A common neural scale for the subjective pleasantness of different primary rewards.

When an economic decision is taken, it is between goals with different values, and the values must be on the same scale. Here, we used functional MRI to search for a brain region that represents the subjective pleasantness of two different rewards on the same neural scale. We found activity in the ventral prefrontal cortex that correlated with the subjective pleasantness of two fundamentally different rewards, taste in the mouth and warmth on the hand. The evidence came from two different investigations, a between-group comparison of two independent fMRI studies, and from a within-subject study. In the latter, we showed that neural activity in the same voxels in the ventral prefrontal cortex correlated with the subjective pleasantness of the different rewards. Moreover, the slope and intercept for the regression lines describing the relationship between activations and subjective pleasantness were highly similar for the different rewards. We also provide evidence that the activations did not simply represent multisensory integration or the salience of the rewards. The findings demonstrate the existence of a specific region in the human brain where neural activity scales with the subjective pleasantness of qualitatively different primary rewards. This suggests a principle of brain processing of importance in reward valuation and decision-making

How the brain represents the reward value of fat in the mouth.

The palatability and pleasantness of the sensory properties of foods drive food selection and intake and may contribute to overeating and obesity. Oral fat texture can make food palatable and pleasant. To analyze its neural basis, we correlated humans’ subjective reports of the pleasantness of the texture and flavor of a high- and low-fat food with a vanilla or strawberry flavor, with neural activations measured with functional magnetic resonance imaging. Activity in the midorbitofrontal and anterior cingulate cortex was correlated with the pleasantness of oral fat texture and in nearby locations with the pleasantness of flavor. The pregenual cingulate cortex showed a supralinear response to the combination of high fat and pleasant, sweet flavor, implicating it in the convergence of fat texture and flavor to produce a representation of highly pleasant stimuli. The subjective reports of oral fattiness were correlated with activations in the midorbitofrontal cortex and ventral striatum. The lateral hypothalamus and amygdala were more strongly activated by high- versus low-fat stimuli. This discovery of which brain regions track the subjective hedonic experience of fat texture will help to unravel possible differences in the neural responses in obese versus lean people to oral fat, a driver of food intake

Neural Basis for Economic Saving Strategies in Human Amygdala-Prefrontal Reward Circuits.

Economic saving is an elaborate behavior in which the goal of a reward in the future directs planning and decision-making in the present. Here, we measured neural activity while subjects formed simple economic saving strategies to accumulate rewards and then executed their strategies through choice sequences of self-defined lengths. Before the initiation of a choice sequence, prospective activations in the amygdala predicted subjects' internal saving plans and their value up to two minutes before a saving goal was achieved. The valuation component of this planning activity persisted during execution of the saving strategy and predicted subjects' economic behavior across different tasks and testing days. Functionally coupled amygdala and prefrontal cortex activities encoded distinct planning components that signaled the transition from saving strategy formation to execution and reflected individual differences in saving behavior. Our findings identify candidate neural mechanisms for economic saving in amygdala and prefrontal cortex and suggest a novel planning function for the human amygdala in directing strategic behavior toward self-determined future rewards

Primate amygdala neurons evaluate the progress of self-defined economic choice sequences.

The amygdala is a prime valuation structure yet its functions in advanced behaviors are poorly understood. We tested whether individual amygdala neurons encode a critical requirement for goal-directed behavior: the evaluation of progress during sequential choices. As monkeys progressed through choice sequences toward rewards, amygdala neurons showed phasic, gradually increasing responses over successive choice steps. These responses occurred in the absence of external progress cues or motor preplanning. They were often specific to self-defined sequences, typically disappearing during instructed control sequences with similar reward expectation. Their build-up rate reflected prospectively the forthcoming choice sequence, suggesting adaptation to an internal plan. Population decoding demonstrated a high-accuracy progress code. These findings indicate that amygdala neurons evaluate the progress of planned, self-defined behavioral sequences. Such progress signals seem essential for aligning stepwise choices with internal plans. Their presence in amygdala neurons may inform understanding of human conditions with amygdala dysfunction and deregulated reward pursuit

