:561–580
Kaplan E, Mukherjee P, Shapley R (1993) Information filtering in the lateral geniculate nucleus. In: Shapley R, Lam DM-K (eds) Contrast sensitivity, MIT Press, Cambridge, MA, pp 183–200
Kaplan E, Purpura K, Shapley RM (1987) Contrast affects the transmission of visual information through the mammalian lateral geniculate nucleus. J Physiol 391:267–288
Kirkland KL, Gerstein GL (1998) A model of cortically induced synchronization in the lateral geniculate nucleus of the cat: a role for low-threshold calcium channels. Vision Res 38:2007–2022
Kirkland KL, Sillito AM, Jones HE, West DC, Gerstein GL (2000) Oscillations and long-lasting correlations in a model of the lateral geniculate nucleus and visual cortex. J Neurophysiol 84:1863–1868
Köhn J, Wörgötter F (1996) Corticofugal feedback can reduce the visual latency of responses to antagonistic stimuli. Biol Cybern 75(3):199–209
Liang L, Wang R, Zhang Z (2010) The modeling and simulation of visuospatial working memory. Cogn Neurodyn 4:359–366
Lumer ED, Edelman GM, Tononi G (1997) Neural Dynamics in a model of the thalamocortical System. I Layers, loops and the emergence of fast synchronous rhythms. Cerebral Cortex 7:207–227
MacDonald M (1979) Time lags in biological models (Lecture Notes in Biomathematics). Springer, Berlin
Marrocco RT, McClurkin JW, Alkire MT (1996) The influence of the visual cortex on the spatiotemporal response properties of lateral geniculate nucleus cells. Brain Res 737(1–2):110–118
Marrocco RT, McClurkin JW, Young RA (1982) Modulation of lateral geniculate nucleus cell responsiveness by visual activation of the corticogeniculate pathway. J Neurosci 2(2):256–263
Mastronarde DN (1987) Two classes of single-input x-cells in cat lateral geniculate nucleus. i. receptive-field properties and classification of cells. J Neurophysiol 57(2):357–380
Mastronarde DN (1987) Two classes of single-input x-cells in cat lateral geniculate nucleus. ii. retinal inputs and the generation of receptive-field properties. J Neurophysiol 57(2):381–413
Mayer J, Schuster HG, Claussen JC, Mölle M (2007) Corticothalamic projections control synchronization in locally coupled bistable thalamic oscillators. Phys Rev Lett 99:068102
McClurkin JW, Marrocco RT (1984) Visual cortical input alters spatial tuning in monkey lateral geniculate nucleus cells. J Physiol 348:135–152
McClurkin JW, Optican LM, Richmond BJ (1994) Cortical feedback increases visual information transmitted by monkey parvocellular lateral geniculate nucleus neurons. Vis Neurosci 11(3):601–617
McCormick DA, von Krosigk M (1992) Corticothalamic activation modulates thalamic firing through glutamate “metabotropic” receptors. Proc Natl Acad Sci USA 89:2774–2778
Mukherjee P, Kaplan E (1995) Dynamics of neurons in the cat lateral geniculate nucleus: in vivo electrophysiology and computational modeling. J Neurophysiol 74:1222–1243
Murphy PC, Sillito AM (1987) Corticofugal feedback influences the generation of length tuning in the visual pathway. Nature 329(6141):727–729
Nordbø O, Wyller J, Einevoll GT (2007) Neural network firing-rate models on integral form: effects of temporal coupling kernels on equilibrium-state stability. Biol Cybern 97(3):195–209
Nordlie E, Gewaltig M-O, Plesser HE (2009) Towards reproducible descriptions of neuronal network models. PLoS Comput Biol 5(8):e1000456
Nordlie E, Tetzlaff T, Einevoll GT (2010) Firing-rate response properties of spiking neurons: beyond the diffusion limit. Front Comput Neurosci 4:459
Oppenheim A, Willsky A (1996) Signals and systems, 2nd ed. Prentice Hall, Upper Saddle River, NJ
Rodieck R (1965) Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vis Res 5:583–601
Ruksenas O, Fjeld IT, Heggelund P (2000) Spatial summation and center-surround antagonism in the receptive field of single units in the dorsal lateral geniculate nucleus of cat: comparison with retinal input. Vis Neurosci 17:855–870
Saglam M, Hayashida Y, Murayama N (2009) A retinal circuit model accounting for wide-field amacrine cells. Cogn Neurodyn 1:25–32
Satoh S, Usui S (2009) Engineering-approach accelerates computational understanding of V1–V2 neural properties. Cogn Neurodyn 3:1–8
Shapley R, Lennie P (1985) Spatial frequency analysis in the visual system. Annu Rev Neurosci 8:547–583
Sherman S, Guillery R (2001) Exploring the thalamus. Academic Press, New York
Sillito AM, Cudeiro J, Murphy PC (1993) Orientation sensitive elements in the corticofugal influence on centre-surround interactions in the dorsal lateral geniculate nucleus. Exp Brain Res 93(1):6–16
Sillito AM, Jones HE (2002) Corticothalamic interactions in the transfer of visual information. Philos Trans R Soc Lond B Biol Sci 357(1428):1739–1752
Sillito AM, Jones HE (2004) Feedback systems in visual processing. In: Chalupa LM, Wernes JS (eds) The visual neurosciences, Vol 1, MIT Press, Cambridge, MA, pp 609–624
Sillito AM, Jones HE, Gerstein GL, West DC (1994) Feature-linked synchronization of thalamic relay cell firing induced by feedback from visual cortex. Nature 369:479–482
Troyer TW, Krukowski AE, Priebe NJ, Miller KD (1998) Contrast-invariant orientation tuning in cat visual cortex: thalamocortical input tuning and correlation-based intracortical connectivity. J Neurosci 18:5908–5927
Troyer TW, Krukowski AE, Miller KD (2002) LGN input to simple cells and contrast-invariant orientation tuning: an analysis. J Neurophysiol 87:2741–2752
Usrey WM, Reppas JB, Reid RC (1999) Specificity and strength of retinogeniculate connections. J Neurophysiol 82(6):3527–3540
Vidyasagar TR, Urbas JV (1982) Orientation sensitivity of cat lgn neurones with and without inputs from visual cortical areas 17 and 18. Exp Brain Res 46(2):157–169
Wang W, Jones HE, Andolina IM, Sillito AM (2006) Functional alignment of feedback effects from visual cortex to thalamus. Nat Neurosci 9:1330–1336
Wang R, Zhang Z (2007) Energy coding in biological neural networks. Cogn Neurodyn 3:203–212
Wolfe J, Palmer LA (1998) Temporal diversity in the lateral geniculate nucleus of cat. Vis Neurosci 15:653–675
Wörgötter F, Nelle E, Li B, Funke K (1998) The influence of corticofugal feedback on the temporal structure of visual responses of cat thalamic relay cells. J Physiol 509(Pt 3):797–815
Yousif N, Denham M (2007) The role of cortical feedback in the generation of the temporal receptive field responses of lateral geniculate nucleus neurons: a computational modelling study. Biol Cybern 97(4):269–277