Biology subjects

Neef, A.

Publications and source records attributed to Neef, A..

9 recordsLinked to original sources

bioRxiv2026

Striatal and frontal signatures of social context and cost-benefit decision making in developmental stuttering

Developmental stuttering is usually framed as a sensorimotor disorder, yet it manifests in communicative situations that engage motivational, self-referential, and regulatory processes. In this case-control study, we combined a socio-economic decision task outside the scanner with a socially modulated speech task during functional MRI to test how listener presence and self-referential speech shape neural activity in 34 adults who stutter and 32 controls. Both groups valued talking with another person about themselves more than talking with another person about someone else or talking to themselves. On the neural level, listener-directed (vs. private) speech and self-disclosure (vs. guessing the preferences of a famous other) elicited stronger responses in the ventral striatum and medial prefrontal cortex, with no significant group differences in the central listener-directed versus private contrast. Within the stuttering group, individual differences revealed a systematic reweighting of socially modulated activation as a function of symptom burden: higher anticipation of stuttering and greater self-reported impact of stuttering on everyday life were associated with stronger engagement of motivational circuitry, greater recruitment of frontal evaluative-control regions, and reduced contextual differentiation within speech-language cortex. Stuttering anticipation and lived experience gradually shift the balance between control, language, and motivational salience-processing systems, contributing to the disorder's marked heterogeneity and context sensitivity. These findings indicate system-level signatures of the interaction between social context and symptom severity in developmental stuttering, extending accounts based on sensorimotor deficits.

neuroscience↗

bioRxiv2024

Single neuron diversity supports area functional specialization along the visual cortical pathways

Humans and other primates have specialized visual pathways composed of interconnected cortical areas. The input area V1 contains neurons that encode basic visual features, whereas downstream in the lateral prefrontal cortex (LPFC) neurons acquire tuning for novel complex feature associations. It has been assumed that each cortical area is composed of repeatable neuronal subtypes, and variations in synaptic strength and connectivity patterns underlie functional specialization. Here we test the hypothesis that diversity in the intrinsic make-up of single neurons contributes to area specialization along the visual pathways. We measured morphological and electrophysiological properties of single neurons in areas V1 and LPFC of marmosets. Excitatory neurons in LPFC were larger, less excitable, and fired broader spikes than V1 neurons. Some inhibitory fast spiking interneurons in the LPFC had longer axons and fired spikes with longer latencies and a more depolarized action potential trough than in V1. Intrinsic bursting was found in subpopulations of both excitatory and inhibitory LPFC but not V1 neurons. The latter may favour temporal summation of spikes and therefore enhanced synaptic plasticity in LPFC relative to V1. Our results show that specialization within the primate visual system permeates the most basic processing level, the single neuron.

neuroscience↗

bioRxiv2024

Spike frequency adaptation in primate lateral prefrontal cortex neurons results from interplay between intrinsic properties and circuit dynamics

Recordings of cortical neurons isolated from brain slices and dissociated from their networks, display intrinsic spike frequency adaptation (I-SFA) to a constant current input. Interestingly, extracellular recordings in behaving subjects also show extrinsic-SFA (E-SFA) in response to sustained visual stimulation. Because neurons are isolated from brain networks in slice recordings, it is challenging to infer how I-SFA contributes to E-SFA in interconnected brains during behavior. To investigate this, we recorded responses of macaque lateral prefrontal cortex neurons in vivo during a visually guided saccade task and in acute brain slices in vitro. Broad spiking (BS) putative pyramidal cells and narrow spiking (NS) putative inhibitory interneurons exhibited E-SFA in vivo. In acute brain slices, both cell types displayed I-SFA though their magnitudes differed. To investigate how in vitro I-SFA contributes to in vivo E-SFA, we developed a data-driven hybrid circuit model in which local NS neurons are driven by BS input. We observed that model NS cell responses show longer SFA than observed in vivo. Introducing inhibition of NS cells to the model circuit removed this discrepancy. Our results indicate that both I-SFA and inhibitory circuit dynamics contribute to E-SFA in LPFC neurons. They highlight the contribution of single neuron and network dependent computations to neural activity underlying behavior.

neuroscience↗

bioRxiv2024

Near-optimal information relay by the neuronal population of layer 4 barrel cortex

Sixty years after the concept of population coding in neuronal networks was introduced, we still lack a comprehensive understanding of its performance limits and the role of neuronal physiology. Here, we use dynamic gain analysis in a general model of population coding and demonstrate that disparate parameters of neurons and populations determine how accurately they can encode information. These are cell number, cell size, and the correlation time of the background noise. We experimentally test and confirm these predictions on neurons of excitatory populations in the mouse barrel cortex. Surprisingly, dendrite size and background correlations are precisely matched with the number of neurons in layer 4, such that even a single thalamocortical spike at the input is reliably reflected in the population output. However, this encoding performance can be modulated by the channels that mediate M-current, suggesting that coding in layer 4 may vary as a function of brain state.

neuroscience↗

bioRxiv2023

Revealing a hidden conducting state by manipulating the intracellular domains in KV10.1 exposes the coupling between two gating mechanisms.

