Biology subjects

Loeffler, H.

Publications and source records attributed to Loeffler, H..

7 recordsLinked to original sources

bioRxiv2026

Measuring neuronal input-output operations in vivo with random access projection microscopy

Neurons transform thousands of synaptic inputs into spiking output, and understanding this transformation requires measuring many submicron synapses at millisecond timescales in vivo. Here we present SLAP2, a two-photon random access projection microscope with no per-target access time cost, yielding over 5-fold faster imaging than existing methods, and performant real-time hardware motion correction. Flexible scanning modes enable measurement of hundreds of synapses at ~200 Hz, >800 synapses volumetrically at 50-100 Hz, and compartment-resolved dendritic voltage at 2-10 kHz in behaving mice. Simultaneous dendritic glutamate and somatic calcium imaging in visual cortex pyramidal neurons revealed nonlinear input-output amplification of stimulus onset and preferred stimulus orientation responses. Amplified features are associated with spatially organized inputs and stronger trial-to-trial coupling between synaptic activity and somatic output. These measurements establish SLAP2 as a powerful tool for recording intricate patterns of subcellular fluorescence dynamics in behaving animals.

neuroscience↗

bioRxiv2026

Psilocybin collapses visual change detection and drives cortical dynamics toward a state of surprise

Psilocybin profoundly alters visual perception, yet the neuronal mechanisms underlying these effects remain unclear. Here we combined large-scale Neuropixels recordings with cell-type specific optogenetics in head-fixed mice performing a visual change-detection task. Psilocybin severely impaired task performance without overt motor deficits. In cortex, the drug modestly suppressed activity of layer 5 neurons while preserving representations of image identity. By contrast, psilocybin imposed a 4-Hz oscillation on visually evoked activity that preferentially affected neurons encoding image change rather than image identity. Under psilocybin, expected image repetitions aberrantly recruited change-encoding ensembles and shifted cortical population dynamics towards trajectories normally evoked by genuine stimulus changes. These effects were strongest in somatostatin-expressing (SST) interneurons in visual cortex. The strength of this modulation depended on image structure and was greatest for images with clear, continuous contours, which preferentially recruited change-encoding ensembles. These findings demonstrate that psilocybin drives internally generated cortical surprise signals, providing a circuit mechanism for altered perception in the acute psychedelic state.

neuroscience↗

bioRxiv2024

Large-scale infra-slow dynamics of extracellular potentials linked to synchronous states revealed by graphene neural probes

Infra-slow (<0.5 Hz) brain dynamics reflect homeostatic and neuromodulatory processes that modulate neuronal excitability and shape faster oscillations across brain regions. Infra-slow brain activity is typically inferred from magnetic or optical imaging, but these methods are limited in temporal resolution and compatibility with unconstrained behavior. Infra-slow local field potentials (isLFPs) could provide a direct measure of infra-slow network dynamics, but have remained poorly characterized due to the absence of scalable, DC-coupled recording methods. Here, we introduce DC-coupled electrophysiological imaging based on arrays of up to 512 multiplexed graphene transistors enabling stable, high-density recordings across cortical regions and cortical layers in freely moving rats. We developed an analytical framework for the analysis of wide-band LFP, revealing that synchronous oscillatory states of variable duration and spatial scale are consistently linked to topographically and translaminarly structured DC potential shifts. We propose a physiological model linking these DC shifts to sustained gradients of extracellular K+ concentration, providing a mechanistic connection between neuronal synchrony and isLFP dynamics. By integrating DC-coupled sensing, multiplexed scalability, and depth-surface co-registration, this work establishes a new modality for imaging-like electrophysiology in freely moving animals and a framework for interpreting infra-slow dynamics.

neuroscience↗

bioRxiv2024

Stimulus history, not expectation, drives sensory prediction errors in mammalian cortex

