Biology subjects

Graupner, M.

Publications and source records attributed to Graupner, M..

6 recordsLinked to original sources

bioRxiv2026

Directionally tuned signals in mouse visual and subicular cortex during passive rotation

Head-direction (HD) cells integrate visual and vestibular inputs and provide an internal compass which is essential for navigation, but how the directional activity in the subicular complex (SUB) and in the visual cortex (VIS) depends on the visual scene has not been compared directly. Here, we recorded simultaneously from the two regions with Neuropixels probes, while rotating head-fixed mice across all azimuthal directions, in controlled visual conditions, and in darkness. We found many directionally tuned units in both SUB and VIS. The preferred directions of SUB units were distributed uniformly and followed the rotation of a single prominent visual cue. The preferred directions of VIS units on the other hand were concentrated towards the visual cue. Heading was decoded with good accuracy from population activity from either region in cue rich visual conditions. In the presence of a single cue, decoding performance was higher in VIS. In darkness, the directional tuning was apparently lost at the single cell level, in both VIS and SUB. Importantly, even in darkness, the tuning-ordered structure of pairwise correlations was largely maintained in SUB, but not in VIS. This dissociation suggests that the SUB coherence reflects an internally organized attractor that can maintain its structure without vision or active movement, whereas VIS coherence largely reflects the external sensory structure. A wave-like distortion in decoded heading with respect to a visual cue suggests that a single salient landmark can shape the HD signal. Taken together, visual and head direction signals allow for an internal compass with continuity in the absence of landmarks, and recalibration as landmarks are reinstated.

neuroscience↗

bioRxiv2026

Sharp and Fast Dynamic Extraction and Tracking of Emitted Cellular Transients

Genetically encoded fluorescent sensors have expanded our ability to image cellular activity and transmitter release. Yet, sparse and low-salience events remain difficult to resolve against complex and fluctuating fluorescence backgrounds. Here we introduce DETECT, Dynamic Extraction and Tracking of Emitted Cellular Transients, which combines adaptive background suppression, probabilistic classification and multi-object tracking to extract fluorescence events while preserving their identity. Across synthetic datasets, DETECT improved detection and segmentation accuracy and reduced computational cost relative to established event-based methods. We validated DETECT across confocal, two-photon and miniscope imaging, ex vivo and in vivo, using calcium indicators and monoamine sensors. Beyond its technical performance, DETECT extends event-based analysis to low-salience fluorescence signals while resolving events spanning broad ranges of amplitude, morphology and dynamics. By resolving spontaneous dopamine and noradrenaline signals as distinct, trackable release events, DETECT reveals the spatiotemporal organization of neuromodulatory activity and provides a broadly applicable approach to quantitative fluorescence analysis.

neuroscience↗

bioRxiv2025

Interleaving asynchronous and synchronous activity in balanced cortical networks with short-term synaptic depression

Cortical populations are in a broadly asynchronous state that is sporadically interrupted by brief epochs of coordinated population activity. Cortical models are at a loss to explain this combination of states. At one extreme are network models where recurrent inhibition dynamically stabilizes an asynchronous low activity state. While these networks are widely used, they cannot produce the coherent population-wide activity that is reported in a variety of datasets. At the other extreme are models in which strong recurrent excitation that is quickly tamed by short term synaptic depression between excitatory neurons leads to short epochs of population- wide activity. However, in these networks, inhibition plays only a perfunctory role in network stability, which is at odds with many reports across cortex. In this study we analyze spontaneously active in vitro preparations of primary auditory cortex that show dynamics that are emblematic of this mixture of states. To capture this complex population activity we use firing rate-based networks as well as biologically realistic networks of spiking neuron models where large excitation is balanced by recurrent inhibition, yet we include short-term synaptic depression dynamics of the excitatory connections. These models give very rich nonlinear behavior that mimics the core features of the in vitro data, including the possibility of low frequency (2-12 Hz) rhythmic dynamics within population events. In these networks, synaptic depression enables activity fluctuations to induce a weakening of inhibitory recruitment, which in turn triggers population events. In sum, our study extends balanced network models to account for nonlinear, population-wide correlated activity, thereby providing a critical step in a mechanistic theory of realistic cortical activity.

neuroscience↗

bioRxiv2023

Cerebellar interneuron activity is triggered by reach endpoint during learning of a complex locomotor task

