Pairs Of Neurons Research Articles

Neural activity in the mouse claustrum in a cross-modal sensory selection task

The claustrum, a subcortical nucleus forming extensive connections with the neocortex, has been implicated in sensory selection. Sensory-evoked claustrum activity is thought to modulate the neocortex's context-dependent response to sensory input. Recording from claustrum neurons while mice performed a tactile-visualsensory-selection task, we found that neurons in the anterior claustrum, including putative optotagged claustrocortical neurons projecting to the primary somatosensory cortex (S1), were rarely modulated by sensory input. Rather, they exhibited different types of direction-tuned motor responses. Furthermore, we found that claustrum neurons encoded upcoming movement during intertrial intervals and that pairs of claustrum neurons exhibiting synchronous firing were enriched for pairs preferring contralateral lick directions, suggesting that the activity of specific ensembles of similarly tuned claustrum neurons may modulate cortical activity. Chemogenetic inhibition of claustrocortical neurons decreased lick responses to inappropriate sensory stimuli. Altogether, our data indicate that the claustrum is integrated into higher-order premotor circuits recently implicated in decision-making.

Analysis of the limiting behavior of a biological neurons system with delay

In this work an analytical and numerical analysis of the limiting behaviors of a system consisting of a pair of biological neurons was carried out. In this case connection between neurons will occur with a delay. As a neuron model, the FitzHugh-Nagumo model was chosen as a model that can reproduce many dynamic behaviors of a real neuron and, at the same time, is not very complex computationally.

FARCI: Fast and Robust Connectome Inference.

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using in silico datasets from the Neural Connectomics Challenge (NCC) and those generated using the state-of-the-art simulator of Neural Anatomy and Optimal Microscopy (NAOMi) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison with the best performing connectome inference algorithm in the NCC, Generalized Transfer Entropy (GTE), and Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP), FARCI produces more accurate networks over different network sizes, while providing significantly better computational speed and scaling.

Modulation of Spike Count Correlations Between Macaque Primary Visual Cortex Neurons by Difficulty of Attentional Task.

Studies have shown that spatial attention remarkably affects the trial-to-trial response variability shared between neurons. Difficulty in the attentional task adjusts how much concentration we maintain on what is currently important and what is filtered as irrelevant sensory information. However, how task difficulty mediates the interactions between neurons with separated receptive fields (RFs) that are attended to or attended away is still not clear. We examined spike count correlations between single-unit activities recorded simultaneously in the primary visual cortex (V1) while monkeys performed a spatial attention task with two levels of difficulty. Moreover, the RFs of the two neurons recorded were non-overlapping to allow us to study fluctuations in the correlated responses between competing visual inputs when the focus of attention was allocated to the RF of one neuron. While increasing difficulty in the spatial attention task, spike count correlations were either decreased to become negative between neuronal pairs, implying competition among them, with one neuron (or none) exhibiting attentional enhancement of firing rate, or increased to become positive, suggesting inter-neuronal cooperation, with one of the pair showing attentional suppression of spiking responses. Besides, the modulation of spike count correlations by task difficulty was independent of the attended locations. These findings provide evidence that task difficulty affects the functional interactions between different neuronal pools in V1 when selective attention resolves the spatial competition.

Sequential and efficient neural-population coding of complex task information

Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference and coherently maintained/updated through time? We recorded from excitatory neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that highly correlated task variables were represented by less-correlated neural population modes, while pairs of neurons exhibited a spectrum of signal correlations. This finding relates to principles of efficient coding, but notably utilizes neural population modes as the encoding unit and suggests partial whitening of task-specific information where different variables are represented with different signal-to-noise levels. Remarkably, this encoding function was multiplexed with sequential neural dynamics yet reliably followed changes in task-variable correlations throughout the trial. We suggest that neural circuits can implement time-dependent encodings in a simple way using random sequential dynamics as a temporal scaffold.

Metabolic flux from the Krebs cycle to glutamate transmission tunes a neural brake on seizure onset.