Hierarchical predictive coding (HPC) models have recently flourished in neuroscience1-9. Feedforward and feedback processing are at the heart of HPC models. Previous experimental studies using fMRI, EEG/MEG, and LFP9-11 do not reliably resolve feedback modulation from local computations and feedforward outputs. Here, using open-science8, multi-species, multi-area, high-density12, laminar neurophysiology13, we empirically test whether hierarchical predictive coding is a key component shaping cortical processing of visual stimuli. To isolate visual information processing and eliminate motor/reward confounders9-11, we use a no-report task. Our task leveraged so-called global oddballs (GO) as unpredictable, deviant stimuli that circumvent low-level adaptation. We examined their responses relative to local oddballs (LO) that we habituated into highly predictable priors. Four surprising findings in this dataset challenge many existing hierarchical predictive coding models. First, GO responses were exclusive to higher-order, more cognitive areas rather than early-to-mid visual cortex. Second, inhibitory interneuron-targeted optogenetics in primates and mice and waveform shape analysis in primates revealed no evidence that predictive suppression was implemented via these interneurons. Third, highly predictable LO responses dominated in over 50% of all neurons, including in higher-order cortex, which should have anticipated them, indicating limited evidence for predictive suppression. Lastly, prediction error responses evoked by GOs did not evoke feedforward processing. These results reveal circuit dynamics that govern how prediction shapes visual processing, motivating more neurally constrained predictive processing models.

neuroscience↗

bioRxiv2024

Electrophysiological signatures of a developmental delay in a stem cell model of KCNQ2 developmental and epileptic encephalopathy

BackgroundKCNQ2, encoding KV7.2 ion channels, has emerged as one of the prominent genes causing early onset seizures with developmental delay (KCNQ2 developmental and epileptic encephalopathy; KCNQ2-DEE). KCNQ2 de novo loss-of-function (LOF) and associated neuronal hyperexcitability have been accepted as mechanisms contributing to seizures. To investigate the developmental impact of KCNQ2 LOF, we generated patient iPSC-derived models for two previously reported de novo variants, p.(Arg325Gly) and p.(Gly315Arg), linked to severe congenital DEE. MethodsFunctional investigation of the two variants was initially performed in Xenopus laevis oocyte system. Patient-derived iPSC lines were differentiated using NGN2- and embryoid body-based protocols yielding neurons roughly corresponding to mid- and mid-late gestational stages, respectively. KV7- mediated M-current, passive neuronal properties, action potential generation and spontaneous oscillatory network activities were analysed with whole-cell patch clamping. FindingsStudied KCNQ2 variants showed LOF with a dominant-negative effect in the heterologous system. Reduced M-currents in patient iPSC-derived neurons corroborated a LOF as the main pathomechanism. Interestingly, this led to the reduced neuronal firing of the early neurons and to a disruption of complex oscillatory activity, with significantly reduced duration and amplitude of these events in patient iPSC-derived neurons. InterpretationWe provide experimental evidence for changing roles of the M-current throughout development and place disease variant-mediated M-current reduction in the context of the neuronal maturation in the prenatal brain. Based on the reduced neuronal firing and disrupted oscillatory activity seen in patient iPSC-derived neurons, we propose that a delayed/impaired maturation of neuronal and network properties underlies KCNQ-DEE caused by LOF variants.

neuroscience↗

bioRxiv2023

SHIELD: Skull-shaped hemispheric implants enabling large-scale-electrophysiology datasets in the mouse brain

To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. While new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe a novel 3D-printed cranial-replacement implant (SHIELD) enabling electrophysiological recordings from distributed areas of the mouse brain. This skull-shaped implant is designed with customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedures high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase the scientific utility of the SHIELD implant, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful large-scale electrophysiological measurements for the study of distributed brain computation.

neuroscience↗

bioRxiv2020

Spatially organized genomic and physiological heterogeneity of the olfactory bulb mitral cell layer

Sensory inputs to the dorsal vs ventral olfactory bulb derive from distinct receptor families, and drive distinct behaviors. To address whether second-order OB neurons and circuits exhibit matching heterogeneity for input-specific readout, we clustered spatial expression profiles of >2,000 genes from the mitral cell layer (MCL). We observed clear dorsal and ventral clusters, together with dorsoventral differences in mitral cell physiology. Bulbar circuits may therefore be tuned for zone-specific computation.

neuroscience↗