Biology subjects

Bast, A.

Publications and source records attributed to Bast, A..

6 recordsLinked to original sources

bioRxiv2024

FOXP2-immunoreactive, corticothalamic pyramidal cells in neocortical layers 6a and 6b are tightly regulated by neuromodulatory systems

The FOXP2/Foxp2 gene is involved in fine motor control in many vertebrate species; in humans, it is one of the candidate genes thought to play a prominent role in language production. Several studies suggest that in the neocortex, Foxp2 is exclusively expressed in a subset of corticothalamic (CT) pyramidal cells (PCs) in layer 6 (L6). However, the morphological and intrinsic electrophysiological, synaptic and neuromodulatory properties of Foxp2-expressing L6 PCs remain largely unknown. Here we systematically characterise these properties for FOXP2-positive (FOXP2+) PCs across L6 in the rat somatosensory cortex. We find that L6 FOXP2+ PCs are distinct in all of these properties from those of L6 FOXP2-negative (FOXP2-) neuronal cell types. We show that L6 FOXP2+ PCs project exclusively to thalamus. In upper L6 (L6a), FOXP2+ PCs innervate either the first-order thalamus or both first and higher-order thalamic nuclei. FOXP2+ PCs in deep L6 (L6b) project almost exclusively to higher-order thalamus. Synaptic connections established by L6a and L6b FOXP2+ PCs exhibit low synaptic release probability, whereas L6 corticocortical PCs have a high release probability. Both L6a and L6b FOXP2+ PCs respond strongly to acetylcholine (ACh), which in the absence of TTX results in firing of action potential (AP) trains. Notably, L6b but not L6a FOXP2- PCs are highly sensitive to ACh. In addition, L6b FOXP2+ PCs close to the white matter border show strong responses to dopamine that develop into prolonged AP firing. Our data suggest that FOXP2 is a marker for CT PCs in L6 that are strongly controlled by neurotransmitters such as ACh and dopamine. These findings are in line with a pivotal role for both L6a and L6b CT PCs as modulators of thalamic activity.

neuroscience↗

bioRxiv2023

Heterogeneity of synaptic connectivity in the fly visual system

Visual systems are homogeneous structures, where repeating columnar units are stereotypically arranged to retinotopically cover the visual field. Each of these columns contain many of the same neuron types that are distinguished by anatomic, genetic and - generally - by functional properties. However, there are exceptions to this rule. In the 800 visual columns of the Drosophila eye, there is an anatomically and genetically identifiable cell type with variable functional properties, Tm9. Since anatomical connectivity shapes functional neuronal properties, we identified the presynaptic inputs of several hundred Tm9s across both optic lobes using the FAFB connectome dataset and FlyWire analysis. Our work shows that Tm9 has three major, stereotypic, and many weaker, sparsely distributed inputs. This differs from the presynaptic connectivity of neurons with uniform properties, Tm1 and Tm2, which have only one major, and more stereotypic inputs than Tm9. Within the heterogeneous circuit architecture, we identified specific motifs, such as a set of wide-field neurons, which can be the source of the variable Tm9 physiology. Genetic synapse labeling combined with expansion microscopy showed that the heterogeneous wiring exists across individuals. Together, our data argue that the visual system uses heterogeneous, distributed circuit properties to achieve robust visual processing.

