Biology subjects

Luhmann, H. J.

Publications and source records attributed to Luhmann, H. J..

6 recordsLinked to original sources

bioRxiv2026

Oligodendrocyte subtype diversity underlines clinical progression in Parkinsons disease

Despite growing evidence for glial involvement in Parkinsons disease, oligodendrocyte dysfunction remains poorly defined. To address this gap, we compared single-cell RNA sequencing from a mouse model of -synuclein aggregation pathology with fresh human brain tissue from deep brain stimulation surgery to build a cross-species framework of disease progression. In total, we profiled over 200,000 cortical transcriptomes, including 55,000 oligodendrocytes. Early disease in mice was characterized by inflammatory activation, while advanced stages in both species converged on metabolic dysfunction, including impaired ribosomal output, chaperone stress responses, ubiquitination deficits, and lysosomal perturbation. In patients, APLP1 was upregulated and correlated with clinical disease progression and increased levodopa demand, linking -synuclein spread in oligodendrocytes to disease severity. APP and CNTN pathways emerged as key signalling axes, with CNTN reflecting weakened reparative communication and reduced resilience. Together, these findings define oligodendrocyte subtype dynamics as shared and clinically relevant features of PD progression.

neuroscience↗

bioRxiv2023

Spiking neural networks provide accurate, efficient and robust models for whisker stimulus classification and allow for inter-individual generalization

With the help of high-performance computing, we benchmarked a selection of machine learning classification algorithms on the tasks of whisker stimulus detection, stimulus classification and behavior prediction based on electrophysiological recordings of layer-resolved local field potentials from the barrel cortex of awake mice. Machine learning models capable of accurately analyzing and interpreting the neuronal activity of awake animals during a behavioral experiment are promising for neural prostheses aimed at restoring a certain functionality of the brain for patients suffering from a severe brain injury. The liquid state machine, a highly efficient spiking neural network classifier that was designed for implementation on neuromorphic hardware, achieved the same level of accuracy compared to the other classifiers included in our benchmark study. Based on application scenarios related to the barrel cortex and relevant for neuroprosthetics, we show that the liquid state machine is able to find patterns in the recordings that are not only highly predictive but, more importantly, generalizable to data from individuals not used in the model training process. The generalizability of such models makes it possible to train a model on data obtained from one or more individuals without any brain lesion and transfer this model to a prosthesis required by the patient. Author SummaryA neural prosthesis is a computationally driven device that restores the functionality of a damaged brain region for locked-in patients suffering from the aftereffects of a brain injury or severe stroke. As such devices are chronically implanted, they rely on small, low-powered microchips with limited computational resources. Based on recordings describing the neural activity of awake mice, we show that spiking neural networks, which are especially designed for microchips, are able to provide accurate classification models in application scenarios relevant in neuroprosthetics. Furthermore, models were generalizable across mice, corroborating that it will be possible to train a model on recordings from healthy individuals and transfer it to the patients prosthesis.

neuroscience↗

bioRxiv2021

Identification of a developmental switch in information transfer between whisker S1 and S2 cortex in mice

The whiskers of rodents are a key sensory organ that provides critical tactile information for animal navigation and object exploration throughout life. Previous work has explored the developmental sensory-driven activation of the primary sensory cortex processing whisker information (wS1), also called barrel cortex. This body of work has shown that the barrel cortex is already activated by sensory stimuli during the first post-natal week. However, it is currently unknown when over the course of development these stimuli begin being processed by higher order cortical areas, such as secondary whisker somatosensory area (wS2). Here we investigate for the first time the developmental engagement of wS2 by sensory stimuli and the emergence of cortico-cortical communication from wS1 to wS2. Using in vivo wide-field imaging and electrophysiological recordings in control and conditional knock-out mice we find that wS1 and wS2 are able to process bottom-up information coming from the thalamus already right after birth. We identify that it is only at the end of the first post-natal week that wS1 begins to provide excitation into wS2, a connection which begins to acquire feed-forward inhibition characteristics after the second post-natal week. Therefore, we have uncovered a developmental window during which excitatory versus inhibitory functional connectivity between wS1 and wS2 takes place.

neuroscience↗

bioRxiv2021

Modelling the spatial and temporal constrains of the GABAergic influence on neuronal excitability

