Biology subjects

DiGregorio, D.

Publications and source records attributed to DiGregorio, D..

5 recordsLinked to original sources

bioRxiv2024

A dendritic substrate for temporal diversity of cortical inhibition

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

neuroscience↗

bioRxiv2023

Demonstration that sublinear dendrites enable linearly non-separable computations

Theory predicts that nonlinear summation of synaptic potentials within dendrites allows neurons to perform linearly non-separable computations (LNSCs). Using Boolean analysis approaches, we predicted that both supralinear and sublinear synaptic summation could allow single neurons to implement a type of LNSC, the feature binding problem (FBP), which does not require inhibition contrary to the XOR. Notably, sublinear dendritic operations enable LNSCs when scattered synaptic activation generates increased somatic spike output. However, experimental demonstrations of scatter-sensitive neuronal computations have not yet been described. Using glutamate uncaging onto cerebellar molecular layer interneurons, we show that scattered synaptic-like activation of dendrites evoked larger compound EPSPs than clustered synaptic activation, generating a higher output spiking probability. Moreover, we also demonstrate that single interneurons can indeed implement the FBP. We use a biophysical model to predict under what conditions a neuron can implement the FBP and what leads to failures. Experimental results agree with the model-determined conditions and hence validate our protocol as a solid benchmark for a neuron to implement linearly non-separable computations. Since sublinear synaptic summation is a property of passive dendrites we expect that many different neuron types can implement LNSCs.

neuroscience↗

bioRxiv2022

Synaptic basis of a sub-second representation of time

Temporal sequences of neural activity are essential for driving well-timed behaviors, but the underlying cellular and circuit mechanisms remain elusive. We leveraged the well-defined architecture of the cerebellum, a brain region known to support temporally precise actions, to explore theoretically whether the experimentally observed diversity of short-term synaptic plasticity (STP) at the input layer could generate neural dynamics sufficient for subsecond temporal learning. Simulated synaptic input generated a diverse set of transient, firing patterns in granule cells (GCs) that provided a temporal basis set for learning precisely timed pauses of Purkinje cell activity associated with delayed eyelid conditioning and Bayesian interval estimation. The learning performance across time intervals was influenced by the temporal bandwidth of the GC basis, which was determined by the input layer synaptic properties. The ubiquity of STP throughout the brain positions it as a general, tunable cellular mechanism for sculpting neural dynamics and fine-tuning behavior.

neuroscience↗

bioRxiv2021

Developmental emergence of two-stage nonlinear synaptic integration in cerebellar interneurons

Synaptic transmission, connectivity, and dendritic morphology mature in parallel during brain development and are often disrupted in neurodevelopmental disorders. Yet how these changes influence the neuronal computations necessary for normal brain function are not well understood. To identify cellular mechanisms underlying the maturation of synaptic integration in interneurons, we combined patch-clamp recordings of excitatory inputs in cerebellar stellate cells (SCs), 3D-reconstruction of SC morphology with excitatory synapse location, and biophysical modeling. We found that, during development, synaptic strength was homogeneously reduced along the somato-dendritic axis, but that dendritic integration was always sublinear. However, dendritic branching increased without changes in synapse density, leading to a substantial gain in distal inputs. Thus, changes in synapse distribution, rather than dendrite cable properties, are the dominant mechanism underlying the maturation of neuronal computation. These mechanisms favor the emergence of a spatially compartmentalized two-stage integration model promoting location-dependent integration within dendritic subunits.

neuroscience↗

bioRxiv2018

Distinct nanoscale calcium channel and synaptic vesicle topographies contribute to the diversity of synaptic function

The nanoscale topographical arrangement of voltage-gated calcium channels (VGCC) and synaptic vesicles (SVs) determines synaptic strength and plasticity, but whether distinct spatial distributions underpin diversity of synaptic function is unknown. We performed single bouton Ca2+ imaging, Ca2+ chelator competition, immunogold electron microscopic (EM) localization of VGCCs and the active zone (AZ) protein Munc13-1, at two cerebellar synapses. Unexpectedly, we found that weak synapses exhibited 3-fold more VGCCs than strong synapses, while the coupling distance was 5-fold longer. Reaction-diffusion modelling could explain both functional and structural data with two strikingly different nanotopographical motifs: strong synapses are composed of SVs that are tightly coupled ([~]10 nm) to VGCC clusters, whereas at weak synapses VGCCs were excluded from the vicinity ([~]50 nm) of docked vesicles. The distinct VGCC-SV topographical motifs also confer differential sensitivity to neuromodulation. Thus VGCC-SV arrangements are not canonical across CNS synapses and their diversity could underlie functional heterogeneity.

neuroscience↗