Biology subjects

Feyerabend, M.

Publications and source records attributed to Feyerabend, M..

3 recordsLinked to original sources

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

In Search of Transcriptomic Correlates of Neuronal Firing-Rate Adaptation across Subtypes, Regions and Species: A Patch-seq Analysis

Can the transcriptomic profile of a neuron predict its physiological properties? Using a Patch-seq dataset of the primary visual cortex, we addressed this question by focusing on spike rate adaptation (SRA), a well-known phenomenon that depends on small conductance calcium (Ca)-dependent potassium (SK) channels. We first show that in parvalbumin-expressing (PV) and somatostatin-expressing (SST) interneurons, expression levels of genes encoding the ion channels underlying action potential generation are correlated with the half-width (HW) of spikes. Surprisingly, the SK encoding genes are not correlated with the degree of SRA (dAdap). Instead, genes that encode proteins upstream from the SK current, as well as the low-voltage-activated Calcium channel, are correlated with dAdap. This general principle is supported by datasets from the mouse primary motor cortex and multiple macaque brain regions. Finally, we generate testable predictions by constructing a minimal model.

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↗