Neuronal Populations Research Articles

Separate cue- and alpha-related mechanisms for distractor suppression.

Research on selective attention has largely focused on the enhancement of behaviorally important information, with less focus on the suppression of distracting information. Enhancement and suppression can operate through a push-pull relationship attributable to competitive interactions among neural populations. There has been considerable debate, however, regarding (i) whether suppression can be voluntarily deployed, independent of enhancement, and (ii) whether the voluntary deployment of suppression is associated with neural processes that occur prior to distractor onset. Here, we investigated the interplay between pre- and post-distractor neural processes, while male and female human subjects performed a visual search task with a cue that indicated the location of an upcoming distractor. We utilized two established EEG markers of suppression: the distractor positivity (PD) and alpha power (∼8-15 Hz). The PD-a component of event-related potentials-has been linked with successful distractor suppression, and increased alpha power has been linked with attenuated sensory processing. Cueing the location of an upcoming distractor speeded responses and led to an earlier PD, consistent with earlier suppression due to the strategic use of a spatial cue. In comparison, higher pre-distractor alpha power contralateral to distractors led to a later PD, consistent with later suppression. Lower alpha power contralateral to distractors instead led to distractor-related attentional capture. Lateralization of alpha power was not linked to the spatial cue. This observation, combined with differences in the timing of successful suppression-as indexed by earlier and later PD components-demonstrates that cue-related, voluntary suppression can occur separate from alpha-related gating of sensory processing.Significance Statement Selective suppression of distracting information is important for survival. There are ongoing debates, however, regarding whether and how selective enhancement can be voluntarily deployed independent of selective enhancement. Here, we recorded EEG while subjects performed a visual search task with cues that indicated the location of upcoming distractors. Behavioral and electrophysiological results revealed that foreknowledge of a distractor's location speeded suppression (relative to non-cued trials), thereby facilitating target detection. The results further revealed that such cue-related suppression of a distractor can occur separate from alpha-related gating of sensory processing. That is, alpha-related suppression in the present task occurred independent of the spatially informative cue (i.e., on both cued and non-cued trials) and later than cue-related suppression (as indexed by later and earlier PD components).

Multifunctional and Flexible Neural Probe with Thermally Drawn Fibers for Bidirectional Synaptic Probing in the Brain.

Synapses in the brain utilize two distinct communication mechanisms: chemical and electrical. For a comprehensive investigation of neural circuitry, neural interfaces should be capable of both monitoring and stimulating these types of physiological interactions. However, previously developed interfaces for neurotransmitter monitoring have been limited in interaction modality due to constraints in device size, fabrication techniques, and the usage of flexible materials. To address this obstacle, we propose a multifunctional and flexible fiber probe fabricated through the microwire codrawing thermal drawing process, which enables the high-density integration of functional components with various materials such as polymers, metals, and carbon fibers. The fiber enables real-time monitoring of transient dopamine release in vivo, real-time stimulation of cell-specific neuronal populations via optogenetic stimulation, single-unit electrophysiology of individual neurons localized to the tip of the neural probe, and chemical stimulation via drug delivery. This fiber will improve the accessibility and functionality of bidirectional interrogation of neurochemical mechanisms in implantable neural probes.

Distributed and dynamical communication: a mechanism for flexible cortico-cortical interactions and its functional roles in visual attention

Perceptual and cognitive processing relies on flexible communication among cortical areas; however, the underlying neural mechanism remains unclear. Here we report a mechanism based on the realistic spatiotemporal dynamics of propagating wave patterns in neural population activity. Using a biophysically plausible, multiarea spiking neural circuit model, we demonstrate that these wave patterns, characterized by their rich and complex dynamics, can account for a wide variety of empirically observed neural processes. The coordinated interactions of these wave patterns give rise to distributed and dynamic communication (DDC) that enables flexible and rapid routing of neural activity across cortical areas. We elucidate how DDC unifies the previously proposed oscillation synchronization-based and subspace-based views of interareal communication, offering experimentally testable predictions that we validate through the analysis of Allen Institute Neuropixels data. Furthermore, we demonstrate that DDC can be effectively modulated during attention tasks through the interplay of neuromodulators and cortical feedback loops. This modulation process explains many neural effects of attention, underscoring the fundamental functional role of DDC in cognition.

Immunological isolation and characterization of neuronal progenitors from human dental pulp: A laboratory-based investigation.

