Induced Gamma-band Activity Elicited by Visual Representation of Unattended Objects

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Brain mechanisms of successful recognition through retrieval of semantic context

Episodic memory is associated with the encoding and retrieval of context information and with a subjective sense of reexperiencing past events. The neural correlates of episodic retrieval have been extensively studied using fMRI, leading to the identification of a "general recollection network" including medial temporal, parietal, and prefrontal regions. However, in these studies, it is difficult to disentangle the effects of context retrieval from recollection. In this study, we used fMRI to determine the extent to which the recruitment of regions in the recollection network is contingent on context reinstatement. Participants were scanned during a cued recognition test for target words from encoded sentences. Studied target words were preceded by either a cue word studied in the same sentence (thus congruent with encoding context) or a cue word studied in a different sentence (thus incongruent with encoding context). Converging fMRI results from independently defined ROIs and whole-brain analysis showed regional specificity in the recollection network. Activity in hippocampus and parahippocampal cortex was specifically increased during successful retrieval following congruent context cues, whereas parietal and prefrontal components of the general recollection network were associated with confident retrieval irrespective of contextual congruency. Our findings implicate medial temporal regions in the retrieval of semantic context, contributing to, but dissociable from, recollective experience

Probabilistic Hybrid Action Models for Predicting Concurrent Percept-driven Robot Behavior

This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, several modes of their interferences, and the achievement of triggering conditions in closed-loop robot plans. The main contributions of this article are: (1) PHAMs, a model of concurrent percept-driven behavior, its formalization, and proofs that the model generates probably, qualitatively accurate predictions; and (2) a resource-efficient inference method for PHAMs based on sampling projections from probabilistic action models and state descriptions. We show how PHAMs can be applied to planning the course of action of an autonomous robot office courier based on analytical and experimental results

The neural bases of event monitoring across domains: a simultaneous ERP-fMRI study.

The ability to check and evaluate the environment over time with the aim to detect the occurrence of target stimuli is supported by sustained/tonic as well as transient/phasic control processes, which overall might be referred to as event monitoring. The neural underpinning of sustained control processes involves a fronto-parietal network. However, it has not been well-defined yet whether this cortical circuit acts irrespective of the specific material to be monitored and whether this mediates sustained as well as transient monitoring processes. In the current study, the functional activity of brain during an event monitoring task was investigated and compared between two cognitive domains, whose processing is mediated by differently lateralized areas. Namely, participants were asked to monitor sequences of either faces (supported by right-hemisphere regions) or tools (left-hemisphere). In order to disentangle sustained from transient components of monitoring, a simultaneous EEG-fMRI technique was adopted within a block design. When contrasting monitoring versus control blocks, the conventional fMRI analysis revealed the sustained involvement of bilateral fronto-parietal regions, in both task domains. Event-related potentials (ERPs) showed a more positive amplitude over frontal sites in monitoring compared to control blocks, providing evidence of a transient monitoring component. The joint ERP-fMRI analysis showed that, in the case of face monitoring, these transient processes rely on right-lateralized areas, including the inferior parietal lobule and the middle frontal gyrus. In the case of tools, no fronto-parietal areas correlated with the transient ERP activity, suggesting that in this domain phasic monitoring processes were masked by tonic ones. Overall, the present findings highlight the role of bilateral fronto-parietal regions in sustained monitoring, independently of the specific task requirements, and suggest that right-lateralized areas subtend transient monitoring processes, at least in some task contexts

Parkinson's disease dementia: a neural networks perspective.

In the long-term, with progression of the illness, Parkinson's disease dementia affects up to 90% of patients with Parkinson's disease. With increasing life expectancy in western countries, Parkinson's disease dementia is set to become even more prevalent in the future. However, current treatments only give modest symptomatic benefit at best. New treatments are slow in development because unlike the pathological processes underlying the motor deficits of Parkinson's disease, the neural mechanisms underlying the dementing process and its associated cognitive deficits are still poorly understood. Recent insights from neuroscience research have begun to unravel the heterogeneous involvement of several distinct neural networks underlying the cognitive deficits in Parkinson's disease dementia, and their modulation by both dopaminergic and non-dopaminergic transmitter systems in the brain. In this review we collate emerging evidence regarding these distinct brain networks to give a novel perspective on the pathological mechanisms underlying Parkinson's disease dementia, and discuss how this may offer new therapeutic opportunities

Can biological quantum networks solve NP-hard problems?

There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines. During the last decades the question has therefore been raised whether we need to consider quantum effects to explain the imagined cognitive power of a conscious mind. This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness and cognition. The purpose is to be able to identify and evaluate instances where quantum effects might play a significant role in cognitive processes. Not surprisingly, the conclusion is that quantum-enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence the functionality of various components and signalling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. So, the conclusion is that biological quantum networks can only approximately solve small instances of NP-hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to efficiently solve NP-hard problems approximately. In the end it is a question of precision - Nature is approximate.Comment: 38 page

The eye contact effect: mechanisms and development

The ‘eye contact effect’ is the phenomenon that perceived eye contact with another human face modulates certain aspects of the concurrent and/or immediately following cognitive processing. In addition, functional imaging studies in adults have revealed that eye contact can modulate activity in structures in the social brain network, and developmental studies show evidence for preferential orienting towards, and processing of, faces with direct gaze from early in life. We review different theories of the eye contact effect and advance a ‘fast-track modulator’ model. Specifically, we hypothesize that perceived eye contact is initially detected by a subcortical route, which then modulates the activation of the social brain as it processes the accompanying detailed sensory information

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

Coding of visual object features and feature conjunctions in the human brain

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