Neuronal cell body analysis is crucial for quantifying changes in neuronal sizes under different physiological and pathologic conditions. Neuronal cell body detection and segmentation mainly rely on manual or pseudo-manual annotations. Manual annotation of neuronal boundaries is time-consuming, requires human expertise, and has intra/interobserver variances. Also, determining where the neuron’s cell body ends and where the axons and dendrites begin is taxing. We developed a deep-learning-based approach that uses a state-of-the-art shifted windows (Swin) transformer for automated, reproducible, fast, and unbiased 2D detection and segmentation of neuronal somas imaged in mouse acute brain slices by multiphoton microscopy. We tested our Swin algorithm during different experimental conditions of low and high signal fluorescence. Our algorithm achieved a mean Dice score of 0.91, a precision of 0.83, and a recall of 0.86. Compared with two different convolutional neural networks, the Swin transformer outperforme...

Creativity can be driven by negative intentions, and this is called malevolent creativity (MC). It is a type of creativity that serves antisocial purposes and deliberately leads to harmful or immoral results. A possible classification indicates that there are three kinds of MC in daily life: hurting people, lying, and playing tricks. This study aimed to explore similar and distinct neural substrates underlying these different kinds of MC idea generation. The participants were asked to perform different MC tasks, and their neural responses were recorded using a functional near-infrared spectroscopy device. The findings revealed that most regions within the prefrontal and temporal lobes [e.g., the right dorsolateral prefrontal cortex (rDLPFC), and right angular gyrus] were involved in the three MC tasks. However, the right frontopolar cortex (rFPC) was more activated and less coupled with the rDLPFC and right precuneus during the lying task than during the other tasks. Thus, rFPC may play an important role i...

In neurophysiology, achieving precise correlation between physiological responses and anatomic structures is a significant challenge. Therefore, the accuracy of the electrode marking method is crucial. In this study, we describe a tungsten-deposition method, in which tungsten oxide is generated by applying biphasic current pulses to conventional tungsten electrodes. The electrical current used was 40–50 μA, which is similar to that used in electrical microstimulation experiments. The size of the markings ranged from 10 to 100 μm, corresponding to the size of the electrode tip, which is smaller than that of existing marking methods. Despite the small size of the markings, detection is easy as the marking appears in bright red under dark-field observation after Nissl staining. This marking technique resulted in low tissue damage and was maintained in vivo for at least two years. The feasibility of this method was tested in mouse and macaque brains.

The cerebellum communicates with brain areas critically involved in control of goal-directed behaviors including the prefrontal and orbitofrontal cortices and midbrain and basal ganglia structures. In particular, the posterior cerebellum is important for cognitive flexibility and has been implicated in alcohol and drug-related memory. We hypothesized that the cerebellum, through its multiple connections to reward-related brain circuitry, regulates alcohol consumption. To test this, we expressed inhibitory designer receptors exclusively activated by designer drugs (DREADDs) in molecular layer interneurons (MLIs) in anterior (IV–V) or posterior (VI–VIII) cerebellar lobules of male and female mice and activated them during alcohol drinking sessions. In a home-cage drinking paradigm, alcohol consumption was significantly decreased by clozapine-N-oxide (CNO) or deschloroclozapine (DCZ) administration in male mice expressing DREADDs in posterior but not anterior lobules. CNO/DCZ injections did not affect drinkin...

EEG phase is increasingly used in cognitive neuroscience, brain–computer interfaces, and closed-loop stimulation devices. However, it is unknown how accurate EEG phase prediction is across cognitive states. We determined the EEG phase prediction accuracy of parieto-occipital alpha waves across rest and task states in 484 participants over 11 public datasets. We were able to track EEG phase accurately across various cognitive conditions and datasets, especially during periods of high instantaneous alpha power and signal-to-noise ratio (SNR). Although resting states generally have higher accuracies than task states, absolute accuracy differences were small, with most of these differences attributable to EEG power and SNR. These results suggest that experiments and technologies using EEG phase should focus more on minimizing external noise and waiting for periods of high power rather than inducing a particular cognitive state.

