Abstract
For the brain to synthesize information from different sensory modalities, connections from different sensory systems must converge onto individual neurons. However, despite being the definitive, first step in the multisensory process, little is known about multisensory convergence at the neuronal level. This lack of knowledge may be due to the difficulty for biological experiments to manipulate and test the connectional parameters that define convergence. Therefore, the present study used a computational network of spiking neurons to measure the influence of convergence from two separate projection areas on the responses of neurons in a convergent area. Systematic changes in the proportion of extrinsic projections, the proportion of intrinsic connections, or the amount of local inhibitory contacts affected the multisensory properties of neurons in the convergent area by influencing (1) the proportion of multisensory neurons generated, (2) the proportion of neurons that generate integrated multisensory responses, and (3) the magnitude of multisensory integration. These simulations provide insight into the connectional parameters of convergence that contribute to the generation of populations of multisensory neurons in different neural regions as well as indicate that the simple effect of multisensory convergence is sufficient to generate multisensory properties like those of biological multisensory neurons.
Similar content being viewed by others
References
Allman BL, Keniston LP, Meredith MA (2009) Not just for bimodal neurons anymore: the contribution of unimodal neurons to cortical multisensory processing. Brain Topogr 21:157–167
Anastasio TJ, Patton PE (2003) A two-stage unsupervised learning algorithm reproduces multisensory enhancement in a neural network model of the corticotectal system. J Neurosci 23:6713–6727
Anastasio TJ, Patton PE, Belkacem-Boussaid K (2002) Using Bayes’ rule to model multisensory enhancement in the superior colliculus. Neural Comput 12(5):1165–1187
Avillac M, Hamed SB, Duhamel J-R (2007) Multisensory integration in ventral intraparietal area of the macaque monkey. J Neurosci 27:1922–1932
Barraclough NE, Xiao D, Baker CI, Oram MW, Perret DI (2005) Integration of visual and auditory information by superior temporal sulcus neurons responsive to the sight of actions. J Cognit Neurosci 17:377–391
Bell AH, Corneil BD, Meredith MA, Munoz DP (2001) The influence of stimulus properties on multisensory processing in the awake primate superior colliculus. Can J Exp Psychol 55:125–134
Bower JM, Beeman D (1998) The book of GENESIS: exploring realistic neural models with the GEneral NEural simulation system. Springer-Verlag, New York
Breveglieri R, Galletti C, Monaco S, Fattori P (2008) Visual, somatosensory and bimodal activities in the macaque parietal area PEc. Cereb Cortex 18:806–816
Calvert GA (2001) Crossmodal processing in the human brain: insights from functional neuroimaging studies. Cereb Cortex 11:1110–1123
Carnevale NT, Hines ML (2006) The NEURON book. Cambridge University Press, Cambridge
Clemo HR, Allman BL, Donlan MA, Meredith MA (2007) Sensory and multisensory representations within the cat rostral suprasylvian cortices. J Comp Neurol 503:110–127
Colonius H, Diederich A (2001) A maximum-likelihood approach to modeling multisensory enhancement. In: Dietterich TG, Becker S, Ghahramani Z (eds) NIPS. MIT Press, Cambridge, pp 181–187
Colonius H, Diederich A (2004) Why aren’t all deep superior colliculus neurons multisensory? A Bayes’ ratio analysis. Cogn Affect Behav Neurosci 4:344–353
Cuppini C, Ursino M, Magosso E, Rowland BA, Stein BE (2010) An emergent model of multisensory integration in superior colliculus neurons. Front Integr Neurosci 4:1–15
Dahl CD, Logothetis NK, Kayser C (2009) Spatial organization of multisensory responses in temporal association cortex. J Neurosci 29:11924–11932
DeFilipe J (1993) Neocortical neuronal diversity: chemical heterogeneity revealed by colocalization studies of classic neurotransmitters, neuropeptides, calcium-binding proteins, and cell surface molecules. Cereb Cortex 3:273–289
Dehner LR, Keniston LP, Clemo HR, Meredith MA (2004) Crossmodal circuitry between auditory and somatosensory areas of the cat anterior ectosylvian sulcal cortex: a ‘new’ inhibitory form of multisensory convergence. Cereb Cortex 14:387
Diederich A, Colonius H (2004) Bimodal and trimodal multisensory enhancement: effects of stimulus onset and intensity on reaction time. Percept Psychophys 66:1388–1404
Ermentrout GB, Galan RF, Urban NN (2008) Reliability, synchrony and noise. Trends Neurosci 31:428–434
FitzHugh R (1961) Impulses and physiological states in theoretical models of nerve membrane. Biophysical J 1:445–466
Fuentes-Santamaria V, Alvarado JC, McHaffie JG, Stein BE (2009) Axon morphologies and convergence patterns of projections from different sensory-specific cortices of the anterior ectosylvian sulcus onto multisensory neurons in the cat superior colliculus. Cereb Cortex 19:2902–2915
