Steuber, V. | Search bioRxiv

bioRxiv2025

Mesoscale differences in brain organization in schizophrenia revealed by topological data analysis

We present MesoSCOUT (Mesoscale Structural Connectome Order-complex Unveiling Topology), a framework for characterizing white matter connectivity using a method developed from computational algebraic topology: persistent homology (PH) via clique topology. Applying this method to schizophrenia, we uncover a novel, mesoscale perspective of the differences in the white-matter connectome between healthy controls (HC) and subjects with schizophrenia (SCH). We extract and compare topological motifs found in the structural connectomes of the subjects in the two groups and find significant differences. We explore the overlap of mesoscale structures found in two different datasets, COBRE (Center of Biomedical Research Excellence) and HCP (Human Connectome Project). Differences in acquisition usually render experiments recorded on different scanners incomparable, but MesoSCOUT enables cross-dataset comparisons. Our method offers a way to establish connectomic fingerprinting that could lead to a neuroimaging-based diagnosis of schizophrenia and other psychiatric and neurological conditions as well as the development of new treatments.

neuroscience↗

bioRxiv2024

Decoding the amplitude and slope of continuous signals into spikes with a spiking point neuron model

Scalable and efficient neural models with biological plausibility are crucial for real-time applications in neuromorphic hardware and robotics. While biophysically detailed compartmental models are valuable for their accuracy, their complexity and computational cost limit real-world application on currently available hardware. In this study, we harness the signal processing potential of the Izhikevich point neuron model to decode slope and amplitude, both important dynamical features of sensory signals. Results demonstrate that our slope-detector effectively signals up-stokes of naturalistic input signals across a wide range of frequencies. It exhibits bidirectional slope detection, with burst duration encoding slope magnitude in a graded manner. We compare to a biophysically detailed two-compartment pyramidal neuron model, showing that our bursting slope-detector performs similarly. We then demonstrate that our slope-detector does not need to burst, improving efficiency and producing more precise, discrete output by signalling events with single spikes. This makes it well-suited for real-time robotics control systems or neuromorphic hardware applications, offering greater efficiency and enabling large-scale simulations using the same computational power.

neuroscience↗

bioRxiv2023

Autapses enable temporal pattern recognition in spiking neural networks

Most sensory stimuli are temporal in structure. How action potentials encode the information incoming from sensory stimuli remains one of the central research questions in neuroscience. Although there is evidence that the precise timing of spikes represents information in spiking neuronal networks, information processing in spiking networks is still not fully understood. One feasible way to understand the working mechanism of a spiking network is to associate the structural connectivity of the network with the corresponding functional behaviour. This work demonstrates the structure-function mapping of spiking networks evolved (or handcrafted) for a temporal pattern recognition task. The task is to recognise a specific order of the input signals so that the Out put neurone of the network spikes only for the correct placement and remains silent for all others. The minimal networks obtained for this task revealed the twofold importance of autapses in recognition; first, autapses simplify the switching among different network states. Second, autapses enable a network to maintain a network state, a form of memory. To show that the recognition task is accomplished by transitions between network states, we map the network states of a functional spiking neural network (SNN) onto the states of a finite-state transducer (FST, a formal model of computation that generates output symbols, here: spikes or no spikes at specific times, in response to input, here: a series of input signals). Finally, based on our understanding, we define rules for constructing the topology of a network handcrafted for recognising a subsequence of signals (pattern) in a particular order. The analysis of minimal networks recognising patterns of different lengths (two to six) revealed a positive correlation between the pattern length and the number of autaptic connections in the network. Furthermore, in agreement with the behaviour of neurones in the network, we were able to associate specific functional roles of locking, switching, and accepting to neurones.

