Biology subjects

Neumann, H.

Publications and source records attributed to Neumann, H..

13 recordsLinked to original sources

bioRxiv2026

Coherence from Context - Two-Point Neuron Models for Contextual Integration in Visual Information Processing

The integration of contextual information is crucial for coherent perception and cognition. The morphology and conductance properties of cortical pyramidal cells suggest that they operate as "two-point neurons" (TPNs), asymmetrically combining driving sensory input at basal dendrites with modulating context at apical compartments. We present a mechanistic computational TPN model that captures the causal cell-internal apical-basal integration. The model is extended incorporating the interactions between pyramidal cells and local inhibitory interneuron circuits of PV, SOM, and VIP cells. The model rests on guiding principles of asymmetric feedforward-feedback integration, contextual feedback, and pooled inhibition to implement local competition and global cooperation supporting the selective amplification of coherent signals. We validate our approach against detailed multi-compartment pyramidal cell simulations reproducing key electrophysiological phenomena. We then extend it to interacting TPN populations with joint spatial and feature selectivity. In such networks, contextual signals propagate through structured lateral recurrence and top-down feedback, exhibiting contextual integration, coherence formation, and evidence propagation. To support larger-scale network simulations, we derive a reduced mathematical model that preserves the core computational principles of TPNs, while substantially reducing complexity. We demonstrate the models applicability in biological vision, showing how it explains motion integration and incremental grouping--processes requiring dynamic resolution of perceptual ambiguity. Finally, we discuss how the proposed framework connects cellular and circuit-level mechanisms of pyramidal neurons to broader questions about cortical computation, the formation of representations for globally consistent perceptual states, and the potential for embedding TPN principles into artificial neural network architectures. HighlightsO_LIMechanistic TPN model integrates basal driving input and apical context modulation. C_LIO_LILocal inhibitory circuits (PV/SOM/VIP) regulate competition and cooperation. C_LIO_LINetworks of TPN populations exhibit global coherence via context propagation. C_LIO_LIReduced models retain core computations for efficient large-scale vision networks. C_LIO_LILinks pyramidal cell mechanisms to cortical computation and AI models. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/721094v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@18a10b2org.highwire.dtl.DTLVardef@14e33a1org.highwire.dtl.DTLVardef@11f9afborg.highwire.dtl.DTLVardef@1f7dc7e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Flatfish intestinal microbiota depend on various host traits, and vary with sediment type and bottom trawling effort

The intestinal microbiota of fishes support digestion, nutrient uptake and play an important role in the immune system, development and reproduction. Flatfish live in close contact with the seafloor, and are particularly exposed to anthropogenic disturbances such as bottom trawling. Bottom trawling impacts the ecosystem in various ways and it recent evidence indicates that the microbial composition and diversity in marine sediments varies with fishing intensity. It is presently unknown whether this trawling signal applies to the seafloor alone, or may also extend to microbiota of marine holobionts inhabiting it, such as flatfishes. Here, three flatfish species (Buglossidium luteum, Limanda limanda and Pleuronectes platessa) were sampled across the southeastern North Sea. We characterized the intestinal microbiota using 16S rDNA metabarcoding of 162 individuals, and disentangled how intestinal microbial composition and diversity are jointly shaped by various host traits (species, sex, age, weight, and condition factor) and environmental factors (sediment type and trawling intensity). Intestinal diversity varied among species and changed with age, weight and sediment type. Community composition was dependent on species, age, condition factor and sediment type. In addition, we found that trawling intensity explained shifts in intestinal microbial community composition, suggesting that the known impacts of bottom trawling on the benthic environment may cascade to intestinal microbiota of flatfish. Our findings provide important insight into host-microbiota interactions in marine ecosystems and highlight the interplay between host traits and environment as drivers of intestinal microbial diversity and community composition in flatfish. HighlightsO_LIFlatfish microbiota are shaped by host traits and environmental factors C_LIO_LIHost species and age affect intestinal microbial diversity and composition C_LIO_LIIntestinal microbiota vary along a bottom trawling intensity gradient C_LIO_LIBottom trawling impacts may cascade from sediments to fish intestinal microbiota C_LI

ecology↗

bioRxiv2025

Current and future relevance of marine spatial planning for the distribution of epibenthic invertebrate and fish species in a heavily used regional sea

