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Sejnowski, T. J.

Publications and source records attributed to Sejnowski, T. J..

5 recordsLinked to original sources

A conserved principle of glial organization in the paleocortex and neocortex

The organizational principles of glia remain largely unknown despite their vital role in nervous system function. Previous work has shown that the number of glia per unit volume of neocortex is constant across mammalian species. We hypothesize that the conservation of glia volume density within brain regions might be a governing principle of organization across species. To test this hypothesis, we used stereology, light microscopy, and data available in the literature to examine five brain regions: the cerebral cortex and four brain regions that differ from the cerebral cortex and each other - the anterior piriform cortex, the posterior piriform cortex, the entorhinal cortex, and the cerebellum. We discovered two orderly relationships: First, glia volume density within a brain region was constant across species, including humans, although it significantly differed between regions, suggesting that glia density might constitute a region-specific marker. Second, the ratio of glia to neuron increased with brain volume according to a [1/4] power law in the primate frontal cortex and the neocortex, the mammalian paleocortex, and the cerebellum. These relationships show that the development of glia and neurons are coupled, and suggest that what a neural circuit computes depends as much on its glial components as on its neurons. Main PointsO_LIThe volume density of glia (i.e., number of glia per unit volume) within a brain region is con-served across mammalian species including humans. C_LIO_LIThe ratio of glia to neuron increases with bigger brains. C_LIO_LIThe volume density of glia is significantly different across functionally and architecturally dif-ferent brain regions and could function as a region-specific marker. C_LIO_LIGlia obey scaling constraints that are different from scaling constraints for neurons. C_LI

neuroscience

Geometric principles of second messenger dynamics in dendritic spines.

Dendritic spines are small, bulbous protrusions along dendrites in neurons and play a critical role in synaptic transmission. Dendritic spines come in a variety of shapes that depend on their developmental state. Additionally, roughly 14-19% of mature spines have a specialized endoplasmic reticulum called the spine apparatus. How does the shape of a postsynaptic spine and its internal organization affect the spatio-temporal dynamics of short timescale signaling? Answers to this question are central to our understanding the initiation of synaptic transmission, learning, and memory formation. In this work, we investigated the effect of spine and spine apparatus size and shape on the spatio-temporal dynamics of second messengers using mathematical modeling using reaction-diffusion equations in idealized geometries (ellipsoids, spheres, and mushroom-shaped). Our analyses and simulations showed that in the short timescale, spine size and shape coupled with the spine apparatus geometries govern the spatiotemporal dynamics of second messengers. We show that the curvature of the geometries gives rise to pseudo-harmonic functions, which predict the locations of maximum and minimum concentrations along the spine head. Furthermore, we showed that the lifetime of the concentration gradient can be fine-tuned by localization of fluxes on the spine head and varying the relative curvatures and distances between the spine apparatus and the spine head. Thus, we have identified several key geometric determinants of how the spine head and spine apparatus may regulate the short timescale chemical dynamics of small molecules that control synaptic plasticity.

biophysics

Thalamocortical and Intracortical Laminar Connectivity Determines Sleep Spindle Properties

Spindle oscillations are brief oscillatory activity during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the properties of the core vs. matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, projecting to the middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. Our model demonstrates that this property is sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Futhermore, consistent with human recordings, in the model, spindles occurred independently in the core system but matrix system spindles commonly co-occurred with core one. We found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of the intra and inter cortical connectivity can potentially be a mechanism for increasing in spindle density as observed during learning.\n\nAuthor summaryThe density of sleep spindles has been shown to correlate with memory consolidation. Further, sleep spindles occur more often in human MEG than EEG. We developed thalamocortical network model that is capable of spontaneous generation of spindles across cortical layers and that captures the essential statistical features of spindles observed in experiments. We predict that differences in thalamo-cortical connectivity, known from anatomical studies, lead to the differences in the spindle properties between EEG and MEG as observed in human recordings. Further, we predict that the intracortical connectivity between cortical layers, a property influenced by sleep preceding learning, increases spindle density. Results from our study highlight the role of cortical and thalamic projections on the occurrence and properties of spindles.

neuroscience

Pre-post synaptic alignment through neuroligin tunes synaptic transmission efficiency

The nanoscale organization of neurotransmitter receptors relative to pre-synaptic release sites is a fundamental determinant of both the amplitude and reliability of synaptic transmission. How modifications in the alignment between pre- and post-synaptic machineries affect synaptic current properties has only been addressed with computer modeling, and therefore remains hypothetical. Using dual-color single molecule based super-resolution microscopy, we found a strong spatial correlation between AMPA receptor (AMPAR) nanodomains and the post-synaptic adhesion protein neuroligin-1 (NLG1). Expression of a C-terminal truncated form of NLG1 disrupted this correlation without affecting the intrinsic organization of AMPAR nanodomains. Moreover, this NLG1 dominant-negative mutant significantly shifted the pre-synaptic release machinery from AMPAR synaptic clusters. Electrophysiology and computer modeling show that this physical shift is sufficient to induce a significant decrease in synaptic transmission. Thus, our results suggest the necessity for synapses to release glutamate in front of AMPAR nanodomains, to maintain a high efficiency of synaptic responses.

neuroscience

Multidimensional imbalances in cortical circuit activity in Fragile-X Syndrome mice

A leading theory for multiple brain disorders, such as schizophrenia and autism, is that they arise from developmental imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this simple 1-dimensional model is sufficiently rich to capture the set of key alterations of neural circuit processing in brain disorders. Here we used a combination of computational modeling and large-scale analysis of in vivo 2-photon Ca2+ imaging data from somatosensory cortex of wild-type and Fmr1 knock-out (KO) mice, a model of Fragile X syndrome, to test the E/I imbalance model. Our main findings were: 1) the E/I imbalance model was not rich enough to capture the alterations in neural activity statistics in Fmr1 KO mice; 2) in a computational model we found greatly varying magnitudes and directions of effects of synaptic and cellular properties on network activity; 3) evidence for opposite changes in circuit properties of Fmr1 KO mice at different stages of development; 4) a reduction in the entropy of circuit activity in young Fmr1 KO mice compared to wild-type, but an opposite increase in adult Fmr1 KO mice. These findings suggest qualitatively new strategies for developing treatments for Fragile-X Syndrome and related disorders.

neuroscience