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Cerebellum (London, England) Oct 2023Given the importance of the cerebellum in controlling movements, it might be expected that its main role in eating would be the control of motor elements such as chewing... (Review)
Review
Given the importance of the cerebellum in controlling movements, it might be expected that its main role in eating would be the control of motor elements such as chewing and swallowing. Whilst such functions are clearly important, there is more to eating than these actions, and more to the cerebellum than motor control. This review will present evidence that the cerebellum contributes to homeostatic, motor, rewarding and affective aspects of food consumption.Prediction and feedback underlie many elements of eating, as food consumption is influenced by expectation. For example, circadian clocks cause hunger in anticipation of a meal, and food consumption causes feedback signals which induce satiety. Similarly, the sight and smell of food generate an expectation of what that food will taste like, and its actual taste will generate an internal reward value which will be compared to that expectation. Cerebellar learning is widely thought to involve feed-forward predictions to compare expected outcomes to sensory feedback. We therefore propose that the overarching role of the cerebellum in eating is to respond to prediction errors arising across the homeostatic, motor, cognitive, and affective domains.
Topics: Feeding Behavior; Hunger; Satiation; Cerebellum; Learning; Eating
PubMed: 36121552
DOI: 10.1007/s12311-022-01476-3 -
Nature Communications Nov 2023Inaccessibility of stored memory in ensemble cells through the forgetting process causes animals to be unable to respond to natural recalling cues. While accumulating...
Inaccessibility of stored memory in ensemble cells through the forgetting process causes animals to be unable to respond to natural recalling cues. While accumulating evidence has demonstrated that reactivating memory-stored cells can switch cells from an inaccessible state to an accessible form and lead to recall of previously learned information, the underlying cellular and molecular mechanisms remain elusive. The current study used Drosophila as a model to demonstrate that the memory of one-trial aversive olfactory conditioning, although inaccessible within a few hours after learning, is stored in KCαβ and retrievable after mild retraining. One-trial aversive conditioning triggers protein synthesis to form a long-lasting cellular memory trace, approximately 20 days, via creb in KCαβ, and a transient cellular memory trace, approximately one day, via orb in MBON-α3. PPL1-α3 negatively regulates forgotten one-trial conditioning memory retrieval. The current study demonstrated that KCαβ, PPL1-α3, and MBON-α3 collaboratively regulate the formation of forgotten one-cycle aversive conditioning memory formation and retrieval.
Topics: Animals; Drosophila; Memory; Learning; Conditioning, Psychological; Mental Recall
PubMed: 37935667
DOI: 10.1038/s41467-023-42753-x -
Current Opinion in Insect Science Oct 2023Sleep and memory are highly intertwined, yet the integrative neural network of these two fundamental physiological behaviors remains poorly understood. Multiple cell... (Review)
Review
Sleep and memory are highly intertwined, yet the integrative neural network of these two fundamental physiological behaviors remains poorly understood. Multiple cell types and structures of the Drosophila brain have been shown involved in the regulation of sleep and memory, and recent efforts are focusing on bridging them at molecular and circuit levels. Here, we briefly review 1) identified neurons as key nodes of olfactory-associative memory circuits involved in different memory processes; 2) how neurons of memory circuits participate in sleep regulation; and 3) other cell types and circuits besides the mushroom body in linking sleep and memory. We also attempt to provide the remaining gaps of circuitry integration of sleep and memory, which may spark some new thinking for future efforts.
Topics: Animals; Drosophila; Memory; Neurons; Brain; Sleep
PubMed: 37625641
DOI: 10.1016/j.cois.2023.101105 -
Plants (Basel, Switzerland) Jan 2024Florivory, i.e., flower herbivory, of various types is common and can strongly reduce plant fitness. Flowers suffer two very different types of herbivory: (1) the... (Review)
Review
Florivory, i.e., flower herbivory, of various types is common and can strongly reduce plant fitness. Flowers suffer two very different types of herbivory: (1) the classic herbivory of consuming tissues and (2) nectar theft. Unlike the non-reversibility of consumed tissues, nectar theft, while potentially reducing a plant's fitness by lowering its attraction to pollinators, can, in various cases, be fixed quickly by the production of additional nectar. Therefore, various mechanisms to avoid or reduce florivory have evolved. Here, I focus on one of the flowers' defensive mechanisms, aposematism, i.e., warning signaling to avoid or at least reduce herbivory via the repelling of herbivores. While plant aposematism of various types was almost ignored until the year 2000, it is a common anti-herbivory defense mechanism in many plant taxa, operating visually, olfactorily, and, in the case of nectar, via a bitter taste. Flower aposematism has received only very little focused attention as such, and many of the relevant publications that actually demonstrated herbivore repellence and avoidance learning following flower signaling did not refer to repellence as aposematism. Here, I review what is known concerning visual-, olfactory-, and nectar-taste-based flower aposematism, including some relevant cases of mimicry, and suggest some lines for future research.
PubMed: 38337924
DOI: 10.3390/plants13030391 -
Rhinology Oct 2023Patients with septal deviation and/or turbinal hypertrophy may experience olfactory disfunction (OD). The aim of this study was to analyse the effect of septoplasty...
BACKGROUND
Patients with septal deviation and/or turbinal hypertrophy may experience olfactory disfunction (OD). The aim of this study was to analyse the effect of septoplasty and/or turbinoplasty on both lateralized and bilateral olfactory function.
