Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation

Detection of regularities and their violations in sensory input is key to perception. Violations are indexed by an early EEG component called the mismatch negativity (MMN) – even if participants are distracted or unaware of the stimuli. On a mechanistic level, two dominant models have been suggested to contribute to the MMN: adaptation and prediction. Whether and how context conditions, such as awareness and task relevance, modulate the mechanisms of MMN generation is unknown. We conducted an EEG study disentangling influences of task relevance and awareness on the visual MMN. Then, we estimated different computational models for the generation of single-trial amplitudes in the MMN time window. Amplitudes were best explained by a prediction error model when stimuli were task-relevant but by an adaptation model when task-irrelevant and unaware. Thus, mismatch generation does not rely on one predominant mechanism but mechanisms vary with task relevance of s

Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation

Detection of regularities and their violations in sensory input is key to perception. Violations are indexed by an early EEG component called the mismatch negativity (MMN) – even if participants are distracted or unaware of the stimuli. On a mechanistic level, two dominant models have been suggested to contribute to the MMN: adaptation and prediction. Whether and how context conditions, such as awareness and task relevance, modulate the mechanisms of MMN generation is unknown. We conducted an EEG study disentangling influences of task relevance and awareness on the visual MMN. Then, we estimated different computational models for the generation of single-trial amplitudes in the MMN time window. Amplitudes were best explained by a prediction error model when stimuli were task-relevant but by an adaptation model when task-irrelevant and unaware. Thus, mismatch generation does not rely on one predominant mechanism but mechanisms vary with task relevance of stimuli

Origins Of Heterospory And The Seed Habit: The Role Of Heterochrony

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149713/1/tax04577.pd

Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research

Tackling antibiotic resistance: the environmental framework

Antibiotic resistance is a threat to human and animal health worldwide, and key measures are required to reduce the risks posed by antibiotic resistance genes that occur in the environment. These measures include the identification of critical points of control, the development of reliable surveillance and risk assessment procedures, and the implementation of technological solutions that can prevent environmental contamination with antibiotic resistant bacteria and genes. In this Opinion article, we discuss the main knowledge gaps, the future research needs and the policy and management options that should be prioritized to tackle antibiotic resistance in the environment

Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation

Detection of regularities and their violations in sensory input is key to perception. Violations are indexed by an early EEG component called the mismatch negativity (MMN) – even if participants are distracted or unaware of the stimuli. On a mechanistic level, two dominant models have been suggested to contribute to the MMN: adaptation and prediction. Whether and how context conditions, such as awareness and task relevance, modulate the mechanisms of MMN generation is unknown. We conducted an EEG study disentangling influences of task relevance and awareness on the visual MMN. Then, we estimated different computational models for the generation of single-trial amplitudes in the MMN time window. Amplitudes were best explained by a prediction error model when stimuli were task-relevant but by an adaptation model when task-irrelevant and unaware. Thus, mismatch generation does not rely on one predominant mechanism but mechanisms vary with task relevance of stimuli

Differential effects of prediction error and adaptation along the auditory cortical hierarchy during deviance processing

Neural mismatch responses have been proposed to rely on different mechanisms, including prediction error-related activity and adaptation to frequent stimuli. However, the hierarchical cortical structure of these mechanisms is unknown. To investigate this question, we recorded hemodynamic responses while participants (N = 54) listened to an auditory oddball sequence as well as a suited control condition. In addition to effects in sensory processing areas (Heschl's gyrus, superior temporal gyrus (STG)), we found several distinct clusters that indexed deviance processing in frontal and parietal regions (anterior cingulate cortex/supplementary motor area (ACC/SMA), inferior parietal lobule (IPL), anterior insula (AI), inferior frontal junction (IFJ)). Comparing responses to the control stimulus with the deviant and standard enabled us to delineate the contributions of prediction error- or adaptation-related brain activation, respectively. We observed significant effects of adaptation in Heschl's gyrus, STG and ACC/SMA, while prediction error-related activity was observed in STG, IPL, AI and IFJ. Additional dynamic causal modeling confirmed the superiority of a hierarchical processing structure compared to a flat structure. Thus, we found that while prediction-error related processes increased with the hierarchical level of the brain area, adaptation declined. This suggests that the relative contribution of different mechanisms in deviance processing varies across the cortical hierarchy