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bioRxiv2021

EEG Spectral Feature Modulations Associated with Fatigue in Robot-Mediated Upper Limb Gross Motor and Fine Motor Interactions

This paper investigates the EEG spectral feature modulations associated with fatigue induced by robot-mediated upper limb gross motor and fine motor interactions. Twenty healthy participants were randomly assigned to either perform a gross motor interaction with HapticMASTER or a fine motor interaction with SCRIPT passive orthosis for 20 minutes or until volitional fatigue. EEG relative and ratio band power measures were estimated from the data recorded before and after the interactions. Paired-samples t-tests found a significant increase in relative alpha band power on FC3, C3, P3 electrodes, and ({theta} + )/{beta} and /{beta} on C3 electrode following the gross motor interaction. Conversely, relative delta band power on C3 significantly decreased. A significant increase in relative alpha band power on FP1, C3 electrodes and relative theta band power on C4 electrode were found following the fine motor interaction whereas relative delta band power on FP1 electrode significantly decreased. Most participants reported an increase in their physical fatigue level following the gross movements and an increase in their mental fatigue level following the fine movements. Findings affirm that changes to localised brain activity patterns are an indication of fatigue developed from the robot-mediated interactions. It can be concluded that regional differences in the prominent EEG spectral features are most likely due to the differences in the nature of the task (fine/gross motor and distal/proximal upper limb) that may have differently altered an individuals physical and mental fatigue level. The findings could potentially be utilised to monitor and moderate fatigue during robot-mediated post-stroke therapies.

neuroscience↗

bioRxiv2021

The beta component of gamma-band auditory steady-state responses in patients with schizophrenia

The mechanisms underlying circuit dysfunctions in schizophrenia (SCZ) remain poorly understood. Auditory steady-state responses (ASSRs), especially in the gamma and beta band, have been suggested as a potential biomarker for SCZ. While the reduction of 40Hz power for 40Hz drive has been well established and replicated in SCZ patients, studies are inconclusive when it comes to an increase in 20Hz power during 40Hz drive. There might be several factors explaining the inconsistencies, including differences in the sensitivity of the recording modality (EEG vs MEG), differences in stimuli (click-trains vs amplitude-modulated tones) and large differences in the amplitude of the stimuli. Here, we used a computational model of ASSR deficits in SCZ and explored the effect of three SCZ-associated microcircuit alterations: reduced GABA activity, increased GABA decay times and NMDA receptor hypofunction. We investigated the effect of input strength on gamma (40 Hz) and beta (20 Hz) band power during gamma ASSR stimulation and saw that the pronounced increase in beta power during gamma stimulation seen experimentally could only be reproduced in the model when GABA decay times were increased and only for a specific range of input strengths. More specifically, when the input was in this specific range, the rhythmic drive at 40Hz produced a strong 40Hz rhythm in the control network; however, in the SCZ-like network, the prolonged inhibition led to a so-called beat-skipping, where the network would only strongly respond to every other input. This mechanism was responsible for the emergence of the pronounced 20Hz beta peak in the power spectrum. The other two microcircuit alterations were not able to produce a substantial 20 Hz component but they further narrowed the input strength range for which the network produced a beta component when combined with increased GABAergic decay times. Our finding that the beta component only existed for a specific range of input strengths might explain the seemingly inconsistent reporting in experimental studies and suggests that future ASSR studies should systematically explore different amplitudes of their stimuli. Furthermore, we provide a mechanistic link between a microcircuit alterations and an electrophysiological marker in schizophrenia and argue that more complex ASSR stimuli are needed to disentangle the nonlinear interactions of microcircuit alterations. The computational modelling approach put forward here is ideally suited to facilitate the development of such stimuli in a theory-based fashion.

neuroscience↗

bioRxiv2020

The Effect of Alterations of Schizophrenia-Associated Genes on Gamma Band Oscillations

Abnormalities in the synchronized oscillatory activity of neurons in general and, specifically in the gamma band, might play a crucial role in the pathophysiology of schizophrenia. While these changes in oscillatory activity have traditionally been linked to alterations at the synaptic level, we demonstrate here, using computational modeling, that common genetic variants of ion channels can contribute strongly to this effect. Our model of primary auditory cortex highlights multiple schizophrenia-associated genetic variants that reduce gamma power in an auditory steady-state response task. Furthermore, we show that combinations of several of these schizophrenia-associated variants can produce similar effects as the more traditionally considered synaptic changes. Overall, our study provides a mechanistic link between schizophrenia-associated common genetic variants, as identified by genome-wide association studies, and one of the most robust neurophysiological endophenotypes of schizophrenia.

