Decreasing the degree of polymerization of microcrystalline cellulose by mechanical impact and acid hydrolysis.

Depolymerization of cellulose is often used as a (pre)treatment protocol within the catalytic valorization strategies of cellulose. Typical depolymerization protocols yield polymerization degrees above 70 anhydroglucose units (AGU). However, shorter cellulose fibers are of interest in the search for accessible dietary fiber additives or renewable materials with distinct mechanical properties (bio-composites). In this work, short-polymer microcrystalline celluloses (SMCC) with an average polymerization degree between 29 and 70 AGU were produced with material yields of 95 % and above by combining a planetary ball mill pretreatment with mild acid hydrolysis. By first decreasing the levelling-off degree of polymerization (LODP) with an intensive ball mill treatment, a mild acid hydrolysis protocol was sufficient to ensure high yields of SMCC. Furthermore, the desired polymerization degree could be obtained by tuning the process parameters.

Engineering Curcumin Biosynthesis in Poplar Affects Lignification and Biomass Yield.

Lignocellulosic biomass is recalcitrant toward deconstruction into simple sugars mainly due to the presence of lignin. By engineering plants to partially replace traditional lignin monomers with alternative ones, lignin degradability and extractability can be enhanced. Previously, the alternative monomer curcumin has been successfully produced and incorporated into lignified cell walls of Arabidopsis by the heterologous expression of DIKETIDE-CoA SYNTHASE (DCS) and CURCUMIN SYNTHASE2 (CURS2). The resulting transgenic plants did not suffer from yield penalties and had an increased saccharification yield after alkaline pretreatment. Here, we translated this strategy into the bio-energy crop poplar. Via the heterologous expression of DCS and CURS2 under the control of the secondary cell wall CELLULOSE SYNTHASE A8-B promoter (ProCesA8-B), curcumin was also produced and incorporated into the lignified cell walls of poplar. ProCesA8-B:DCS_CURS2 transgenic poplars, however, suffered from shoot-tip necrosis and yield penalties. Compared to that of the wild-type (WT), the wood of transgenic poplars had 21% less cellulose, 28% more matrix polysaccharides, 23% more lignin and a significantly altered lignin composition. More specifically, ProCesA8-B:DCS_CURS2 lignin had a reduced syringyl/guaiacyl unit (S/G) ratio, an increased frequency of p-hydroxyphenyl (H) units, a decreased frequency of p-hydroxybenzoates and a higher fraction of phenylcoumaran units. Without, or with alkaline or hot water pretreatment, the saccharification efficiency of the transgenic lines was equal to that of the WT. These differences in (growth) phenotype illustrate that translational research in crops is essential to assess the value of an engineering strategy for applications. Further fine-tuning of this research strategy (e.g., by using more specific promoters or by translating this strategy to other crops such as maize) might lead to transgenic bio-energy crops with cell walls more amenable to deconstruction without settling in yield.

Hyperrealistic neural decoding for reconstructing faces from fMRI activations via the GAN latent space.

Neural decoding can be conceptualized as the problem of mapping brain responses back to sensory stimuli via a feature space. We introduce (i) a novel experimental paradigm that uses well-controlled yet highly naturalistic stimuli with a priori known feature representations and (ii) an implementation thereof for HYPerrealistic reconstruction of PERception (HYPER) of faces from brain recordings. To this end, we embrace the use of generative adversarial networks (GANs) at the earliest step of our neural decoding pipeline by acquiring fMRI data as participants perceive face images synthesized by the generator network of a GAN. We show that the latent vectors used for generation effectively capture the same defining stimulus properties as the fMRI measurements. As such, these latents (conditioned on the GAN) are used as the in-between feature representations underlying the perceived images that can be predicted in neural decoding for (re-)generation of the originally perceived stimuli, leading to the most accurate reconstructions of perception to date.

No Evidence for Neural Overlap between Unconsciously Processed and Imagined Stimuli.

