Responses Of Neurons Research Articles

Nonnegative matrix factorization for analyzing state dependent neuronal network dynamics in calcium recordings.

Calcium imaging allows recording from hundreds of neurons in vivo with the ability to resolve single cell activity. Evaluating and analyzing neuronal responses, while also considering all dimensions of the data set to make specific conclusions, is extremely difficult. Often, descriptive statistics are used to analyze these forms of data. These analyses, however, remove variance by averaging the responses of single neurons across recording sessions, or across combinations of neurons, to create single quantitative metrics, losing the temporal dynamics of neuronal activity, and their responses relative to each other. Dimensionally Reduction (DR) methods serve as a good foundation for these analyses because they reduce the dimensions of the data into components, while still maintaining the variance. Nonnegative Matrix Factorization (NMF) is an especially promising DR analysis method for analyzing activity recorded in calcium imaging because of its mathematical constraints, which include positivity and linearity. We adapt NMF for our analyses and compare its performance to alternative dimensionality reduction methods on both artificial and in vivo data. We find that NMF is well-suited for analyzing calcium imaging recordings, accurately capturing the underlying dynamics of the data, and outperforming alternative methods in common use.

Interactions between arousal state and CO₂ determine the activity of central chemoreceptor neurons that drive breathing.

The homeostatic regulation of pulmonary ventilation, and ultimately arterial PCO2, depends on interactions between respiratory chemoreflexes and arousal state. The ventilatory response to CO2 is triggered by neurons in the retrotrapezoid nucleus (RTN) that function as sensors of central pH, which can be identified in adulthood by expression of Phox2b and Neuromedin B. Here we examine the dynamic response of genetically-defined RTN neurons to hypercapnia and arousal state in freely-behaving adult male and female mice using the calcium indicator jGCaMP7 and fiber photometry. We found that hypercapnia vigorously activates RTN neurons with a low CO2 recruitment threshold and with response kinetics that match respiratory activity whereas hypoxia had little effect. RTN activity increased transiently during wakefulness and respiratory-related arousals, rose persistently during REM sleep and their CO2 response persisted under anesthesia. Complementary studies using inhibitory optogenetics show that RTN activity supports eupneic breathing under anesthesia as well as during states of high arousal, but their activity is redundant for voluntary breathing patterns. Collectively, this study demonstrates that CO2-activated RTN neurons are exquisitely sensitive to arousal state, which determines their contribution to alveolar ventilation in relation to arterial PCO2 Significance statement Respiratory chemoreceptors stimulate neural respiratory motor output to regulate arterial PCO2 and PO2, thereby maintaining optimal gas exchange. Central chemoreceptor neurons expressing Phox2b and Neuromedin B in the Retrotrapezoid Nucleus (RTN) are required for the hypercapnia ventilatory response. However, the dynamic activity of RTN neurons in conditions of normal and elevated carbon dioxide has not been described in unanesthetized conditions. Here, we use a genetically-encoded calcium indicator to demonstrate that RTN neurons exquisitely sensitivity to hypercapnia and variations in arousal and sleep-state in freely-behaving mice. This work has implications for understanding the central control of breathing across arousal-states, particularly during sleep and anesthesia.

Encoding manifolds constructed from grating responses organize responses to natural scenes across mouse cortical visual areas.

