Experience-dependent plasticity in early stations of sensory processing in mature brains: effects of environmental enrichment on dendrite measures in trigeminal nuclei

Nervous systems respond with structural changes to environmental changes even in adulthood. In recent years, experience-dependent structural plasticity was shown not to be restricted to the cerebral cortex, as it also occurs at subcortical and even peripheral levels. We have previously shown that two populations of trigeminal nuclei neurons, trigeminothalamic barrelette neurons of the principal nucleus (Pr5), and intersubnuclear neurons in the caudal division of the spinal trigeminal nucleus (Sp5C) that project to Pr5 underwent morphometric and topological changes in their dendritic trees after a prolonged total or partial loss of afferent input from the vibrissae. Here we examined whether and what structural alterations could be elicited in the dendritic trees of the same cell populations in young adult rats after being exposed for 2 months to an enriched environment (EE), and how these changes evolved when animals were returned to standard housing for an additional 2 months. Neurons were retrogradely labeled with BDA delivered to, respectively, the ventral posteromedial thalamic nucleus or Pr5. Fully labeled cells were digitally reconstructed with Neurolucida and analyzed with NeuroExplorer. EE gave rise to increases in dendritic length, number of trees and branching nodes, spatial expansion of the trees, and dendritic spines, which were less pronounced in Sp5C than in Pr5 and differed between sides. In Pr5, these parameters returned, but only partially, to control values after EE withdrawal. These results underscore a ubiquity of experience-dependent changes that should not be overlooked when interpreting neuroplasticity and developing plasticity-based therapeutic strategies.

Diverse processing underlying frequency integration in midbrain neurons of barn owls

Emergent response properties of sensory neurons depend on circuit connectivity and somatodendritic processing. Neurons of the barn owl’s external nucleus of the inferior colliculus (ICx) display emergence of spatial selectivity. These neurons use interaural time difference (ITD) as a cue for the horizontal direction of sound sources. ITD is detected by upstream brainstem neurons with narrow frequency tuning, resulting in spatially ambiguous responses. This spatial ambiguity is resolved by ICx neurons integrating inputs over frequency, a relevant processing in sound localization across species. Previous models have predicted that ICx neurons function as point neurons that linearly integrate inputs across frequency. However, the complex dendritic trees and spines of ICx neurons raises the question of whether this prediction is accurate. Data from in vivo intracellular recordings of ICx neurons were used to address this question. Results revealed diverse frequency integration properties, where some ICx neurons showed responses consistent with the point neuron hypothesis and others with nonlinear dendritic integration. Modeling showed that varied connectivity patterns and forms of dendritic processing may underlie observed ICx neurons’ frequency integration processing. These results corroborate the ability of neurons with complex dendritic trees to implement diverse linear and nonlinear integration of synaptic inputs, of relevance for adaptive coding and learning, and supporting a fundamental mechanism in sound localization.

Any neuron can perform linearly non-separable computations

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturating dendrites. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with dendrites has more computational capacity than without. Because any neuron has one or more layer, and all dendrites do saturate, we show that any dendrited neuron can implement linearly non-separable computations.

Common micro- and macroscale principles of connectivity in the human brain

The brain requires efficient information transfer between neurons and between large-scale brain regions. Brain connectivity follows predictable organizational principles: at the cellular level, larger supragranular pyramidal neurons have larger dendritic trees, more synapses, more complex branching and perform more complex neuronal computations; at the macro-scale, region-to-region connections are suggested to display a diverse architecture with highly connected hub-areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as known for the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across ten cortical areas in five human donor brains (1M/4F). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct ‘white matter trees’ of cortico-cortical wiring. Examining the complexity of the resulting white matter trees using the same measures as for dendritic trees shows multimodal association areas to have larger, more complexly branched white matter trees than primary areas (all p<0.0001) and regional macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r=0.677, p=0.032), branch points (r=0.790, p=0.006), total tree length (r=0.664, p=0.036) and branching complexity (r=0.724, p=0.018). Our findings support the integrative theory that brain connectivity is structured following similar ‘principles of connectivity’ at the neuronal and macroscale level, and provide a framework to study connectivity changes in brain conditions at multiple levels of brain organization.

Neuron tracing and quantitative analyses of dendritic architecture reveal symmetrical three-way-junctions and phenotypes of git-1 in C. elegans

Complex dendritic trees are a distinctive feature of neurons. Alterations to dendritic morphology are associated with developmental, behavioral and neurodegenerative changes. The highly-arborized PVD neuron of C. elegans serves as a model to study dendritic patterning; however, quantitative, objective and automated analyses of PVD morphology are missing. Here, we present a method for neuronal feature extraction, based on deep-learning and fitting algorithms. The extracted neuronal architecture is represented by a database of structural elements for abstracted analysis. We obtain excellent automatic tracing of PVD trees and uncover that dendritic junctions are unevenly distributed. Surprisingly, these junctions are three-way-symmetrical on average, while dendritic processes are arranged orthogonally. We quantify the effect of mutation in git-1, a regulator of dendritic spine formation, on PVD morphology and discover a localized reduction in junctions. Our findings shed new light on PVD architecture, demonstrating the effectiveness of our objective analyses of dendritic morphology and suggest molecular control mechanisms.

