Unique spatially and temporary-regulated/sex-specific expression of a long ncRNA, Nb-1, suggesting its pleiotropic functions associated with honey bee lifecycle.

Honey bees are social insects, and each colony member has unique morphological and physiological traits associated with their social tasks. Previously, we identified a long non-coding RNA from honey bees, termed Nb-1, whose expression in the brain decreases associated with the age-polyethism of workers and is detected in some neurosecretory cells and octopaminergic neurons, suggesting its role in the regulation of worker labor transition. Herein, we investigated its spatially and temporary-regulated/sex-specific expression. Nb-1 was expressed as an abundant maternal RNA during oogenesis and embryogenesis in both sexes. In addition, Nb-1 was expressed preferentially in the proliferating neuroblasts of the mushroom bodies (a higher-order center of the insect brain) in the pupal brains, suggesting its role in embryogenesis and mushroom body development. On the contrary, Nb-1 was expressed in a drone-specific manner in the pupal and adult retina, suggesting its role in the drone visual development and/or sense. Subcellular localization of Nb-1 in the brain during development differed depending on the cell type. Considering that Nb-1 is conserved only in Apidae, our findings suggest that Nb-1 potentially has pleiotropic functions in the expression of multiple developmental, behavioral, and physiological traits, which are closely associated with the honey bee lifecycle.

Modulate the impact of the drowsiness on the resting state functional connectivity.

This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.

Increased anger and stress and heightened connectivity between IFG and vmPFC in victims during social interaction.

Self-identification as a victim of violence may lead to increased negative emotions and stress and thus, may change both structure and function of the underlying neural network(s). In a trans-diagnostic sample of individuals who identified themselves as victims of violence and a matched control group with no prior exposure to violence, we employed a social exclusion paradigm, the Cyberball task, to stimulate the re-experience of stress. Participants were partially excluded in the ball-tossing game without prior knowledge. We analyzed group differences in brain activity and functional connectivity during exclusion versus inclusion in exclusion-related regions. The victim group showed increased anger and stress levels during all conditions. Activation patterns during the task did not differ between groups but an enhanced functional connectivity between the IFG and the right vmPFC distinguished victims from controls during exclusion. This effect was driven by aberrant connectivity in victims during inclusion rather than exclusion, indicating that victimization affects emotional responses and inclusion-related brain connectivity rather than exclusion-related brain activity or connectivity. Victims may respond differently to the social context itself. Enhanced negative emotions and connectivity deviations during social inclusion may depict altered social processing and may thus affect social interactions.

Cortical specialization associated with native speech category acquisition in early infancy.

This study investigates neural processes in infant speech processing, with a focus on left frontal brain regions and hemispheric lateralization in Mandarin-speaking infants' acquisition of native tonal categories. We tested 2- to 6-month-old Mandarin learners to explore age-related improvements in tone discrimination, the role of inferior frontal regions in abstract speech category representation, and left hemisphere lateralization during tone processing. Using a block design, we presented four Mandarin tones via [ta] and measured oxygenated hemoglobin concentration with functional near-infrared spectroscopy. Results showed age-related improvements in tone discrimination, greater involvement of frontal regions in older infants indicating abstract tonal representation development and increased bilateral activation mirroring native adult Mandarin speakers. These findings contribute to our broader understanding of the relationship between native speech acquisition and infant brain development during the critical period of early language learning.

Visual perception of highly memorable images is mediated by a distributed network of ventral visual regions that enable a late memorability response.