We have created "encoding manifolds" to reveal the overall responses of a brain area to a variety of stimuli. Encoding manifolds organize response properties globally: each point on an encoding manifold is a neuron, and nearby neurons respond similarly to the stimulus ensemble in time. We previously found, using a large stimulus ensemble including optic flows, that encoding manifolds for the retina were highly clustered, with each cluster corresponding to a different ganglion cell type. In contrast, the topology of the V1 manifold was continuous. Now, using responses of individual neurons from the Allen Institute Visual Coding-Neuropixels dataset in the mouse, we infer encoding manifolds for V1 and for five higher cortical visual areas (VISam, VISal, VISpm, VISlm, and VISrl). We show here that the encoding manifold topology computed only from responses to various grating stimuli is also continuous, not only for V1 but also for the higher visual areas, with smooth coordinates spanning it that include, among others, orientation selectivity and firing-rate magnitude. Surprisingly, the encoding manifold for gratings also provides information about natural scene responses. To investigate whether neurons respond more strongly to gratings or natural scenes, we plot the log ratio of natural scene responses to grating responses (mean firing rates) on the encoding manifold. This reveals a global coordinate axis organizing neurons' preferences between these two stimuli. This coordinate is orthogonal (i.e., uncorrelated) to that organizing firing rate magnitudes in VISp. Analyzing layer responses, a preference for gratings is concentrated in layer 6, whereas preference for natural scenes tends to be higher in layers 2/3 and 4. We also find that preference for natural scenes dominates the responses of neurons that prefer low (0.02 cpd) and high (0.32 cpd) spatial frequencies, rather than intermediate ones (0.04 to 0.16 cpd). Conclusion: while gratings seem limited and natural scenes unconstrained, machine learning algorithms can reveal subtle relationships between them beyond linear techniques.

Separate anterior paraventricular thalamus projections differentially regulate sensory and affective aspects of pain

The experience of pain is complex, involving both sensory and affective components, yet the underlying neural mechanisms remain elusive. Here, we show that formalin-induced pain behaviors coincide with increased responses in glutamatergic neurons within the anterior paraventricular nucleus of the thalamus (PVA). Furthermore, we describe non-overlapping subpopulations of PVAVgluT2 neurons involved in sensory and affective pain processing, whose activity varies across different pain states. Activating PVA glutamatergic neurons is sufficient to induce mechanical hypersensitivity and aversion behaviors, whereas suppression ameliorates formalin-induced pain. Furthermore, we identify the segregation of PVAVgluT2 projections to the bed nucleus of the stria terminalis (BNST) and nucleus accumbens (NAc), each influencing specific aspects of pain-like behavior. This finding provides an important insight into the mechanism of distinct components of pain, highlighting the pivotal role of PVA in mediating different aspects of pain-like behavior with distinct circuits.

The similarity and difference: response and molecular characteristics of peripheral sensory neurons associated with pain and itch

The similarity and difference: response and molecular characteristics of peripheral sensory neurons associated with pain and itch

MiR-30c-5p Gain and Loss of Function Modulate Sciatic Nerve Injury-Induced Nucleolar Stress Response in Dorsal Root Ganglia Neurons.

Neuropathic pain is a prevalent and debilitating chronic syndrome that is often resistant to treatment. It frequently arises as a consequence of damage to first-order nociceptive neurons in the lumbar dorsal root ganglia (DRG), with chromatolysis being the primary neuropathological response following sciatic nerve injury (SNI). Nevertheless, the function of miRNAs in modulating this chromatolytic response in the context of neuropathic pain remains unexplored. Our previous research demonstrated that the intracisternal administration of a miR-30c mimic accelerates the development of neuropathic pain, whereas the inhibition of miR-30c prevents pain onset and reverses established allodynia. In the present study, we sought to elucidate the role of miR-30c-5p in the pathogenesis of neuropathic pain, with a particular focus on its impact on DRG neurons following SNI. The organisation and ultrastructural changes in DRG neurons, particularly in the protein synthesis machinery, nucleolus, and Cajal bodies (CBs), were analysed. The results demonstrated that the administration of a miR-30c-5p mimic exacerbates chromatolytic damage and nucleolar stress and induces CB depletion in DRG neurons following SNI, whereas the administration of a miR-30c-5p inhibitor alleviates these effects. We proposed that three essential cellular responses-nucleolar stress, CB depletion, and chromatolysis-are the pathological mechanisms in stressed DRG neurons underlying neuropathic pain. Moreover, miR-30c-5p inhibition has a neuroprotective effect by reducing the stress response in DRG neurons, which supports its potential as a therapeutic target for neuropathic pain management. This study emphasises the importance of miR-30c-5p in neuropathic pain pathogenesis and supports further exploration of miRNA-based treatments.

Gut-first Parkinson's disease is encoded by gut dysbiome.