The SNS has recently become a European hub for installations of offshore wind farms (OWF), while extensive areas have been designated as marine protected areas (MPAs). Together with the already noticeable effects of climate warming, the region transforms from an area dominated by free ranging fisheries and shipping into an industrial landscape dominated by stationary activities. To inform decision making processes around the spatial allocation of fisheries, conservation measures and licence areas for offshore renewables in the southern North Sea, we modelled the spatial distribution of 179 epibenthic invertebrate and fish species. We identify both current and future hotspots of epibenthic and demersal fish diversity and their overlap with OWFs and MPAs. Hotspots of epibenthic and fish diversity are mostly found along the English Coast, located within an extensive network of MPA and OWF sites, which may provide opportunities for conservation and fisheries alike. In the central SNS, the MPA network could be complemented by OWF, where co-use regulations with other human uses are excluded, to protect sensitive species as well as epibenthic and demersal fish communities. Scenarios for three different time periods (until 2040, 2070 & 2100) revealed that global warming might cause an increase in the probability of occurrence for more than half of the analysed demersal fish species (n = 63). The applications in our study demonstrate the relevance of comprehensive knowledge about current, near and far future distribution patterns of species and species communities to enhance the effectiveness of marine spatial planning including spatial conservation measures.

ecology↗

bioRxiv2024

Teaching deep networks to see shape: Lessons from a simplified visual world.

Deep neural networks have been remarkably successful as models of the primate visual system. One crucial problem is that they fail to account for the strong shape-dependence of primate vision. Whereas humans base their judgements of category membership to a large extent on shape, deep networks rely much more strongly on other features such as color and texture. While this problem has been widely documented, the underlying reasons remain unclear. We design simple, artificial image datasets in which shape, color, and texture features can be used to predict the image class. By training networks to classify images with single features and feature combinations, we show that some network architectures are unable to learn to use shape features, whereas others are able to use shape in principle but are biased towards the other features. We show that the bias can be explained by the interactions between the weight updates for many images in mini-batch gradient descent. This suggests that different learning algorithms with sparser, more local weight changes are required to make networks more sensitive to shape and improve their capability to describe human vision. Author summaryWhen humans recognize objects, the cue they rely on most is shape. In contrast, deep neural networks mostly use local features like color and texture to classify images. We investigated how this difference arises, using images of simple shapes like rectangles and the letters L and T, combined with color and texture features. By testing different feature combinations, we show that some networks are generally unable to learn about shape, whereas others could learn to recognize shapes in isolation, but ignored shape if another feature was present. We show that this bias for color and texture arises from the way in which networks are trained: by averaging the learning signal over many images, the training algorithm favors simple features that are relatively similar in many images and removes sparser, more varied shape features. These insights can help build networks that are more sensitive to shape and work better as models of human vision.

