Concept: Membrane potential
Behavioral output of neural networks depends on a delicate balance between excitatory and inhibitory synaptic connections. However, it is not known whether network formation and stability is constrained by the sign of synaptic connections between neurons within the network. Here we show that switching the sign of a synapse within a neural circuit can reverse the behavioral output. The inhibitory tyramine-gated chloride channel, LGC-55, induces head relaxation and inhibits forward locomotion during the Caenorhabditis elegans escape response. We switched the ion selectivity of an inhibitory LGC-55 anion channel to an excitatory LGC-55 cation channel. The engineered cation channel is properly trafficked in the native neural circuit and results in behavioral responses that are opposite to those produced by activation of the LGC-55 anion channel. Our findings indicate that switches in ion selectivity of ligand-gated ion channels (LGICs) do not affect network connectivity or stability and may provide an evolutionary and a synthetic mechanism to change behavior.
The TRPM8 channel is a principal cold transducer that is expressed on some primary afferents of the somatic and cranial sensory systems. However, it is uncertain whether TRPM8-expressing afferent neurons have the ability to convey innocuous and noxious cold stimuli with sensory discrimination between the two sub-modalities. Using rat dorsal root ganglion (DRG) neurons and the patch-clamp recording technique, we characterized membrane and action potential properties of TRPM8-expressing DRG neurons at 24°C and 10°C. TRPM8-expressing neurons could be classified into TTX-sensitive (TTXs/TRPM8) and TTX-resistant (TTXr/TRPM8) subtypes based on the sensitivity to tetrodotoxin (TTX) block of their action potentials. These two subtypes of cold-sensing cells displayed different membrane and action potential properties. Voltage-activated inward Na+ currents were highly susceptible to cooling temperature and abolished by ~95% at 10°C in TTXs/TRPM8 DRG neurons, but remained substantially large at 10°C in TTXr/TRPM8 cells. In both TTXs/TRPM8 and TTXr/TRPM8 cells, voltage-activated outward K+ currents were substantially inhibited at 10°C, and the cooling-sensitive outward currents resembled A-type K+ currents. TTXs/TRPM8 neurons and TTXr/TRPM8 neurons were shown to fire action potentials at innocuous and noxious cold temperatures respectively, demonstrating sensory discrimination between innocuous and noxious cold by the two subpopulations of cold-sensing DRG neurons. The effects of cooling temperatures on voltage-gated Na+ channels and A-type K+ currents are likely to be contributing factors to sensory discrimination of cold by TTXs/TRPM8 and TTXr/TRPM8 afferent neurons.
Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na(+) and K(+) channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.Journal of Cerebral Blood Flow & Metabolism advance online publication, 19 June 2013; doi:10.1038/jcbfm.2013.103.
Studies on neural plasticity associated with brain-machine interface (BMI) exposure have primarily documented changes in single neuron activity, and largely in intact subjects. Here, we demonstrate significant changes in ensemble-level functional connectivity among primary motor cortical (MI) neurons of chronically amputated monkeys exposed to control a multiple-degree-of-freedom robot arm. A multi-electrode array was implanted in M1 contralateral or ipsilateral to the amputation in three animals. Two clusters of stably recorded neurons were arbitrarily assigned to control reach and grasp movements, respectively. With exposure, network density increased in a nearly monotonic fashion in the contralateral monkeys, whereas the ipsilateral monkey pruned the existing network before re-forming a denser connectivity. Excitatory connections among neurons within a cluster were denser, whereas inhibitory connections were denser among neurons across the two clusters. These results indicate that cortical network connectivity can be modified with BMI learning, even among neurons that have been chronically de-efferented and de-afferented due to amputation.
Type 1 cannabinoid receptors (CB1Rs) are widely expressed in the vertebrate retina but the role of endocannabinoids in vision is not fully understood. Here we identified a novel mechanism underlying a CB1R-mediated increase in retinal ganglion cell (RGC) intrinsic excitability acting through AMPK-dependent inhibition of NKCC1 activity. Clomeleon imaging and patch clamp recordings revealed that inhibition of NKCC1 downstream of CB1R activation reduces intracellular Cl(-) levels in RGCs, hyperpolarizing the resting membrane potential. We confirmed that such hyperpolarization enhances RGC action potential firing in response to subsequent depolarization, consistent with the increased intrinsic excitability of RGCs observed with CB1R activation. Using a dot avoidance assay in freely swimming Xenopus tadpoles we demonstrate that CB1R activation markedly improves visual contrast sensitivity under low light conditions. These results highlight a role for endocannabinoids in vision, and present a novel mechanism for cannabinoid modulation of neuronal activity through Cl(-) regulation.