In Parkinson's patients, intestinal dysbiosis can occur years before clinical diagnosis, implicating the gut and its microbiota in the disease. Recent evidence suggests the gut microbiota may trigger body-first Parkinson Disease (PD), yet the underlying mechanisms remain unclear. This study aims to elucidate how a dysbiotic microbiome through intestinal immune alterations triggers PD-related neurodegeneration. To determine the impact of gut dysbiosis on the development and progression of PD pathology, wild-type male C57BL/6 mice were transplanted with fecal material from PD patients and age-matched healthy donors to challenge the gut-immune-brain axis. This study demonstrates that patient-derived intestinal microbiota caused midbrain tyrosine hydroxylase positive (TH +) cell loss and motor dysfunction. Ileum-associated microbiota remodeling correlates with a decrease in Th17 homeostatic cells. This event led to an increase in gut inflammation and intestinal barrier disruption. In this regard, we found a decrease in CD4 + cells and an increase in pro-inflammatory cytokines in the blood of PD transplanted mice that could contribute to an increase in the permeabilization of the blood-brain-barrier, observed by an increase in mesencephalic Ig-G-positive microvascular leaks and by an increase of mesencephalic IL-17 levels, compatible with systemic inflammation. Furthermore, alpha-synuclein aggregates can spread caudo-rostrally, causing fragmentation of neuronal mitochondria. This mitochondrial damage subsequently activates innate immune responses in neurons and triggers microglial activation. We propose that the dysbiotic gut microbiome (dysbiome) in PD can disrupt a healthy microbiome and Th17 homeostatic immunity in the ileum mucosa, leading to a cascade effect that propagates to the brain, ultimately contributing to PD pathophysiology. Our landmark study has successfully identified new peripheral biomarkers that could be used to develop highly effective strategies to prevent the progression of PD into the brain.

Convergent representation of values from tactile and visual inputs for efficient goal-directed behavior in the primate putamen

Animals can discriminate diverse sensory values with a limited number of neurons, raising questions about how the brain utilizes neural resources to efficiently process multi-dimensional inputs for decision-making. Here, we demonstrate that this efficiency is achieved by reducing sensory dimensions and converging towards the value dimension essential for goal-directed behavior in the putamen. Humans and monkeys performed tactile and visual value discrimination tasks while their neural responses were examined. Value information, whether originating from tactile or visual stimuli, was found to be processed within the human putamen using fMRI. Notably, at the single-neuron level in the macaque putamen, half of the individual neurons encode values independently of sensory inputs, while the other half selectively encode tactile or visual value. The responses of bimodal value neurons correlate with value-guided finger insertion behavior in both tasks, whereas modality-selective value neurons show task-specific correlations. Simulation using these neurons reveals that the presence of bimodal value neurons enables value discrimination with a significantly reduced number of neurons compared to simulations without them. Our data indicate that individual neurons in the primate putamen process different values in a convergent manner, thereby facilitating the efficient use of constrained neural resources for value-guided behavior.

Impairment of neuronal tyrosine phosphatase STEP worsens post-ischemic inflammation and brain injury under hypertensive condition

Hypertension is associated with poor outcome and higher mortality in patients with ischemic stroke. The impairment of adaptive vascular mechanisms under hypertensive condition compromises collateral blood flow after arterial occlusion in patients with acute ischemic stroke resulting in hypoperfusion. The increased oxidative stress caused by hypoperfusion is thought to be a trigger for the rapid evolution of ischemic infarct volume under hypertensive condition. However, the cellular factors and pathways that contribute to the exacerbation of ischemic brain injury under hypertensive condition is not yet understood. The current study reveals that predisposition to hypertension leads to basal loss of function of the neuron-specific tyrosine phosphatase STEP, which plays a crucial role in neuroprotection against excitotoxic insult. The findings further show that a mild ischemic insult in hypertensive rats triggers an early onset and sustained activation of the neuronal extracellular signal regulated kinase (ERK MAPK), a member of the mitogen activated protein kinase family and a substrate of STEP. This leads to rapid increase in the activation of neuronal NF-κB, expression of neuronal cyclooxygenase-2 and subsequent biosynthesis of the pro-inflammatory mediator prostaglandin E2, resulting in rapid morphological transformation of microglia to the pro-inflammatory state and subsequent exacerbation of ischemic brain injury. Restoration of STEP signaling with intravenous administration of a STEP-derived peptide mimetic reduces the pro-inflammatory response in neurons, activation of microglia, and ischemic brain injury. The findings suggest that the basal loss of STEP function under hypertensive condition contributes to the exacerbation of ischemic brain injury by enhancing post-ischemic inflammatory response. The study not only presents a novel role of STEP in regulating neuroimmune communication but also highlights the therapeutic potential of a STEP-mimetic in mitigating ischemic brain damage under hypertensive condition.