neuroscience↗

bioRxiv2023

Thalamo-Cortical Interaction for Incremental Binding in Mental Contour-Tracing

Visual object-based attention marks a key process of mammalian perception. By which mechanisms this process is implemented and how it can be interacted with by means of attentional control is not completely understood yet. Incremental binding is a mechanism required in more demanding scenarios of object-based attention and is likewise experimentally investigated quite well. Attention spreads across a representation of the visual object and labels bound elements by constant up-modulation of neural activity. The speed of incremental binding was found to be dependent on the spatial arrangement of distracting elements in the scene and to be scale invariant giving rise to the growth-cone hypothesis. In this work, we propose a neural dynamical model of incremental binding that provides a mechanistic account for these findings. Through simulations, we investigate the model properties and demonstrate how an attentional spreading mechanism tags neurons that participate in the object binding process. They utilize Gestalt properties and eventually show growth-cone characteristics labeling perceptual items by delayed activity enhancement of neuronal firing rates. We discuss the algorithmic process underlying incremental binding and relate it to the models computation. This theoretical investigation encompasses complexity considerations and finds the model to be not only of explanatory value in terms of neurohpysiological evidence, but also to be an efficient implementation of incremental binding striving to establish a normative account. By relating the connectivity motifs of the model to neuroanatomical evidence, we suggest thalamo-cortical interactions to be a likely candidate for the flexible and efficient realization suggested by the model. There, pyramidal cells are proposed to serve as the processors of incremental grouping information. Local bottom-up evidence about stimulus features is integrated via basal dendritic sites. It is combined with an apical signal consisting of contextual grouping information which is gated by attentional task-relevance selection mediated via higher-order thalamic representations. Author SummaryUnderstanding a visual scene requires us to tell apart visual objects from one another. Object-based attention is the process by which mammals achieve this. Mental processing of object components determines whether they are compatible to the overall object and, thus, should be grouped together to be perceived as a whole or not. For complicated objects, this processing needs to happen serially, determining the compatibility step by step. In this work, we propose a neural model of this process and try to answer the question of how it might be implemented in the brain. We test the model on a case of object-based attention for grouping elongated lines and compare it to the available experimental evidence. We additionally show that the model not only explains this evidence, but it does so also by spending neurons and connections efficiently -- a property likewise desirable for brains and machines. Together, these findings suggest which brain areas might be involved in realizing this process and how to reason about the complexity of this computation.

neuroscience↗

bioRxiv2023

From microbial communities to regional biogeography: Unraveling patterns, determinants and the influence of bottom trawling in benthic microbiota

Microbial composition and diversity in marine sediments are shaped by environmental, biological, and anthropogenic processes that operate on different scales. However, our understanding of benthic microbial biogeography remains limited. Here, we study how benthic microbiota vary at a regional scale in the North Sea with sediment characteristics, temperature, organic matter content, shear bed stress and bottom trawling intensity, a prevalent industrial fishing practice which heavily impacts benthic ecosystems. Using 16S rDNA amplicon sequencing, we characterized benthic microbiota from the top centimeter of 349 sediment samples and used uni-and multivariate statistical models, accounting for spatial autocorrelation, to disentangle the effects of the different predictors. Fitted models demonstrate how the geographic interplay of different environmental anthropogenic drivers shapes the structure and functioning of benthic microbial communities. Sediment properties were the primary determinants, with diversity increasing with sediment permeability but at the same time increasing with mud content, highlighting different underlying processes. Alpha diversity also increased nonlinearly with total organic matter content and temperature and showed a more complex relationship with bottom shear stress but decreased with bottom trawling intensity. These trawling associated diversity changes were accompanied by shifts in functional groups related to energy metabolism. Specifically, with increasing trawling intensity, we observed a transition toward more aerobic heterotrophic and less denitrifying metabolism. Our findings provide first insights of benthic microbial biogeographic patterns on a large spatial scale and illustrate how anthropogenic activity such as bottom trawling may influence the distribution and abundances of microbes and overall benthic metabolism at macroecological scales.