Behavioral and neuroscience studies in humans and primates have shown that memorability is an intrinsic property of an image that predicts its strength of encoding into and retrieval from memory. While previous work has independently probed when or where this memorability effect may occur in the human brain, a description of its spatiotemporal dynamics is missing. Here, we used representational similarity analysis (RSA) to combine functional magnetic resonance imaging (fMRI) with source-estimated magnetoencephalography (MEG) to simultaneously measure when and where the human cortex is sensitive to differences in image memorability. Results reveal that visual perception of High Memorable images, compared to Low Memorable images, recruits a set of regions of interest (ROIs) distributed throughout the ventral visual cortex: a late memorability response (from around 300 ms) in early visual cortex (EVC), inferior temporal cortex, lateral occipital cortex, fusiform gyrus, and banks of the superior temporal sulcus. Image memorability magnitude results are represented after high-level feature processing in visual regions and reflected in classical memory regions in the medial temporal lobe (MTL). Our results present, to our knowledge, the first unified spatiotemporal account of visual memorability effect across the human cortex, further supporting the levels-of-processing theory of perception and memory.

Optogenetics in chronic neurodegenerative diseases, controlling the brain with light: A systematic review.

Neurodegenerative diseases are progressive disorders characterized by synaptic loss and neuronal death. Optogenetics combines optical and genetic methods to control the activity of specific cell types. The efficacy of this approach in neurodegenerative diseases has been investigated in many reviews, however, none of them tackled it systematically. Our study aimed to review systematically the findings of optogenetics and its potential applications in animal models of chronic neurodegenerative diseases and compare it with deep brain stimulation and designer receptors exclusively activated by designer drugs techniques. The search strategy was performed based on the PRISMA guidelines and the risk of bias was assessed following the Systematic Review Centre for Laboratory Animal Experimentation tool. A total of 247 articles were found, of which 53 were suitable for the qualitative analysis. Our data revealed that optogenetic manipulation of distinct neurons in the brain is efficient in rescuing memory impairment, alleviating neuroinflammation, and reducing plaque pathology in Alzheimer's disease. Similarly, this technique shows an advanced understanding of the contribution of various neurons involved in the basal ganglia pathways with Parkinson's disease motor symptoms and pathology. However, the optogenetic application using animal models of Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis was limited. Optogenetics is a promising technique that enhanced our knowledge in the research of neurodegenerative diseases and addressed potential therapeutic solutions for managing these diseases' symptoms and delaying their progression. Nevertheless, advanced investigations should be considered to improve optogenetic tools' efficacy and safety to pave the way for their translatability to the clinic.

High-dimensional multisubject time series transition matrix inference with application to brain connectivity analysis.

Brain-effective connectivity analysis quantifies directed influence of one neural element or region over another, and it is of great scientific interest to understand how effective connectivity pattern is affected by variations of subject conditions. Vector autoregression (VAR) is a useful tool for this type of problems. However, there is a paucity of solutions when there is measurement error, when there are multiple subjects, and when the focus is the inference of the transition matrix. In this article, we study the problem of transition matrix inference under the high-dimensional VAR model with measurement error and multiple subjects. We propose a simultaneous testing procedure, with three key components: a modified expectation-maximization (EM) algorithm, a test statistic based on the tensor regression of a bias-corrected estimator of the lagged auto-covariance given the covariates, and a properly thresholded simultaneous test. We establish the uniform consistency for the estimators of our modified EM, and show that the subsequent test achieves both a consistent false discovery control, and its power approaches one asymptotically. We demonstrate the efficacy of our method through both simulations and a brain connectivity study of task-evoked functional magnetic resonance imaging.

Differences in Discounting Behavior and Brain Responses for Food and Money Reward.

Most neuroeconomic research seeks to understand how value influences decision-making. The influence of reward type is less well understood. We used functional magnetic resonance imaging (fMRI) to investigate delay discounting of primary (i.e., food) and secondary rewards (i.e., money) in 28 healthy, normal-weighted participants (mean age = 26.77; 18 females). To decipher differences in discounting behavior between reward types, we compared how well-different option-based statistical models (exponential, hyperbolic discounting) and attribute-wise heuristic choice models (intertemporal choice heuristic, dual reasoning and implicit framework theory, trade-off model) captured the reward-specific discounting behavior. Contrary to our hypothesis of different strategies for different rewards, we observed comparable discounting behavior for money and food (i.e., exponential discounting). Higher k values for food discounting suggest that individuals decide more impulsive if confronted with food. The fMRI revealed that money discounting was associated with enhanced activity in the right dorsolateral prefrontal cortex, involved in executive control; the right dorsal striatum, associated with reward processing; and the left hippocampus, involved in memory encoding/retrieval. Food discounting, instead, was associated with higher activity in the left temporoparietal junction suggesting social reinforcement of food decisions. Although our findings do not confirm our hypothesis of different discounting strategies for different reward types, they are in line with the notion that reward types have a significant influence on impulsivity with primary rewards leading to more impulsive choices.