Kohlschütter-Tönz syndrome (KTS) manifests as neurological dysfunctions, including early-onset seizures. Mutations in the citrate transporter SLC13A5 are associated with KTS, yet their underlying mechanisms remain elusive. Here, we report that a Drosophila SLC13A5 homolog, I'm not dead yet (Indy), constitutes a neurometabolic pathway that suppresses seizure. Loss of Indy function in glutamatergic neurons caused "bang-induced" seizure-like behaviors. In fact, glutamate biosynthesis from the citric acid cycle was limiting in Indy mutants for seizure-suppressing glutamate transmission. Oral administration of the rate-limiting α-ketoglutarate in the metabolic pathway rescued low glutamate levels in Indy mutants and ameliorated their seizure-like behaviors. This metabolic control of the seizure susceptibility was mapped to a pair of glutamatergic neurons, reversible by optogenetic controls of their activity, and further relayed onto fan-shaped body neurons via the ionotropic glutamate receptors. Accordingly, our findings reveal a micro-circuit that links neural metabolism to seizure, providing important clues to KTS-associated neurodevelopmental deficits.

Concept neurons in the human medial temporal lobe flexibly represent abstract relations between concepts

Concept neurons in the medial temporal lobe respond to semantic features of presented stimuli. Analyzing 61 concept neurons recorded from twelve patients who underwent surgery to treat epilepsy, we show that firing patterns of concept neurons encode relations between concepts during a picture comparison task. Thirty-three of these responded to non-preferred stimuli with a delayed but well-defined onset whenever the task required a comparison to a response-eliciting concept, but not otherwise. Supporting recent theories of working memory, concept neurons increased firing whenever attention was directed towards this concept and could be reactivated after complete activity silence. Population cross-correlations of pairs of concept neurons exhibited order-dependent asymmetric peaks specifically when their response-eliciting concepts were to be compared. Our data are consistent with synaptic mechanisms that support reinstatement of concepts and their relations after activity silence, flexibly induced through task-specific sequential activation. This way arbitrary contents of experience could become interconnected in both working and long-term memory.

A pair of dopamine neurons mediate chronic stress signals to induce learning deficit in Drosophila melanogaster

Chronic stress could induce severe cognitive impairments. Despite extensive investigations in mammalian models, the underlying mechanisms remain obscure. Here, we show that chronic stress could induce dramatic learning and memory deficits in Drosophila melanogaster The chronic stress-induced learning deficit (CSLD) is long lasting and associated with other depression-like behaviors. We demonstrated that excessive dopaminergic activity provokes susceptibility to CSLD. Remarkably, a pair of PPL1-γ1pedc dopaminergic neurons that project to the mushroom body (MB) γ1pedc compartment play a key role in regulating susceptibility to CSLD so that stress-induced PPL1-γ1pedc hyperactivity facilitates the development of CSLD. Consistently, the mushroom body output neurons (MBON) of the γ1pedc compartment, MBON-γ1pedc>α/β neurons, are important for modulating susceptibility to CSLD. Imaging studies showed that dopaminergic activity is necessary to provoke the development of chronic stress-induced maladaptations in the MB network. Together, our data support that PPL1-γ1pedc mediates chronic stress signals to drive allostatic maladaptations in the MB network that lead to CSLD.

Switch-like and persistent memory formation in individual Drosophila larvae.

Associative learning allows animals to use past experience to predict future events. The circuits underlying memory formation support immediate and sustained changes in function, often in response to a single example. Larval Drosophila is a genetic model for memory formation that can be accessed at molecular, synaptic, cellular, and circuit levels, often simultaneously, but existing behavioral assays for larval learning and memory do not address individual animals, and it has been difficult to form long-lasting memories, especially those requiring synaptic reorganization. We demonstrate a new assay for learning and memory capable of tracking the changing preferences of individual larvae. We use this assay to explore how activation of a pair of reward neurons changes the response to the innately aversive gas carbon dioxide (CO2). We confirm that when coupled to CO2 presentation in appropriate temporal sequence, optogenetic reward reduces avoidance of CO2. We find that learning is switch-like: all-or-none and quantized in two states. Memories can be extinguished by repeated unrewarded exposure to CO2 but are stabilized against extinction by repeated training or overnight consolidation. Finally, we demonstrate long-lasting protein synthesis dependent and independent memory formation.

