Input Zone-Selective Dysrhythmia in Motor Thalamus after Dopamine Depletion.

The cerebral cortex, basal ganglia and motor thalamus form circuits important for purposeful movement. In Parkinsonism, basal ganglia neurons often exhibit dysrhythmic activity during, and with respect to, the slow (∼1 Hz) and beta-band (15-30 Hz) oscillations that emerge in cortex in a brain state-dependent manner. There remains, however, a pressing need to elucidate the extent to which motor thalamus activity becomes similarly dysrhythmic after dopamine depletion relevant to Parkinsonism. To address this, we recorded single-neuron and ensemble outputs in the basal ganglia-recipient zone (BZ) and cerebellar-recipient zone (CZ) of motor thalamus in anesthetized male dopamine-intact rats and 6-OHDA-lesioned rats during two brain states, respectively defined by cortical slow-wave activity and activation. Two forms of thalamic input zone-selective dysrhythmia manifested after dopamine depletion: (1) BZ neurons, but not CZ neurons, exhibited abnormal phase-shifted firing with respect to cortical slow oscillations prevalent during slow-wave activity; and (2) BZ neurons, but not CZ neurons, inappropriately synchronized their firing and engaged with the exaggerated cortical beta oscillations arising in activated states. These dysrhythmias were not accompanied by the thalamic hypoactivity predicted by canonical firing rate-based models of circuit organization in Parkinsonism. Complementary recordings of neurons in substantia nigra pars reticulata suggested that their altered activity dynamics could underpin the BZ dysrhythmias. Finally, pharmacological perturbations demonstrated that ongoing activity in the motor thalamus bolsters exaggerated beta oscillations in motor cortex. We conclude that BZ neurons are selectively primed to mediate the detrimental influences of abnormal slow and beta-band rhythms on circuit information processing in Parkinsonism.SIGNIFICANCE STATEMENT Motor thalamus neurons mediate the influences of basal ganglia and cerebellum on the cerebral cortex to govern movement. Chronic depletion of dopamine from the basal ganglia causes some symptoms of Parkinson's disease. Here, we elucidate how dopamine depletion alters the ways motor thalamus neurons engage with two distinct oscillations emerging in cortico-basal ganglia circuits in vivo We discovered that, after dopamine depletion, neurons in the thalamic zone receiving basal ganglia inputs are particularly prone to becoming dysrhythmic, changing the phases and/or synchronization (but not rate) of their action potential firing. This bolsters cortical dysrhythmia. Our results provide important new insights into how aberrant rhythmicity in select parts of motor thalamus could detrimentally affect neural circuit dynamics and behavior in Parkinsonism.

Risk factors associated with hospitalization in patients with asymptomatic or mild COVID-19 in public accommodation facilities in Tokyo.

INTRODUCTION: In Japan, patients with coronavirus disease 2019 (COVID-19) who do not require medical intervention are provided care in recovery accommodation facilities (RAFs). However, some patients may require hospitalization if their symptoms become more severe during their stay. We conducted an observational study using epidemiological data of patients with COVID-19 admitted to RAFs in Tokyo. METHODS: This was an observational cohort study using data from COVID-19 patients admitted to one of the RAFs in Tokyo from December 2020 to November 2021. Admissions to the facilities were limited to patients with asymptomatic or mild COVID-19 with no underlying disease or at least stable underlying disease at the time of admission. Patients were hospitalized when they required oxygen administration or when they had, or persistent fever, or severe respiratory symptoms. We evaluated the association between hospitalization and the risk factors for hospitalization using a Cox regression model. RESULTS: The number of patients with COVID-19 admitted to the RAF was 6176. The number of hospitalized patients was 393 (6.4%), and the median length of stay was 5.50 days (IQR: 4.50, 6.50). In the Cox regression analysis, the hazard ratio increased with age and was significantly higher among patients aged >60 years (HR = 10.23, 95% CI: 6.72-15.57) than those in other age groups. This trend is similar to that observed in the sensitivity analysis. CONCLUSION: Patients with diabetes, the elderly, obesity, and medications for gout and psychiatric diseases may be at a high risk of hospitalization. In particular, an age over 60 years was strongly associated with hospitalization.

Enhanced desensitization followed by unusual resensitization in GABAA receptors in phospholipase C-related catalytically inactive protein-1/2 double-knockout mice.

