scholarly journals A unified neural circuit of causal inference and multisensory integration

2019 ◽  
Vol 358 ◽  
pp. 355-368 ◽  
Author(s):  
Ying Fang ◽  
Zhaofei Yu ◽  
Jian K. Liu ◽  
Feng Chen
Keyword(s):  
Causal Inference ◽  
Multisensory Integration ◽  
Neural Circuit

scholarly journals A causal inference explanation for enhancement of multisensory integration by co-articulation

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
John F. Magnotti ◽  
Kristen B. Smith ◽  
Marcelo Salinas ◽  
Jacqunae Mays ◽  
Lin L. Zhu ◽  
...  
Keyword(s):  
Causal Inference ◽  
Multisensory Integration

scholarly journals Bayesian causal inference modeling of attentional effects on the temporal binding window of multisensory integration

2019 ◽  
Vol 19 (10) ◽  
pp. 19
Author(s):  
Leslie D Kwakye ◽  
Victoria Fisher ◽  
Margaret Jackson ◽  
Oona Jung-Beeman
Keyword(s):  
Causal Inference ◽  
Multisensory Integration ◽  
Temporal Binding ◽  
Temporal Binding Window

scholarly journals Emergence of opposite neurons in a firing-rate model of multisensory integration

2019 ◽  
Author(s):  
Ho Yin Chau ◽  
Wen-Hao Zhang ◽  
Tai Sing Lee
Keyword(s):  
Multisensory Integration ◽  
Neural Circuit ◽  
Hebbian Learning ◽  
Medial Superior Temporal ◽  
Learning Rules ◽  
Vestibular Cues ◽  
The One ◽  
Von Mises ◽  
Integrated Or ◽  
Self Motion

ABSTRACTOpposite neurons, found in macaque dorsal medial superior temporal (MSTd) and ventral intraparietal (VIP) areas, combine visual and vestibular cues of self-motion in opposite ways. A neural circuit recently proposed utilizes opposite neurons to perform causal inference and decide whether the visual and vestibular cues in MSTd and VIP should be integrated or segregated. However, it is unclear how these opposite connections can be formed with biologically realistic learning rules. We propose a network model capable of learning these opposite neurons, using Hebbian and Anti-Hebbian learning rules. The learned neurons are topographically organized and have von Mises-shaped feedforward connections, with tuning properties characteristic of opposite neurons. Our purpose is two-fold: on the one hand, we provide a circuit-level mechanism that explains the properties and formation of opposite neurons; on the other hand, we present a way to extend current theories of multisensory integration to account for appropriate segregation of sensory cues.

scholarly journals Audiovisual integration in the Mauthner cell enhances escape probability and reduces response latency

2021 ◽  
Author(s):  
Nicolas Martorell ◽  
Violeta Medan
Keyword(s):  
Multisensory Integration ◽  
Response Latency ◽  
Neural Circuit ◽  
Escape Behavior ◽  
Audiovisual Integration ◽  
Auditory Stimuli ◽  
Threat Detection ◽  
Direct Link ◽  
Neural Basis ◽  
Mauthner Cell

Fast and accurate threat detection is critically important for animal survival. Reducing perceptual ambiguity by integrating multiple sources of sensory information can enhance threat detection and reduce response latency. However, studies showing a direct link between behavioral correlates of multisensory integration and its underlying neural basis are rare. In fish, an explosive escape behavior known as C-start is driven by an identified neural circuit centered on the Mauthner cell. The Mauthner cell can trigger C-starts in response to visual and auditory stimuli allowing to investigate how multisensory integration in a single neuron affects behavioral outcome after threat detection. Here we demonstrate that in goldfish visual looms and brief auditory stimuli can be integrated to increase C-start probability and that this enhancement is inversely correlated to the saliency of the cues with weaker auditory cues producing a proportionally stronger multisensory effect. We also show that multisensory stimuli reduce response latency locked to the presentation of the auditory cue. Finally, we make a direct link between behavioral data and its underlying neural mechanism by reproducing empirical data with an integrate-and-fire computational model of the Mauthner cell.

scholarly journals Causal inference in the multisensory brain

2018 ◽  
Author(s):  
Yinan Cao ◽  
Christopher Summerfield ◽  
Hame Park ◽  
Bruno L. Giordano ◽  
Christoph Kayser
Keyword(s):  
Prefrontal Cortex ◽  
Causal Inference ◽  
Frontal Lobe ◽  
Multisensory Integration ◽  
Multisensory Perception ◽  
Adaptive Behaviour ◽  
Sensory Fusion ◽  
Spatio Temporal ◽  
The Brain ◽  
Combining Information

When combining information across different senses humans need to flexibly select cues of a common origin whilst avoiding distraction from irrelevant inputs. The brain could solve this challenge using a hierarchical principle, by deriving rapidly a fused sensory estimate for computational expediency and, later and if required, filtering out irrelevant signals based on the inferred sensory cause(s). Analysing time- and source-resolved human magnetoencephalographic data we unveil a systematic spatio-temporal cascade of the relevant computations, starting with early segregated unisensory representations, continuing with sensory fusion in parietal-temporal regions and culminating as causal inference in the frontal lobe. Our results reconcile previous computational accounts of multisensory perception by showing that prefrontal cortex guides flexible integrative behaviour based on candidate representations established in sensory and association cortices, thereby framing multisensory integration in the generalised context of adaptive behaviour.

Supra-optimality may emanate from suboptimality, and hence optimality is no benchmark in multisensory integration

2018 ◽  
Vol 41 ◽  
Author(s):  
Jean-Paul Noel
Keyword(s):  
Multisensory Integration

AbstractWithin a multisensory context, “optimality” has been used as a benchmark evidencing interdependent sensory channels. However, “optimality” does not truly bifurcate a spectrum from suboptimal to supra-optimal – where optimal and supra-optimal, but not suboptimal, indicate integration – as supra-optimality may result from the suboptimal integration of a present unisensory stimuli and an absent one (audio = audio + absence of vision).

Beyond metaphors and semantics: A framework for causal inference in neuroscience

2019 ◽  
Vol 42 ◽  
Author(s):  
Roberto A. Gulli
Keyword(s):  
Causal Inference ◽  
Causal Power

Abstract The long-enduring coding metaphor is deemed problematic because it imbues correlational evidence with causal power. In neuroscience, most research is correlational or conditionally correlational; this research, in aggregate, informs causal inference. Rather than prescribing semantics used in correlational studies, it would be useful for neuroscientists to focus on a constructive syntax to guide principled causal inference.

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