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  • 1
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 01 April 2014, Vol.111(13), pp.5000-5
    Description: A large body of evidence has implicated the posterior parietal and orbitofrontal cortex in the processing of value. However, value correlates perfectly with salience when appetitive stimuli are investigated in isolation. Accordingly, considerable uncertainty has remained about the precise nature of the previously identified signals. In particular, recent evidence suggests that neurons in the primate parietal cortex signal salience instead of value. To investigate neural signatures of value and salience, here we apply multivariate (pattern-based) analyses to human functional MRI data acquired during a noninstrumental outcome-prediction task involving appetitive and aversive outcomes. Reaction time data indicated additive and independent effects of value and salience. Critically, we show that multivoxel ensemble activity in the posterior parietal cortex encodes predicted value and salience in superior and inferior compartments, respectively. These findings reinforce the earlier reports of parietal value signals and reconcile them with the recent salience report. Moreover, we find that multivoxel patterns in the orbitofrontal cortex correlate with value. Importantly, the patterns coding for the predicted value of appetitive and aversive outcomes are similar, indicating a common neural scale for appetite and aversive values in the orbitofrontal cortex. Thus orbitofrontal activity patterns satisfy a basic requirement for a neural value signal.
    Keywords: Mvpa ; Attention ; Decision-Making ; Punishment ; Reward ; Cues ; Behavior -- Physiology ; Brain -- Physiology ; Neurons -- Physiology
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 2
    Language: English
    In: NeuroImage, 15 October 2018, Vol.180, pp.324-333
    Description: Information about potential rewards in the environment is essential for guiding adaptive behavior, and understanding neural reward processes may provide insights into neuropsychiatric dysfunctions. Over the past 10 years, multivoxel pattern analysis (MVPA) techniques have been used to study brain areas encoding information about expected and experienced outcomes. These studies have identified reward signals throughout the brain, including the striatum, medial prefrontal cortex, orbitofrontal cortex, dorsolateral prefrontal cortex, and parietal cortex. This review article discusses some of the assumptions and models that are used to interpret results from these studies, and how they relate to findings from animal electrophysiology. The article reviews and summarizes some of the key findings from MVPA studies on reward. In particular, it first focuses on studies that, in addition to mapping out the brain areas that process rewards, have provided novel insights into the coding mechanisms of value and reward. Then, it discusses examples of how multivariate imaging approaches are being used more recently to decode features of expected rewards that go beyond value, such as the identity of an expected outcome or the action required to obtain it. The study of such complex and multifaceted reward representations highlights the key advantage of using representational methods, which are uniquely able to reveal these signals and may narrow the gap between animal and human research. Applied in a clinical context, MVPA may advance our understanding of neuropsychiatric disorders and the development of novel treatment strategies.
    Keywords: Reward ; Decision-Making ; Decoding ; Multivoxel Pattern Analysis ; Fmri ; Orbitofrontal Cortex ; Medicine
    ISSN: 1053-8119
    E-ISSN: 1095-9572
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  • 3
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 2010, Vol.107(13), pp.6010-6015
    Description: An optimal choice among alternative behavioral options requires precise anticipatory representations of their possible outcomes. A fundamental question is how such anticipated outcomes are represented in the brain. Reward coding at the level of single cells in the orbitofrontal cortex (OFC) follows a more heterogeneous coding scheme than suggested by studies using functional MRI (fMRI) in humans. Using a combination of multivariate pattern classification and fMRI we show that the reward value of sensory cues can be decoded from distributed fMRI patterns in the OFC. This distributed representation is compatible with previous reports from animal electrophysiology that show that reward is encoded by different neural populations with opposing coding schemes. Importantly, the fMRI patterns representing specific values during anticipation are similar to those that emerge during the receipt of reward. Furthermore, we show that the degree of this coding similarity is related to subjects' ability to use value information to guide behavior. These findings narrow the gap between reward coding in humans and animals and corroborate the notion that value representations in OFC are independent of whether reward is anticipated or actually received. ; Includes references ; p. 6010-6015.