Phospholipase C-related catalytically inactive proteins (PRIP-1/2) are previously reported to be involved in the membrane trafficking of GABAA receptor (GABAAR) and the regulation of intracellular Ca(2+) stores. GABAAR-mediated currents can be regulated by the intracellular Ca(2+). However, in PRIP-1/2 double-knockout (PRIP-DKO) mice, it remains unclear whether the kinetic properties of GABAARs are modulated by the altered regulation of intracellular Ca(2+) stores. Here, we investigated whether GABAAR currents (IGABA) evoked by GABA puff in layer 3 (L3) pyramidal cells (PCs) of the barrel cortex are altered in PRIP-DKO mice. The deletion of PRIP-1/2 enhanced the desensitization of IGABA but induced a hump-like tail current (tail-I) at the GABA puff offset. IGABA and the hump-like tail-I were suppressed by GABAAR antagonists. The enhanced desensitization of IGABA and the hump-like tail-I in PRIP-DKO PCs were mediated by increases in the intracellular Ca(2+) concentration and were largely abolished by a calcineurin inhibitor and ruthenium red. Calcium imaging revealed that Ca(2+)-induced Ca(2+) release (CICR) and subsequent store-operated Ca(2+) entry (SOCE) are more potent in PRIP-DKO PCs than in wild-type PCs. A mathematical model revealed that a slowdown of GABA-unbinding rate and an acceleration of fast desensitization rate by enhancing its GABA concentration dependency are involved in the generation of hump-like tail-Is. These results suggest that in L3 PCs of the barrel cortex in PRIP-DKO mice, the increased calcineurin activity due to the potentiated CICR and SOCE enhances the desensitization of GABAARs and slows the GABA-unbinding rate, resulting in their unusual resensitization following removal of GABA.

Functional Diversity of Dopamine Axons in Prefrontal Cortex During Classical Conditioning.

Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

Functional diversity of dopamine axons in prefrontal cortex during classical conditioning.

Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

A mathematical model of negative covariability of inter-columnar excitatory synaptic actions caused by presynaptic inhibition.

We previously showed that a positive covariability between intracortical excitatory synaptic actions onto the two layer three pyramidal cells (PCs) located in mutually adjacent columns is changed into a negative covariability by column-wise presynaptic inhibition of intracortical inputs, implicated as a basis for the desynchronization of inter-columnar synaptic actions. Here we investigated how the inter-columnar desynchronization is modulated by the strength of presynaptic inhibition or other factors, by using a mathematical model. Based on our previous findings on the paired-pulse depression (PPD) of intracortical excitatory postsynaptic currents (EPSCs) evoked in PCs located in the stimulated home column (HC) but no PPD in PCs located in the adjacent column (AC), a mathematical model of synaptic connections between PCs and inhibitory interneurons was constructed. When the paired-pulse ratio (PPR) was decreased beyond 0.80, the correlation coefficient between the two second EPSC amplitudes in the paired PCs located in the HC and AC and that in the paired PCs located in the same HC exhibited opposite changes, and reached a global negative maximum and local positive maximum, respectively, at almost the same PPR (0.40). At this PPR, the desynchronization between the two cell assemblies in mutually adjacent columns would be maximized. These positive and negative covariabilities were not produced without background oscillatory synchronization across columns and were enhanced by increasing the synchronization magnitude, indicating that the synchronization leads to the desynchronization. We propose that a slow oscillatory synchronization across columns may emerge following the liberation from the column-wise presynaptic inhibition of inter-columnar synaptic inputs.

Parvalbumin-producing cortical interneurons receive inhibitory inputs on proximal portions and cortical excitatory inputs on distal dendrites.

