Bernstein Center for Computational Neuroscience Munich

ATP-dependent nucleosome remodelers of the INO80 family regulate chromatin by sliding, spacing and positioning nucleosomes. The INO80 remodeler is organized into structural modules that regulate its remodeling activity. Here, we investigate the role of the Ies6 subunit within the Arp5-Ies6 module towards nucleosome positioning and spacing in Saccharomyces cerevisiae. We show that Ies6 is critical for establishing genome-wide nucleosome organization. Deletion of IES6 reduces nucleosome spacing by 3 bp and disrupts regular nucleosome arrays across most genes. Surprisingly, deletion of IES6 is synthetically lethal with the deletion of ISW2, a remodeler from the ISWI family, indicating functional redundancy in nucleosome organization. Notably, INO80 binding directly predicts the role of Ies6 in INO80-mediated nucleosome organization, whereas changes in gene expression do not correlate with altered nucleosome spacing or array regularity. Together, our results highlight the essential role of the Ies6 subunit in INO80-mediated chromatin organization.

ABSTRACTSchizophrenia spectrum disorders (SSD) are marked by cognitive deficits and clinical symptoms linked to disrupted neural oscillations. While changes in spectral power are well documented in SSD, many studies have not clearly separated rhythmic (periodic) from the nonrhythmic (aperiodic) brain activity. This study examined both periodic and aperiodic resting‐state EEG components in SSD, recorded from 152 healthy controls and 97 SSD participants. EEG features (periodic power, bandwidth, center frequency; aperiodic exponent and offset) were extracted from global scalp averages and frontoinsular regions, including the dorsal anterior cingulate cortex (dACC), right anterior insula (R‐INS), and left anterior insula (L‐INS). At the scalp level, SSD individuals exhibited a global increase in theta power, along with a decreased alpha center frequency. Aperiodic activity showed increased exponent and offset in SSD. In frontoinsular regions, increased theta power was observed in the dACC, R‐INS, and L‐INS, along with lower alpha center frequency in L‐INS. No significant differences were found for aperiodic activity in these regions. Increased frontoinsular theta power, especially in the dACC, was associated with worse cognitive performance, particularly global cognition and working memory. These findings highlight the importance of separating periodic and aperiodic EEG activity in SSD, suggesting that periodic alterations, particularly in frontoinsular theta oscillations, may underlie cognitive dysfunction in SSD.

Abstract The acetyltransferase KAT5/Tip60 is an epigenetic regulator of transcription and the DNA damage response. In Drosophila , Tip60 acetylates histones as part of the DOM-A complex, but it is unclear whether it has other substrates. In this work, we comprehensively studied the functions of Tip60 in a Drosophila proliferative cell model. Depletion of Tip60 arrests the cell cycle, but remaining viable cells resist mutagenic irradiation. The impaired proliferation is explained by reduced expression of critical cell cycle genes. Tip60 binds their transcription start sites and Tip60-dependent acetylation of the histone variant H2A.V correlates with transcription activity. A potentially synergistic pathway for cell cycle regulation involves the acetylation of proteins other than histones. The Tip60-dependent nuclear acetylome contains hundreds of proteins, many of which are involved in diverse aspects of cell growth and division, including replication, mitosis, gene expression, chromatin organization and ribosome biogenesis. We hypothesize that Tip60 coordinates the proliferative state through histone and non-histone effectors. Reversible acetylation of diverse effector proteins bears potential for fine-tuning energy-intensive processes in response to stresses or nutritional shortcomings. Our study portrays the DOM-A/TIP60 complex as a general promoter of cell proliferation.

Agent-based models (ABMs) are widely used to study the complex dynamics and emergent properties of systems with many interacting agents. This includes belief and opinion dynamics as are of relevance to understanding contexts as varied as online social media and the practice of science. This paper argues that such ABMs can capture rich argumentation scenarios in ways that have not been covered in research to date. To clarify the space of potential agent-based models of argument, we distinguish three interrelated notions of argument from the literature. First, arguments as reasons refer simply to the propositional content encoded in arguments. Second, arguments as syllogism describe premise-conclusion relationships that arise between such reasons when asserted as arguments. Third, arguments as dialectics refer to the deployment of reasons and syllogisms in discussions (be they polylogues or dialogues). We show how modelling each of these three notions of argument naturally involves a continuum of complexity. Specifically, we use the NormAN framework (introduced in Assaad et al. A Bayesian agent-based framework for argument exchange across networks.https://doi.org/10.48550/arXiv.2311.09254, 2023), which bases ABMs on the theory of Bayesian networks, as a point of reference and draw out its relationship to other modelling frameworks along each of these dimensions. This provides a novel organising scheme to aid model comparison and model choice, and clarifies ways in which these three notions of argument constrain one another. This shows also that NormAN’s Bayesian framework not only captures familiar facets of argumentation, but also allows one to study how dialectical considerations influence population level diffusion of arguments (as we demonstrate with a small simulation study).