Locomotion in complex environments depends on the precise timing and active control of single paw movements in order to adapt steps to surface structure and coordinate paws. Such motor control crucially depends on the cerebellum, which is thought to support moment-to-moment prediction and correction of paw trajectories. Although cerebellar activity has been linked to limb kinematics on flat surfaces, it remains unknown how cerebellar cortical neurons encode paw movements when gait becomes irregular and the requirements for precise motor control vary dynamically. To address this question, we developed LocoReach: a new task which combines continuous and discrete aspects of motor control by requiring mice to walk on a runged treadmill, where each step involves reaching for the next rung. Over several days of learning, mice became increasingly proficient at LocoReach, so that they made fewer, longer strides with faster swings and fewer missteps. Through real-time optogenetic disruption of cerebellar processing, we shortened the swing of the perturbed paw highlighting the online contribution of lobule simplex to precise limb control the task. We next investigated the role of the cerebellar lobule simplex during LocoReach learning using electrophysiological recordings, with particular focus on molecular layer interneurons (MLIs) that shape the timing and gain of Purkinje cell (PC) output. When analyzing behaviorally-evoked responses in MLIs and PCs, we found sharp changes in activity around paw-specific transitions from swing to stance and vice versa. Cells in lobule simplex showed clear behavioral specificity: most neurons were tuned to swing-stance transitions of the ipsilateral paw, a large proportion encoded transitions of other or even multiple paws. Specifically MLIs exhibited larger amplitude firing-rate changes during longer strides acquired through learning, indicating increased engagement during higher-demand steps. These results show that cerebellar activity is tightly aligned to defined events in the step cycle, providing a mechanism through which cerebellar cortical circuits can contribute to the precise control of paw placement during adaptive locomotion.

neuroscience↗

bioRxiv2020

A calcium-based plasticity model predicts long-term potentiation and depression in the neocortex

Long-term potentiation (LTP) and long-term depression (LTD) of pyramidal cell connections are among the key mechanisms underlying learning and memory in the brain. Despite their important role, only a few of these connections have been characterized in terms of LTP/LTD dynamics, such as the one between layer 5 thick-tufted pyramidal cells (L5-TTPCs). Comparing the available evidence on different pyramidal connection types reveals a large variability of experimental outcomes, possibly indicating the presence of connection-type-specific mechanisms. Here, we show that a calcium-based plasticity rule regulating L5-TTPC synapses holds also for several other pyramidal-to-pyramidal connections in a digital model of neocortical tissue. In particular, we show that synaptic physiology, cell morphology and innervation patterns jointly determine LTP/LTD dynamics without requiring a different model or parameter set for each connection type. We therefore propose that a similar set of plasticity mechanisms is shared by seemingly very different neocortical connections and that only a small number of targeted experiments is required for generating a complete map of synaptic plasticity dynamics in the neocortex.

neuroscience↗

bioRxiv2019

Short-term depression and long-term plasticity together tune sensitive range of synaptic plasticity

Synaptic efficacy is subjected to activity-dependent changes on short- and long time scales. While short-term changes decay over minutes, long-term modifications last from hours up to a lifetime and are thought to constitute the basis of learning and memory. Both plasticity mechanisms have been studied extensively but how their interaction shapes synaptic dynamics is little known. To investigate how both short- and long-term plasticity together control the induction of synaptic depression and potentiation, we used numerical simulations and mathematical analysis of a calcium-based model, where pre- and postsynaptic activity induces calcium transients driving synaptic long-term plasticity. We found that the model implementing known synaptic short-term dynamics in the calcium transients can be successfully fitted to long-term plasticity data obtained in visual- and somatosensory cortex. Interestingly, the impact of spike-timing and firing rate changes on plasticity occurs in the prevalent firing rate range, which is different in both cortical areas considered here. Our findings suggest that short- and long-term plasticity are together tuned to adapt plasticity to area-specific activity statistics such as firing rates. Author summarySynaptic long-term plasticity, the long-lasting change in efficacy of connections between neurons, is believed to underlie learning and memory. Synapses furthermore change their efficacy reversibly in an activity-dependent manner on the subsecond time scale, referred to as short-term plasticity. It is not known how both synaptic plasticity mechanisms - long- and short-term - interact during activity epochs. To address this question, we used a biologically-inspired plasticity model in which calcium drives changes in synaptic efficacy. We applied the model to plasticity data from visual- and somatosensory cortex and found that synaptic changes occur in very different firing rate ranges, which correspond to the prevalent firing rates in both structures. Our results suggest that short- and long-term plasticity act in a well concerted fashion.

neuroscience↗