To examine inputs to parvalbumin (PV)-producing interneurons, we generated transgenic mice expressing somatodendritic membrane-targeted green fluorescent protein specifically in the interneurons, and completely visualized their dendrites and somata. Using immunolabeling for vesicular glutamate transporter (VGluT)1, VGluT2, and vesicular GABA transporter, we found that VGluT1-positive terminals made contacts 4- and 3.1-fold more frequently with PV-producing interneurons than VGluT2-positive and GABAergic terminals, respectively, in the primary somatosensory cortex. Even in layer 4, where VGluT2-positive terminals were most densely distributed, VGluT1-positive inputs to PV-producing interneurons were 2.4-fold more frequent than VGluT2-positive inputs. Furthermore, although GABAergic inputs to PV-producing interneurons were as numerous as VGluT2-positive inputs in most cortical layers, GABAergic inputs clearly preferred the proximal dendrites and somata of the interneurons, indicating that the sites of GABAergic inputs were more optimized than those of VGluT2-positive inputs. Simulation analysis with a PV-producing interneuron model compatible with the present morphological data revealed a plausible reason for this observation, by showing that GABAergic and glutamatergic postsynaptic potentials evoked by inputs to distal dendrites were attenuated to 60 and 87%, respectively, of those evoked by somatic inputs. As VGluT1-positive and VGluT2-positive axon terminals were presumed to be cortical and thalamic glutamatergic inputs, respectively, cortical excitatory inputs to PV-producing interneurons outnumbered the thalamic excitatory and intrinsic inhibitory inputs more than two-fold in any cortical layer. Although thalamic inputs are known to evoke about two-fold larger unitary excitatory postsynaptic potentials than cortical ones, the present results suggest that cortical inputs control PV-producing interneurons at least as strongly as thalamic inputs.

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Shiga University's endeavor to promote human resources development for data science in Japan.

In 2017, Shiga University established the Faculty of Data Science, which was the first faculty in Japan specializing in data science and statistics. This paper reports the Faculty's historical context, curricula, and collaboration with industry and other universities. The career paths of the graduates and the massive open online courses and textbooks provided by the Faculty of Data Science are also summarized.

The Nature of Noradrenergic Volume Transmission From Locus Coeruleus to Brainstem Mesencephalic Trigeminal Sensory Neurons.

Noradrenergic neurons in the locus coeruleus (LC) release noradrenaline (NA) that acts via volume transmission to activate extrasynaptic G-protein coupled receptors (GPCRs) in target cells throughout the brain. As the closest projection, the dorsal LC laterally adjoins the mesencephalic trigeminal nucleus (MTN), in which proprioceptive primary sensory neurons innervating muscle spindles of jaw-closing muscles are exceptionally located. MTN neurons express α2-adrenergic receptors (α2-ARs) and display hyperpolarization-activated cyclic nucleotide-gated (HCN) currents (Ihs), which is downregulated by α2-AR activation. To quantify the activity-dependent outcome of volume transmission of NA from LC to MTN, we investigated how direct LC activation inhibits Ih in MTN neurons by performing dual whole-cell recordings from LC and MTN neurons. Repetition of 20 Hz spike-train evoked with 1-s current-pulse in LC neurons every 30 s resulted in a gradual decrease in Ih evoked every 30 s, revealing a Hill-type relationship between the number of spike-trains in LC neurons and the degree of Ih inhibition in MTN neurons. On the other hand, when microstimulation was applied in LC every 30 s, an LC neuron repeatedly displayed a transient higher-frequency firing followed by a tonic firing at 5-10 Hz for 30 s. This subsequently caused a similar Hill-type inhibition of Ih in the simultaneously recorded MTN neuron, but with a smaller Hill coefficient, suggesting a lower signal transduction efficacy. In contrast, 20 Hz activity induced by a 1-s pulse applied every 5-10 s caused only a transient facilitation of Ih inhibition followed by a forced termination of Ih inhibition. Thus, the three modes of LC activities modulated the volume transmission to activate α2-adrenergic GPCR to differentially inhibit Ih in MTN neurons.

Multistable attractors in a network of phase oscillators with three-body interactions.

Three-body interactions have been found in physics, biology, and sociology. To investigate their effect on dynamical systems, as a first step, we study numerically and theoretically a system of phase oscillators with a three-body interaction. As a result, an infinite number of multistable synchronized states appear above a critical coupling strength, while a stable incoherent state always exists for any coupling strength. Owing to the infinite multistability, the degree of synchrony in an asymptotic state can vary continuously within some range depending on the initial phase pattern.

Inter-Brain Synchronization During Sandplay Therapy: Individual Analyses.

