Multiple sensitivity profiles to diversity and transition structure in non-stationary input.

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Multiple sensitivity profiles to diversity and transition structure in non-stationary input. / Tobia, Michael; Iacovella, Vittorio; Hasson, Uri.

in: NEUROIMAGE, Jahrgang 60, Nr. 2, 2, 2012, S. 991-1005.

Publikationen: SCORING: Beitrag in Fachzeitschrift/ZeitungSCORING: ZeitschriftenaufsatzForschungBegutachtung

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@article{93fe64abe7ac4b7dbcdd849f1c7db1a2,
title = "Multiple sensitivity profiles to diversity and transition structure in non-stationary input.",
abstract = "Recent formalizations suggest that the human brain codes for the degree of order in the environment and utilizes this knowledge to optimize perception and performance in the immediate future. However, the neural bases of how the brain spontaneously codes for order are poorly understood. It has been shown that activity in lateral temporal cortex and the hippocampus is linearly correlated with the order of short visual series under tasks requiring attention to the input and when series order is invariant over time. Here, we examined if sensitivity to order is manifested in both linear and non-linear BOLD response profiles, quantified the degree to which order-sensitive regions operate as a functional network, and evaluated these questions using a paradigm in which performance of the ongoing task could be completed without any attention to the stimulus whose order was manipulated. Participants listened to a 10-minute sequence of tones characterized by non-stationary order, and fMRI identified cortical regions sensitive to time-varying statistical features of this input. Activity in perisylvian regions was negatively correlated with input diversity, quantified via Shannon's Entropy. Activity in ventral premotor, lateral temporal, and insular regions was correlated linearly, parabolically, or via a step-function with the strength of transition constraints in the series, quantified via Markov Entropy. Granger-causality analysis revealed that order-sensitive regions form a functional network, with regions showing non-linear responses to order associated with more afferent connectivity than those showing linear responses. These findings identify networks that spontaneously code and respond to diverse aspects of order via multiple response profiles, and that play a central role in generating and gating predictive neural activity.",
keywords = "Adult, Humans, Male, Female, Magnetic Resonance Imaging, Hippocampus/*physiology, Cerebral Cortex/*physiology, Markov Chains, Mental Processes/*physiology, Uncertainty, Adult, Humans, Male, Female, Magnetic Resonance Imaging, Hippocampus/*physiology, Cerebral Cortex/*physiology, Markov Chains, Mental Processes/*physiology, Uncertainty",
author = "Michael Tobia and Vittorio Iacovella and Uri Hasson",
year = "2012",
language = "English",
volume = "60",
pages = "991--1005",
journal = "NEUROIMAGE",
issn = "1053-8119",
publisher = "Academic Press",
number = "2",

}

RIS

TY - JOUR

T1 - Multiple sensitivity profiles to diversity and transition structure in non-stationary input.

AU - Tobia, Michael

AU - Iacovella, Vittorio

AU - Hasson, Uri

PY - 2012

Y1 - 2012

N2 - Recent formalizations suggest that the human brain codes for the degree of order in the environment and utilizes this knowledge to optimize perception and performance in the immediate future. However, the neural bases of how the brain spontaneously codes for order are poorly understood. It has been shown that activity in lateral temporal cortex and the hippocampus is linearly correlated with the order of short visual series under tasks requiring attention to the input and when series order is invariant over time. Here, we examined if sensitivity to order is manifested in both linear and non-linear BOLD response profiles, quantified the degree to which order-sensitive regions operate as a functional network, and evaluated these questions using a paradigm in which performance of the ongoing task could be completed without any attention to the stimulus whose order was manipulated. Participants listened to a 10-minute sequence of tones characterized by non-stationary order, and fMRI identified cortical regions sensitive to time-varying statistical features of this input. Activity in perisylvian regions was negatively correlated with input diversity, quantified via Shannon's Entropy. Activity in ventral premotor, lateral temporal, and insular regions was correlated linearly, parabolically, or via a step-function with the strength of transition constraints in the series, quantified via Markov Entropy. Granger-causality analysis revealed that order-sensitive regions form a functional network, with regions showing non-linear responses to order associated with more afferent connectivity than those showing linear responses. These findings identify networks that spontaneously code and respond to diverse aspects of order via multiple response profiles, and that play a central role in generating and gating predictive neural activity.

AB - Recent formalizations suggest that the human brain codes for the degree of order in the environment and utilizes this knowledge to optimize perception and performance in the immediate future. However, the neural bases of how the brain spontaneously codes for order are poorly understood. It has been shown that activity in lateral temporal cortex and the hippocampus is linearly correlated with the order of short visual series under tasks requiring attention to the input and when series order is invariant over time. Here, we examined if sensitivity to order is manifested in both linear and non-linear BOLD response profiles, quantified the degree to which order-sensitive regions operate as a functional network, and evaluated these questions using a paradigm in which performance of the ongoing task could be completed without any attention to the stimulus whose order was manipulated. Participants listened to a 10-minute sequence of tones characterized by non-stationary order, and fMRI identified cortical regions sensitive to time-varying statistical features of this input. Activity in perisylvian regions was negatively correlated with input diversity, quantified via Shannon's Entropy. Activity in ventral premotor, lateral temporal, and insular regions was correlated linearly, parabolically, or via a step-function with the strength of transition constraints in the series, quantified via Markov Entropy. Granger-causality analysis revealed that order-sensitive regions form a functional network, with regions showing non-linear responses to order associated with more afferent connectivity than those showing linear responses. These findings identify networks that spontaneously code and respond to diverse aspects of order via multiple response profiles, and that play a central role in generating and gating predictive neural activity.

KW - Adult

KW - Humans

KW - Male

KW - Female

KW - Magnetic Resonance Imaging

KW - Hippocampus/physiology

KW - Cerebral Cortex/physiology

KW - Markov Chains

KW - Mental Processes/physiology

KW - Uncertainty

KW - Adult

KW - Humans

KW - Male

KW - Female

KW - Magnetic Resonance Imaging

KW - Hippocampus/physiology

KW - Cerebral Cortex/physiology

KW - Markov Chains

KW - Mental Processes/physiology

KW - Uncertainty

M3 - SCORING: Journal article

VL - 60

SP - 991

EP - 1005

JO - NEUROIMAGE

JF - NEUROIMAGE

SN - 1053-8119

IS - 2

M1 - 2

ER -