Synchronous inhibitory synaptic inputs to layer II/III pyramidal neurons in the murine barrel cortex

The barrel cortex exhibits obvious columnar organization. Although GABAergic inhibition plays a critical role in regulating neural excitation in response to mechanical stimuli applied to whiskers, the profiles of synchronous events for inhibitory synaptic transmission in intracolumnar and transcolumnar pyramidal neurons remain unknown. To explore a functional mechanism of synchronous inhibition of pyramidal neurons, we performed paired whole-cell patch-clamp recordings and recorded spontaneous inhibitory postsynaptic currents (sIPSCs) from layer II/III pyramidal neurons. A cross-correlogram of sIPSCs (1 ms bin) was used to detect synchronous sIPSCs. Synchronous neuron pairs were defined as those whose peak number of sIPSCs between −3 and 3 ms exceeded the mean + 2 SD of the number of sIPSCs in the period of −50 to 50 ms minus the number in that of −3 to 3 ms period. In the recording of pyramidal neurons located in the same column (intracolumn), 61.5% of neuron pairs were classified as synchronous neuron pairs, while 52.6% of pyramidal neuron pairs in adjacent columns (transcolumn) were defined as synchronous neuron pairs. The amplitude of synchronous sIPSCs was comparable to that of asynchronous sIPSCs in asynchronous neuron pairs, whereas that of synchronous sIPSCs was larger than that of asynchronous sIPSCs in synchronous neuron pairs. Synchronicity of sIPSCs did not depend on the distance of neuron pairs. These results suggest that layer II/III pyramidal neurons receive synchronous inhibitory synaptic inputs generated by a certain type of GABAergic interneuron that induces large IPSCs in pyramidal neurons, likely to be fast-spiking cells.

State-Dependent Synchrony and Functional Connectivity in the Primary and Secondary Whisker Somatosensory Cortices.

Synchronized activity plays an important role in sensory coding and memory and is a hallmark of functional network connectivity. However, the effect of sensory activation on synchronization and cortical functional connectivity is largely unknown. In this study, we investigated the effect of whisker activation on synchronization and functional connectivity of the primary (wS1) and secondary (wS2) whisker somatosensory cortices at the single-cell level. The results showed that during the spontaneous pre-stimulus state, neurons tended to be functionally connected with nearby neurons which shared similar tuning characteristics. Whisker activation using either ramp-and-hold stimulation or artificial whisking against sandpaper has significantly reduced the average overall pairwise synchronization and functional connectivity within the wS1 barrel and wS2 cortices. Whisker stimulation disconnected approximately a third of neuronal pairs that were functionally connected during the unstimulated state. Nearby neurons with congruent tuning properties were more likely to remain functionally connected during whisker activation. The findings of this study indicated that cortical somatosensory networks are organized in non-random small world networks composed of neurons sharing relatively similar tuning properties. Sensory whisker activation intensifies these properties and further subdivides the cortical network into smaller more functionally uniform subnetworks, which possibly serve to increase the computational capacity of the network.

Learning in Convolutional Neural Networks Accelerated by Transfer Entropy.

Recently, there is a growing interest in applying Transfer Entropy (TE) in quantifying the effective connectivity between artificial neurons. In a feedforward network, the TE can be used to quantify the relationships between neuron output pairs located in different layers. Our focus is on how to include the TE in the learning mechanisms of a Convolutional Neural Network (CNN) architecture. We introduce a novel training mechanism for CNN architectures which integrates the TE feedback connections. Adding the TE feedback parameter accelerates the training process, as fewer epochs are needed. On the flip side, it adds computational overhead to each epoch. According to our experiments on CNN classifiers, to achieve a reasonable computational overhead–accuracy trade-off, it is efficient to consider only the inter-neural information transfer of the neuron pairs between the last two fully connected layers. The TE acts as a smoothing factor, generating stability and becoming active only periodically, not after processing each input sample. Therefore, we can consider the TE is in our model a slowly changing meta-parameter.

Synergistic roles of homeodomain proteins UNC-62 homothorax and MLS-2 HMX/NKX in the specification of olfactory neurons in Caenorhabditis elegans.

General identity of the Caenorhabditis elegans AWC olfactory neuron pair is specified by the OTX/OTD transcription factor CEH-36 and the HMG-box transcription factor SOX-2, followed by asymmetrical differentiation of the pair into two distinct subtypes, default AWCOFF and induced AWCON, through a stochastic signaling event. The HMX/NKX transcription factor MLS-2 regulates the expression of ceh-36 to specify general AWC identity. However, general AWC identity is lost in only one of the two AWC cells in the majority of mls-2 null mutants displaying defective general AWC identity, suggesting that additional transcription factors have a partially overlapping role with MLS-2 in the specification of general AWC identity. Here, we identify a role of unc-62, encoding a homothorax/Meis/TALE homeodomain protein, in the specification of general AWC identity. As in mls-2 null mutants, unc-62 null mutants showed an incomplete penetrance in loss of general AWC identity. However, unc-62; mls-2 double mutants display a nearly complete penetrance of identity loss in both AWC cells. Thus, unc-62 and mls-2 have a partially overlapping function in the specification of general AWC identity. Furthermore, our genetic results suggest that mls-2 and unc-62 act cell autonomously in promoting the AWCON subtype. Together, our findings reveal the sequential roles of the unc-62 and mls-2 pair in AWC development, specification of general AWC identity in early embryogenesis, and asymmetric differentiation of AWC subtypes in late embryogenesis.