Interactions between the client (Cl) and therapist (Th) evolve therapeutic relationships in psychotherapy. An interpersonal link or therapeutic space is implicitly developed, wherein certain important elements are expressed and shared. However, neural basis of psychotherapy, especially of non-verbal modalities, have scarcely been explored. Therefore, we examined the neural backgrounds of such therapeutic alliances during sandplay, a powerful art/play therapy technique. Real-time and simultaneous measurement of hemodynamics was conducted in the prefrontal cortex (PFC) of Cl-Th pairs participating in sandplay and subsequent interview sessions through multichannel near-infrared spectroscopy. As sandplay is highly individualized, and no two sessions and products (sandtrays) are the same, we expected variation in interactive patterns in the Cl-Th pairs. Nevertheless, we observed a statistically significant correlation between the spatio-temporal patterns in signals produced by the homologous regions of the brains. During the sandplay condition, significant correlations were obtained in the lateral PFC and frontopolar (FP) regions in the real Cl-Th pairs. Furthermore, a significant correlation was observed in the FP region for the interview condition. The correlations found in our study were explained as a "remote" synchronization (i.e., unconnected peripheral oscillators synchronizing through a hub maintaining free desynchronized dynamics) between two subjects in a pair, possibly representing the neural foundation of empathy, which arises commonly in sandplay therapy (ST).

Low Cycle Fatigue Characteristics of Oxygen-Free Copper for Electric Power Equipment.

The effect of heat treatment on tensile and low cycle fatigue properties of the oxygen-free copper for electric power equipment was investigated. The heat treatment at 850 °C for 20 min, which corresponds to the vacuum brazing process, caused the grain growth and relaxation of strain by recrystallization, and thus, the residual stress in the oxygen-free copper was reduced. The tensile strength and 0.2% proof stress were decreased, and elongation was increased by the heat treatment accompanying recrystallization. The plastic strain in the heat-treated specimen was increased compared with that in the untreated specimen under the same stress amplitude condition, and thus, the low cycle fatigue life of the oxygen-free copper was degraded by the heat treatment. Striation was observed in the crack initiation area of the fractured surface in the case of the stress amplitude less than 100 MPa regardless of the presence of the heat treatment. With an increase in the stress amplitude, the river pattern and the quasicleavage fracture were mainly observed in the fracture surfaces of the untreated specimens, and they were observed with striations in the fracture surfaces of the heat-treated ones. The result of the electron backscattered diffraction (EBSD) analysis showed that the grain reference orientation deviation (GROD) map was confirmed to be effective to investigate the fatigue damage degree in the grain by low cycle fatigue. In addition, the EBSD analysis revealed that the grains were deformed, and the GROD value reached approximately 28° in the fractured areas of heat-treated specimens after the low cycle fatigue test.

Money flow network among firms' accounts in a regional bank of Japan.

In this study, we investigate the flow of money among bank accounts possessed by firms in a region by employing an exhaustive list of all the bank transfers in a regional bank in Japan, to clarify how the network of money flow is related to the economic activities of the firms. The network statistics and structures are examined and shown to be similar to those of a nationwide production network. Specifically, the bowtie analysis indicates what we refer to as a "walnut" structure with core and upstream/downstream components. To quantify the location of an individual account in the network, we used the Hodge decomposition method and found that the Hodge potential of the account has a significant correlation to its position in the bowtie structure as well as to its net flow of incoming and outgoing money and links, namely the net demand/supply of individual accounts. In addition, we used non-negative matrix factorization to identify important factors underlying the entire flow of money; it can be interpreted that these factors are associated with regional economic activities. One factor has a feature whereby the remittance source is localized to the largest city in the region, while the destination is scattered. The other factors correspond to the economic activities specific to different local places. This study serves as a basis for further investigation on the relationship between money flow and economic activities of firms.

Low-dimensional dynamics of phase oscillators driven by Cauchy noise.

Phase oscillator systems with global sine coupling are known to exhibit low-dimensional dynamics. In this paper, such characteristics are extended to phase oscillator systems driven by Cauchy noise. The low-dimensional dynamics solution agreed well with the numerical simulations of noise-driven phase oscillators in the present study. The low-dimensional dynamics of identical oscillators with Cauchy noise coincided with those of heterogeneous oscillators with Cauchy-distributed natural frequencies. This allows for the study of noise-driven identical oscillator systems through heterogeneous oscillators without noise and vice versa.