    Keywords: Frontal Lobes -- Properties ; Magnetic Resonance Imaging -- Methods ; Decision Making -- Psychological Aspects ; Encoding (Memory) -- Physiological Aspects;
    ISSN: 0027-8424
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  • 4
    Language: English
    In: Neuron, 2011, Vol.70(3), pp.549-559
    Description: The dominant view that perceptual learning is accompanied by changes in early sensory representations has recently been challenged. Here we tested the idea that perceptual learning can be accounted for by reinforcement learning involving changes in higher decision-making areas. We trained subjects on an orientation discrimination task involving feedback over 4 days, acquiring fMRI data on the first and last day. Behavioral improvements were well explained by a reinforcement learning model in which learning leads to enhanced readout of sensory information, thereby establishing noise-robust representations of decision variables. We find stimulus orientation encoded in early visual and higher cortical regions such as lateral parietal cortex and anterior cingulate cortex (ACC). However, only activity patterns in the ACC tracked changes in decision variables during learning. These results provide strong evidence for perceptual learning-related changes in higher order areas and suggest that perceptual and reward learning are based on a common neurobiological mechanism. ► Reinforcement learning model accounts for human visual perceptual learning ► Frontal cortex encodes learning-related changes in model-derived decision variables ►Perceptual learning is driven by reinforcement learning processes
    Keywords: Biology ; Anatomy & Physiology
    ISSN: 0896-6273
    E-ISSN: 1097-4199
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  • 5
    Language: English
    In: Journal of the American Chemical Society, 29 June 2011, Vol.133(25), pp.9863-71
    Description: Electron-transfer reactions are fundamental to many practical devices, but because of their complexity, it is often very difficult to interpret measurements done on the complete device. Therefore, studies of model systems are crucial. Here the rates of charge separation and recombination in donor-acceptor systems consisting of a series of butadiyne-linked porphyrin oligomers (n = 1-4, 6) appended to C(60) were investigated. At room temperature, excitation of the porphyrin oligomer led to fast (5-25 ps) electron transfer to C(60) followed by slower (200-650 ps) recombination. The temperature dependence of the charge-separation reaction revealed a complex process for the longer oligomers, in which a combination of (i) direct charge separation and (ii) migration of excitation energy along the oligomer followed by charge separation explained the observed fluorescence decay kinetics. The energy migration is controlled by the temperature-dependent conformational dynamics of the longer oligomers and thereby limits the quantum yield for charge separation. Charge recombination was also studied as a function of temperature through measurements of femtosecond transient absorption. The temperature dependence of the electron-transfer reactions could be successfully modeled using the Marcus equation through optimization of the electronic coupling (V) and the reorganization energy (λ). For the charge-separation rate, all of the donor-acceptor systems could be successfully described by a common electronic coupling, supporting a model in which energy migration is followed by charge separation. In this respect, the C(60)-appended porphyrin oligomers are suitable model systems for practical charge-separation devices such as bulk-heterojunction solar cells, where conformational disorder strongly influences the electron-transfer reactions and performance of the device.
    Keywords: Article;
    ISSN: 00027863
    E-ISSN: 1520-5126
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  • 6
    Language: English
    In: Journal of the American Chemical Society, 15 February 2012, Vol.134(6), pp.3271-80
    Description: [Fe]-hydrogenase catalyzes the reversible hydride transfer from H(2) to methenyltetrahydromethanoptherin, which is an intermediate in methane formation from H(2) and CO(2) in methanogenic archaea. The enzyme harbors a unique active site iron-guanylylpyridinol (FeGP) cofactor, in which a low-spin Fe(II) is coordinated by a pyridinol-N, an acyl group, two carbon monoxide, and the sulfur of the enzyme's cysteine. Here, we studied the biosynthesis of the FeGP cofactor by following the incorporation of (13)C and (2)H from labeled precursors into the cofactor in growing methanogenic archaea and by subsequent NMR, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS) and IR analysis of the isolated cofactor and reference compounds. The pyridinol moiety of the cofactor was found to be synthesized from three C-1 of acetate, two C-2 of acetate, two C-1 of pyruvate, one carbon from the methyl group of l-methionine, and one carbon directly from CO(2). The metabolic origin of the two CO-ligands was CO(2) rather than C-1 or C-2 of acetate or pyruvate excluding that the two CO are derived from dehydroglycine as has previously been shown for the CO-ligands in [FeFe]-hydrogenases. A formation of CO from CO(2) via direct reduction catalyzed by a nickel-dependent CO dehydrogenase or from formate could also be excluded. When the cells were grown in the presence of (13)CO, the two CO-ligands and the acyl group became (13)C-labeled, indicating either that free CO is an intermediate in their synthesis or that free CO can exchange with these iron-bound ligands. Based on these findings, we propose pathways for how the FeGP cofactor might be synthesized.
    Keywords: Archaea -- Metabolism ; Hydrogenase -- Chemistry ; Iron -- Chemistry ; Iron-Sulfur Proteins -- Chemistry ; Isotope Labeling -- Methods ; Methane -- Chemistry
    ISSN: 00027863
    E-ISSN: 1520-5126
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  • 7
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 21 April 2015, Vol.112(16), pp.5195-200
    Description: Nervous systems must encode information about the identity of expected outcomes to make adaptive decisions. However, the neural mechanisms underlying identity-specific value signaling remain poorly understood. By manipulating the value and identity of appetizing food odors in a pattern-based imaging paradigm of human classical conditioning, we were able to identify dissociable predictive representations of identity-specific reward in orbitofrontal cortex (OFC) and identity-general reward in ventromedial prefrontal cortex (vmPFC). Reward-related functional coupling between OFC and olfactory (piriform) cortex and between vmPFC and amygdala revealed parallel pathways that support identity-specific and -general predictive signaling. The demonstration of identity-specific value representations in OFC highlights a role for this region in model-based behavior and reveals mechanisms by which appetitive behavior can go awry.