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bioRxiv2019

Growth Rules for the Repair of Asynchronous Irregular Neuronal Networks after Peripheral Lesions

Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model, simulations of which accurately reproduce network rewiring after peripheral lesions as reported in experiments, to study these activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we deafferent a biologically realistic network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed model of homeostatic structural plasticity and the inhibitory synaptic plasticity mechanism that also balances our AI network are both necessary for successful rewiring of the network. Author summaryAn accumulating body of evidence suggests that our brain can compensate for peripheral lesions by adaptive rewiring of its neuronal circuitry. The underlying process, structural plasticity, can modify the connectivity of neuronal networks in the brain, thus affecting their function. To better understand the mechanisms of structural plasticity in the brain, we have developed a novel model of peripheral lesions and the resulting activity-dependent rewiring in a simplified cortical network model that exhibits biologically realistic asynchronous irregular activity. In order to accurately reproduce the directionality and time course of rewiring after injury that is observed in peripheral lesion experiments, we derive activity dependent growth rules for different synaptic elements: dendritic and axonal contacts. Our simulation results suggest that excitatory and inhibitory synaptic elements have to react to changes in neuronal activity in opposite ways. We show that these rules result in a homeostatic stabilisation of activity in individual neurons. In our simulations, both synaptic and structural plasticity mechanisms are necessary for network repair. Furthermore, our simulations indicate that while activity is restored in neurons deprived by the peripheral lesion, the temporal firing characteristics of the network can be changed by the rewiring process.

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bioRxiv2019

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

Despite an increasing body of evidence demonstrating subcellular alterations in parvalbumin-positive (PV+) interneurons in schizophrenia, their functional consequences remain elusive. Since PV+ interneurons are involved in the generation of fast cortical rhythms, these changes have been hypothesized to contribute to well-established alterations of beta and gamma range oscillations in patients suffering from schizophrenia. However, the precise role of these alterations and the role of different subtypes of PV+ interneurons is still unclear. Here we used a computational model of auditory steady-state response (ASSR) deficits in schizophrenia. We investigated the differential effects of decelerated synaptic dynamics, caused by subcellular alterations at two subtypes of PV+ interneurons: basket cells and chandelier cells. Our simulations suggest that subcellular alterations at basket cell synapses rather than chandelier cell synapses are the main contributor to these deficits Particularly, basket cells might serve as target for innovative therapeutic interventions aiming at reversing the oscillatory deficits.

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bioRxiv2019

Binding of Filamentous Actin to CaMKII as a Potential Mechanism for the Regulation of Bidirectional Synaptic Plasticity by betaCaMKII in Cerebellar Purkinje Cells