GABA ({gamma}-amino butyric acid) is an inhibitory neurotransmitter in the adult brain that can mediate depolarizing responses during development or after neuropathological insults. Under which conditions GABAergic membrane depolarizations are sufficient to impose excitatory effects is hard to predict, as shunting inhibition and GABAergic effects on spatiotemporal filtering of excitatory inputs must be considered. To evaluate at which reversal potential a net excitatory effect was imposed by GABA (EGABAThr), we performed a detailed in-silico study using simple neuronal topologies and distinct spatiotemporal relations between GABAergic and glutamatergic inputs. These simulations revealed for GABAergic synapses located at the soma an EGABAThr close to action potential threshold (EAPThr), while with increasing dendritic distance EGABAThr shifted to positive values. The impact of GABA on AMPA-mediated inputs revealed a complex temporal and spatial dependency. EGABAThr depends on the temporal relation between GABA and AMPA inputs, with a striking negative shift in EGABAThr for AMPA inputs appearing after the GABA input. The spatial dependency between GABA and AMPA inputs revealed a complex profile, with EGABAThr being shifted to values negative to EAPThr for AMPA synapses located proximally to the GABA input, while for distally located AMPA synapses the dendritic distance had only a minor effect on EGABAThr. For tonic GABAergic conductances EGABAThr was negative to EAPThr over a wide range of gGABAtonic values. In summary, these results demonstrate that for several physiologically relevant situations EGABAThr is negative to EAPThr, suggesting that depolarizing GABAergic responses can mediate excitatory effects even if EGABA did not reach EAPThr. Author summaryThe neurotransmitter GABA mediates an inhibitory action in the mature brain, while it was found that GABA provokes depolarizations in the immature brain of after neurological insults. It is, however, not clear to which extend these GABAergic depolarizations con contribute to an excitatory effect. In the present manuscript we approached this question with a computational model of a simplified neurons to determine which amount of a GABAergic depolarizing effect, which we quantified by the so called GABA reversal potential (EGABA), was required to turn GABAergic inhibition to excitation. The results of our simulations revealed that if GABA was applied alone a GABAergic excitation was induced when EGABA was around the action potential threshold. When GABA was applied together with additional excitatory inputs, which is the physiological situation in the brain, only for spatially and temporally correlated inputs EGABA was close to the action potential threshold. For situations in which the additional excitatory inputs appear after the GABA input or are distant to the GABA input, an excitatory effect of GABA could be observed already at EGABA substantially negative to the action potential threshold. This results indicate that even slightly depolarizing GABA responses, which may be induced during or after neurological insults, can potentially turn GABAergic inhibition into GABAergic excitation.

neuroscience↗

bioRxiv2020

Rapid nucleus-scale reorganization of chromatin in neurons enables transcriptional adaptation for memory consolidation

The interphase nucleus is functionally organized in active and repressed territories defining the transcriptional status of the cell. However, it remains poorly understood how the nuclear architecture of neurons adapts in response to behaviorally relevant stimuli that trigger fast alterations in gene expression patterns. Imaging of fluorescently tagged nucleosomes revealed that pharmacological manipulation of neuronal activity in vitro and auditory cued fear conditioning in vivo induce nucleus-scale restructuring of chromatin within minutes. Furthermore, the acquisition of auditory fear memory is impaired after infusion of a drug into auditory cortex which blocks chromatin reorganization in vitro. We propose that active chromatin movements at the nucleus scale act together with local gene-specific modifications to enable transcriptional adaptations at fast time scales. Introducing a transgenic mouse line for photolabeling of histones, we extend the realm of systems available for imaging of chromatin dynamics to living animals.

neuroscience↗

bioRxiv2020

Coincident glutamatergic depolarizations enhance GABAA receptor-dependent Cl- influx in mature and suppress Cl- efflux in immature neurons

The impact of GABAergic transmission on neuronal excitability depends on the Cl--gradient across membranes. However, the Cl--fluxes through GABAA receptors alter the intracellular Cl- concentration ([Cl-]i) and in turn attenuate GABAergic responses, a process termed ionic plasticity. Recently it has been shown that coincident glutamatergic inputs significantly affect ionic plasticity. Yet how the [Cl-]i changes depend on the properties of glutamatergic inputs and their spatiotemporal relation to GABAergic stimuli is unknown. To investigate this issue, we used compartmental biophysical models of Cl- dynamics simulating either a simple ball-and-stick topology or a reconstructed immature CA3 neuron. These computational experiments demonstrated that glutamatergic co-stimulation enhances GABA receptor-mediated Cl- influx at low and attenuates or reverses the Cl- efflux at high initial [Cl-]i. The size of glutamatergic influence on GABAergic Cl--fluxes depends on the conductance, decay kinetics, and localization of glutamatergic inputs. Surprisingly, the glutamatergic shift in GABAergic Cl--fluxes is invariant to latencies between GABAergic and glutamatergic inputs over a substantial interval. In agreement with experimental data, simulations in a reconstructed CA3 pyramidal neuron with physiological patterns of correlated activity revealed that coincident glutamatergic synaptic inputs contribute significantly to the activity-dependent [Cl-]i changes. Whereas the influence of spatial correlation between distributed glutamatergic and GABAergic inputs was negligible, their temporal correlation played a significant role. In summary, our results demonstrate that glutamatergic co-stimulation had a substantial impact on ionic plasticity of GABAergic responses, enhancing the destabilization of GABAergic inhibition in the mature nervous systems, but suppressing GABAergic [Cl-]i changes in the immature brain. Therefore, glutamatergic shift in GABAergic Cl--fluxes should be considered as a relevant factor of short term plasticity. Author SummaryInformation processing in the brain requires that excitation and inhibition are balanced. The main inhibitory neurotransmitter in the brain is gamma-amino-butyric acid (GABA). GABA actions depend on the Cl--gradient, but activation of ionotropic GABA receptors causes Cl--fluxes and thus reduces GABAergic inhibition. Here, we investigated how a coincident membrane depolarization by excitatory, glutamatergic synapses influences GABA-induced Cl--fluxes using a biophysical compartmental model of Cl- dynamics, simulating either simple or realistic neuron topologies. We demonstrate that glutamatergic co-stimulation directly affects GABA-induced Cl--fluxes, with the size of glutamatergic effects depending on the conductance, the decay kinetics, and localization of glutamatergic inputs. We also show that the glutamatergic shift in GABAergic Cl--fluxes is surprisingly stable over a substantial range of latencies between glutamatergic and GABAergic inputs. We conclude from these results that glutamatergic co-stimulation alters GABAergic Cl--fluxes and in turn affects the strength of GABAergic inhibition. These coincidence-dependent ionic changes should be considered as a relevant factor of short term plasticity in the CNS.

neuroscience↗