ecology↗

bioRxiv2021

Just-in-time: gaze guidance behavior while action planning and execution in VR

Natural eye movements have primarily been studied for over-learned activities such as tea-making, sandwich-making, and hand-washing, which have a fixed sequence of associated actions. These studies indicate a sequential activation of low-level cognitive schemas facilitating task completion. However, it is unclear if these action schemas are activated in the same pattern when a task is novel and a sequence of actions must be planned in the moment. Here, we recorded gaze and body movements in a naturalistic task to study action-oriented gaze behavior. In a virtual environment, subjects moved objects on a life-size shelf to achieve a given order. In order to compel cognitive planning, we added complexity to the sorting tasks. Fixations aligned with the action onset showed gaze as tightly coupled with the action sequence, and task complexity moderately affected the proportion of fixations on the task-relevant regions. Our analysis further revealed that the gaze was allocated to action-relevant targets just in time. Planning behavior predominantly corresponded to a greater visual search for task-relevant objects before the action onset. The results support the idea that natural behavior relies very little on working memory, and humans refrain from encoding objects in the environment to plan long-term actions. Instead, they prefer just-in-time planning by searching for action-relevant items in the moment, directing their body and hand to it, monitoring the action until it is terminated, and moving on to the next action. Author SummaryEye movements in the natural environment have primarily been studied for over-learned and habitual everyday activities (tea-making, sandwich-making, hand-washing) with a fixed sequence of associated actions. These studies show eye movements correspond to a specific order of actions learned over time. In this study, we were interested in how humans plan and execute actions for tasks that do not have an inherent action sequence. To that end, we asked subjects to sort objects based on object features on a life-size shelf in a virtual environment as we recorded their eye and body movements. We investigated the general characteristics of gaze behavior while acting under natural conditions. Our paper provides a comprehensive approach to preprocess naturalistic gaze data in virtual reality. Furthermore, we provide a data-driven method of analyzing the different action-oriented functions of gaze. The results show that bereft of a predefined action sequence, humans prefer to plan only their immediate actions where eye movements are used to search for the target object to immediately act on, then to guide the hand towards it, and to monitor the action until it is terminated. Such a simplistic approach ensures that humans choose sub-optimal behavior over planning under sustained cognitive load.

neuroscience↗

bioRxiv2020

Binaural Signal Integration Improves Vertical Sound Source Localization

Early studies have shown that the localization of a sound source in the vertical plane can be accomplished with only a single ear, thus assumed the localization mechanism to be based on monaural cues. Such cues are induced by the pinna and consist of notches and peaks in the perceived spectrum which vary systematically with the elevation of sound sources. These processes pose several problems to the auditory system like identifying and extracting spectral cues on a neural level, as well as, distinguishing pinna induced peaks and notches from features already present in the source spectrum. Interestingly, at the stage of elevation estimate binaural information from both ears is already available and it seems plausible that the auditory system takes advantage of this information. Especially, since such a binaural integration can improve the localization performance dramatically as we demonstrate in the current study. For that, we first introduce a computational model architecture that takes advantage of binaural signal integration to localize sound sources in the median plane. Model performance is tested under different conditions which reveal that localization of monaural, as well as binaural inputs is best when the model is trained with binaural inputs. Furthermore, modeling results lead to the hypothesis that sound type specific prior information is taken into account to further improve localization quality. This deduced hypothesis about vertical sound source localization is confirmed in a behavioral experiment. Based on these results, we propose that elevation estimation of sound sources is facilitated by an early binaural signal integration and can incorporate sound type specific prior information for higher accuracy.

neuroscience↗

bioRxiv2020

14-3-3 protein Bmh1 triggers short-range compaction of mitotic chromosomes by recruiting sirtuin deacetylase Hst2

Mitotic chromosome compaction is licensed by kinetochores in yeast. Recruitment of Aurora kinase B elicits a cascade of events starting with phosphorylation of H3 S10, which signals the recruitment of lysine deacetylase Hst2 and the removal of H4 K16ac. The unmasked H4 tails interact with the acidic patch of neighbouring nucleosomes to drive short-range compaction of chromatin. Here, we demonstrate that the interaction of Hst2 with H3 S10ph is mediated by 14-3-3 protein Bmh1. As a homodimer, Bmh1 binds simultaneously to H3 S10ph and the phosphorylated C-terminus of Hst2. The Hst2-Bmh1 interaction is cell cycle dependent, reaching its maximum in M phase. Furthermore, we show that phosphorylation of C-terminal residues of Hst2 stimulates its deacetylase activity. Hence, the data presented here identify Bmh1 as a key player in the mechanism of licensing of chromosome compaction in mitosis. Key PointsO_LI14-3-3 protein Bmh1 bridges the interaction of Hst2 with phosphorylated H3 tails C_LIO_LIHst2 is multiply phosphorylated on its unstructured C-terminal tail C_LIO_LIThe interaction of Bmh1 with Hst2 is cell cycle dependent C_LIO_LIHst2 phosphorylation enhances its enzymatic activity C_LI

biochemistry↗

bioRxiv2020

Interaction of RSC chromatin remodelling complex with nucleosomes is modulated by H3 K14 acetylation and H2B SUMOylation in vivo

