Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions.
Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.
Smooth pursuit adaptation (SPA) is an example of cerebellum-dependent motor learning that depends on the integrity of the oculomotor vermis (OMV). In an attempt to unveil the neuronal basis of the role of the OMV in SPA, we recorded Purkinje cell simple spikes (PC SS) of trained monkeys. Individual PC SS exhibited specific changes of their discharge patterns during the course of SPA. However, these individual changes did not provide a reliable explanation of the behavioral changes. On the other hand, the population response of PC SS perfectly reflected the changes resulting from adaptation. Population vector was calculated using all cells recorded independent of their location. A population code conveying the behavioral changes is in full accordance with the anatomical convergence of PC axons on target neurons in the cerebellar nuclei. Its computational advantage is the ease with which it can be adjusted to the needs of the behavior by changing the contribution of individual PC SS based on error feedback.
The PACSIN (protein kinase C and casein kinase 2 substrate in neurons) adapter proteins couple components of the clathrin-mediated endocytosis machinery with regulators of actin polymerization and thereby regulate the surface expression of specific receptors. The brain-specific PACSIN 1 is enriched at synapses and has been proposed to affect neuromorphogenesis and the formation and maturation of dendritic spines. In studies of how phosphorylation of PACSIN 1 contributes to neuronal function, we identified serine 358 as a specific site used by casein kinase 2 (CK2) in vitro and in vivo. Phosphorylated PACSIN 1 was found in neuronal cytosol and membrane fractions. This localization could be modulated by trophic factors such as BDNF. We further show that expression of a phospho-negative PACSIN 1 mutant, S358A, or inhibition of CK2 drastically reduces spine formation in neurons. We identified a novel protein complex containing the spine regulator Rac1, its GAP neuron-associated developmentally-regulated protein (NADRIN) and PACSIN 1. CK2 phosphorylation of PACSIN 1 leads to a dissociation of the complex upon BDNF-treatment and induces Rac1-dependent spine formation in dendrites of hippocampal neurons. These findings suggest that upon BDNF signaling PACSIN 1 is phosphorylated by CK2 which is essential for spine formation.
The fly visual system offers a unique opportunity to explore computations performed by single neurons. Two previous studies characterized, in vivo, the receptive field (RF) of the vertical system (VS) cells of the blowfly (calliphora vicina), both intracellularly in the axon, and, independently using Ca2+ imaging, in hundreds of distal dendritic branchlets. We integrated this information into detailed passive cable and compartmental models of 3D reconstructed VS cells. Within a given VS cell type, the transfer resistance (TR) from different branchlets to the axon differs substantially, suggesting that they contribute unequally to the shaping of the axonal RF. Weighting the local RFs of all dendritic branchlets by their respective TR yielded a faithful reproduction of the axonal RF. The model also predicted that the various dendritic branchlets are electrically decoupled from each other, thus acting as independent local functional subunits. The study suggests that single neurons in the fly visual system filter dendritic noise and compute the weighted average of their inputs.
Neurons are the computational elements that compose the brain and their fundamental principles of activity are known for decades. According to the long-lasting computational scheme, each neuron sums the incoming electrical signals via its dendrites and when the membrane potential reaches a certain threshold the neuron typically generates a spike to its axon. Here we present three types of experiments, using neuronal cultures, indicating that each neuron functions as a collection of independent threshold units. The neuron is anisotropically activated following the origin of the arriving signals to the membrane, via its dendritic trees. The first type of experiments demonstrates that a single neuron’s spike waveform typically varies as a function of the stimulation location. The second type reveals that spatial summation is absent for extracellular stimulations from different directions. The third type indicates that spatial summation and subtraction are not achieved when combining intra- and extra- cellular stimulations, as well as for nonlocal time interference, where the precise timings of the stimulations are irrelevant. Results call to re-examine neuronal functionalities beyond the traditional framework, and the advanced computational capabilities and dynamical properties of such complex systems.
Brief periods of sleep loss have long-lasting consequences such as impaired memory consolidation. Structural changes in synaptic connectivity have been proposed as a substrate of memory storage. Here, we examine the impact of brief periods of sleep deprivation on dendritic structure. In mice, we find that five hours of sleep deprivation decreases dendritic spine numbers selectively in hippocampal area CA1 and increased activity of the filamentous actin severing protein cofilin. Recovery sleep normalizes these structural alterations. Suppression of cofilin function prevents spine loss, deficits in hippocampal synaptic plasticity, and impairments in long-term memory caused by sleep deprivation. The elevated cofilin activity is caused by cAMP-degrading phosphodiesterase-4A5 (PDE4A5), which hampers cAMP-PKA-LIMK signaling. Attenuating PDE4A5 function prevents changes in cAMP-PKA-LIMK-cofilin signaling and cognitive deficits associated with sleep deprivation. Our work demonstrates the necessity of an intact cAMP-PDE4-PKA-LIMK-cofilin activation-signaling pathway for sleep deprivation-induced memory disruption and reduction in hippocampal spine density.
How sleep helps learning and memory remains unknown. We report in mouse motor cortex that sleep after motor learning promotes the formation of postsynaptic dendritic spines on a subset of branches of individual layer V pyramidal neurons. New spines are formed on different sets of dendritic branches in response to different learning tasks and are protected from being eliminated when multiple tasks are learned. Neurons activated during learning of a motor task are reactivated during subsequent non-rapid eye movement sleep, and disrupting this neuronal reactivation prevents branch-specific spine formation. These findings indicate that sleep has a key role in promoting learning-dependent synapse formation and maintenance on selected dendritic branches, which contribute to memory storage.
Dimethyltryptamines are entheogenic serotonin-like molecules present in traditional Amerindian medicine recently associated with cognitive gains, antidepressant effects, and changes in brain areas related to attention. Legal restrictions and the lack of adequate experimental models have limited the understanding of how such substances impact human brain metabolism. Here we used shotgun mass spectrometry to explore proteomic differences induced by 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) on human cerebral organoids. Out of the 6,728 identified proteins, 934 were found differentially expressed in 5-MeO-DMT-treated cerebral organoids. In silico analysis reinforced previously reported anti-inflammatory actions of 5-MeO-DMT and revealed modulatory effects on proteins associated with long-term potentiation, the formation of dendritic spines, including those involved in cellular protrusion formation, microtubule dynamics, and cytoskeletal reorganization. Our data offer the first insight about molecular alterations caused by 5-MeO-DMT in human cerebral organoids.
The development of neural connectivity is essential for brain function, and disruption of this process is associated with autism spectrum disorders (ASDs). DIX domain containing 1 (DIXDC1) has previously been implicated in neurodevelopmental disorders, but its role in postnatal brain function remains unknown. Using a knockout mouse model, we determined that DIXDC1 is a regulator of excitatory neuron dendrite development and synapse function in the cortex. We discovered that MARK1, previously linked to ASDs, phosphorylates DIXDC1 to regulate dendrite and spine development through modulation of the cytoskeletal network in an isoform-specific manner. Finally, rare missense variants in DIXDC1 were identified in ASD patient cohorts via genetic sequencing. Interestingly, the variants inhibit DIXDC1 isoform 1 phosphorylation, causing impairment to dendrite and spine growth. These data reveal that DIXDC1 is a regulator of cortical dendrite and synaptic development and provide mechanistic insight into morphological defects associated with neurodevelopmental disorders.