Dental pulp stem cells (DPSCs) contain a population of stem cells with a broad range of differentiation potentials, as well as more lineage-committed progenitors. Such heterogeneity is a significant obstacle to experimental and clinical applications. The aim of this study is to isolate and characterize a homogenous neuronal progenitor cell population from human DPSCs. Polysialylated-neural cell adhesion molecule (PSA-NCAM+) neural progenitors were isolated from the dental pulp of three independent donors using magnetic-activated cell sorting (MACS) technology. Immunofluorescent staining with a panel of neural and non-neural markers was used to characterize the magnetically isolated PSA-NCAM+ fraction. PSA-NCAM+ cells were then cultured in Neurobasal A supplemented with neurotrophic factors: dibutyryl cyclic-AMP, neurotrophin-3, B27 and N2 supplements to induce neuronal differentiation. Both PSA-NCAM+ and differentiated PSA-NCAM+ cells were used in Ca2+ imaging studies to assess the functionality of P2X3 receptors as well as membrane depolarization. PSA-NCAM+ neural progenitors were isolated from a heterogeneous population of hDPSCs using magnetic-activated cell sorting and anti-PSA-NCAM MicroBeads. Flow cytometry analysis demonstrated that immunomagnetic sorting significantly increased the purity of PSA-NCAM+ cells. Immunofluorescent staining revealed expression of pan-neuronal and mature neuronal markers, PGP9.5 and MAP2, respectively, as well as weak expression of the mature sensory markers, peripherin and islet1. ATP-induced response was mediated predominately by P2X3 receptors in both undifferentiated and differentiated cells, with a greater magnitude observed in the latter. In addition, membrane depolarizations were also detected in cells before and after differentiation when loaded with fast-voltage-responding fluorescent molecule, FluoVolt™ in response to potassium chloride. Interestingly, only differentiated PSA-NCAM+ cells were capable of spontaneous membrane oscillations. In summary, DPSCs contain a population of neuronal progenitors with enhanced neural differentiation and functional neural-like properties that can be effectively isolated with magnetic-activated cell sorting (MACS).

Drift of neural ensembles driven by slow fluctuations of intrinsic excitability.

Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not known. Since intrinsic neural excitability is suggested to play a key role in regulating memory allocation, fluctuations of excitability could bias the reactivation of previously stored memory ensembles and therefore act as a motor for drift. Here, we propose a rate-based plastic recurrent neural network with slow fluctuations of intrinsic excitability. We first show that subsequent reactivations of a neural ensemble can lead to drift of this ensemble. The model predicts that drift is induced by co-activation of previously active neurons along with neurons with high excitability which leads to remodeling of the recurrent weights. Consistent with previous experimental works, the drifting ensemble is informative about its temporal history. Crucially, we show that the gradual nature of the drift is necessary for decoding temporal information from the activity of the ensemble. Finally, we show that the memory is preserved and can be decoded by an output neuron having plastic synapses with the main region.

Drift of neural ensembles driven by slow fluctuations of intrinsic excitability

Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not known. Since intrinsic neural excitability is suggested to play a key role in regulating memory allocation, fluctuations of excitability could bias the reactivation of previously stored memory ensembles and therefore act as a motor for drift. Here, we propose a rate-based plastic recurrent neural network with slow fluctuations of intrinsic excitability. We first show that subsequent reactivations of a neural ensemble can lead to drift of this ensemble. The model predicts that drift is induced by co-activation of previously active neurons along with neurons with high excitability which leads to remodeling of the recurrent weights. Consistent with previous experimental works, the drifting ensemble is informative about its temporal history. Crucially, we show that the gradual nature of the drift is necessary for decoding temporal information from the activity of the ensemble. Finally, we show that the memory is preserved and can be decoded by an output neuron having plastic synapses with the main region.

Chemogenetic activation of mammalian brain neurons expressing insect Ionotropic Receptors by systemic ligand precursor administration

Chemogenetic approaches employing ligand-gated ion channels are advantageous regarding manipulation of target neuronal population functions independently of endogenous second messenger pathways. Among them, Ionotropic Receptor (IR)-mediated neuronal activation (IRNA) allows stimulation of mammalian neurons that heterologously express members of the insect chemosensory IR repertoire in response to their cognate ligands. In the original protocol, phenylacetic acid, a ligand of the IR84a/IR8a complex, was locally injected into a brain region due to its low permeability of the blood-brain barrier. To circumvent this invasive injection, we sought to develop a strategy of peripheral administration with a precursor of phenylacetic acid, phenylacetic acid methyl ester, which is efficiently transferred into the brain and converted to the mature ligand by endogenous esterase activities. This strategy was validated by electrophysiological, biochemical, brain-imaging, and behavioral analyses, demonstrating high utility of systemic IRNA technology in the remote activation of target neurons in the brain.