METHODOLOGY
Prospective study of 47 patients with nasal obstruction secondary to septal deviation and/or turbinal hypertrophy and 20 healthy controls. The Barcelona Olfactory test (BOT-8), a new supraliminal orthonasal subjective olfactometry, was applied 3 times in a row (in each nostril separately and in both simultaneously). The 8 items were applied randomly to minimize the possible risk of learning. The test has not established the minimal clinically important difference (MCID). Anterior rhinomanometry and acoustic rhinometry were performed. All participants self-assessed smell loss and nasal obstruction using a visual analogue scale (VAS) and completed questionnaires for nasal obstruction (Nasal Obstruction Symptom Evaluation, NOSE) and for quality of life (QoL), using disease-specific (SinoNasal Outcome Test-22, SNOT-22) and generic (Short Form-12 Health Survey, SF-12) questionnaires. Nasal measurements and questionnaires were performed preoperatively and 12 months after surgery.
RESULTS
Before surgery, patients reported worse VAS on smell loss and on nasal obstruction compared to controls. Patients scored lower BOT-8 than controls. Lateralized preoperative olfactory function showed that all BOT-8 characteristics were lower at the narrow side than the wider one. Smell function and QoL improved significantly one year after surgery.
CONCLUSIONS
Nasal septal deviation and turbinal hypertrophy lead to an olfactory impairment on the obstructed nostril. Nasal surgery provides a positive outcome on olfactory function, as well as on subjective and objective outcomes.
Topics: Humans; Smell; Quality of Life; Nasal Obstruction; Prospective Studies; Anosmia; Treatment Outcome; Rhinoplasty; Nasal Septum; Nose Deformities, Acquired
PubMed: 37475674
DOI: 10.4193/Rhin22.461 -
NPJ Parkinson's Disease Jul 2023Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning...
Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.
PubMed: 37443179
DOI: 10.1038/s41531-023-00556-3 -
Learning & Memory (Cold Spring Harbor,... May 2024In this review, we aggregated the different types of learning and memory paradigms developed in adult and attempted to assess the similarities and differences in the... (Review)
Review
In this review, we aggregated the different types of learning and memory paradigms developed in adult and attempted to assess the similarities and differences in the neural mechanisms supporting diverse types of memory. The simplest association memory assays are conditioning paradigms (olfactory, visual, and gustatory). A great deal of work has been done on these memories, revealing hundreds of genes and neural circuits supporting this memory. Variations of conditioning assays (reversal learning, trace conditioning, latent inhibition, and extinction) also reveal interesting memory mechanisms, whereas mechanisms supporting spatial memory (thermal maze, orientation memory, and heat box) and the conditioned suppression of innate behaviors (phototaxis, negative geotaxis, anemotaxis, and locomotion) remain largely unexplored. In recent years, there has been an increased interest in multisensory and multicomponent memories (context-dependent and cross-modal memory) and higher-order memory (sensory preconditioning and second-order conditioning). Some of this work has revealed how the intricate mushroom body (MB) neural circuitry can support more complex memories. Finally, the most complex memories are arguably those involving social memory: courtship conditioning and social learning (mate-copying and egg-laying behaviors). Currently, very little is known about the mechanisms supporting social memories. Overall, the MBs are important for association memories of multiple sensory modalities and multisensory integration, whereas the central complex is important for place, orientation, and navigation memories. Interestingly, several different types of memory appear to use similar or variants of the olfactory conditioning neural circuitry, which are repurposed in different ways.
Topics: Animals; Memory; Drosophila; Mushroom Bodies; Behavior, Animal
PubMed: 38862165
DOI: 10.1101/lm.053810.123 -
Alzheimer's Research & Therapy Jul 2023We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using... (Clinical Trial)
Clinical Trial
Quantification of identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy with machine learning: a post hoc analysis of a diagnostic trial and validation of an external additional trial.
BACKGROUND
We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using machine learning through a post hoc analysis of a previous diagnostic trial and an external additional trial.
METHODS
We conducted two independent, patient-level, single-group, diagnostic interventional trials (original and additional trials) involving elderly volunteers (aged > 60 years) with suspected declining cognitive function. All volunteers were assessed by measuring the oxygenation difference in the orbitofrontal cortex using an open-label olfactory-stimulated functional near-infrared spectroscopy approach, medical interview, amyloid positron emission tomography, brain magnetic resonance imaging, Mini-Mental State Examination, and Seoul Neuropsychological Screening Battery.
RESULTS
In total, 97 (original trial) and 36 (additional trial) elderly volunteers with suspected decline in cognitive function met the eligibility criteria. The statistical model reported classification accuracies of 87.3% in patients with mild cognitive impairment and Alzheimer's disease in internal validation (original trial) but 63.9% in external validation (additional trial). The machine learning algorithm achieved 92.5% accuracy with the internal validation data and 82.5% accuracy with the external validation data. For the diagnosis of mild cognitive impairment, machine learning performed better than statistical methods with internal (86.0% versus 85.2%) and external validation data (85.4% versus 68.8%).
INTERPRETATION
In two independent trials, machine learning models using olfactory-stimulated oxygenation differences in the orbitofrontal cortex were superior in diagnosing mild cognitive impairment and Alzheimer's disease compared to classic statistical models. Our results suggest that the machine learning algorithm is stable across different patient groups and increases generalization and reproducibility.
TRIAL REGISTRATION
Clinical Research Information Service (CRiS) of Republic of Korea; CRIS numbers, KCT0006197 and KCT0007589.
Topics: Aged; Humans; Alzheimer Disease; Cognitive Dysfunction; Machine Learning; Reproducibility of Results; Spectroscopy, Near-Infrared; Middle Aged
PubMed: 37481573
DOI: 10.1186/s13195-023-01268-9