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...

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...

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...

Understanding the neural basis of emotions is a critical step to uncover the biological substrates of neuropsychiatric disorders. To study this aspect in freely behaving mice, neuroscientists have relied on the observation of ethologically relevant bodily cues to infer the affective content of the subject, both in neutral conditions or in response to a stimulus. The best example of that is the widespread assessment of freezing in experiments testing both conditioned and unconditioned fear responses. While robust and powerful, these approaches come at a cost: they are usually confined within selected time windows, accounting for only a limited portion of the complexity of emotional fluctuation. Moreover, they often rely on visual inspection and subjective judgement, resulting in inconsistency across experiments and questionable result interpretations. To overcome these limitations, novel tools are arising, fostering a new avenue in the study of the mouse naturalistic behavior. In this work we developed a co...

When a Pavlovian cue is presented separately from its associated reward, some animals will acquire a sign tracking (ST) response, approach and/or interaction with the cue, while others will acquire a goal tracking response, approach to the site of reward. We have previously shown that cue-evoked excitations in the nucleus accumbens (NAc) encode the vigor of both behaviors; in contrast, reward-related responses diverge over the course of training, possibly reflecting neurochemical differences between sign tracker and goal tracker individuals. However, a substantial subset of neurons in the NAc exhibit inhibitory, rather than excitatory, cue-evoked responses, and the evolution of their signaling during Pavlovian conditioning remains unknown. Using single-neuron recordings in behaving rats, we show that NAc neurons with cue-evoked inhibitions have distinct coding properties from neurons with cue-evoked excitations. Cue-evoked inhibitions become more numerous over the course of training and, like excitations, ...

While it is commonly assumed that stressful events are vividly remembered, it remains largely unknown whether all aspects of memory for a stressful episode are enhanced. In this preregistered study, we tested whether stress enhances later remembering of individual elements of a stressful episode at the cost of impaired processing of the association between these elements. Therefore, male and female participants (N=122) underwent a stressful (or control) episode during which they encoded a series of stimuli. To investigate stress effects on the memory for individual events and the links between these, we utilized temporal sequence effects in recognition memory tested 24 hours after encoding. Specifically, we tested whether stress would affect the memory enhancement for a target item if this is preceded by another item that also preceded the target during encoding (recognition priming). Our results showed that participants recalled single events encoded under stress better than those encoded under non-stress...

To survive, animals must meet their biological needs while simultaneously avoiding danger. However, the neurobiological basis of appetitive and aversive survival behaviors has historically been studied using separate behavioral tasks. While recent studies in mice have quantified appetitive and aversive conditioned responses simultaneously (Heinz et al., 2017; Jikomes et al., 2016), these tasks required different behavioral responses to each stimulus. As many brain regions involved in survival behavior process stimuli of opposite valence, we developed a paradigm in which mice perform the same response (nosepoke) to distinct auditory cues to obtain a rewarding outcome (palatable food) or avoid an aversive outcome (mild footshoock). This design allows for both within- and between-subject comparisons as animals respond to appetitive and aversive cues. The central nucleus of the amygdala (CeA) is implicated in the regulation of responses to stimuli of either valence. Considering its role in threat processing (H...

Neuropathic pain is stubborn and associated with peripheral nerve regeneration process. Nicotine has been found to reduce pain but whether it is involved in the regulation of nerve regeneration and the underlying mechanism are unknown. In this study, we examined the mechanical allodynia, thermal hyperalgesia together with the peripheral nerve regeneration after nicotine exposure in two rat neuropathic pain models. In the spinal nerve ligation (SNL) model, in which anatomical nerve regeneration can be easily observed, nicotine reduced anatomical measures of regeneration as well as expression of regeneration marker growth associated protein 43 (GAP43). In the tibial nerve crush model, nicotine treatment significantly suppressed GAP43 expression and functional reinnervation as measured by myelinated action potential and electromyography of gastrocnemius. In both models, nicotine treatment reduced macrophage density in the sensory ganglia and peripheral nerve. These effects of nicotine were reversed by the sel...