Precise optical control of gene expression in C elegans using improved genetic code expansion and Cre recombinase.

Synthetic strategies for optically controlling gene expression may enable the precise spatiotemporal control of genes in any combination of cells that cannot be targeted with specific promoters. We develop an improved genetic code expansion system in Caenorhabditis elegans and use it to create a photoactivatable Cre recombinase. We laser-activate Cre in single neurons within a bilaterally symmetric pair to selectively switch on expression of a loxP-controlled optogenetic channel in the targeted neuron. We use the system to dissect, in freely moving animals, the individual contributions of the mechanosensory neurons PLML/PLMR to the C. elegans touch response circuit, revealing distinct and synergistic roles for these neurons. We thus demonstrate how genetic code expansion and optical targeting can be combined to break the symmetry of neuron pairs and dissect behavioural outputs of individual neurons that cannot be genetically targeted.

Alteration in information flow through a pair of feeding command neurons underlies a form of Pavlovian conditioning in the Drosophila brain

Pavlovian conditioning1 is a broadly used learning paradigm where defined stimuli are associated to induce behavioral switching. To define a causal relationship between activity change in a single neuron and behavioral switching, we took advantage of a "command neuron" that connects cellular function to behavior.2 To examine the cellular and molecular basis of Pavlovian conditioning, we previously identified a pair of feeding command neurons termed "feeding neurons" in the adult Drosophila brain3 using genetic screening4 and opto- and thermo-genetic techniques.5-7 The feeding neuron is activated by sweet signals like sucrose and induces the full complement of feeding behaviors, such as proboscis extension and food pumping. Ablation or inactivation of the pair of feeding neurons abolishes feeding behavior, suggesting that this single pair of neurons is indispensable for natural feeding behaviors.2,3 Here, we describe a novel conditioning protocol to associate a signal-mediating rod removal from legs (conditioned stimulus [CS]) to feeding behavior induced by sucrose stimulation (unconditioned stimulus [US]). Calcium imaging of the feeding neuron demonstrated it acquires responsiveness to CS during conditioning, with inactivation of the feeding neuron during conditioning suppressing plasticity. These results suggest conditioning alters signals flowing from the CS into the feeding circuit, with the feeding neuron functioning as a key integrative hub for Hebbian plasticity.

Clustering and control for adaptation uncovers time-warped spike time patterns in cortical networks in vivo

How information in the nervous system is encoded by patterns of action potentials (i.e. spikes) remains an open question. Multi-neuron patterns of single spikes are a prime candidate for spike time encoding but their temporal variability requires further characterisation. Here we show how known sources of spike count variability affect stimulus-evoked spike time patterns between neurons separated over multiple layers and columns of adult rat somatosensory cortex in vivo. On subsets of trials (clusters) and after controlling for stimulus-response adaptation, spike time differences between pairs of neurons are “time-warped” (compressed/stretched) by trial-to-trial changes in shared excitability, explaining why fixed spike time patterns and noise correlations are seldom reported. We show that predicted cortical state is correlated between groups of 4 neurons, introducing the possibility of spike time pattern modulation by population-wide trial-to-trial changes in excitability (i.e. cortical state). Under the assumption of state-dependent coding, we propose an improved potential encoding capacity.

Spinal Cord Injury Significantly Alters the Properties of Reticulospinal Neurons: I. Biophysical Properties, Firing Patterns, Excitability, and Synaptic Inputs.