Grid cells in the rodent medial entorhinal cortex preferentially fire spikes when the animal is within certain regions of space. When experimental data are averaged over time, spatial firing fields become apparent. If these firing fields represented only the current position of the animal, a grid cell′s firing should not depend on whether the animal is running into or out of a firing field. Yet many grid cells are sensitive to the animal′s direction of motion relative to the firing-field center. Such apparent egocentric ″inbound-outbound tuning″ could be a sign of prospective encoding of future position, but it is unclear whether grid cells code ahead in space or in time. To investigate this question, we decided to undo the inbound-outbound modulation by shifting all spikes within a given firing field by a fixed distance in space or in time. For grid-cell data recorded in mice, optimizing in space requires a forward shift of around 2.5 cm, whereas optimizing in time yielded a forward shift of about 170 ms. In either case the firing-field sizes decrease. Minimizing just the field size yields somewhat smaller shifts (roughly 1.8 cm and around 115 ms ahead). Jointly optimizing along the temporal and spatial dimension reveals a continuum of flat inbound-outbound tuning curves and a shallow minimum for field sizes, located at about 2.3 cm and 35 ms. These findings call into question a purely spatial or purely temporal interpretation of grid-cell firing fields and inbound- outbound tuning.

The processing of sensory information, even at early stages, is influenced by the internal state of the animal. Internal states, such as arousal, are often characterized by relating neural activity to a single "level" of arousal, defined by a behavioral indicator such as pupil size. In this study, we expand the understanding of arousal-related modulations in sensory systems by uncovering multiple timescales of pupil dynamics and their relationship to neural activity. Specifically, we observed a robust coupling between spiking activity in the mouse dorsolateral geniculate nucleus (dLGN) of the thalamus and pupil dynamics across timescales spanning a few seconds to several minutes. Throughout all these timescales, 2 distinct spiking modes-individual tonic spikes and tightly clustered bursts of spikes-preferred opposite phases of pupil dynamics. This multi-scale coupling reveals modulations distinct from those captured by pupil size per se, locomotion, and eye movements. Furthermore, coupling persisted even during viewing of a naturalistic movie, where it contributed to differences in the encoding of visual information. We conclude that dLGN spiking activity is under the simultaneous influence of multiple arousal-related processes associated with pupil dynamics occurring over a broad range of timescales.

Recent work on bats flying over long distances has revealed that single hippocampal cells have multiple place fields of different sizes. At the network level, a multi-scale, multi-field place cell code outperforms classical single-scale, single-field place codes, yet the performance boundaries of such a code remain an open question. In particular, it is unknown how general multi-field codes compare to a highly regular grid code, in which cells form distinct modules with different scales. In this work, we address the coding properties of theoretical spatial coding models with rigorous analyses of comprehensive simulations. Starting from a multi-scale, multi-field network, we performed evolutionary optimization. The resulting multi-field networks sometimes retained the multi-scale property at the single-cell level but most often converged to a single scale, with all place fields in a given cell having the same size. We compared the results against a single-scale single-field code and a one-dimensional grid code, focusing on two main characteristics: the performance of the code itself and the dynamics of the network generating it. Our simulation experiments revealed that, under normal conditions, a regular grid code outperforms all other codes with respect to decoding accuracy, achieving a given precision with fewer neurons and fields. In contrast, multi-field codes are more robust against noise and lesions, such as random drop-out of neurons, given that the significantly higher number of fields provides redundancy. Contrary to our expectations, the network dynamics of all models, from the original multi-scale models before optimization to the multi-field models that resulted from optimization, did not maintain activity bumps at their original locations when a position-specific external input was removed. Optimized multi-field codes appear to strike a compromise between a place code and a grid code that reflects a trade-off between accurate positional encoding and robustness. Surprisingly, the recurrent neural network models we implemented and optimized for either multi- or single-scale, multi-field codes did not intrinsically produce a persistent "memory" of attractor states. These models, therefore, were not continuous attractor networks.

Abstract Recent studies have provided evidence for the concurrent encoding of sensory percepts and visual working memory contents (VWM) across visual areas; however, it has remained unclear how these two types of representations are concurrently present. Here, we reanalyzed an open-access fMRI dataset where participants memorized a sensory stimulus while simultaneously being presented with sensory distractors. First, we found that the VWM code in several visual regions did not fully generalize between different time points, suggesting a dynamic code. A more detailed analysis revealed that this was due to shifts in coding spaces across time. Second, we collapsed neural signals across time to assess the degree of interference between VWM contents and sensory distractors, specifically by testing the alignment of their encoding spaces. We find that VWM and feature-matching sensory distractors are encoded in coding spaces that do not fully overlap, but the separation decreases when distractors negatively impact behavioral performance in recalling the target. Together, these results indicate a role of dynamic coding and temporally stable coding spaces in helping multiplex perception and VWM within visual areas.