Chromatin remodelling complexes are multi-subunit nucleosome translocases that reorganize chromatin in the context of DNA replication, repair and transcription. A key question is how these complexes find their target sites on chromatin. Here, we use genetically encoded photo-crosslinker amino acids to map the footprint of Sth1, the catalytic subunit of the RSC (remodels the structure of chromatin) complex, on the nucleosome in living yeast. We find that the interaction of the Sth1 bromodomain with the H3 tail depends on K14 acetylation by Gcn5. This modification does not recruit RSC to chromatin but mediates its interaction with neighbouring nucleosomes. We observe a preference of RSC for H2B SUMOylated nucleosomes in vivo and show that this modification moderately enhances RSC binding to nucleosomes in vitro. Furthermore, RSC is not ejected from chromatin in mitosis, but its mode of nucleosome binding differs between interphase and mitosis. In sum, our in vivo analyses show that RSC recruitment to specific chromatin targets involves multiple histone modifications most likely in combination with other components such as histone variants and transcription factors. Key PointsO_LIIn vivo photo-crosslinking reveals the footprint of the ATPase subunit of RSC on the nucleosome. C_LIO_LIRSC binds to H3 K14ac nucleosomes via the C-terminal bromodomain of its ATPase-subunit Sth1. C_LIO_LIRSC preferentially localizes to H2B-SUMOylated nucleosomes. C_LI

biochemistry↗

bioRxiv2020

Computational Investigation of Visually Guided Learningof Spatially Aligned Auditory Maps in the Colliculus

The development of spatially registered auditory maps in the external nucleus of the inferior colliculus in young owls and their maintenance in adult animals is visually guided and evolves dynamically. To investigate the underlying neural mechanisms of this process, we developed a model of stabilized neoHebbian correlative learning which is augmented by an eligibility signal and a temporal trace of activations. This 3-component learning algorithm facilitates stable, yet flexible, formation of spatially registered auditory space maps composed of conductance-based topographically organized neu- ral units. Spatially aligned maps are learned for visual and auditory input stimuli that arrive in temporal and spatial registration. The reliability of visual sensory inputs can be used to regulate the learning rate in the form of an eligibility trace. We show that by shifting visual sensory inputs at the onset of learning the topography of auditory space maps is shifted accordingly. Simulation results explain why a shift of auditory maps in mature animals is possible only if corrections are induced in small steps. We conclude that learning spatially aligned auditory maps is flexibly controlled by reliable visual sensory neurons and can be formalized by a biological plausible unsupervised learning mechanism.