Any neuron can perform linearly non-separable computations

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturating dendrites. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with dendrites has more computational capacity than without. Because any neuron has one or more layer, and all dendrites do saturate, we show that any dendrited neuron can implement linearly non-separable computations.

The CATP-8/P5A-type ATPase functions in multiple pathways during neuronal patterning

The assembly of neuronal circuits involves the migrations of neurons from their place of birth to their final location in the nervous system, as well as the coordinated growth and patterning of axons and dendrites. In screens for genes required for patterning of the nervous system, we identified the catp-8/P5A-ATPase as an important regulator of neural patterning. P5A-ATPases are part of the P-type ATPases, a family of proteins known to serve a conserved function as transporters of ions, lipids and polyamines in unicellular eukaryotes, plants, and humans. While the function of many P-type ATPases is relatively well understood, the function of P5A-ATPases in metazoans remained elusive. We show here, that the Caenorhabditis elegans ortholog catp-8/P5A-ATPase is required for defined aspects of nervous system development. Specifically, the catp-8/P5A-ATPase serves functions in shaping the elaborately sculpted dendritic trees of somatosensory PVD neurons. Moreover, catp-8/P5A-ATPase is required for axonal guidance and repulsion at the midline, as well as embryonic and postembryonic neuronal migrations. Interestingly, not all axons at the midline require catp-8/P5A-ATPase, although the axons run in the same fascicles and navigate the same space. Similarly, not all neuronal migrations require catp-8/P5A-ATPase. A CATP-8/P5A-ATPase reporter is localized to the ER in most, if not all, tissues and catp-8/P5A-ATPase can function both cell-autonomously and non-autonomously to regulate neuronal development. Genetic analyses establish that catp-8/P5A-ATPase can function in multiple pathways, including the Menorin pathway, previously shown to control dendritic patterning in PVD, and Wnt signaling, which functions to control neuronal migrations. Lastly, we show that catp-8/P5A-ATPase is required for localizing select transmembrane proteins necessary for dendrite morphogenesis. Collectively, our studies suggest that catp-8/P5A-ATPase serves diverse, yet specific, roles in different genetic pathways and may be involved in the regulation or localization of transmembrane and secreted proteins to specific subcellular compartments.

Experience-Dependent Plasticity in Early Stations of Sensory Processing in Mature Brains: Effects of Environmental Enrichment On Dendrite Measures in Trigeminal Nuclei

Nervous systems respond with structural changes to environmental changes even in adulthood. In recent years it has been shown that experience-dependent structural plasticity is not restricted to the cerebral cortex, but also occurs at subcortical and even peripheral levels. We have previously shown that two populations of trigeminal nuclei neurons, trigeminothalamic barrelette neurons of the principal nucleus (Pr5), and intersubnuclear neurons in the caudal division of the spinal trigeminal nucleus (Sp5C) that project to Pr5 underwent morphometric and topological changes in their dendritic trees after a prolonged total or partial loss of afferent input from the vibrissae. Here we examined whether and what structural alterations could be elicited in the dendritic trees of the same cell populations in young adult rats after being exposed for two months to an enriched environment (EE), and how these changes evolved when animals were returned to standard housing for an additional two months. Neurons were retrogradely labeled with dextran amine delivered to, respectively, the ventral posteromedial thalamic nucleus or Pr5. Fully labeled cells were digitally reconstructed with Neurolucida and analyzed with NeuroExplorer. EE gave rise to increases in dendritic length, number of trees and branching nodes, spatial expansion of the trees, and dendritic spines, which were less pronounced in Sp5C than in Pr5 and differed between sides. In Pr5 these parameters returned, but only partially, to control values after EE withdrawal. These results underscore a ubiquity of experience-dependent changes that should not be overlooked when interpreting neuroplasticity and developing plasticity-based therapeutic strategies.

Expansion of cortical layers 2 and 3 in human left temporal cortex associates with verbal intelligence

The expansion of supragranular cortical layers is thought to have enabled evolutionary development of human cognition and language. However, whether increased volume of supragranular cortical layers can actually support greater cognitive and language abilities in humans has not been demonstrated. Here, we find that subjects with higher general and verbal intelligence test (VIQ) scores have selectively expanded layers 2 and 3 only in the left temporal cortex, an area associated with language and IQ-test performance. This expansion is accompanied by lower neuron densities and larger cell-body size. Furthermore, individuals with higher VIQ scores had neurons with larger dendritic trees in left temporal cortex, potentially impacting their function. Indeed, neurons of subjects with higher VIQ scores had faster action potential upstroke kinetics, which improves information processing. These data show that expansion of supragranular layer volume, cortical and cellular micro-architecture and function are associated with improved verbal mental ability in human subjects.