Visual representations can be generated via feedforward or feedback processes. The extent to which these processes result in overlapping representations remains unclear. Previous work has shown that imagined stimuli elicit similar representations as perceived stimuli throughout the visual cortex. However, while representations during imagery are indeed only caused by feedback processing, neural processing during perception is an interplay of both feedforward and feedback processing. This means that any representational overlap could be because of overlap in feedback processes. In the current study, we aimed to investigate this issue by characterizing the overlap between feedforward- and feedback-initiated category representations during imagined stimuli, conscious perception, and unconscious processing using fMRI in humans of either sex. While all three conditions elicited stimulus representations in left lateral occipital cortex (LOC), significant similarities were observed only between imagery and conscious perception in this area. Furthermore, connectivity analyses revealed stronger connectivity between frontal areas and left LOC during conscious perception and in imagery compared with unconscious processing. Together, these findings can be explained by the idea that long-range feedback modifies visual representations, thereby reducing representational overlap between purely feedforward- and feedback-initiated stimulus representations measured by fMRI. Neural representations influenced by feedback, either stimulus driven (perception) or purely internally driven (imagery), are, however, relatively similar.

Low molecular weight and highly functional RCF lignin products as a full bisphenol a replacer in bio-based epoxy resins.

Herein, we present a full lignocellulose-to-chemicals valorization chain, wherein low molecular weight and highly functional lignin oligomers, obtained from reductive catalytic fractionation (RCF) of pine wood, were used to fully replace bisphenol A (BPA) for synthesizing bio-based epoxy resins.

Population codes of prior knowledge learned through environmental regularities.

How the brain makes correct inferences about its environment based on noisy and ambiguous observations is one of the fundamental questions in Neuroscience. Prior knowledge about the probability with which certain events occur in the environment plays an important role in this process. Humans are able to incorporate such prior knowledge in an efficient, Bayes optimal, way in many situations, but it remains an open question how the brain acquires and represents this prior knowledge. The long time spans over which prior knowledge is acquired make it a challenging question to investigate experimentally. In order to guide future experiments with clear empirical predictions, we used a neural network model to learn two commonly used tasks in the experimental literature (i.e. orientation classification and orientation estimation) where the prior probability of observing a certain stimulus is manipulated. We show that a population of neurons learns to correctly represent and incorporate prior knowledge, by only receiving feedback about the accuracy of their inference from trial-to-trial and without any probabilistic feedback. We identify different factors that can influence the neural responses to unexpected or expected stimuli, and find a novel mechanism that changes the activation threshold of neurons, depending on the prior probability of the encoded stimulus. In a task where estimating the exact stimulus value is important, more likely stimuli also led to denser tuning curve distributions and narrower tuning curves, allocating computational resources such that information processing is enhanced for more likely stimuli. These results can explain several different experimental findings, clarify why some contradicting observations concerning the neural responses to expected versus unexpected stimuli have been reported and pose some clear and testable predictions about the neural representation of prior knowledge that can guide future experiments.

A sustainable wood biorefinery for low-carbon footprint chemicals production.

The profitability and sustainability of future biorefineries are dependent on efficient feedstock use. Therefore, it is essential to valorize lignin when using wood. We have developed an integrated biorefinery that converts 78 weight % (wt %) of birch into xylochemicals. Reductive catalytic fractionation of the wood produces a carbohydrate pulp amenable to bioethanol production and a lignin oil. After extraction of the lignin oil, the crude, unseparated mixture of phenolic monomers is catalytically funneled into 20 wt % of phenol and 9 wt % of propylene (on the basis of lignin weight) by gas-phase hydroprocessing and dealkylation; the residual phenolic oligomers (30 wt %) are used in printing ink as replacements for controversial para-nonylphenol. A techno-economic analysis predicts an economically competitive production process, and a life-cycle assessment estimates a lower carbon dioxide footprint relative to that of fossil-based production.

Evidence for confounding eye movements under attempted fixation and active viewing in cognitive neuroscience.

Eye movements can have serious confounding effects in cognitive neuroscience experiments. Therefore, participants are commonly asked to fixate. Regardless, participants will make so-called fixational eye movements under attempted fixation, which are thought to be necessary to prevent perceptual fading. Neural changes related to these eye movements could potentially explain previously reported neural decoding and neuroimaging results under attempted fixation. In previous work, under attempted fixation and passive viewing, we found no evidence for systematic eye movements. Here, however, we show that participants' eye movements are systematic under attempted fixation when active viewing is demanded by the task. Since eye movements directly affect early visual cortex activity, commonly used for neural decoding, our findings imply alternative explanations for previously reported results in neural decoding.