The KCNH family of potassium channels serves relevant physiological functions in both excitable and non-excitable cells, reflected in the massive consequences of mutations or pharmacological manipulation of their function. This group of channels shares structural homology with other voltage-gated K+ channels, but the mechanisms of gating in this family show significant differences with respect to the canonical electromechanical coupling in these molecules. In particular, the large intracellular domains of KCNH channels play a crucial role in gating that is still only partly understood. Using KCNH1(KV10.1) as a model, we have characterized the behavior of a series of modified channels that could not be explained by the current models. With electrophysiological and biochemical methods combined with mathematical modeling, we show that the uncovering of an open state can explain the behavior of the mutants. This open state, which is not detectable in wild-type channels, appears to lack the rapid flicker block of the conventional open state. Because it is accessed from deep closed states, it elucidates intermediate gating events well ahead of channel opening in the wild type. This allowed us to study gating steps prior to opening, which, for example, explain the mechanism of gating inhibition by Ca2+-Calmodulin and generate a model that describes the characteristic features of KCNH channels gating.

biophysics↗

bioRxiv2022

Dynamic gain decomposition reveals functional effects of dendrites, ion channels and input statistics in ultrafast population encoding

Modern, high-density neuronal recordings reveal at ever higher precision how information is represented by neural populations. Still, we lack the tools to understand these processes bottom-up, emerging from the biophysical properties of neurons, synapses, and network structure. The concept of the dynamic gain function, a spectrally resolved approximation of a populations coding capability, has the potential to link cell-level properties to network-level performance. However, the concept is not only useful but also very complex because the dynamic gains shape is co-determined by axonal and somatodendritic parameters and the populations operating regime. Previously, this complexity precluded an understanding of any individual parameters impact. Here, we decomposed the dynamic gain function into three components corresponding to separate signal transformations. This allowed attribution of network-level encoding features to specific cell-level parameters. Applying the method to data from real neurons and biophysically plausible models, we found: 1. The encoding bandwidth of real neurons, approximately 400 Hz, is constrained by the voltage dependence of axonal currents during early action potential initiation. 2. State-of-the-art models only achieve encoding bandwidths around 100 Hz and are limited mainly by subthreshold processes instead. 3. Large dendrites and low-threshold potassium currents modulate the bandwidth by shaping the subthreshold stimulus-to-voltage transformation. Our decomposition provides physiological interpretations when the dynamic gain curve changes, for instance during spectrinopathies and neurodegeneration. By pinpointing shortcomings of current models, it also guides inference of neuron models best suited for large-scale network simulations. Significant StatementThe dynamic gain function quantifies how neurons can engage in collective, network-level activity, shape brain rhythms and information encoding. Its shape results from a complex interaction between properties of different molecules (ion channels) and cell compartments (morphology, resistance), and is so far only understood for the simplest neuron models. Here we provide an interpretable analysis, decomposing the dynamic gain based on the stimulus transformation steps in individual neurons. We apply the decomposition to data from real neurons and complex models, and attribute changes of the dynamic gain to specific sub- and suprathreshold processes. Using this decomposition method, we reveal the relevance of subthreshold potassium channels for ultrafast information encoding and expose the shortcomings of even the state-of-the-art neuron models.

neuroscience↗

bioRxiv2021

Ultrafast population coding and axo-somatic compartmentalization

Populations of cortical neurons respond to common input within a millisecond. Morphological features and active ion channel properties were suggested to contribute to this astonishing processing speed. Here we report an exhaustive study of ultrafast population coding for varying axon initial segment (AIS) location, soma size, and axonal current properties. In particular, we studied their impact on two experimentally observed features 1) precise action potential timing, manifested in a wide-bandwidth dynamic gain, and 2) high-frequency boost under slowly fluctuating correlated input. While the density of axonal channels and their distance from the soma had a very small impact on bandwidth, it could be moderately improved by increasing soma size. When the voltage sensitivity of axonal currents was increased we observed ultrafast coding and high-frequency boost. We conclude that these computationally relevant features are strongly dependent on axonal ion channels voltage sensitivity, but not their number or exact location. We point out that ion channel properties, unlike dendrite size, can undergo rapid physiological modification, suggesting that the temporal accuracy of neuronal population encoding could be dynamically regulated. Our results are in line with recent experimental findings in AIS pathologies and establish a framework to study structure-function relations in AIS molecular design.

neuroscience↗

bioRxiv2019

Background correlations selectively boost the gamma-sensitivity of cortical GABAergic neurons

Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background inputs statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons sensitivity to gamma- and ripple-frequencies. A novel time-resolved dynamic gain analysis revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism presumably contributes substantially to cross-frequency coupling and predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms.

neuroscience↗

bioRxiv2019

Macromolecular and electrical coupling between inner hair cells in the rodent cochlea

Inner hair cells (IHCs) are the primary receptors for hearing. They are housed in the cochlea and convey sound information to the brain via synapses with the auditory nerve. IHCs have been thought to be electrically and metabolically independent from each other. We report that, upon developmental maturation, 30% of the IHCs are electrochemically coupled in mini-syncytia. This coupling permits transfer of fluorescently-labeled metabolites and macromolecular tracers. The membrane capacitance, Ca2+-current, and resting current increase with the number of dye-coupled IHCs. Dual voltage-clamp experiments substantiate low resistance electrical coupling. Pharmacology and tracer permeability rule out coupling by gap junctions and purinoceptors. 3D-electron-microscopy indicates instead that IHCs are coupled by membrane fusion sites. Consequently, depolarization of one IHC triggers presynaptic Ca2+-influx at active zones in the entire mini-syncytium. Based on our findings and modeling, we propose that IHC-mini-syncytia enhance sensitivity and reliability of cochlear sound encoding.

neuroscience↗