Faster bi-stable visual switching in psychosis

Bi-stable stimuli evoke two distinct perceptual interpretations that alternate and compete for dominance. Bi-stable perception is thought to be driven at least in part by mutual suppression between distinct neural populations that represent each percept. Abnormal visual perception has been observed among people with psychotic psychopathology (PwPP), and there is evidence to suggest that these visual deficits may depend on impaired neural suppression in the visual cortex. However, it is not yet clear whether bi-stable visual perception is abnormal among PwPP. Here, we examined bi-stable perception in a visual structure-from-motion task using a rotating cylinder illusion in a group of 65 PwPP, 44 first-degree biological relatives, and 43 healthy controls. Data from a ‘real switch’ task, in which physical depth cues signaled real switches in rotation direction were used to exclude individuals who did not show adequate task performance. In addition, we measured concentrations of neurochemicals, including glutamate, glutamine, and γ-amino butyric acid (GABA), involved in excitatory and inhibitory neurotransmission. These neurochemicals were measured non-invasively in the visual cortex using 7 tesla MR spectroscopy. We found that PwPP and their relatives showed faster bi-stable switch rates than healthy controls. Faster switch rates also correlated with significantly higher psychiatric symptom levels, specifically disorganization, across all participants. However, we did not observe any significant relationships across individuals between neurochemical concentrations and SFM switch rates. Our results are consistent with a reduction in suppressive neural processes during structure-from-motion perception in PwPP, and suggest that genetic liability for psychosis is associated with disrupted bi-stable perception.

Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of Aβ pathology.

Alzheimer's Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behavioral deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventral CA1 (vCA1), two hippocampal areas known to be structurally and functionally diverse, in the APP/PS1 mouse model of amyloidosis. Despite similar levels of Aβ pathology, dCA1 and vCA1 showed distinct disruptions in neuronal population activity as animals navigated a virtual reality environment. In dCA1, pairwise correlations and entropy, a measure of the diversity of activity patterns, were decreased in APP/PS1 mice relative to age-matched C57BL/6 controls. However, in vCA1, APP/PS1 mice had increased pair-wise correlations and entropy as compared to age matched controls. Finally, using maximum entropy models, we connected the microscopic features of population activity (correlations) to the macroscopic features of the population code (entropy). We found that the models' performance increased in predicting dCA1 activity, but decreased in predicting vCA1 activity, in APP/PS1 mice relative to the controls. Taken together, we found that Aβ exerts distinct effects across different hippocampal regions, suggesting that the various behavioral deficits of AD may reflect underlying heterogeneities in neuronal circuits and the different disruptions that Aβ pathology causes in those circuits.

A dynamic neural resource model bridges sensory and working memory

Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or ‘iconic’ memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.

A dynamic neural resource model bridges sensory and working memory.

Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or 'iconic' memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.

Post-transcriptional regulation and subcellular localization of G-protein γ7 subunit: implications for striatal function and behavioral responses to cocaine

The striatal D1 dopamine receptor (D1R) and A2a adenosine receptor (A2aR) signaling pathways play important roles in drug-related behaviors. These receptors activate the Golf protein comprised of a specific combination of αolfβ2γ7 subunits. During assembly, the γ7 subunit sets the cellular level of the Golf protein. In turn, the amount of Golf protein determines the collective output from both D1R and A2aR signaling pathways. This study shows the Gng7 gene encodes multiple γ7 transcripts differing only in their non-coding regions. In striatum, Transcript 1 is the predominant isoform. Preferentially expressed in the neuropil, Transcript 1 is localized in dendrites where it undergoes post-transcriptional regulation mediated by regulatory elements in its 3′ untranslated region that contribute to translational suppression of the γ7 protein. Earlier studies on gene-targeted mice demonstrated loss of γ7 protein disrupts assembly of the Golf protein. In the current study, morphological analysis reveals the loss of the Golf protein is associated with altered dendritic morphology of medium spiny neurons. Finally, behavioral analysis of conditional knockout mice with cell-specific deletion of the γ7 protein in distinct populations of medium spiny neurons reveals differential roles of the Golf protein in mediating behavioral responses to cocaine. Altogether, these findings provide a better understanding of the regulation of γ7 protein expression, its impact on Golf function, and point to a new potential target and mechanisms for treating addiction and related disorders.

The quality and complexity of pairwise maximum entropy models for large cortical populations.

