Literature DB >> 15535170

Why aren't all deep superior colliculus neurons multisensory? A Bayes' ratio analysis.

Hans Colonius1, Adele Diederich.   

Abstract

Multisensory neurons in the deep superior colliculus (SC) show response enhancement to cross-modal stimuli that coincide in time and space. However, multisensory SC neurons respond to unimodal input as well. It is thus legitimate to ask why not all deep SC neurons are multisensory or, at least, develop multisensory behavior during an organism's maturation. The novel answer given here derives from a signal detection theory perspective. A Bayes' ratio model of multisensory enhancement is suggested. It holds that deep SC neurons operate under the Bayes' ratio rule, which guarantees optimal performance-that is, it maximizes the probability of target detection while minimizing the false alarm rate. It is shown that optimal performance of multisensory neurons vis-à-vis cross-modal stimuli implies, at the same time, that modality-specific neurons will outperform multisensory neurons in processing unimodal targets. Thus, only the existence of both multisensory and modality-specific neurons allows optimal performance when targets of one or several modalities may occur.

Mesh:

Year:  2004        PMID: 15535170     DOI: 10.3758/cabn.4.3.344

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.282


  23 in total

1.  A two-stage unsupervised learning algorithm reproduces multisensory enhancement in a neural network model of the corticotectal system.

Authors:  Thomas J Anastasio; Paul E Patton
Journal:  J Neurosci       Date:  2003-07-30       Impact factor: 6.167

2.  Two corticotectal areas facilitate multisensory orientation behavior.

Authors:  Wan Jiang; Huai Jiang; Barry E Stein
Journal:  J Cogn Neurosci       Date:  2002-11-15       Impact factor: 3.225

Review 3.  Target selection and the superior colliculus: goals, choices and hypotheses.

Authors:  Richard J Krauzlis; Dorion Liston; Christopher D Carello
Journal:  Vision Res       Date:  2004-06       Impact factor: 1.886

4.  Bayesian computation in recurrent neural circuits.

Authors:  Rajesh P N Rao
Journal:  Neural Comput       Date:  2004-01       Impact factor: 2.026

5.  Relationship between visual and tactile representations in cat superior colliculus.

Authors:  B E Stein; B Magalhães-Castro; L Kruger
Journal:  J Neurophysiol       Date:  1976-03       Impact factor: 2.714

6.  Multisensory integration in the superior colliculus of the alert cat.

Authors:  M T Wallace; M A Meredith; B E Stein
Journal:  J Neurophysiol       Date:  1998-08       Impact factor: 2.714

7.  Representation and integration of multiple sensory inputs in primate superior colliculus.

Authors:  M T Wallace; L K Wilkinson; B E Stein
Journal:  J Neurophysiol       Date:  1996-08       Impact factor: 2.714

8.  Visual, auditory, and somatosensory convergence on cells in superior colliculus results in multisensory integration.

Authors:  M A Meredith; B E Stein
Journal:  J Neurophysiol       Date:  1986-09       Impact factor: 2.714

9.  Visual-auditory interactions modulate saccade-related activity in monkey superior colliculus.

Authors:  M A Frens; A J Van Opstal
Journal:  Brain Res Bull       Date:  1998-06       Impact factor: 4.077

10.  Superior colliculus lesions preferentially disrupt multisensory orientation.

Authors:  L R Burnett; B E Stein; D Chaponis; M T Wallace
Journal:  Neuroscience       Date:  2004       Impact factor: 3.590

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  9 in total

1.  Computing an optimal time window of audiovisual integration in focused attention tasks: illustrated by studies on effect of age and prior knowledge.

Authors:  Hans Colonius; Adele Diederich
Journal:  Exp Brain Res       Date:  2011-05-31       Impact factor: 1.972

2.  Connectional parameters determine multisensory processing in a spiking network model of multisensory convergence.

Authors:  H K Lim; L P Keniston; J H Shin; B L Allman; M A Meredith; K J Cios
Journal:  Exp Brain Res       Date:  2011-04-12       Impact factor: 1.972

3.  Hebbian mechanisms help explain development of multisensory integration in the superior colliculus: a neural network model.

Authors:  C Cuppini; E Magosso; B Rowland; B Stein; M Ursino
Journal:  Biol Cybern       Date:  2012-08-04       Impact factor: 2.086

4.  The optimal time window of visual-auditory integration: a reaction time analysis.

Authors:  Hans Colonius; Adele Diederich
Journal:  Front Integr Neurosci       Date:  2010-05-11

5.  The effect of spatial-temporal audiovisual disparities on saccades in a complex scene.

Authors:  Marc M Van Wanrooij; Andrew H Bell; Douglas P Munoz; A John Van Opstal
Journal:  Exp Brain Res       Date:  2009-05-05       Impact factor: 1.972

6.  Organization, maturation, and plasticity of multisensory integration: insights from computational modeling studies.

Authors:  Cristiano Cuppini; Elisa Magosso; Mauro Ursino
Journal:  Front Psychol       Date:  2011-05-02

Review 7.  Effects of Aging in Multisensory Integration: A Systematic Review.

Authors:  Alix L de Dieuleveult; Petra C Siemonsma; Jan B F van Erp; Anne-Marie Brouwer
Journal:  Front Aging Neurosci       Date:  2017-03-28       Impact factor: 5.750

8.  Development of a Bayesian Estimator for Audio-Visual Integration: A Neurocomputational Study.

Authors:  Mauro Ursino; Andrea Crisafulli; Giuseppe di Pellegrino; Elisa Magosso; Cristiano Cuppini
Journal:  Front Comput Neurosci       Date:  2017-10-04       Impact factor: 2.380

9.  Modeling multisensory enhancement with self-organizing maps.

Authors:  Jacob G Martin; M Alex Meredith; Khurshid Ahmad
Journal:  Front Comput Neurosci       Date:  2009-06-24       Impact factor: 2.380

  9 in total

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