DNA Origami Nanoantennas for Fluorescence Enhancement

[Image: see text] The possibility to increase fluorescence by plasmonic effects in the near-field of metal nanostructures was recognized more than half a century ago. A major challenge, however, was to use this effect because placing single quantum emitters in the nanoscale plasmonic hotspot remained unsolved for a long time. This not only presents a chemical problem but also requires the nanostructure itself to be coaligned with the polarization of the excitation light. Additional difficulties arise from the complex distance dependence of fluorescence emission: in contrast to other surface-enhanced spectroscopies (such as Raman spectroscopy), the emitter should not be placed as close as possible to the metallic nanostructure but rather needs to be at an optimal distance on the order of a few nanometers to avoid undesired quenching effects. Our group addressed these challenges almost a decade ago by exploiting the unique positioning ability of DNA nanotechnology and reported the first self-assembled DNA origami nanoantennas. This Account summarizes our work spanning from this first proof-of-principle study to recent advances in utilizing DNA origami nanoantennas for single DNA molecule detection on a portable smartphone microscope. We summarize different aspects of DNA origami nanoantennas that are essential for achieving strong fluorescence enhancement and discuss how single-molecule fluorescence studies helped us to gain a better understanding of the interplay between fluorophores and plasmonic hotspots. Practical aspects of preparing the DNA origami nanoantennas and extending their utility are also discussed. Fluorescence enhancement in DNA origami nanoantennas is especially exciting for signal amplification in molecular diagnostic assays or in single-molecule biophysics, which could strongly benefit from higher time resolution. Additionally, biophysics can greatly profit from the ultrasmall effective detection volumes provided by DNA nanoantennas that allow single-molecule detection at drastically elevated concentrations as is required, e.g., in single-molecule DNA sequencing approaches. Finally, we describe our most recent progress in developing DNA NanoAntennas with Cleared HOtSpots (NACHOS) that are fully compatible with biomolecular assays. The developed DNA origami nanoantennas have proven robustness and remain functional after months of storage. As an example, we demonstrated for the first time the single-molecule detection of DNA specific to antibiotic-resistant bacteria on a portable and battery-driven smartphone microscope enabled by DNA origami nanoantennas. These recent developments mark a perfect moment to summarize the principles and the synthesis of DNA origami nanoantennas and give an outlook of new exciting directions toward using different nanomaterials for the construction of nanoantennas as well as for their emerging applications

The anticipation of events in time

Humans anticipate events signaled by sensory cues. It is commonly assumed that two uncertainty parameters modulate the brain's capacity to predict: the hazard rate (HR) of event probability and the uncertainty in time estimation which increases with elapsed time. We investigate both assumptions by presenting event probability density functions (PDFs) in each of three sensory modalities. We show that perceptual systems use the reciprocal PDF and not the HR to model event probability density. We also demonstrate that temporal uncertainty does not necessarily grow with elapsed time but can also diminish, depending on the event PDF. Previous research identified neuronal activity related to event probability in multiple levels of the cortical hierarchy (sensory (V4), association (LIP), motor and other areas) proposing the HR as an elementary neuronal computation. Our results—consistent across vision, audition, and somatosensation—suggest that the neurobiological implementation of event anticipation is based on a different, simpler and more stable computation than HR: the reciprocal PDF of events in time

An Investigation of the Excess Credit Hour Surcharge Policy and Its Impact on First-Time-In-College Students at a Large Metropolitan University in the State of Florida

An Excess Credit Hour policy assesses a tuition surcharge for any credits taken beyond a predetermined threshold (Smith, 2017, para. 1). In 2009, the State of Florida implemented legislation on excess credit hours at four-year public institutions, Fla. Stat. § 1009.286 (State of Florida, 2012). Legislation found under title forty-eight (XLVIII) of the K-20 Education Code, Fla. Stat. § 1009.286, relating to Educational Scholarships, Fees, and Financial Assistance, discussed the intent of the Legislature to encourage each undergraduate student who enrolls in a state university to complete the student\u27s respective baccalaureate degree program in the most efficient way possible… (State of Florida, 2018, para. 1). Throughout the duration of the policy, various entities were deficient in monitoring or delivering an assessment of this legislation to determine its effectiveness. Minimal legislative follow up and a small number of empirical studies have tried to confirm the proficiency of this policy in the State of Florida (Carvajal, 2021; State of Florida, 2018). A lack of empirical research exists regarding the relationship between first time-in-college students (FTIC) in the mechanical and aerospace engineering disciplines at a Large Metropolitan University (LMU) and the Excess Credit Hour Surcharge policy\u27s effect on student demographics and baccalaureate degree completion. This quantitative study will use pre-existing data to analyze the complex relationship between variables in collaboration with descriptive statistics. The data collection methods will report specific data points and demographics of students in mechanical and aerospace engineering at LMU. Findings from this study will provide further insight into the implementation of this policy and impart confirmation regarding its objective of increasing graduation rates while attempting to minimize credit hour utilization among students at State of Florida universities