Previous research has questioned whether motor adaptation is shaped by an optimal combination of multisensory error signals. Here, we expanded on this work by investigating how the use of visual and somatosensory error signals during online correction influences single-trial adaptation. To this end, we exposed participants to a random sequence of force-field perturbations and recorded their corrective responses as well as the after-effects exhibited during the subsequent unperturbed movement. In addition to the force perturbation, we artificially decreased or increased visual errors by multiplying hand deviations by a gain smaller or larger than one. Corrective responses to the force perturbation clearly scaled with the size of the visual error, but this scaling did not transfer one-to-one to motor adaptation and we observed no consistent interaction between limb and visual errors on adaptation. However, reducing visual errors during perturbation led to a small reduction of after-effects and this residual ...

When movements become inaccurate, the resultant error induces motor adaptation to improve accuracy. This error-based motor learning is regarded as a cerebellar function. However, the influence of the other brain areas on adaptation is poorly understood. During saccade adaptation, a type of error-based motor learning, the superior colliculus (SC) sends a postsaccadic error signal to the cerebellum to drive adaptation. Since the SC is directly inhibited by the substantia nigra pars reticulata (SNr), we hypothesized that the SNr might influence saccade adaptation by affecting the SC error signal. In fact, previous studies indicated that the SNr encodes motivation and motivation influences saccade adaptation. In this study, we first established that the SNr projects to the rostral SC, where small error signals are generated, in nonhuman primates. Then, we examined SNr activity while the animal underwent adaptation. SNr neurons paused their activity in association with the error. This pause was shallower and de...

Obesity affects more than a third adult population in the United States; the prevalence is even higher in patients with major depression disorders. GWAS studies identify the receptor tyrosine kinase ErbB4 as a risk gene for obesity and for major depression disorders. We found that ErbB4 was enriched in the paraventricular nucleus of the hypothalamus (PVH). To investigate its role in metabolism, we deleted ErbB4 by injecting a Cre-expressing virus into the PVH of ErbB4-floxed male mice and found that PVH ErbB4 deletion increased weight gain without altering food intake. ErbB4 PVH deletion also reduced nighttime activity and decreased intrascapular brown adipose tissue (iBAT) thermogenesis. Analysis of covariance (ANCOVA) revealed that ErbB4 PVH deletion reduced O2 consumption, CO2 production and heat generation in a manner independent of body weight. Immunostaining experiments show that ErbB4+ neurons in the PVH were positive for oxytocin (OXT); ErbB4 PVH deletion reduces serum levels of OXT. We characteriz...

Reliable measurements of motor learning and coordination in mice are fundamental aspects of neuroscience research. Despite the advent of deep-learning approaches for motor assessment, performance testing on a rotating rod (rotarod) has remained a staple in the neuroscientist’s toolbox. Surprisingly, commercially available rotarod instruments offer limited experimental flexibility at a relatively high cost. In order to address these concerns, we engineered a highly-customizable, low-budget rotarod device with increased functionality. Here, we present a detailed guide to assemble this rotarod using simple materials. Our apparatus incorporates a variation of interchangeable rod sizes and designs which provides for adjustable testing sensitivity. Moreover, our rotarod is driven by open-source software enabling bespoke acceleration ramps and sequences. Finally, we report the strengths and weaknesses of each rod design following multiday testing on cohorts of C57BL/6 mice. We expect explorations in deviant rod t...

The spinal motor neurons are the only neural cells whose individual activity can be non-invasively identified. This is usually done using grids of surface electromyographic (EMG) electrodes and source separation algorithms; an approach called EMG decomposition. In this study, we combined computational and experimental analyses to assess how the design parameters of grids of electrodes influence the number and the properties of the identified motor units. We first computed the percentage of motor units that could be theoretically discriminated within a pool of 200 simulated motor units when decomposing EMG signals recorded with grids of various sizes and interelectrode distances (IED). Increasing the density, the number of electrodes, and the size of the grids, increased the number of motor units that our decomposition algorithm could theoretically discriminate, i.e., up to 83.5% of the simulated pool (range across conditions: 30.5-83.5%). We then identified motor units from experimental EMG signals recorde...