We investigate the ability of the pairwise maximum entropy (PME) model to describe the spiking activity of large populations of neurons recorded from the visual, auditory, motor, and somatosensory cortices. To quantify this performance, we use (1) Kullback-Leibler (KL) divergences, (2) the extent to which the pairwise model predicts third-order correlations, and (3) its ability to predict the probability that multiple neurons are simultaneously active. We compare these with the performance of a model with independent neurons and study the relationship between the different performance measures, while varying the population size, mean firing rate of the chosen population, and the bin size used for binarizing the data. We confirm the previously reported excellent performance of the PME model for small population sizes N < 20. But we also find that larger mean firing rates and bin sizes generally decreases performance. The performance for larger populations were generally not as good. For large populations, pairwise models may be good in terms of predicting third-order correlations and the probability of multiple neurons being active, but still significantly worse than small populations in terms of their improvement over the independent model in KL-divergence. We show that these results are independent of the cortical area and of whether approximate methods or Boltzmann learning are used for inferring the pairwise couplings. We compared the scaling of the inferred couplings with N and find it to be well explained by the Sherrington-Kirkpatrick (SK) model, whose strong coupling regime shows a complex phase with many metastable states. We find that, up to the maximum population size studied here, the fitted PME model remains outside its complex phase. However, the standard deviation of the couplings compared to their mean increases, and the model gets closer to the boundary of the complex phase as the population size grows.

Nucleus accumbens neuronal ensembles vary with cocaine reinforcement in male and female rats.

Neuronal ensembles in the medial prefrontal cortex mediate cocaine self-administration via projections to the nucleus accumbens. We have recently shown that neuronal ensembles in the prelimbic cortex form rapidly to mediate cocaine self-administration. However, the role of neuronal ensembles within the nucleus accumbens in initial cocaine-seeking behaviour remains unknown. Here, we sought to expand the current literature by testing the necessity of the cocaine self-administration ensemble in the nucleus accumbens core (NAcCore) 1 day after male and female rats acquire cocaine self-administration by using the Daun02 inactivation procedure. We found that disrupting the NAcCore ensembles after a no-cocaine reward-seeking test increased subsequent cocaine seeking, while disrupting NAcCore ensembles following a cocaine self-administration session decreased subsequent cocaine seeking. We then characterized neuronal cell type in the NAcCore using RNAscope in situ hybridization. In the no-cocaine session, we saw reduced dopamine D1 type neuronal activation, while in the cocaine self-administration session, we found preferential dopamine D1 type neuronal activity in the NAcCore.

Cell-Type Specific and Frequency-Dependent Centrifugal Modulation in Olfactory Bulb Output Neurons in Vivo.

Mitral/tufted cells (M/TCs) form complex local circuits with interneurons in olfactory bulb and are powerfully inhibited by these interneurons. The horizontal limb of the diagonal band of Broca (HDB), the only GABAergic/inhibitory source of centrifugal circuit with olfactory bulb is known to target olfactory bulb interneurons and we have shown targeting also to olfactory bulb glutamatergic neurons in vitro. However, the net efficacy of these circuits under different patterns of activation in vivo and the relative balance between the various targeted intact local and centrifugal circuits was the focus of this study. Here ChR2 was expressed in HDB GABAergic neurons to investigate the short-term plasticity of HDB-activated disinhibitory rebound excitation of M/TCs. Optical activation of HDB interneurons increased spontaneous M/TC firing without odor presentation and increased odor-evoked M/TC firing. HDB activation induced-disinhibitory rebound excitation (burst or cluster of spiking) in all classes of M/TCs. This excitation was frequency dependent, with short term facilitation only at higher HDB stimulation frequency (5 Hz and above). However, frequency-dependent HDB regulation was more potent in the deeper layer M/TCs compared to more superficial layer M/TCs. In all neural circuits the balance between inhibition and excitation in local and centrifugal circuits plays a critical functional role and this patterned input-dependent regulation of inhibitory centrifugal inputs to the olfactory bulb may help maintain the precise balance across the populations of output neurons in the different environmental odors, putatively to sharpen the enhancement of tuning specificity of individual or classes of M/TCs to odors.

Excitatory Spinal Lhx9-Derived Interneurons Modulate Locomotor Frequency in Mice.