Theoretical framework for learning through structural plasticity

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pattern of activity of biological neural networks, including probability distributions of neuron firing rates, selectivity of the responses of single neurons to multiple stimuli, probabilistic connection rules, and noisy stimuli. More importantly, it describes the effects of stabilization, pruning, and reorganization of synaptic connections. This framework is used to compute the values of some relevant quantities used to characterize the learning and memory capabilities of the neuronal network in training and testing procedures as the number of training patterns and other model parameters vary. The results are then compared with those obtained through simulations with firing-rate-based neuronal network models. Published by the American Physical Society 2024

Bilateral Alignment of Receptive Fields in the Olfactory Cortex.

Each olfactory cortical hemisphere receives ipsilateral odor information directly from the olfactory bulb and contralateral information indirectly from the other cortical hemisphere. Since neural projections to the olfactory cortex are disordered and non-topographic, spatial information cannot be used to align projections from the two sides like in the visual cortex. Therefore, how bilateral information is integrated in individual cortical neurons is unknown. We have found, in mice, that the odor responses of individual neurons to selective stimulation of each of the two nostrils are significantly correlated, such that odor identity decoding optimized with information arriving from one nostril transfers very well to the other side. Nevertheless, these aligned responses are asymmetric enough to allow decoding of stimulus laterality. Computational analysis shows that such matched odor tuning is incompatible with purely random connections but is explained readily by Hebbian plasticity structuring bilateral connectivity. Our data reveal that despite the distributed and fragmented sensory representation in the olfactory cortex, odor information across the two hemispheres is highly coordinated.Significance statement Like other sense organs, animals typically have two nostrils, but how odor information from the two sides is combined to build bilateral olfactory representations remains largely unknown. Grimaud et al. find that the responses of neurons in the olfactory cortex in awake mice to odors presented separately to the ipsilateral or contralateral nostril are significantly correlated, beyond chance. Such aligned responses could arise from Hebbian plasticity in interhemispheric connections that relies on common odor experiences across the two nostrils. While responses are correlated, the remaining asymmetries in responses to the two nostrils allowed decoding of stimulus laterality. This study points to unexpected order in an olfactory circuit and prompts future work on how olfactory experience can shape interhemispheric information integration.

Unaltered Responses of Distal Motor Neurons to Non-Targeted Thoracic Spinal Cord Stimulation in Chronic Pain Patients.

Spinal cord stimulation (SCS) represents an established interventional pain therapeutic; however, the SCS effects of SCS waveforms on motor neuron recruitment of the lower limbs of chronic pain patients remain largely unknown. We investigated these effects by performing isometric ankle-dorsal flexions at varying force levels under four SCS conditions: SCS Off (1week), burst SCS (40Hz), SCS Off (acute), and tonic SCS (130Hz). Muscle activity was recorded via high-density surface electromyography (64-electrode grid) on the tibialis anterior muscle. Motor unit action (MUs) potentials were analyzed for recruitment and de-recruitment thresholds, discharge rate, inter-spike interval, and common synaptic input. In this prospective study, we included nine patients (five females; four males; mean age 59years) with chronic pain treated with thoracic (Th7-Th8) epidural spinal stimulation. A total of 97 MUs were found for 15% maximal voluntary torque (MVT) and 83 for 30%MVT, an average of 10.8±3.7 for 15%MVT and 10.4±3.5 for 30%MVT. While a few subject-specific variations were observed, our study suggests that the different SCS frequencies applied do not significantly influence motor unit discharge characteristics in the TA muscle among the participants (p values at 15%MVT were 0.586 (Chi2=1.933), 0.737 (Chi2=1.267), 0.706 (Chi2=1.4) and 0.586 (Chi2=1.933), respectively. The p values of the Friedman test at 30%MVT were 0.896 (Chi2=0.6), 0.583 (Chi2=1.95), 0.896 (Chi2=0.6) and 0.256 (Chi2=4.05). No significant difference was found for the different stimulation types for the delta (0-5Hz), alpha (5-12Hz), and beta (15-30Hz) bands at both force levels. In summary, we did not observe any changes in motor unit oscillatory activity at any low and high bandwidths, indicating that SCS using different waveforms (tonic/burst) does not significantly influence motor neuron recruitment for non-motor individuals with chronic pain.