Predictive coding networks for temporal prediction.

One of the key problems the brain faces is inferring the state of the world from a sequence of dynamically changing stimuli, and it is not yet clear how the sensory system achieves this task. A well-established computational framework for describing perceptual processes in the brain is provided by the theory of predictive coding. Although the original proposals of predictive coding have discussed temporal prediction, later work developing this theory mostly focused on static stimuli, and key questions on neural implementation and computational properties of temporal predictive coding networks remain open. Here, we address these questions and present a formulation of the temporal predictive coding model that can be naturally implemented in recurrent networks, in which activity dynamics rely only on local inputs to the neurons, and learning only utilises local Hebbian plasticity. Additionally, we show that temporal predictive coding networks can approximate the performance of the Kalman filter in predicting behaviour of linear systems, and behave as a variant of a Kalman filter which does not track its own subjective posterior variance. Importantly, temporal predictive coding networks can achieve similar accuracy as the Kalman filter without performing complex mathematical operations, but just employing simple computations that can be implemented by biological networks. Moreover, when trained with natural dynamic inputs, we found that temporal predictive coding can produce Gabor-like, motion-sensitive receptive fields resembling those observed in real neurons in visual areas. In addition, we demonstrate how the model can be effectively generalized to nonlinear systems. Overall, models presented in this paper show how biologically plausible circuits can predict future stimuli and may guide research on understanding specific neural circuits in brain areas involved in temporal prediction.

Alpha desynchronization during the filtering initiation phase reflects active processing of distractors.

The ability to select task-relevant information and filter out task-irrelevant information is critical to our success in daily goal-directed behavior. Researchers call this ability filtering efficiency and divide it into three cognitive processing stages: detection of distractors, initiation of filtering, and unnecessary storage. Although researchers have conducted more studies on ERP components related to filtration efficiency, there are few studies related to neural oscillations. Alpha oscillation activity is related to the active processing of information and the suppression of distractors. In the current EEG study, we used the change detection task with distracted items to examine whether alpha activity during filtering initiation reflects reactive suppression of distractors by manipulating memory load levels and the presence or absence of distractors. Results showed that, the presence of the distractors caused an increase in the degree of desynchronization of the alpha oscillations, and in the subsequent time, the alpha activity level returned to a level consistent with the absence of interference conditions. Phase synchronization between frontal and posterior brain regions in the upper alpha oscillations found no effects associated with distractors. Based on these results, we believed that the alpha activity during the filtering initiation phase reflected the active processing of distractors, but this may also be due to lower perceptual load of the target items. In addition, we observed a dominance effect of the right hemisphere in both time-frequency results and connectivity results. We speculate that this effect is related to the activation of the right ventral frontoparietal network.

Understanding the effects of stress on the P300 response during naturalistic simulation of heights exposure.