neuroscience↗

bioRxiv2023

Interpretable modelling of input-output computations in cortex

Neurons receive input from thousands of synapses, which they transform into action potentials (APs) via their complex dendrites. How the dendritic location of these inputs, their timing, strength, and presynaptic origin impact AP output remains generally unknown. Here we demonstrate how to reveal which properties of the input causally underlie AP output, and how this input-output computation is influenced by the morphology and biophysical properties of the dendrites. For this purpose, we derive analytically tractable, interpretable models of the input-output computation that layer 5 pyramidal tract neurons (L5PTs) - the major output cell type of the cerebral cortex - perform upon sensory stimulation. We find that this input-output computation is preserved across L5PTs despite morphological and biophysical diversity. We show that three features are sufficient to explain in vivo observed sensory responses and receptive fields of L5PTs with high accuracy: the count of active excitatory versus inhibitory synapses preceding the response, their spatial distribution on the dendrites, and the AP history. Based on this analytically tractable and interpretable description of the input-output computation, we show how to dissect the contributions of different input populations in thalamus and cortex to sensory responses of L5PTs. Thus, our approach provides a roadmap for revealing cellular input-output computations across different in vivo conditions. Author SummaryRevealing how synaptic inputs drive action potential output is one of the major challenges in neuroscience research. An increasing number of approaches therefore seek to combine detailed measurements at synaptic, cellular and network scales into biologically realistic brain models. Indeed, such models have started to make empirically testable predictions about the inputs that underlie in vivo observed activity patterns. However, the enormous complexity of these models generally prevents the derivation of interpretable descriptions that explain how neurons transform synaptic input into action potential output, and how these input-output computations depend on synaptic, cellular and network properties. Here we introduce an approach to reveal input-output computations that neurons in the cerebral cortex perform upon sensory stimulation. We reduce a realistic multi-scale cortex model to the minimal description that accounts for in vivo observed responses. Thereby, we identify the input-output computation that these cortical neurons perform under this in vivo condition, and we show that this computation is preserved across neurons despite morphological and biophysical diversity. Our approach provides analytically tractable and interpretable descriptions of neuronal input-output computations during specific in vivo conditions.

neuroscience↗

bioRxiv2021

Ion channel distributions in cortical neurons are optimized for energy-efficient active dendritic computations

The mammalian brain has an enormous demand for energy, which is thought to impose strong selective pressure by which the neurons evolve in ways that ensure robust function at minimal energy cost. However, which principles drive the ion channel distributions in the dendrites to implement different neuronal functions is yet unclear. Here we found that an energy-efficient generation of dendritic calcium action potentials in cortical pyramidal neurons requires a low expression of slow inactivating potassium channels. We demonstrate that this relationship between energy cost and neuronal function is independent of the dendritic morphology and the expression patterns of other ion channels that implement additional perisomatic and dendritic functions. Moreover, we found that calcium action potentials can arise from a wide spectrum of ion channel expression patterns, including configurations with high potassium channel densities in the dendrites. These configurations can account equally well for the characteristic intrinsic physiology of the pyramidal neurons. However, only configurations with low potassium channel densities in the distal dendrites are observed empirically. Thus, our findings indicate that cortical neurons do not utilize all theoretically possible ways to implement their functions, but instead select those optimized for energy-efficient active dendritic computations.

neuroscience↗

bioRxiv2021

Thalamus gates active dendritic computations in cortex during sensory processing

Perception is linked to a calcium-dependent dendritic spiking mechanism that enables the major output cells of the cerebral cortex - layer 5 pyramidal tract neurons - to combine inputs from different information streams. Which circuits activate this mechanism upon sensory input is unclear. Here we found that thalamocortical axons, which provide sensory input to cortex, target specifically the dendritic domains in pyramidal tract neurons that initiate calcium spikes. Sensory input thereby enables distal dendritic inputs preceding the stimulus to transform the first responses that leave cortex into bursts of action potentials. Thus, thalamus can drive active dendritic coupling of sensory with prestimulus information streams to modulate cortical output. Our findings indicate that thalamocortical coupling is first in a cascade of mechanisms that transform sensory input into perception.

neuroscience↗

bioRxiv2019

Thalamus drives two complementary input strata of the neocortex in parallel

Sensory information enters the neocortex via thalamocortical axons that define the major input layer 4. The same thalamocortical axons, however, additionally innervate the deep output layers 5/6. How such bistratification impacts cortical processing remains unknown. Here, we find a class of neurons that cluster specifically around thalamocortical axons at the layer 5/6 border. We show that these border stratum cells are characterized by extensive horizontal axons, that they receive strong convergent input from the thalamus, and that this input is sufficient to drive reliable sensory-evoked responses, which precede those in layer 4. These cells are hence strategically placed to amplify and relay thalamocortical inputs across the cortical area, for example to drive the fast onsets of cortical output patterns. Layer 4 is therefore not the sole starting point of cortical processing. Instead, parallel activation of layer 4 and the border stratum is necessary to broadcast information out of the neocortex.

neuroscience↗