Freezing of movements and its correspondence with MLG1 neurons response to looming stimuli in the crab Neohelice.

Upon visually detecting a moving predator animals often freeze, i.e. stop moving, to minimize being uncovered and to gather detailed information of the object's movements and properties. In certain conditions the freezing behavior can be enough to avoid a predatory menace but, when the risk is high or increases to a higher level, animals switch strategy and engage in an escape response. The neural bases underlying escape responses to visual stimuli are extensively investigated both in vertebrates and arthropods. However, those involved in freezing behaviors are much less studied. Here, we investigated the freezing behavior displayed by the crab Neohelice granulata when confronted with a variety of looming stimuli simulating objects of distinct sizes approaching on a collision course at different speeds. The experiments were performed in a treadmill-like device. Animals engaged in exploratory walks respond to the looming stimulus with freezing followed by escaping. The analysis of the stimulus optical variables shows that regardless of the looming dynamic, the freezing decision is made when the angular size of the object increases by 1.4°. In vivo intracellular recording responses of Monostratified Lobula Giant Neurons (MLG1) to the same looming stimuli show that the freezing times correlate with the times predicted by a hypothetical spike counter of this neuron.

Activation of ionotropic and group I metabotropic glutamate receptors stimulates kisspeptin neuron activity in mice.

Different populations of hypothalamic kisspeptin (KISS1) neurons located in the rostral periventricular area of the third ventricle (RP3V) and arcuate nucleus (ARC) are thought to generate the sex-specific patterns of gonadotropin secretion. These neuronal populations integrate gonadal sex steroid feedback with internal and external cues relayed via the actions of neurotransmitters and neuropeptides. The excitatory amino acid neurotransmitter glutamate, the main excitatory neurotransmitter in the brain, plays a role in regulating gonadotropin secretion, at least partially through engaging KISS1 signaling. The expression and function of individual glutamate receptor subtypes in KISS1 neurons, however, are not well characterized. Here, we used GCaMP-based calcium imaging and patch-clamp electrophysiology to assess the impact of activating individual ionotropic (iGluR) and group I metabotropic (mGluR) glutamate receptors on KISS1 neuron activity in the mouse RP3V and ARC. Our results indicate that activation of all iGluR subtypes and of group I mGluRs, likely mGluR1, consistently drives activity in the majority of KISS1 neurons within the RP3V and ARC of males and females. Our results also revealed, somewhat unexpectedly, sex- and region-specific differences. Indeed, activating (S)-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) type iGluRs evoked larger responses in female ARCKISS1 neurons than in their male counterparts whereas activating group I mGluRs induced larger responses in RP3VKISS1 neurons than in ARCKISS1 neurons in females. Together, our findings suggest that glutamatergic neurotransmission in KISS1 neurons, and its impact on the activity of these cells, might be sex- and region-dependent in mice.

Netrin-1 stimulated axon growth requires the polyglutamylase TTLL1.