Pyramidal neurons represent the majority of excitatory neurons in the neocortex. Each pyramidal neuron receives input from thousands of excitatory synapses that are segregated onto dendritic branches. The dendrites themselves are segregated into apical, basal, and proximal integration zones, which have different properties. It is a mystery how pyramidal neurons integrate the input from thousands of synapses, what role the different dendrites play in this integration, and what kind of network behavior this enables in cortical tissue. It has been previously proposed that non-linear properties of dendrites enable cortical neurons to recognize multiple independent patterns. In this paper we extend this idea in multiple ways. First we show that a neuron with several thousand synapses segregated on active dendrites can recognize hundreds of independent patterns of cellular activity even in the presence of large amounts of noise and pattern variation. We then propose a neuron model where patterns detected on proximal dendrites lead to action potentials, defining the classic receptive field of the neuron, and patterns detected on basal and apical dendrites act as predictions by slightly depolarizing the neuron without generating an action potential. By this mechanism, a neuron can predict its activation in hundreds of independent contexts. We then present a network model based on neurons with these properties that learns time-based sequences. The network relies on fast local inhibition to preferentially activate neurons that are slightly depolarized. Through simulation we show that the network scales well and operates robustly over a wide range of parameters as long as the network uses a sparse distributed code of cellular activations. We contrast the properties of the new network model with several other neural network models to illustrate the relative capabilities of each. We conclude that pyramidal neurons with thousands of synapses, active dendrites, and multiple integration zones create a robust and powerful sequence memory. Given the prevalence and similarity of excitatory neurons throughout the neocortex and the importance of sequence memory in inference and behavior, we propose that this form of sequence memory may be a universal property of neocortical tissue.
Purkinje neurons are central to cerebellar function and show membrane bistability when recorded in vitro or in vivo under anesthesia. The existence of bistability in vivo in awake animals is disputed. Here, by recording intracellularly from Purkinje neurons in unanesthetized larval zebrafish (Danio rerio), we unequivocally demonstrate bistability in these neurons. Tonic firing was seen in depolarized regimes and bursting at hyperpolarized membrane potentials. In addition, Purkinje neurons could switch from one state to another spontaneously or with current injection. While GABAAR or NMDAR were not required for bursting, activation of AMPARs by climbing fibers (CFs) was sufficient to trigger bursts. Further, by recording Purkinje neuron membrane potential intracellularly, and motor neuron spikes extracellularly, we show that initiation of motor neuron spiking is correlated with increased incidence of CF EPSPs and membrane depolarization. Developmentally, bistability was observed soon after Purkinje neuron specification and persists at least until late larval stages.
Goal-directed sensorimotor transformation drives important aspects of mammalian behavior. The striatum is thought to play a key role in reward-based learning and action selection, receiving glutamatergic sensorimotor signals and dopaminergic reward signals. Here, we obtain whole-cell membrane potential recordings from the dorsolateral striatum of mice trained to lick a reward spout after a whisker deflection. Striatal projection neurons showed strong task-related modulation, with more depolarization and action potential firing on hit trials compared to misses. Direct pathway striatonigral neurons, but not indirect pathway striatopallidal neurons, exhibited a prominent early sensory response. Optogenetic stimulation of direct pathway striatonigral neurons, but not indirect pathway striatopallidal neurons, readily substituted for whisker stimulation evoking a licking response. Our data are consistent with direct pathway striatonigral neurons contributing a “go” signal for goal-directed sensorimotor transformation leading to action initiation.
Converging experimental data indicate a neuroprotective action of L-Lactate. Using Digital Holographic Microscopy, we observe that transient application of glutamate (100 μM; 2 min) elicits a NMDA-dependent death in 65% of mouse cortical neurons in culture. In the presence of L-Lactate (or Pyruvate), the percentage of neuronal death decreases to 32%. UK5099, a blocker of the Mitochondrial Pyruvate Carrier, fully prevents L-Lactate-mediated neuroprotection. In addition, L-Lactate-induced neuroprotection is not only inhibited by probenicid and carbenoxolone, two blockers of ATP channel pannexins, but also abolished by apyrase, an enzyme degrading ATP, suggesting that ATP produced by the Lactate/Pyruvate pathway is released to act on purinergic receptors in an autocrine/paracrine manner. Finally, pharmacological approaches support the involvement of the P2Y receptors associated to the PI3-kinase pathway, leading to activation of KATP channels. This set of results indicates that L-Lactate acts as a signalling molecule for neuroprotection against excitotoxicity through coordinated cellular pathways involving ATP production, release and activation of a P2Y/KATP cascade.
During navigation, grid cells increase their spike rates in firing fields arranged on a markedly regular triangular lattice, whereas their spike timing is often modulated by theta oscillations. Oscillatory interference models of grid cells predict theta amplitude modulations of membrane potential during firing field traversals, whereas competing attractor network models predict slow depolarizing ramps. Here, using in vivo whole-cell recordings, we tested these models by directly measuring grid cell intracellular potentials in mice running along linear tracks in virtual reality. Grid cells had large and reproducible ramps of membrane potential depolarization that were the characteristic signature tightly correlated with firing fields. Grid cells also demonstrated intracellular theta oscillations that influenced their spike timing. However, the properties of theta amplitude modulations were not consistent with the view that they determine firing field locations. Our results support cellular and network mechanisms in which grid fields are produced by slow ramps, as in attractor models, whereas theta oscillations control spike timing.