Calcium-calmodulin dependent protein kinase II (CaMKII) regulates many forms of synaptic plasticity, but little is known about its functional role during plasticity induction in the cerebellum. Experiments have indicated that the {beta} isoform of CaMKII controls the bidirectional inversion of plasticity at parallel fibre (PF)-Purkinje cell (PC) synapses in cerebellar cortex. Because the cellular events that underlie these experimental findings are still poorly understood, we developed a simple computational model to investigate how {beta}CaMKII regulates the direction of plasticity in cerebellar PCs. We present the first model of AMPA receptor phosphorylation that simulates the induction of long-term depression (LTD) and potentiation (LTP) at the PF-PC synapse. Our simulation results suggest that the balance of CaMKII-mediated phosphorylation and protein phosphatase 2B (PP2B)-mediated dephosphorylation of AMPA receptors can determine whether LTD or LTP occurs in cerebellar PCs. The model replicates experimental observations that indicate that {beta}CaMKII controls the direction of plasticity at PF-PC synapses, and demonstrates that the binding of filamentous actin to CaMKII can enable the {beta} isoform of the kinase to regulate bidirectional plasticity at these synapses.\n\nAuthor SummaryMany molecules and the complex interactions between them are involved in synaptic plasticity in the cerebellum. However, the exact relationship between cerebellar plasticity and the different signalling cascades remains unclear. Calcium-calmodulin dependent protein kinase II (CaMKII) is an important component of the signalling network that is responsible for plasticity in cerebellar Purkinje cells (PCs). The CaMKII holoenzyme contains different isoforms such as CaMKII and {beta}CaMKII. Experiments with Camk2b knockout mice that lack the {beta} isoform of CaMKII demonstrated that {beta}CaMKII regulates the direction of plasticity at parallel fibre (PF)-PC synapses. Stimulation protocols that induce long-term depression in wild-type mice, which contain both and {beta}CaMKII, lead to long-term potentiation in knockout mice without {beta}CaMKII, and vice versa. We developed a kinetic simulation of the phosphorylation and dephosphorylation of AMPA receptors by CaMKII and protein phosphatase 2B to investigate how {beta}CaMKII can control bidirectional synaptic plasticity in cerebellar PCs. Our simulation results demonstrate that the binding of filamentous actin to {beta}CaMKII can contribute to the regulation of bidirectional plasticity at PF-PC synapses. Our computational model of intracellular signalling significantly advances the understanding of the mechanisms of synaptic plasticity induction in the cerebellum.

neuroscience↗

bioRxiv2019

Binding of Filamentous Actin to CaMKII as a Potential Mechanism for the Regulation of Bidirectional Plasticity by βCaMKII in Cerebellar Purkinje Cells

Calcium-calmodulin dependent protein kinase II (CaMKII) regulates many forms of synaptic plasticity, but little is known about its functional role during plasticity induction in the cerebellum. Experiments have indicated that the {beta} isoform of CaMKII controls the bidirectional inversion of plasticity at parallel fibre (PF)-Purkinje cell (PC) synapses in cerebellar cortex. Because the cellular events that underlie these experimental findings are still poorly understood, we developed a simple computational model to investigate how {beta}CaMKII regulates the direction of plasticity in cerebellar PCs. We present the first model of AMPA receptor phosphorylation that simulates the induction of long-term depression (LTD) and potentiation (LTP) at the PF-PC synapse. Our simulation results suggest that the balance of CaMKII-mediated phosphorylation and protein phosphatase 2B (PP2B)-mediated dephosphorylation of AMPA receptors can determine whether LTD or LTP occurs in cerebellar PCs. The model replicates experimental observations that indicate that {beta}CaMKII controls the direction of plasticity at PF-PC synapses, and demonstrates that the binding of filamentous actin to CaMKII can enable the {beta} isoform of the kinase to regulate bidirectional plasticity at these synapses.\n\nAuthor SummaryMany molecules and the complex interactions between them are involved in synaptic plasticity in the cerebellum. However, the exact relationship between cerebellar plasticity and the different signalling cascades remains unclear. Calcium-calmodulin dependent protein kinase II (CaMKII) is an important component of the signalling network that is responsible for plasticity in cerebellar Purkinje cells (PCs). The CaMKII holoenzyme contains different isoforms such as CaMKII and {beta}CaMKII. Experiments with Camk2b knockout mice that lack the {beta} isoform of CaMKII demonstrated that {beta}CaMKII regulates the direction of plasticity at parallel fibre (PF)-PC synapses. Stimulation protocols that induce long-term depression in wild-type mice, which contain both and {beta}CaMKII, lead to long-term potentiation in knockout mice without {beta}CaMKII, and vice versa. We developed a kinetic simulation of the phosphorylation and dephosphorylation of AMPA receptors by CaMKII and protein phosphatase 2B to investigate how {beta}CaMKII can control bidirectional synaptic plasticity in cerebellar PCs. Our simulation results demonstrate that the binding of filamentous actin to {beta}CaMKII can contribute to the regulation of bidirectional plasticity at PF-PC synapses. Our computational model of intracellular signalling significantly advances the understanding of the mechanisms of synaptic plasticity induction in the cerebellum.

neuroscience↗