In the developing brain, neurons extend an axonal process through a complex and changing environment to form synaptic connections with the correct targets in response to extracellular cues. Microtubule and actin filaments provide mechanical support and drive axon growth in the correct direction. The axonal cytoskeleton responds to extracellular guidance cues. Netrin-1 is a multifunctional guidance cue that can induce alternate responses based on the bound receptor. The mechanism by which actin responds to Netrin-1 is well described. However, how Netrin-1 influences the microtubule cytoskeleton is less understood. Appropriate microtubule function is required for axon pathfinding, as mutations in tubulin phenocopy axon crossing defects of Netrin-1 and DCC mutants. Microtubule stabilization is required for attractive guidance cue response. The C-terminal tails of microtubules can be post-translationally modified. Post-translational modifications (PTMs) help control the microtubule cytoskeleton. We measured polyglutamylation in cultured primary mouse cortical neurons before and after Netrin-1 stimulation. We used immunohistochemistry to measure how Netrin-1 stimulation alters microtubule-associated protein localization. Next, we manipulated TTLL1 to determine if Netrin-1-induced axon growth and MAP localization depend on polyglutamylation levels. In this study, we investigated if Netrin-1 signaling alters microtubule PTMs in the axon. We found that microtubule polyglutamylation increases after Netrin-1 stimulation. This change in polyglutamylation is necessary for Netrin-1-induced axonal growth rate increases. We next determined that MAP1B and DCX localization changes in response to Netrin-1. These proteins can both stabilize the microtubule cytoskeleton and may be responsible for Netrin-1-induced growth response in neurons. The changes in DCX and MAP1B depend on TTLL1, a protein responsible for microtubule polyglutamylation.

Interpretable logical-probabilistic approximation of neural networks

The paper proposes the approximation of DNNs by replacing each neuron by the corresponding logical-probabilistic neuron. Logical-probabilistic neurons learn their behavior based on the responses of initial neurons on incoming signals and discover all logical-probabilistic causal relationships between the input and output. These logical-probabilistic causal relationships are, in a certain sense, most precise – it was proved in the previous works that they are theoretically (when probability is known) can predict without contradictions. The resulting logical-probabilistic neurons are interconnected by the same connections as the initial neurons after replacing their signals on true/false. The resulting logical-probabilistic neural network produces its own predictions that approximate the predictions of the original DNN. Thus, we obtain an interpretable approximation of DNN, which also allows tracing of DNN by tracing its excitations through the causal relationships. This approximation of DNN is a Distillation method such as Model Translation, which train alternative smaller interpretable models that mimics the total input/output behavior of DNN. It is also locally interpretable and explains every particular prediction. It explains the sequences of logical probabilistic causal relationships that infer that prediction and also show all features that took part in this prediction with the statistical estimation of their significance. Experimental results on approximation accuracy of all intermedia neurons, output neurons and softmax output of DNN are presented, as well as the accuracy of obtained logical-probabilistic neural network. From the practical point of view, interpretable transformation of neural networks is very important for the hybrid artificial intelligent systems, where neural networks are integrated with the symbolic methods of AI. As a practical application we consider smart city.

Lnc-Pim1 Promotes Neurite Outgrowth and Regeneration of Neuron-Like Cells Following ACR-Induced Neuronal Injury.

Decreased regenerative capacity of central nervous system neurons is the main cause for failure of damaged neuron regeneration and functional recovery. Long noncoding RNAs (lncRNAs) are abundant in mammalian transcriptomes, and many time- and tissue-specific lncRNAs are thought to be closely related to specific biological functions. The promoting effect of Pim-1 gene on neural differentiation and regeneration has been documented, but the effect and mechanism of its neighbor gene Lnc-Pim1 in regulating the response of central neurons to injury remain unclear. RT-PCR in this study demonstrated that the expression of Lnc-Pim1 was upregulated in acrylamide (ACR)-induced neuronal injury. FISH and nucleus-cytoplasmic assay demonstrated that Lnc-Pim1 was mainly expressed in the neuron cytoplasm, with a small amount in the nucleus. Western blot analysis proved that Lnc-Pim1 overexpression induced by the lentivirus vector could promote neurite outgrowth in Neuro-2a cells by activating the Erk1/2 signal pathway, and improve neurite regeneration of injured neurons by upregulating GAP-43 and β-Ⅲ tubulin protein expression. However, silencing Lnc-Pim1 expression by interfering RNA could effectively downregulate the GAP-43 and β-Ⅲ tubulin protein expression, and inhibit neurite growth of neurons. In addition, CHIRP-MS was performed to identify several potential targets of Lnc-Pim1 involved in the regulation of neurite regeneration of injured neurons. In conclusion, our study demonstrated that Lnc-Pim1 is a potential lnc-RNA, playing an important role in regulating central nerve regeneration.