Preferences for nutrients and sensory food qualities identify biological sources of economic values in monkeys.

Value is a foundational concept in reinforcement learning and economic choice theory. In these frameworks, individuals choose by assigning values to objects and learn by updating values with experience. These theories have been instrumental for revealing influences of probability, risk, and delay on choices. However, they do not explain how values are shaped by intrinsic properties of the choice objects themselves. Here, we investigated how economic value derives from the biologically critical components of foods: their nutrients and sensory qualities. When monkeys chose nutrient-defined liquids, they consistently preferred fat and sugar to low-nutrient alternatives. Rather than maximizing energy indiscriminately, they seemed to assign subjective values to specific nutrients, flexibly trading them against offered reward amounts. Nutrient-value functions accurately modeled these preferences, predicted choices across contexts, and accounted for individual differences. The monkeys' preferences shifted their daily nutrient balance away from dietary reference points, contrary to ecological foraging models but resembling human suboptimal eating in free-choice situations. To identify the sensory basis of nutrient values, we developed engineering tools that measured food textures on biological surfaces, mimicking oral conditions. Subjective valuations of two key texture parameters-viscosity and sliding friction-explained the monkeys' fat preferences, suggesting a texture-sensing mechanism for nutrient values. Extended reinforcement learning and choice models identified candidate neuronal mechanisms for nutrient-sensitive decision-making. These findings indicate that nutrients and food textures constitute critical reward components that shape economic values. Our nutrient-choice paradigm represents a promising tool for studying food-reward mechanisms in primates to better understand human-like eating behavior and obesity

A dynamic code for economic object valuation in prefrontal cortex neurons.

Neuronal reward valuations provide the physiological basis for economic behaviour. Yet, how such valuations are converted to economic decisions remains unclear. Here we show that the dorsolateral prefrontal cortex (DLPFC) implements a flexible value code based on object-specific valuations by single neurons. As monkeys perform a reward-based foraging task, individual DLPFC neurons signal the value of specific choice objects derived from recent experience. These neuronal object values satisfy principles of competitive choice mechanisms, track performance fluctuations and follow predictions of a classical behavioural model (Herrnstein's matching law). Individual neurons dynamically encode both, the updating of object values from recently experienced rewards, and their subsequent conversion to object choices during decision-making. Decoding from unselected populations enables a read-out of motivational and decision variables not emphasized by individual neurons. These findings suggest a dynamic single-neuron and population value code in DLPFC that advances from reward experiences to economic object values and future choices.Wellcome Trust, Behavioural and Clinical Neuroscience Institute (BCNI) Cambridg

Neural systems underlying decisions about affective odors.

Decision making about affective value may occur after the reward value of a stimulus is represented and may involve different brain areas to those involved in decision-making about the physical properties of stimuli, such as intensity. In an fMRI study, we delivered two odors separated by a delay, with instructions on different trials to decide which odor was more pleasant or more intense or to rate the pleasantness and intensity of the second odor without making a decision. The fMRI signals in the medial pFC area 10 and in regions to which it projects, including the ACC and insula, were higher when decisions were being made compared with ratings, implicating these regions in decision-making. Decision-making about affective value was related to larger signals in the dorsal part of medial area 10 and the agranular insula, whereas decisions about intensity were related to larger activations in the dorsolateral pFC, ventral premotor cortex, and anterior insula. For comparison, the mid-OFC had activations related not to decision making but to subjective pleasantness ratings, providing a continuous representation of affective value. In contrast, areas such as medial area 10 and the ACC are implicated in reaching a decision in which a binary outcome is produced