Stress is a prevalent bodily response universally experienced and significantly affects a person's mental and cognitive state. The P300 response is a commonly observed brain behaviour that provides insight into a person's cognitive state. Previous works have documented the effects of stress on the P300 behaviour; however, only a few have explored the performance in a mobile and naturalistic experimental setup. Our study examined the effects of stress on the human brain's P300 behaviour through a height exposure experiment that incorporates complex visual, vestibular, and proprioceptive stimuli. A more complex sensory environment could produce translatable findings toward real-world behaviour and benefit emerging technologies such as brain-computer interfaces. Seventeen participants experienced our experiment that elicited the stress response through physical and virtual height exposure. We found two unique groups within our participants that exhibited contrasting behavioural performance and P300 target reaction response when exposed to stressors (from walking at heights). One group performed worse when exposed to heights and exhibited a significant decrease in parietal P300 peak amplitude and increased beta and gamma power. On the other hand, the group less affected by stress exhibited a change in their N170 peak amplitude and alpha/mu rhythm desynchronisation. The findings of our study suggest that a more individualised approach to assessing a person's behaviour performance under stress can aid in understanding P300 performance when experiencing stress.

Neuromorphic one-shot learning utilizing a phase-transition material.

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware.

Developmental and adult stress: effects of steroids and neurosteroids.

In humans, exposure to early life adversity has profound implications for susceptibility to developing neuropsychiatric disorders later in life. Studies in rodents have shown that stress experienced during early postnatal life can have lasting effects on brain development. Glucocorticoids and sex steroids are produced in endocrine glands and the brain from cholesterol; these molecules bind to nuclear and membrane-associated steroid receptors. Unlike other steroids that can also be made in the brain, neurosteroids bind specifically to neurotransmitter receptors, not steroid receptors. The relationships among steroids, neurosteroids, and stress are multifaceted and not yet fully understood. However, studies demonstrating altered levels of progestogens, androgens, estrogens, glucocorticoids, and their neuroactive metabolites in both developmental and adult stress paradigms strongly suggest that these molecules may be important players in stress effects on brain circuits and behavior. In this review, we discuss the influence of developmental and adult stress on various components of the brain, including neurons, glia, and perineuronal nets, with a focus on sex steroids and neurosteroids. Gaining an enhanced understanding of how early adversity impacts the intricate systems of brain steroid and neurosteroid regulation could prove instrumental in identifying novel therapeutic targets for stress-related conditions.

Tailoring transcranial alternating current stimulation based on endogenous event-related P3 to modulate premature responses: a feasibility study.

Background: Transcranial alternating current stimulation (tACS) is a brain stimulation method for modulating ongoing endogenous oscillatory activity at specified frequency during sensory and cognitive processes. Given the overlap between event-related potentials (ERPs) and event-related oscillations (EROs), ERPs can be studied as putative biomarkers of the effects of tACS in the brain during cognitive/sensory task performance. Objective: This preliminary study aimed to test the feasibility of individually tailored tACS based on individual P3 (latency and frequency) elicited during a cued premature response task. Thus, tACS frequency was individually tailored to match target-P3 ERO for each participant. Likewise, the target onset in the task was adjusted to match the tACS phase and target-P3 latency. Methods: Twelve healthy volunteers underwent tACS in two separate sessions while performing a premature response task. Target-P3 latency and ERO were calculated in a baseline block during the first session to allow a posterior synchronization between the tACS and the endogenous oscillatory activity. The cue and target-P3 amplitudes, delta/theta ERO, and power spectral density (PSD) were evaluated pre and post-tACS blocks. Results: Target-P3 amplitude significantly increased after activetACS, when compared to sham. Evoked-delta during cue-P3 was decreased after tACS. No effects were found for delta ERO during target-P3 nor for the PSD and behavioral outcomes. Conclusion: The present findings highlight the possible effect of phase synchronization between individualized tACS parameters and endogenous oscillatory activity, which may result in an enhancement of the underlying process (i.e., an increase of target-P3). However, an unsuccessful synchronization between tACS and EEG activity might also result in a decrease in the evoked-delta activity during cue-P3. Further studies are needed to optimize the parameters of endogenous activity and tACS synchronization. The implications of the current results for future studies, including clinical studies, are further discussed since transcranial alternating current stimulation can be individually tailored based on endogenous event-related P3 to modulate responses.

Synthesizing avian dreams.