Transcriptional response of primary hippocampal neurons following exposure to 3.0 GHz radiofrequency electromagnetic fields.

Exposure to radiofrequency (RF) electromagnetic fields (EMF) has been associated with the modulation of neuronal electrophysiology and synaptic plasticity. Given the potential of these changes to coincide with alterations in gene expression, this study investigated whether a transcriptional response would occur in neurons following exposure to RF-EMF, under both thermal and nonthermal conditions. Rat primary hippocampal neurons (PHNs) underwent either a single (one-time) or a multiple (3-times, once a day) exposures to RF-EMF (3.0 GHz, CW) at two different mean specific absorption rate (SAR) values of 0.57 W/kg or 5.91 W/kg, which induced a temperature change (ΔT °C) of approximately 0.3°C or 3.6°C, respectively. Alteration in transcription in the RF-EMF-exposed PHNs versus the sham counterparts was assessed at 0, 4, and 24 h postexposure via high-throughput RNA sequencing using Illumina HiSeq. 2000. A total of 20 differentially expressed genes (DEGs) exhibited significant upregulation due to RF-EMF exposure, observed only with the high SAR dose that induced a thermal rise. However, the expression of these DEGs was not significant at 24 h postexposure. Our findings confirmed a lack of nonthermal effects on gene expression under low RF-EMF exposure conditions as evaluated. Additionally, the results indicated a slight thermal effect of exposures at the dose nearing the standards threshold of 4 W/kg; however, the effect appeared to be transient. The study suggests that RF-EMF exposures at a level close to the standards threshold, despite inducing mild temperature elevations (i.e., 3-5°C above normal), would not trigger biologically critical cellular changes.

Recurrent cortical networks encode natural sensory statistics via sequence filtering.

Recurrent neural networks can generate dynamics, but in sensory cortex it has been unclear if any dynamic processing is supported by the dense recurrent excitatory-excitatory network. Here we show a new role for recurrent connections in mouse visual cortex: they support powerful dynamical computations, but by filtering sequences of input instead of generating sequences. Using two-photon optogenetics, we measure neural responses to natural images and play them back, finding inputs are amplified when played back during the correct movie dynamic context- when the preceding sequence corresponds to natural vision. This sequence selectivity depends on a network mechanism: earlier input patterns produce responses in other local neurons, which interact with later input patterns. We confirm this mechanism by designing sequences of inputs that are amplified or suppressed by the network. These data suggest recurrent cortical connections perform predictive processing, encoding the statistics of the natural world in input-output transformations.

Combinatorial responsiveness of single chemosensory neurons to external stimulation of mouse explants revealed by DynamicNeuronTracker.

Calcium fluorescence imaging enables us to investigate how individual neurons of live animals encode sensory input or drive specific behaviors. Extracting and interpreting large-scale neuronal activity from imaging data are crucial steps in harnessing this information. A significant challenge arises from uncorrectable tissue deformation, which disrupts the effectiveness of existing neuron segmentation methods. Here, we propose an open-source software, DynamicNeuronTracker (DyNT), which generates dynamic neuron masks for deforming and/or incompletely registered 3D calcium imaging data using patch-matching iterations. We demonstrate that DyNT accurately tracks densely populated neurons, whereas a widely used static segmentation method often produces erroneous masks. DyNT also includes automated statistical analyses for interpreting neuronal responses to multiple sequential stimuli. We applied DyNT to analyze the responses of pheromone-sensing neurons in mice to controlled stimulation. We found that four bile acids and four sulfated steroids activated 15 subpopulations of sensory neurons with distinct combinatorial response profiles, revealing a strong bias toward detecting sulfated estrogen and pregnanolone.