Ghazanfar AA, Schroeder CE (2006) Is neocortex essentially multisensory? Trends Cogn Sci 10:278–285
Hebb DO (1949) The organization of behavior. Wiley, New York
Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117:500–544
Izhikevich EM (2003) Simple model of spiking neurons. IEEE Trans Neural Netw 14:1569–1572
Izhikevich EM (2010) Dynamical systems in neuroscience: the geometry of excitability and bursting. MIT Press, Cambridge
Izhikevich EM, Edelman GM (2008) Large-scale model of mammalian thalamocortical systems. PNAS 105:3593–3598
Kayser C, Petkov CI, Augath M, Logothetis NK (2005) Integration of touch and sound in auditory cortex. Neuron 48:373–384
Kayser C, Petkov CI, Logothetis NK (2008) Visual modulation of neurons in auditory cortex. Cereb Cortex 18:1560–1574
Keniston LP, Allman BA, Meredith MA, Clemo HR (2009) Somatosensory and multisensory properties of the medial bank of the ferret rostral suprasylvian sulcus. Exp Brain Res 196:239–251
Keniston LP, Henderson SC, Meredith MA (2010) Neuroanatomical identification of crossmodal auditory inputs to interneurons in somatosensory cortex. Exp Brain Res 202:725–731
Konorski J (1948) Conditioned reflexes and neuron organization. Cambridge University Press, Cambridge
Lakatos P, Chen CM, O’Connell MN, Mills A, Schroeder CE (2007) Neuronal oscillations and multisensory interaction in primary auditory cortex. Neuron 18:279–292
Lim HK, Keniston LP, Shin JH, Nguyen CD, Meredith MA, Cios KJ (2010) A neuronal multisensory processing simulator. In: Proceedings of international joint conference neural networks at WCCI 2010, Barcelona, Spain. IEEE Press, New York, pp 281–287
MacGregor RJ (1987) Neural and brain modeling. Academic Press, San Diego
Magosso E, Cuppini C, Serino A, Di Pellegrino G, Ursino M (2008) A theoretical study of multisensory integration in the superior colliculus by a neural network model. Neural Netw 21:817–829
Markram H (2006) The blue brain project. Nat Rev Neurosci 7:153–160
Martin JG, Meredith MA, Ahmad K (2009) Modeling multisensory enhancement with self-organizing maps. Front Compu Neurosci 3:8
Meredith MA, Stein BE (1986) Visual, auditory, and somatosensory convergence on cells in the superior colliculus results in multisensory integration. J Neurophysiol 56:640–662
Meredith MA, Allman BL, Keniston LP, Clemo HR (2011) Are bimodal neurons the same throughout the brain? In: Wallace MT, Murray MM (eds) Frontiers in the neural bases of multisensory processing (in press)
Mergner T (2007) Modeling sensorimotor control of human upright stance. Prog Brain Res 165:283–297
Oie KS, Kiemel T, Jeka JJ (2002) Multisensory fusion: simultaneous re-weighting of vision and touch for the control of human posture. Brain Res Cogn Brain Res 14:164–176
Perrault TJ Jr, Vaughan JW, Stein BE, Wallace MT (2005) Superior colliculus neurons use distinct operational modes in the integration of multisensory stimuli. J Neurophysiol 93:2575–2586
Reinoso-Suarez F, Roda JM (1985) Topographical organization of the cortical afferent connections to the cortex of the anterior ectosylvian sulcus in the cat. Exp Brain Res 59:313–324
Romanski LM (2007) Representation and integration of auditory and visual stimuli in the primate ventral lateral prefrontal cortex. Cereb Cortex 17:i61–i69
Rowland BA, Quessy S, Stanford TR, Stein BE (2007a) Multisensory integration shortens physiological response latencies. J Neurosci 27:5879–5884
Rowland B, Stanford T, Stein BE (2007b) A Bayseian model unifies multisensory spatial localization with the physiological properties of the superior colliculus. Exp Brain Res 180:153–161
Rowland BA, Stanford RT, Stein BE (2007c) A model of the neural mechanisms underlying multisensory integration in the superior colliculus. Percept 36:1341
Selzer B, Pandya DN (1994) Parietal, temporal, and occipital projections to cortex of the superior temporal sulcus in the rhesus monkey: a retrograde tracer study. J Comp Neurol 343:445–463
Shanahan M (2008) Dynamical complexity in small-world networks of spiking neurons. Phys Rev E Stat Nonlin Soft Matter Phys 78:041924
Shore SE, Vass Z, Wys NL, Altschuler RA (2000) Trigeminal ganglion innervates the auditory brainstem. J Comp Neurol 419:271–285
Song S, Miller KD, Abbot LF (2000) Competitive Hebbian learning through spike timing-dependent synaptic plasticity. Nat Neurosci 3:9
Stein BE, Meredith MA (1993) Merging of the senses. MIT Press, Cambridge
Wallace MT, Carriere BN, Perrault TJ Jr, Vaughan JW, Stein BE (2006) The development of cortical multisensory integration. J Neurosci 26:11844–11849
Acknowledgments
This work was supported by NIH grant NS064675. The authors also thank Dr. JG Martin for his comments.
Conflict of interest
The authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lim, H.K., Keniston, L.P., Shin, J.H. et al. Connectional parameters determine multisensory processing in a spiking network model of multisensory convergence. Exp Brain Res 213, 329–339 (2011). https://doi.org/10.1007/s00221-011-2671-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00221-011-2671-6