Reward and aversion encoding in the lateral habenula for innate and learned behaviours

Throughout life, individuals experience a vast array of positive and aversive events that trigger adaptive behavioural responses. These events are often unpredicted and engage actions that are likely anchored on innate behavioural programs expressed by each individual member of virtually all animal species. In a second step, environmental cues, that are initially neutral, acquire value through the association with external sensory stimuli, and become instrumental to predict upcoming positive or negative events. This process ultimately prompts learned goal-directed actions allowing the pursuit of rewarding experience or the avoidance of a danger. Both innate and learned behavioural programs are evolutionarily conserved and fundamental for survival. Among the brain structures participating in the encoding of positive/negative stimuli and contributing to innate and learned behaviours is the epithalamic lateral habenula (LHb). The LHb provides top-down control of monoaminergic systems, responds to unexpected appetitive/aversive stimuli as well as external cues that predict the upcoming rewards or punishments. Accordingly, the LHb controls a number of behaviours that are innate (originating from unpredicted stimuli), and learned (stemming from predictive cues). In this review, we will discuss the progresses that rodent’s experimental work made in identifying how LHb activity governs these vital processes, and we will provide a view on how these findings integrate within a complex circuit connectivity.

Impact of multisensory extended reality on tourism experience journey

Purpose The use of extended reality (XR) to create memorable experiences has attracted considerable attention, especially in tourism. Multisensory XR offers a new way of virtually previewing a destination before physical holidays. This study aims to explore how multisensory XR can be used at each stage of the tourism experience journey. This study established a model for how destination-image formation is affected by multisensory XR in each phase of tourism experience. Design/methodology/approach The authors followed the preferred reporting items for systematic reviews and meta-analyses guidelines to review studies published between 2013 and 2020, gathered from four research databases. The authors identified the predominant XR technology and sensory stimuli based on the characteristics of various tourism domains. The authors synthesized the previous studies to explain destination-image formation by using multisensory XR. Findings This study summarized the XR study distribution among the three stages of the tourism experience journey. The authors identified the predominant sensory stimuli and dominant XR application and developed a destination-image formation model by using multisensory XR. Originality/value This study highlights the holistic approach of multisensory XR in the tourism experience journey in relation to various tourism domains. It also contributes to destination-image formation in the virtual environment by providing multisensory experiences of predominant sensory stimuli at each stage.

Hyperrealistic neural decoding for reconstructing faces from fMRI activations via the GAN latent space

Neural decoding can be conceptualized as the problem of mapping brain responses back to sensory stimuli via a feature space. We introduce (i) a novel experimental paradigm that uses well-controlled yet highly naturalistic stimuli with a priori known feature representations and (ii) an implementation thereof for HYPerrealistic reconstruction of PERception (HYPER) of faces from brain recordings. To this end, we embrace the use of generative adversarial networks (GANs) at the earliest step of our neural decoding pipeline by acquiring fMRI data as participants perceive face images synthesized by the generator network of a GAN. We show that the latent vectors used for generation effectively capture the same defining stimulus properties as the fMRI measurements. As such, these latents (conditioned on the GAN) are used as the in-between feature representations underlying the perceived images that can be predicted in neural decoding for (re-)generation of the originally perceived stimuli, leading to the most accurate reconstructions of perception to date.

Unsupervised Clustering of Individuals Sharing Selective Attentional Focus Using Physiological Synchrony

Research on brain signals as indicators of a certain attentional state is moving from laboratory environments to everyday settings. Uncovering the attentional focus of individuals in such settings is challenging because there is usually limited information about real-world events, as well as a lack of data from the real-world context at hand that is correctly labeled with respect to individuals' attentional state. In most approaches, such data is needed to train attention monitoring models. We here investigate whether unsupervised clustering can be combined with physiological synchrony in the electroencephalogram (EEG), electrodermal activity (EDA), and heart rate to automatically identify groups of individuals sharing attentional focus without using knowledge of the sensory stimuli or attentional focus of any of the individuals. We used data from an experiment in which 26 participants listened to an audiobook interspersed with emotional sounds and beeps. Thirteen participants were instructed to focus on the narrative of the audiobook and 13 participants were instructed to focus on the interspersed emotional sounds and beeps. We used a broad range of commonly applied dimensionality reduction ordination techniques—further referred to as mappings—in combination with unsupervised clustering algorithms to identify the two groups of individuals sharing attentional focus based on physiological synchrony. Analyses were performed using the three modalities EEG, EDA, and heart rate separately, and using all possible combinations of these modalities. The best unimodal results were obtained when applying clustering algorithms on physiological synchrony data in EEG, yielding a maximum clustering accuracy of 85%. Even though the use of EDA or heart rate by itself did not lead to accuracies significantly higher than chance level, combining EEG with these measures in a multimodal approach generally resulted in higher classification accuracies than when using only EEG. Additionally, classification results of multimodal data were found to be more consistent across algorithms than unimodal data, making algorithm choice less important. Our finding that unsupervised classification into attentional groups is possible is important to support studies on attentional engagement in everyday settings.

Disrupted Association of Sensory Neurons With Enveloping Satellite Glial Cells in Fragile X Mouse Model

Among most prevalent deficits in individuals with Fragile X syndrome (FXS) is hypersensitivity to sensory stimuli and somatosensory alterations. Whether dysfunction in peripheral sensory system contributes to these deficits remains poorly understood. Satellite glial cells (SGCs), which envelop sensory neuron soma, play critical roles in regulating neuronal function and excitability. The potential contributions of SGCs to sensory deficits in FXS remain unexplored. Here we found major structural defects in sensory neuron-SGC association in the dorsal root ganglia (DRG), manifested by aberrant covering of the neuron and gaps between SGCs and the neuron along their contact surface. Single-cell RNAseq analyses demonstrated transcriptional changes in both neurons and SGCs, indicative of defects in neuronal maturation and altered SGC vesicular secretion. We validated these changes using fluorescence microscopy, qPCR, and high-resolution transmission electron microscopy (TEM) in combination with computational analyses using deep learning networks. These results revealed a disrupted neuron-glia association at the structural and functional levels. Given the well-established role for SGCs in regulating sensory neuron function, altered neuron-glia association may contribute to sensory deficits in FXS.