Effect of recurrent infomax on the information processing capability of input-driven recurrent neural networks.

Reservoir computing is a framework for exploiting the inherent transient dynamics of recurrent neural networks (RNNs) as a computational resource. On the basis of this framework, much research has been conducted to evaluate the relationship between the dynamics of RNNs and the RNNs' information processing capability. In this study, we present a detailed analysis of the information processing capability of an RNN optimized by recurrent infomax (RI), an unsupervised learning method that maximizes the mutual information of RNNs by adjusting the connection weights of the network. The results indicate that RI leads to the emergence of a delay-line structure and that the network optimized by the RI possesses a superior short-term memory, which is the ability to store the temporal information of the input stream in its transient dynamics.

Estimation of the percentages of undiagnosed patients of the novel coronavirus (SARS-CoV-2) infection in Hokkaido, Japan by using birth-death process with recursive full tracing.

Estimating the percentages of undiagnosed and asymptomatic patients is essential for controlling the outbreak of SARS-CoV-2, and for assessing any strategy for controlling the disease. In this paper, we propose a novel analysis based on the birth-death process with recursive full tracing. We estimated the numbers of undiagnosed symptomatic patients and the lower bound of the number of total infected individuals per diagnosed patient before and after the declaration of the state of emergency in Hokkaido, Japan. The median of the estimated number of undiagnosed symptomatic patients per diagnosed patient decreased from 1.7 to 0.77 after the declaration, and the median of the estimated lower bound of the number of total infected individuals per diagnosed patient decreased from 4.2 to 2.4. We will discuss the limitations and possible expansions of the model.

Overlapping Projections of Neighboring Direct and Indirect Pathway Neostriatal Neurons to Globus Pallidus External Segment.

Indirect pathway medium-sized spiny neurons (iMSNs) in the neostriatum are well known to project to the external segment of the globus pallidus (GPe). Although direct MSNs (dMSNs) also send axon collaterals to the GPe, it remains unclear how dMSNs and iMSNs converge within the GPe. Here, we selectively labeled neighboring dMSNs and iMSNs with green and red fluorescent proteins using an adeno-associated virus vector and examined axonal projections of dMSNs and iMSNs to the GPe in mice. Both dMSNs and iMSNs formed two axonal arborizations displaying topographical projections in the dorsoventral and mediolateral planes. iMSNs displayed a wider and denser axon distribution, which included that of dMSNs. Density peaks of dMSN and iMSN axons almost overlapped, revealing convergence of dMSN axons in the center of iMSN projection fields. These overlapping projections suggest that dMSNs and iMSNs may work cooperatively via interactions within the GPe.

Focal inputs are a potential origin of local field potential (LFP) in the brain regions without laminar structure.

Current sinks and sources spatially separated between the apical and basal dendrites have been believed to be essential in generating local field potentials (LFPs). According to this theory, LFPs would not be large enough to be observed in the regions without laminar structures, such as striatum and thalamus. However, LFPs are experimentally recorded in these regions. We hypothesized that focal excitatory input induces a concentric current sink and source generating LFPs in these regions. In this study, we tested this hypothesis by the numerical simulations of multicompartment neuron models and the analysis of simplified models. Both confirmed that focal excitatory input can generate LFPs on the order of 0.1 mV in a region without laminar structures. The present results suggest that LFPs in subcortical nuclei indicate localized excitatory input.

Optimal weighted networks of phase oscillators for synchronization.

The phase order parameter of oscillators on a network is optimized using two different sets of constraints. First, the maximization is achieved by adjusting the coupling strengths among the oscillators without changing the total coupling strength and the natural frequencies of the oscillators. This optimization reveals that a stronger weight tends to be assigned to a connection between two oscillators with greatly different natural frequencies. Second, we vary both coupling strengths and natural frequencies while maximizing the phase order and minimizing the penalty function which prevents the natural frequencies of the oscillators from taking the same value. This optimization reveals that a large total coupling strength makes oscillators take two natural frequencies (two-group state), whereas a small total coupling strength facilitates the convergence of natural frequencies to one single value (one-group state). Small and large penalty parameters make the optimized network take the one- and two-group states, respectively. This phase transition is observed in all-to-all, lattice, and scale-free networks although the clustering coefficient of the strongest links in the optimized network reflects the difference of the underlying network topologies.