neuroscience↗

bioRxiv2019

Computational principles of neural adaptation for binaural signal integration

Adaptation to statistics of sensory inputs is an essential ability of neural systems and extends their effective operational range. Having a broad operational range facilitates to react to sensory inputs of different granularities, thus is a crucial factor for survival. The computation of auditory cues for spatial localization of sound sources, particularly the interaural level difference (ILD), has long been considered as a static process. Novel findings suggest that this process of ipsi- and contra-lateral signal integration is highly adaptive and depends strongly on recent stimulus statistics. Here, adaptation aids the encoding of auditory perceptual space of various granularities. To investigate the mechanism of auditory adaptation in binaural signal integration in detail, we developed a neural model architecture for simulating functions of lateral superior olive (LSO) and medial nucleus of the trapezoid body (MNTB) composed of single compartment conductance-based neurons. Neurons in the MNTB serve as an intermediate relay population. Their signal is integrated by the LSO population on a circuit level to represent excitatory and inhibitory interactions of input signals. The circuit incorporates an adaptation mechanism operating at the synaptic level based on local inhibitory feedback signals. The models predictive power is demonstrated in various simulations replicating physiological data. Incorporating the innovative adaptation mechanism facilitates a shift in neural responses towards the most effective stimulus range based on recent stimulus history. The model demonstrates that a single LSO neuron quickly adapts to these stimulus statistics and, thus, can encode an extended range of ILDs in the ipsilateral hemisphere. Most significantly, we provide a unique measurement of the adaptation efficacy of LSO neurons. Prerequisite of normal function is an accurate interaction of inhibitory and excitatory signals, a precise encoding of time and a well-tuned local feedback circuit. We suggest that the mechanisms of temporal competitive-cooperative interaction and the local feedback mechanism jointly sensitize the circuit to enable a response shift towards contra-lateral and ipsi-lateral stimuli, respectively. Author summaryWhy are we more precise in localizing a sound after hearing it several times? Adaptation to the statistics of a stimulus plays a crucial role in this. The present article investigates the abilities of a neural adaptation mechanism for improved localization skills based on a neural network model. Adaptation to stimulus statistics is very prominent in sensory systems of animals and allows them to respond to a wide range of stimuli, thus is a crucial factor for survival. For example, humans are able to navigate under suddenly changing illumination conditions (driving a car into and out of a tunnel). This is possible by courtesy of adaptation abilities of our sensory organs and pathways. Certainly, adaptation is not confined to a single sense like vision but also affects other senses like audition. Especially the perception of sound source location. Compared to vision, the localization of a sound source in the horizontal plane is a rather complicated task since the location cannot be read out from the receptor surface but needs to be computed. This requires the underlying neural system to calculate differences of the intensity between the two ears which provide a distinct cue for the location of a sound source. Here, adaptation to this cue allows to focus on a specific part of auditory space and thereby facilitates improved localisation abilities. Based on recent findings that suggest that the intensity difference computation is a flexible process with distinct adaptation mechanisms, we developed a neural model that computes the intensity difference to two incoming sound signals. The model comprises a novel mechanism for adaptation to sound source locations and provides a means to investigate underlying neural principles of adaptation and compare their effectivenesses. We demonstrate that due this mechanism the perceptual range is extended and a finer resolution of auditory space is obtained. Results explain the neural basis for adaptation and indicate that the interplay between different adaptation mechanisms facilitate highly precise sound source localization in a wide range of locations.

neuroscience↗

bioRxiv2019

Evolved, Selective Erasers of Distinct Lysine Acylations

Lysine acetylation, including related lysine modifications such as butyrylation and crotonylation, is a widespread post-translational modification with important roles in many important physiological processes. However, uncovering the regulatory mechanisms that govern the reverse process, deacylation, has been challenging to address, in great part because the small set of lysine deacetylases (KDACs) that remove the modifications are promiscuous in their substrate and acylation-type preference. This lack of selectivity hinders a broader understanding of how deacylation is regulated at the cellular level and how it is correlated with lysine deacylation-related diseases. To facilitate the dissection of KDACs with respect to substrate specificity and modification type, it would be beneficial to re-engineer KDACs to be selective towards a given substrate and/or modification. To dissect the differential contributions of various acylations to cell physiology, we developed a novel directed evolution approach to create selective KDAC variants that are up to 400-fold selective towards butyryl- over crotonyl-lysine substrates. Structural analyses of this non-promiscuous KDAC revealed unprecedented insights regarding the conformational changes mediating the gain in specificity. As a second case study to illustrate the power of this approach, we re-engineer the human SirT1 to increase its selectivity towards acetylated versus crotonylated substrates. These new enzymes, as well as the generic approach that we report here, will greatly facilitate the dissection of the differential roles of lysine acylation in cell physiology.\n\nSignificance StatementAcetylation of lysine residues features numerous roles in diverse physiological processes and correlates with the manifestation of metabolic diseases, cancer and ageing. The already huge diversity of the acetylome is multiplied by variations in the types of acylation. This complexity is in stark contrast to the small set of lysine deacetylases (KDACs) present in human cells, anticipating a pronounced substrate promiscuity.\n\nWe device a strategy to tackle this disarray by creating KDAC variants with increased selectivity towards particular types of lysine acylations using a novel selection system. The variants facilitate the dissection of the differential contributions of particular acylations to gene expression, development and disease. Our structural analyses shed light on the mechanism of substrate discrimination by Sirtuin-type KDACs.

biochemistry↗