Physiologically distinct neurons within the ventrolateral periaqueductal gray are not defined by mu-opioid receptor expression but are differentially activated by persistent inflammation

The ventrolateral periaqueductal gray (vlPAG) is a key structure within the descending pain modulatory pathway and an important target for opioid-induced analgesia. This area contains heterogeneous neurons with respect to neurotransmitter and receptor expression so it is difficult to define vlPAG neurons that contribute to pain and analgesia. Characterization of intrinsic membrane properties of 371 vlPAG neurons from female and male Long-Evans rats identified 4 neuron types with distinct intrinsic firing patterns: Phasic, Tonic, Onset, and Random. Phasic and Tonic neurons comprise the majority of the neurons sampled. Mu-opioid receptor (MOR) expression was determined by the ability of the selective MOR agonist DAMGO to activate G protein-coupled inwardly-rectifying potassium channel (GIRK) currents. Opioid-sensitive and -insensitive neurons were observed within each neuron type in naive rats and in rats pretreated with Complete Freund's adjuvant in a hindpaw to produce persistent inflammation. The presence of low threshold spikes (LTS) did not correlate with MOR-mediated GIRK currents indicating that MOR expression alone does not define a physiologically distinct neuron type in the vlPAG. MOR activation inhibited firing in nearly all spontaneously active neurons, both in naive and persistent inflammation conditions. CFA-induced inflammation increased Fos expression at both acute (2 h) and persistent inflammation (5-7 d) time points. However, persistent, but not acute, inflammation selectively enhanced spontaneous firing and lowered firing thresholds of Phasic neurons which was maintained in the absence of synaptic inputs. Taken together, persistent inflammation selectively activates Phasic neurons, of which only a subset was opioid-sensitive.

Excitatory cholecystokinin neurons of the midbrain integrate diverse temporal responses and drive auditory thalamic subdomains

The central nucleus of the inferior colliculus (ICC) integrates information about different features of sound and then distributes this information to thalamocortical circuits. However, the lack of clear definitions of circuit elements in the ICC has limited our understanding of the nature of these circuit transformations. Here, we combine virus-based genetic access with electrophysiological and optogenetic approaches to identify a large family of excitatory, cholecystokinin-expressing thalamic projection neurons in the ICC of the Mongolian gerbil. We show that these neurons form a distinct cell type, displaying uniform morphology and intrinsic firing features, and provide powerful, spatially restricted excitation exclusively to the ventral auditory thalamus. In vivo, these neurons consistently exhibit V-shaped receptive field properties but strikingly diverse temporal responses to sound. Our results indicate that temporal response diversity is maintained within this population of otherwise uniform cells in the ICC and then relayed to cortex through spatially restricted thalamic subdomains.

Differential chemoarchitecture of Purkinje neurons contributes to intrinsic firing properties

SummaryPurkinje cells (PCs) are central to cerebellar information coding and appreciation for the diversity of their firing patterns and molecular profiles is growing. Heterogeneous subpopulations of PCs have been identified that display differences in intrinsic firing properties without clear mechanistic insight into what underlies the divergence in firing parameters. Although long used as a general PC marker, we report that the calcium binding protein parvalbumin labels a subpopulation of PCs with a conserved distribution pattern across the animals examined. We trained a convolutional neural network to recognize the parvalbumin-positive subtype and create maps of whole cerebellar distribution and find that PCs within these areas have differences in spontaneous firing that can be modified by altering calcium buffer content. These subtypes also show differential responses to potassium and calcium channel blockade, suggesting a mechanistic role for variability in PC intrinsic firing through differences in ion channel composition. It is proposed that ion channels drive the diversity in PC intrinsic firing phenotype and parvalbumin calcium buffering provides capacity for the highest firing rates observed. These findings open new avenues for detailed classification of PC subtypes.

Introduction to Information Transfer in the Nervous System

This chapter discusses the modalities of information transfer in the nervous system. The nervous system is organised around specialised cells called neurons, which work as integration units that transform all received information into new information. The neurons generate unitary electric pulses of invariant form and duration called action potentials or spikes. Neurons have an intrinsic firing frequency that is their frequency of producing spikes when they are not influenced. The chapter then considers the two major families of neurotransmitters. In general, a neuron releases only one type of neurotransmitter belonging to one of these two families. The first family is that of excitatory neurotransmitters; the neurons that release them are naturally called excitatory neurons. When they bind with postsynaptic receptors, they have a facilitating effect on the production of action potentials. Meanwhile, inhibitory neurons release neurotransmitters whose binding with postsynaptic receptors decreases the discharge frequency of the postsynaptic neuron. The chapter also describes a special family of neurotransmitters: the neuro-modulators.

Conditioning by subthreshold synaptic input changes the intrinsic firing pattern of CA3 hippocampal neurons

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions toward adapting and intrinsic burst behaviors, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade and found that the observed transitions are likely due to recruitment of low-voltage calcium and Kv7 potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits. NEW & NOTEWORTHY Although firing patterns are widely conserved across the animal phyla, it is still a mystery why nerve cells present such diversity of discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit, potentially adjusting their network processing to the temporal statistics of their circuit.

Conditioning by Subthreshold Synaptic Input Changes the Intrinsic Firing Pattern of CA3 Hippocampal Neurons

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike-timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions towards adapting and intrinsic burst behaviours, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade, and found that the observed transitions are likely due to recruitment of calcium and M-type potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits.New & NoteworthyDespite being widely conserved across the animal phyla, it is still a mystery why nerve cells present diverse discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit. This result implies that CA3 neurons collectively adjust their network processing to the temporal statistics of their circuit.