Locomotion allows us to move and interact with our surroundings. Spinal networks that control locomotion produce rhythm and left-right and flexor-extensor coordination. Several glutamatergic populations, Shox2 non-V2a, Hb9-derived interneurons, and, recently, spinocerebellar neurons have been proposed to be involved in the mouse rhythm generating networks. These cells make up only a smaller fraction of the excitatory cells in the ventral spinal cord. Here, we set out to identify additional populations of excitatory spinal neurons that may be involved in rhythm generation or other functions in the locomotor network. We use RNA sequencing from glutamatergic, non-glutamatergic, and Shox2 cells in the neonatal mice from both sexes followed by differential gene expression analyses. These analyses identified transcription factors that are highly expressed by glutamatergic spinal neurons and differentially expressed between Shox2 neurons and glutamatergic neurons. From this latter category, we identified the Lhx9-derived neurons as having a restricted spinal expression pattern with no Shox2 neuron overlap. They are purely glutamatergic and ipsilaterally projecting. Ablation of the glutamatergic transmission or acute inactivation of the neuronal activity of Lhx9-derived neurons leads to a decrease in the frequency of locomotor-like activity without change in coordination pattern. Optogenetic activation of Lhx9-derived neurons promotes locomotor-like activity and modulates the frequency of the locomotor activity. Calcium activities of Lhx9-derived neurons show strong left-right out-of-phase rhythmicity during locomotor-like activity. Our study identifies a distinct population of spinal excitatory neurons that regulates the frequency of locomotor output with a suggested role in rhythm-generation in the mouse alongside other spinal populations.

Sex-biased gene expression during neural differentiation of human embryonic stem cells

Sex-biased gene expression during neural differentiation of human embryonic stem cells

The neural representation of an auditory spatial cue in the primate cortex.

Humans make use of small differences in the timing of sounds at the two ears-interaural time differences (ITDs)-to locate their sources. Despite extensive investigation, however, the neural representation of ITDs in the human brain is contentious, particularly the range of ITDs explicitly represented by dedicated neural detectors. Here, using magneto- and electro-encephalography (MEG and EEG), we demonstrate evidence of a sparse neural representation of ITDs in the human cortex. The magnitude of cortical activity to sounds presented via insert earphones oscillated as a function of increasing ITD-within and beyond auditory cortical regions-and listeners rated the perceptual quality of these sounds according to the same oscillating pattern. This pattern was accurately described by a population of model neurons with preferred ITDs constrained to the narrow, sound-frequency-dependent range evident in other mammalian species. When scaled for head size, the distribution of ITD detectors in the human cortex is remarkably like that recorded invivo from the cortex of rhesus monkeys, another large primate that uses ITDs for source localization. The data solve a long-standing issue concerning the neural representation of ITDs in humans and suggest a representation that scales for head size and sound frequency in an optimal manner.

A body-brain circuit that regulates body inflammatory responses.

The body-brain axis is emerging as a principal conductor of organismal physiology. It senses and controls organ function1,2, metabolism3 and nutritional state4-6. Here, we show that a peripheral immune insult powerfully activates the body-brain axis to regulate immune responses. We demonstrate that pro- and anti-inflammatory cytokines communicate with distinct populations of vagal neurons to inform the brain of an emerging inflammatory response. In turn, the brain tightly modulates the course of the peripheral immune response. Genetic silencing of this body-to-brain circuit produced unregulated and out-of-control inflammatory responses. By contrast, activating, rather than silencing, this circuit affords exceptional neural control of immune responses. We used single-cell RNA sequencing, combined with functional imaging, to identify the circuit components of this neuro-immune axis, and showed that its selective manipulation can effectively suppress the pro-inflammatory response while enhancing an anti-inflammatory state. The brain-evoked transformation of the course of an immune response offers new possibilities in the modulation of a wide range of immune disorders, from autoimmune diseases to cytokine storm and shock.

Differential representation of sensory information and behavioral choice across layers of the mouse auditory cortex.

The activity of neurons in sensory areas sometimes covaries with upcoming choices in decision-making tasks. However, the prevalence, causal origin, and functional role of choice-related activity remain controversial. Understanding the circuit-logic of decision signals in sensory areas will require understanding their laminar specificity, but simultaneous recordings of neural activity across the cortical layers in forced-choice discrimination tasks have not yet been performed. Here, we describe neural activity from such recordings in the auditory cortex of mice during a frequency discrimination task with delayed report, which, as we show, requires the auditory cortex. Stimulus-related information was widely distributed across layers but disappeared very quickly after stimulus offset. Choice selectivity emerged toward the end of the delay period-suggesting a top-down origin-but only in the deep layers. Early stimulus-selective and late choice-selective deep neural ensembles were correlated, suggesting that the choice-selective signal fed back to the auditory cortex is not just action specific but develops as a consequence of the sensory-motor contingency imposed by the task.