    Keywords: Associative Learning ; Multivoxel Pattern Analysis ; Olfaction ; Reward Value ; Ventromedial Prefrontal Cortex ; Reward ; Orbit -- Physiology ; Perception -- Physiology ; Prefrontal Cortex -- Physiology
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 8
    Language: English
    In: NeuroImage, 15 May 2011, Vol.56(2), pp.709-715
    Description: In everyday life, successful decision making requires precise representations of expected values. However, for most behavioral options more than one attribute can be relevant in order to predict the expected reward. Thus, to make good or even optimal choices the reward predictions of multiple attributes need to be integrated into a combined expected value. Importantly, the individual attributes of such multi-attribute objects can agree or disagree in their reward prediction. Here we address where the brain encodes the combined reward prediction (averaged across attributes) and where it encodes the variability of the value predictions of the individual attributes. We acquired fMRI data while subjects performed a task in which they had to integrate reward predictions from multiple attributes into a combined value. Using time-resolved pattern recognition techniques (support vector regression) we find that (1) the combined value is encoded in distributed fMRI patterns in the ventromedial prefrontal cortex (vmPFC) and that (2) the variability of value predictions of the individual attributes is encoded in the dorsolateral prefrontal cortex (dlPFC). The combined value could be used to guide choices, whereas the variability of the value predictions of individual attributes indicates an ambiguity that results in an increased difficulty of the value-integration. These results demonstrate that the different features defining multi-attribute objects are encoded in non-overlapping brain regions and therefore suggest different roles for vmPFC and dlPFC in multi-attribute decision making.
    Keywords: Multi-Attribute Decision Making ; Expected Value ; Functional Magnetic Resonance Imaging (Fmri) ; Multivariate Decoding ; Ventromedial Prefrontal Cortex (Vmpfc) ; Dorsolateral Prefrontal Cortex (Dlpfc) ; Medicine
    ISSN: 1053-8119
    E-ISSN: 1095-9572
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  • 9
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 13 March 2012, Vol.109(11), pp.4285-4289
    Description: To efficiently represent all of the possible rewards in the world, dopaminergic midbrain neurons dynamically adapt their coding range to the momentarily available rewards. Specifically, these neurons increase their activity for an outcome that is better than expected and decrease it for an outcome worse than expected, independent of the absolute reward magnitude. Although this adaptive coding is well documented, it remains unknown how this reseating is implemented. To investigate the adaptive coding of prediction errors and its underlying rescaling process, we used human functional magnetic resonance imaging (fMRI) in combination with a reward prediction task that involved different reward magnitudes. We demonstrate that reward prediction errors in the human striatum are expressed according to an adaptive coding scheme. Strikingly, we show that adaptive coding is gated by changes in effective connectivity between the striatum and other reward-sensitive regions, namely the midbrain and the medial prefrontal cortex. Our results provide evidence that striatal prediction errors are normalized by a magnitude-dependent alteration in the interregional connectivity within the brain's reward system.
    Keywords: Biological sciences -- Biology -- Cytology ; Applied sciences -- Engineering -- Systems engineering ; Biological sciences -- Biology -- Anatomy ; Biological sciences -- Biology -- Neuroscience ; Biological sciences -- Biology -- Zoology ; Health sciences -- Medical diagnosis -- Diagnostic methods ; Biological sciences -- Biology -- Anatomy ; Biological sciences -- Biology -- Anatomy ; Economics -- Economic research -- Economic analysis ; Applied sciences -- Imaging -- Economic analysis
    ISSN: 00278424
    E-ISSN: 10916490
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  • 10
    Language: English
    In: Applied and Environmental Microbiology, Oct 1, 2013, Vol.79(19), p.6176-6179
    Description: The enzyme complex catalyzing the Clostridium acidurici electron-bifurcating formate dehydrogenase reaction was investigated. The enzyme complex was found to consist of four subunits encoded by the gene cluster hylCBA-fdhF2.
    Keywords: Clostridium -- Research ; Clostridium -- Physiological Aspects ; Clostridium -- Genetic Aspects ; Microbial Enzymes -- Research
    ISSN: 0099-2240
    E-ISSN: 10985336
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