The development of bi-directionally coupled self-organizing neurovascular networks captures orientation-selective neural and hemodynamic cortical responses

The network of neurons in the brain is considered the primary substrate of information processing. Despite growing evidence on the possible role of cerebral blood flow in information processing, the cerebrovascular network is generally viewed as an irrigation system that ensures a timely supply of oxygen, glucose, and nutrients to the neural tissue. However, a recent study has shown that cerebral microvessels, like neurons, also exhibit tuned responses to sensory stimuli. Tuned neural responses to sensory stimuli are certainly enhanced with experience-dependent Hebbian plasticity and other forms of learning. Hence it is possible that the densely interconnected microvascular network might also be subject to some form of plasticity or competitive learning rules during early postnatal development such that its fine-scale structure becomes optimized for metabolic delivery to a given neural micro-architecture. To explore the possibility of adaptive lateral interactions and tuned responses in cerebral microvessels, we modeled the cortical neurovascular network by interconnecting two laterally connected self-organizing networks (Laterally Interconnected Synergetically Self-Organizing Map - LISSOM). The afferent and lateral connections of the LISSOM were defined by trainable weights. By varying the topology of lateral connectivity in the vascular network layer, we observed that the partial correspondence of feature selectivity between neural and hemodynamic responses could be explained by lateral coupling across local blood vessels such that the central domain receives an excitatory drive of more blood flow and a more distal surrounding region where blood flow is reduced. Critically, our simulations suggest a new role for feedback from the vascular to the neural network because the radius of vascular perfusion seems to determine whether the cortical neural map develops into a clustered and columnar vs. salt-and-pepper organization.

Neuroplasticity at Home: Improving Home-Based Motor Learning Through Technological Solutions. A Review

Background: Effective science-based motor rehabilitation requires high volume of individualized, intense physical training, which can be difficult to achieve exclusively through physical 1-on-1 sessions with a therapist. Home-based training, enhanced by technological solutions, could be a tool to help facilitate the important factors for neuroplastic motor improvements.Objectives: This review aimed to discover how the inclusion of modern information and communications technology in home-based training programs can promote key neuroplastic factors associated with motor learning in neurological disabilities and identify which challenges are still needed to overcome.Methods: We conducted a thorough literature search on technological home-based training solutions and categorized the different fundamental approaches that were used. We then analyzed how these approaches can be used to promote certain key factors of neuroplasticity and which challenges still need to be solved or require external personalized input from a therapist.Conclusions: The technological approaches to home-based training were divided into three categories: sensory stimuli training, digital exchange of information training, and telerehabilitation. Generally, some technologies could be characterized as easily applicable, which gave the opportunity to promote flexible scheduling and a larger overall training volume, but limited options for individualized variation and progression. Other technologies included individualization options through personalized feedback that might increase the training effect, but also increases the workload of the therapist. Further development of easily applicable and intelligent solutions, which can return precise feedback and individualized training suggestions, is needed to fully realize the potential of home-based training in motor learning activities.

TRP Channels as Molecular Targets to Relieve Cancer Pain

Transient receptor potential (TRP) channels are critical receptors in the transduction of nociceptive stimuli. The microenvironment of diverse types of cancer releases substances, including growth factors, neurotransmitters, and inflammatory mediators, which modulate the activity of TRPs through the regulation of intracellular signaling pathways. The modulation of TRP channels is associated with the peripheral sensitization observed in patients with cancer, which results in mild noxious sensory stimuli being perceived as hyperalgesia and allodynia. Secondary metabolites derived from plant extracts can induce the activation, blocking, and desensitization of TRP channels. Thus, these compounds could act as potential therapeutic agents, as their antinociceptive properties could be beneficial in relieving cancer-derived pain. In this review, we will summarize the role of TRPV1 and TRPA1 in pain associated with cancer and discuss molecules that have been reported to modulate these channels, focusing particularly on the mechanisms of channel activation associated with molecules released in the tumor microenvironment.

FosGFP expression does not capture a sensory learning-related engram in superficial layers of mouse barrel cortex

Immediate-early gene (IEG) expression has been used to identify small neural ensembles linked to a particular experience, based on the principle that a selective subset of activated neurons will encode specific memories or behavioral responses. The majority of these studies have focused on “engrams” in higher-order brain areas where more abstract or convergent sensory information is represented, such as the hippocampus, prefrontal cortex, or amygdala. In primary sensory cortex, IEG expression can label neurons that are responsive to specific sensory stimuli, but experience-dependent shaping of neural ensembles marked by IEG expression has not been demonstrated. Here, we use a fosGFP transgenic mouse to longitudinally monitor in vivo expression of the activity-dependent gene c-fos in superficial layers (L2/3) of primary somatosensory cortex (S1) during a whisker-dependent learning task. We find that sensory association training does not detectably alter fosGFP expression in L2/3 neurons. Although training broadly enhances thalamocortical synaptic strength in pyramidal neurons, we find that synapses onto fosGFP+ neurons are not selectively increased by training; rather, synaptic strengthening is concentrated in fosGFP− neurons. Taken together, these data indicate that expression of the IEG reporter fosGFP does not facilitate identification of a learning-specific engram in L2/3 in barrel cortex during whisker-dependent sensory association learning.