Neuroimaging Findings on Amodal Completion: A Review.

Amodal completion is the phenomenon of perceiving completed objects even though physically they are partially occluded. In this review, we provide an extensive overview of the results obtained from a variety of neuroimaging studies on the neural correlates of amodal completion. We discuss whether low-level and high-level cortical areas are implicated in amodal completion; provide an overview of how amodal completion unfolds over time while dissociating feedforward, recurrent, and feedback processes; and discuss how amodal completion is represented at the neuronal level. The involvement of low-level visual areas such as V1 and V2 is not yet clear, while several high-level structures such as the lateral occipital complex and fusiform face area seem invariant to occlusion of objects and faces, respectively, and several motor areas seem to code for object permanence. The variety of results on the timing of amodal completion hints to a mixture of feedforward, recurrent, and feedback processes. We discuss whether the invisible parts of the occluded object are represented as if they were visible, contrary to a high-level representation. While plenty of questions on amodal completion remain, this review presents an overview of the neuroimaging findings reported to date, summarizes several insights from computational models, and connects research of other perceptual completion processes such as modal completion. In all, it is suggested that amodal completion is the solution to deal with various types of incomplete retinal information, and highly depends on stimulus complexity and saliency, and therefore also give rise to a variety of observed neural patterns.

Eye movements explain decodability during perception and cued attention in MEG.

Eye movements are an integral part of human perception, but can induce artifacts in many magneto-encephalography (MEG) and electroencephalography (EEG) studies. For this reason, investigators try to minimize eye movements and remove these artifacts from their data using different techniques. When these artifacts are not purely random, but consistent regarding certain stimuli or conditions, the possibility arises that eye movements are actually inducing effects in the MEG signal. It remains unclear how much of an influence eye movements can have on observed effects in MEG, since most MEG studies lack a control analysis to verify whether an effect found in the MEG signal is induced by eye movements. Here, we find that we can decode stimulus location from eye movements in two different stages of a working memory match-to-sample task that encompass different areas of research typically done with MEG. This means that the observed MEG effect might be (partly) due to eye movements instead of any true neural correlate. We suggest how to check for eye movement effects in the data and make suggestions on how to minimize eye movement artifacts from occurring in the first place.

Shared Neural Mechanisms of Visual Perception and Imagery.

For decades, the extent to which visual imagery relies on the same neural mechanisms as visual perception has been a topic of debate. Here, we review recent neuroimaging studies comparing these two forms of visual experience. Their results suggest that there is a large overlap in neural processing during perception and imagery: neural representations of imagined and perceived stimuli are similar in the visual, parietal, and frontal cortex. Furthermore, perception and imagery seem to rely on similar top-down connectivity. The most prominent difference is the absence of bottom-up processing during imagery. These findings fit well with the idea that imagery and perception rely on similar emulation or prediction processes.

Introducing curcumin biosynthesis in Arabidopsis enhances lignocellulosic biomass processing.

Lignin is the main cause of lignocellulosic biomass recalcitrance to industrial enzymatic hydrolysis. By partially replacing the traditional lignin monomers by alternative ones, lignin extractability can be enhanced. To design a lignin that is easier to degrade under alkaline conditions, curcumin (diferuloylmethane) was produced in the model plant Arabidopsis thaliana via simultaneous expression of the turmeric (Curcuma longa) genes DIKETIDE-CoA SYNTHASE (DCS) and CURCUMIN SYNTHASE 2 (CURS2). The transgenic plants produced a plethora of curcumin- and phenylpentanoid-derived compounds with no negative impact on growth. Catalytic hydrogenolysis gave evidence that both curcumin and phenylpentanoids were incorporated into the lignifying cell wall, thereby significantly increasing saccharification efficiency after alkaline pretreatment of the transgenic lines by 14-24% as compared with the wild type. These results demonstrate that non-native monomers can be synthesized and incorporated into the lignin polymer in plants to enhance their biomass processing efficiency.

Functionalised heterogeneous catalysts for sustainable biomass valorisation.