Following spinal cord injury (SCI) for larval lampreys, descending axons of reticulospinal (RS) neurons regenerate, and locomotor function gradually recovers. In the present study, the electrophysiological properties of uninjured (left)-injured (right) pairs of large, identified RS neurons were compared following rostral, right spinal cord hemi-transections (HTs). First, changes in firing patterns of injured RS neurons began in as little as 2–3 days following injury, these changes were maximal at ~2–3 weeks (wks), and by 12–16 wks normal firing patterns were restored for the majority of neurons. Second, at ~2–3 wks following spinal cord HTs, injured RS neurons displayed several significant changes in properties compared to uninjured neurons: (a) more hyperpolarized VREST; (b) longer membrane time constant and larger membrane capacitance; (c) increased voltage and current thresholds for action potentials (APs); (d) larger amplitudes and durations for APs; (e) higher slope for the repolarizing phase of APs; (f) virtual absence of some afterpotential components, including the slow afterhyperpolarization (sAHP); (g) altered, injury-type firing patterns; and (h) reduced average and peak firing (spiking) frequencies during applied depolarizing currents. These altered properties, referred to as the “injury phenotype”, reduced excitability and spiking frequencies of injured RS neurons compared to uninjured neurons. Third, artificially injecting a current to add a sAHP waveform following APs for injured neurons or removing the sAHP following APs for uninjured neurons did not convert these neurons to normal firing patterns or injury-type firing patterns, respectively. Fourth, trigeminal sensory-evoked synaptic responses recorded from uninjured and injured pairs of RS neurons were not significantly different. Following SCI, injured lamprey RS neurons displayed several dramatic changes in their biophysical properties that are expected to reduce calcium influx and provide supportive intracellular conditions for axonal regeneration.

Bridging neuronal correlations and dimensionality reduction

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. Although both approaches have been used to study trial-to-trial neuronal variability correlated among neurons, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.

Regulation of Satiety Quiescence by Neuropeptide Signaling in Caenorhabditis elegans.

Sleep and metabolism are interconnected homeostatic states; the sleep cycle can be entrained by the feeding cycle, and perturbation of the sleep often results in dysregulation in metabolism. However, the neuro-molecular mechanism by which metabolism regulates sleep is not fully understood. We investigated how metabolism and feeding regulate sleep using satiety quiescence behavior as a readout in Caenorhabditis elegans, which shares certain key aspects of postprandial sleep in mammals. From an RNA interference-based screen of two neuropeptide families, RFamide-related peptides (FLPs) and insulin-like peptides (INSs), we identified flp-11, known to regulate other types of sleep-like behaviors in C. elegans, as a gene that plays the most significant role in satiety quiescence. A mutation in flp-11 significantly reduces quiescence, whereas over-expression of the gene enhances it. A genetic analysis shows that FLP-11 acts upstream of the cGMP signaling but downstream of the TGFβ pathway, suggesting that TGFβ released from a pair of head sensory neurons (ASI) activates FLP-11 in an interneuron (RIS). Then, cGMP signaling acting in downstream of RIS neurons induces satiety quiescence. Among the 28 INSs genes screened, ins-1, known to play a significant role in starvation-associated behavior working in AIA is inhibitory to satiety quiescence. Our study suggests that specific combinations of neuropeptides are released, and their signals are integrated in order for an animal to gauge its metabolic state and to control satiety quiescence, a feeding-induced sleep-like state in C. elegans.

In Vivo Calcium Imaging of CA3 Pyramidal Neuron Populations in Adult Mouse Hippocampus.

Neuronal population activity in the hippocampal CA3 subfield is implicated in cognitive brain functions such as memory processing and spatial navigation. However, because of its deep location in the brain, the CA3 area has been difficult to target with modern calcium imaging approaches. Here, we achieved chronic two-photon calcium imaging of CA3 pyramidal neurons with the red fluorescent calcium indicator R-CaMP1.07 in anesthetized and awake mice. We characterize CA3 neuronal activity at both the single-cell and population level and assess its stability across multiple imaging days. During both anesthesia and wakefulness, nearly all CA3 pyramidal neurons displayed calcium transients. Most of the calcium transients were consistent with a high incidence of bursts of action potentials (APs), based on calibration measurements using simultaneous juxtacellular recordings and calcium imaging. In awake mice, we found state-dependent differences with striking large and prolonged calcium transients during locomotion. We estimate that trains of >30 APs over 3 s underlie these salient events. Their abundance in particular subsets of neurons was relatively stable across days. At the population level, we found that co-activity within the CA3 network was above chance level and that co-active neuron pairs maintained their correlated activity over days. Our results corroborate the notion of state-dependent spatiotemporal activity patterns in the recurrent network of CA3 and demonstrate that at least some features of population activity, namely co-activity of cell pairs and likelihood to engage in prolonged high activity, are maintained over days.