During sleep, sporadically, it is possible to find neural patterns of activity in areas of the avian brain that are activated during the generation of the song. It has recently been found that in the vocal muscles of a sleeping bird, it is possible to detect activity patterns during these silent replays. In this work, we employ a dynamical systems model for song production in suboscine birds in order to translate the vocal muscles activity during sleep into synthetic songs. Besides allowing us to translate muscle activity into behavior, we argue that this approach poses the biomechanics as a unique window into the avian brain, with biophysical models as its probe.

Probing Our Built-in Calculator: A Systematic Narrative Review of Noninvasive Brain Stimulation Studies on Arithmetic Operation-Related Brain Areas.

This systematic review presented a comprehensive survey of studies that applied transcranial magnetic stimulation and transcranial electrical stimulation to parietal and nonparietal areas to examine the neural basis of symbolic arithmetic processing. All findings were compiled with regard to the three assumptions of the triple-code model (TCM) of number processing. Thirty-seven eligible manuscripts were identified for review (33 with healthy participants and 4 with patients). Their results are broadly consistent with the first assumption of the TCM that intraparietal sulcus both hold a magnitude code and engage in operations requiring numerical manipulations such as subtraction. However, largely heterogeneous results conflicted with the second assumption of the TCM that the left angular gyrus subserves arithmetic fact retrieval, such as the retrieval of rote-learned multiplication results. Support is also limited for the third assumption of the TCM, namely, that the posterior superior parietal lobule engages in spatial operations on the mental number line. Furthermore, results from the stimulation of brain areas outside of those postulated by the TCM show that the bilateral supramarginal gyrus is involved in online calculation and retrieval, the left temporal cortex in retrieval, and the bilateral dorsolateral prefrontal cortex and cerebellum in online calculation of cognitively demanding arithmetic problems. The overall results indicate that multiple cortical areas subserve arithmetic skills.

Clavulanic Acid Decreases Cocaine Cue Reactivity in Addiction-Related Brain Areas, a Randomized fMRI Pilot Study.

Background: Preclinical studies show that clavulanic acid (CLAV) inhibits cocaine self-administration. This study investigates the effect of CLAV on regions of brain activation in response to cocaine cues during functional magnetic resonance imaging (fMRI) in participants with cocaine use disorder (CUD). Methods: A double-masked, placebo-controlled clinical trial with thirteen individuals with severe CUD who were randomized to treatment with CLAV (N = 10, 9 completers) 500 mg/day or matched placebo (PBO) (N = 3) for 3 days. fMRI was used to assess brain reactivity to 18 alternating six-second video clips of cocaine or neutral scenes. In this paradigm, participants were exposed to three different stimulus conditions: NEUTRAL, WATCH (passive watching), and DOWN (actively inhibiting craving while watching). Results: Participants who received CLAV demonstrated a significant reduction in brain activity in the anterior cingulate gyrus (p = 0.009) and the caudate (p = 0.018) in response to DOWN cocaine cues. There was a trend toward lessened cue reactivity in other regions implicated in CUD. Conclusion: CLAV reduced the response of the brain regions associated with motivation and emotional response during the DOWN condition compared to PBO, suggesting CLAV may strengthen voluntary efforts to avoid cocaine use. This pilot data supports the use of CLAV for CUD. (Trial registered in ClinicalTrials.gov NCT04411914).

What do brain oscillations tell about the human sense of smell?

Brain activity may manifest itself as oscillations which are repetitive rhythms of neuronal firing. These local field potentials can be measured via intracranial electroencephalography (iEEG). This review focuses on iEEG used to map human brain structures involved in olfaction. After presenting the methodology of the review, a summary of the brain structures involved in olfaction is given, followed by a review of the literature on human olfactory oscillations in different contexts. A single case is provided as an illustration of the olfactory oscillations. Overall, the timing and sequence of oscillations found in the different structures of the olfactory system seem to play an important role for olfactory perception.