Efficient transformation of biomass to value-added chemicals and high-energy density fuels is pivotal for a more sustainable economy and carbon-neutral society. In this framework, developing potential cascade chemical processes using functionalised heterogeneous catalysts is essential because of their versatile roles towards viable biomass valorisation. Advances in materials science and catalysis have provided several innovative strategies for the design of new appealing catalytic materials with well-defined structures and special characteristics. Promising catalytic materials that have paved the way for exciting scientific breakthroughs in biomass upgrading are carbon materials, metal-organic frameworks, solid phase ionic liquids, and magnetic iron oxides. These fascinating catalysts offer unique possibilities to accommodate adequate amounts of acid-base and redox functional species, hence enabling various biomass conversion reactions in a one-pot way. This review therefore aims to provide a comprehensive account of the most significant advances in the development of functionalised heterogeneous catalysts for efficient biomass upgrading. In addition, this review highlights important progress ensued in tailoring the immobilisation of desirable functional groups on particular sites of the above-listed materials, while critically discussing the role of consequent properties on cascade reactions as well as on other vital processes within the bio-refinery. Current challenges and future opportunities towards a rational design of novel functionalised heterogeneous catalysts for sustainable biomass valorisation are also emphasized.

Differential temporal dynamics during visual imagery and perception.

Visual perception and imagery rely on similar representations in the visual cortex. During perception, visual activity is characterized by distinct processing stages, but the temporal dynamics underlying imagery remain unclear. Here, we investigated the dynamics of visual imagery in human participants using magnetoencephalography. Firstly, we show that, compared to perception, imagery decoding becomes significant later and representations at the start of imagery already overlap with later time points. This suggests that during imagery, the entire visual representation is activated at once or that there are large differences in the timing of imagery between trials. Secondly, we found consistent overlap between imagery and perceptual processing around 160 ms and from 300 ms after stimulus onset. This indicates that the N170 gets reactivated during imagery and that imagery does not rely on early perceptual representations. Together, these results provide important insights for our understanding of the neural mechanisms of visual imagery.

Vividness of Visual Imagery Depends on the Neural Overlap with Perception in Visual Areas.

Research into the neural correlates of individual differences in imagery vividness point to an important role of the early visual cortex. However, there is also great fluctuation of vividness within individuals, such that only looking at differences between people necessarily obscures the picture. In this study, we show that variation in moment-to-moment experienced vividness of visual imagery, within human subjects, depends on the activity of a large network of brain areas, including frontal, parietal, and visual areas. Furthermore, using a novel multivariate analysis technique, we show that the neural overlap between imagery and perception in the entire visual system correlates with experienced imagery vividness. This shows that the neural basis of imagery vividness is much more complicated than studies of individual differences seemed to suggest. SIGNIFICANCE STATEMENT: Visual imagery is the ability to visualize objects that are not in our direct line of sight: something that is important for memory, spatial reasoning, and many other tasks. It is known that the better people are at visual imagery, the better they can perform these tasks. However, the neural correlates of moment-to-moment variation in visual imagery remain unclear. In this study, we show that the more the neural response during imagery is similar to the neural response during perception, the more vivid or perception-like the imagery experience is.

Mnemonic convergence in the human hippocampus.

The ability to form associations between a multitude of events is the hallmark of episodic memory. Computational models have espoused the importance of the hippocampus as convergence zone, binding different aspects of an episode into a coherent representation, by integrating information from multiple brain regions. However, evidence for this long-held hypothesis is limited, since previous work has largely focused on representational and network properties of the hippocampus in isolation. Here we identify the hippocampus as mnemonic convergence zone, using a combination of multivariate pattern and graph-theoretical network analyses of functional magnetic resonance imaging data from humans performing an associative memory task. We observe overlap of conjunctive coding and hub-like network attributes in the hippocampus. These results provide evidence for mnemonic convergence in the hippocampus, underlying the integration of distributed information into episodic memory representations.

Alkane production from biomass: chemo-, bio- and integrated catalytic approaches.

