Associations between brain structure and perceived intensity of sweet and bitter tastes

Investigation of structural and neurobiochemical differences in brains from high-performance and native hen breeds

Selection of livestock has not only led to changes in the level of their performance but also modified their behavior. As a result, within a single species, we have to deal with different behaviors of different breeds. In our study, we assumed that the different behaviors within a species are due to differences in the morphology and physiology of behavior-related systems. Two breeds of hens were used as a model: the highly reactive, fearful and high-performance Leghorn breed and proactive, unselected Green-legged Partridge breed. The higher reactivity and fearfulness of Leghorn hens in comparison to the Green-legged Partridge breed may be related to the greater number of neurons in the paraventricular nucleus and anterior hypothalamus and the higher content of zinc and iron in the brain, as these elements are involved in neuronal conduction and myelination processes. The reactive behaviours of Green-legged Partridge hens may be associated with the lower number of neurons in the paraventricular nucleus and the anterior hypothalamus and the higher concentration of dopamine and copper ions in the brain. The analyses confirmed the hypothesis of the existence of interbreed differences in the morphology and physiology of behaviour-related systems, which most probably emerged through unintentional and correlated selection towards high production performance. Consequently, attention should be drawn that the selection of a given genotype (breed) towards a specific environment could lead to creation of highly specialised lines that may not achieve homeostasis in every maintenance system.

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.

Do People with Lower IQ Have Weaker Taste Perception? A Hidden Supplementary Table in ‘Is the Association Between Sweet and Bitter Perception Due to Genetic Variation?’

This paper is about Nick’s contribution to the field of taste genetics, how I became involved and how a study on the genetic association between the perception of sweetness and bitterness ended up examining the influence of intelligence on taste perception.

Dendritic complexity change in the triple transgenic mouse model of Alzheimer's disease

Alzheimer’s disease (AD) is an irreversible, neurodegenerative disease that is characterized by memory impairment and executive dysfunction. However, the change of fine structure of neuronal morphology remains unclear in the AD model mouse. In this study, high-resolution mouse brain sectional images were scanned by Micro-Optical Sectioning Tomography (MOST) technology and reconstructed three-dimensionally to obtain the pyramidal neurons. The method of Sholl analysis was performed to analyze the neurons in the brains of 6- and 12-month-old AD mice. The results showed that dendritic complexity was not affected in the entorhinal cortex between 6-month-old mice and 12-month-old mice. The dendritic complexity had increased in the primary motor cortex and CA1 region of hippocampus of 12- month-old mice compared with 6-month-old mice. On the contrary, dendritic complexity in the prefrontal cortex was decreased significantly between 6-month-old and 12-month-old mice. To our knowledge, this is the first study to provide high-resolution brain images of triple transgenic AD mice for statistically analyzing neuronal dendrite complexity by MOST technology to reveal the morphological changes of neurons during AD progression.

Artificial selection on brain size leads to matching changes in overall number of neurons

Neurons are the basic computational units of the brain, but brain size is the predominant surrogate measure of brain functional capacity in comparative and cognitive neuroscience. This approach is based on the assumption that larger brains harbor higher numbers of neurons and their connections, and therefore have a higher information-processing capacity. However, recent studies have shown that brain mass may be less strongly correlated with neuron counts than previously thought. Till now, no experimental test has been conducted to examine the relationship between evolutionary changes in brain size and the number of brain neurons. Here, we provide such a test by comparing neuron number in artificial selection lines of female guppies (Poecilia reticulata) with >15% difference in relative brain mass and numerous previously demonstrated cognitive differences. Using the isotropic fractionator, we demonstrate that large-brained females have a higher overall number of neurons than small-brained females, but similar neuronal densities. Importantly, this difference holds also for the telencephalon, a key region for cognition. Our study provides the first direct experimental evidence that selection for brain mass leads to matching changes in number of neurons and shows that brain size evolution is intimately linked to the evolution of neuron number and cognition.

Intensity-related distribution of sweet and bitter taste fMRI responses in the insular cortex

The human gustatory cortex analyzes the chemosensory properties of tastants, particularly the quality, intensity, and affective valence, to determine whether a perceived substance should be ingested or rejected. Among previous studies, the spatial distribution of taste intensity-related activations within the human insula has been scarcely addressed. To spatially characterize a specialized or distributed nature of the cortical responses to taste intensities, a functional magnetic resonance imaging study was performed at 3 T in 44 healthy subjects where sweet and bitter tastants were administered at five increasing concentrations and cortex-based factorial and parametric analyses were performed. Two clusters in the right middle-posterior and left middle insula were found specialized for taste intensity processing, exhibiting a highly nonlinear profile across concentrations. Multiple clusters were found activated by sweet and bitter taste stimuli at most concentrations, in the anterior, middle-posterior, and inferior portion of the bilateral insula. Across these clusters, respectively, for the right and left insula, a superior-to-inferior and an anterior-to-posterior spatial gradient for high-to-low concentrations were observed for the most responsive intensity of both tastes. These findings may gather new insights regarding how the gustatory cortex is spatially organized during the perceptual processing of taste intensity for two basic tastants.