Linear, branched and cyclic alkanes are important intermediates and end products of the chemical industry and are nowadays mainly obtained from fossil resources. In search for alternatives, biomass feedstocks are often presented as a renewable carbon source for the production of fuels, chemicals and materials. However, providing a complete market for all these applications seems unrealistic due to both financial and logistic issues. Despite the very large scale of current alkane-based fuel applications, biomass definitely has the potential to offer a partial solution to the fuel business. For the smaller market of chemicals and materials, a transition to biomass as main carbon source is more realistic and even probably unavoidable in the long term. The appropriate use and further development of integrated chemo- and biotechnological (catalytic) process strategies will be crucial to successfully accomplish this petro-to-bio feedstock transition. Furthermore, a selection of the most promising technologies from the available chemo- and biocatalytic tool box is presented. New opportunities will certainly arise when multidisciplinary approaches are further explored in the future. In an attempt to select the most appropriate biomass sources for each specific alkane-based application, a diagram inspired by van Krevelen is applied, taking into account both the C-number and the relative functionality of the product molecules.

Selective nickel-catalyzed conversion of model and lignin-derived phenolic compounds to cyclohexanone-based polymer building blocks.

Valorization of lignin is essential for the economics of future lignocellulosic biorefineries. Lignin is converted into novel polymer building blocks through four steps: catalytic hydroprocessing of softwood to form 4-alkylguaiacols, their conversion into 4-alkylcyclohexanols, followed by dehydrogenation to form cyclohexanones, and Baeyer-Villiger oxidation to give caprolactones. The formation of alkylated cyclohexanols is one of the most difficult steps in the series. A liquid-phase process in the presence of nickel on CeO2 or ZrO2 catalysts is demonstrated herein to give the highest cyclohexanol yields. The catalytic reaction with 4-alkylguaiacols follows two parallel pathways with comparable rates: 1) ring hydrogenation with the formation of the corresponding alkylated 2-methoxycyclohexanol, and 2) demethoxylation to form 4-alkylphenol. Although subsequent phenol to cyclohexanol conversion is fast, the rate is limited for the removal of the methoxy group from 2-methoxycyclohexanol. Overall, this last reaction is the rate-limiting step and requires a sufficient temperature (>250 °C) to overcome the energy barrier. Substrate reactivity (with respect to the type of alkyl chain) and details of the catalyst properties (nickel loading and nickel particle size) on the reaction rates are reported in detail for the Ni/CeO2 catalyst. The best Ni/CeO2 catalyst reaches 4-alkylcyclohexanol yields over 80 %, is even able to convert real softwood-derived guaiacol mixtures and can be reused in subsequent experiments. A proof of principle of the projected cascade conversion of lignocellulose feedstock entirely into caprolactone is demonstrated by using Cu/ZrO2 for the dehydrogenation step to produce the resultant cyclohexanones (≈80 %) and tin-containing beta zeolite to form 4-alkyl-ε-caprolactones in high yields, according to a Baeyer-Villiger-type oxidation with H2 O2 .

Reinstatement of associative memories in early visual cortex is signaled by the hippocampus.

The cortical reinstatement hypothesis of memory retrieval posits that content-specific cortical activity at encoding is reinstated at retrieval. Evidence for cortical reinstatement was found in higher-order sensory regions, reflecting reactivation of complex object-based information. However, it remains unclear whether the same detailed sensory, feature-based information perceived during encoding is subsequently reinstated in early sensory cortex and what the role of the hippocampus is in this process. In this study, we used a combination of visual psychophysics, functional neuroimaging, multivoxel pattern analysis, and a well controlled cued recall paradigm to address this issue. We found that the visual information human participants were retrieving could be predicted by the activation patterns in early visual cortex. Importantly, this reinstatement resembled the neural pattern elicited when participants viewed the visual stimuli passively, indicating shared representations between stimulus-driven activity and memory. Furthermore, hippocampal activity covaried with the strength of stimulus-specific cortical reinstatement on a trial-by-trial level during cued recall. These findings provide evidence for reinstatement of unique associative memories in early visual cortex and suggest that the hippocampus modulates the mnemonic strength of this reinstatement.

Spatial and temporal aspects of navigation in two neurological patients.

We present two cases (A.C. and W.J.) with navigation problems resulting from parieto-occipital right hemisphere damage. For both the cases, performance on the neuropsychological tests did not indicate specific impairments in spatial processing, despite severe subjective complaints of spatial disorientation. Various aspects of navigation were tested in a new virtual reality task, the Virtual Tübingen task. A double dissociation between spatial and temporal deficits was found; A.C. was impaired in route ordering, a temporal test, whereas W.J. was impaired in scene recognition and route continuation, which are spatial in nature. These findings offer important insights in the functional and neural architecture of navigation.