Progression of phosphorylated α-synuclein in Macaca fuscata

Prion‐like spreading of abnormal proteins is proposed to occur in neurodegenerative diseases, and the progression of α‐synuclein (α‐syn) deposits has been reported in the brains of animal models injected with synthetic α‐syn fibrils or pathological α‐syn prepared from patients with Parkinson's disease (PD) and dementia with Lewy bodies (DLB). However, α‐syn transmission in nonhuman primates, which are more similar to humans, has not been fully clarified. Here, we injected synthetic human α‐syn fibrils into the left striatum of a macaque monkey (Macaca fuscata). At 3 months after the injection, we examined neurodegeneration and α‐syn pathology in the brain using α‐syn epitope‐specific antibodies, antiphosphorylated α‐syn antibodies (pSyn#64 and pSer129), anti‐ubiquitin antibodies, and anti‐p62 antibodies. Immunohistochemical examination with pSyn#64, pSer129, and α‐syn epitope‐specific antibodies revealed Lewy bodies, massive α‐syn‐positive neuronal intracytoplasmic inclusions (NCIs), and neurites in the left putamen. These inclusions were also positive for ubiquitin and p62. LB509, a human‐specific α‐syn antibody targeting amino acid residues 115–122, showed limited immunoreactivity around the injection site. The left substantia nigra (SN) and the bilateral frontal cortex also contained some NCIs and neurites. The left hemisphere, including parietal/temporal cortex presented sparse α‐syn pathology, and no immunoreactivity was seen in olfactory nerves, amygdala, hippocampus, or right parietal/temporal cortex. Neuronal loss and gliosis in regions with α‐syn pathology were mild, except for the left striatum and SN. Our results indicate that abnormal α‐syn fibrils propagate throughout the brain of M. fuscata via projection, association, and commissural fibers, though the progression of α‐syn pathology is limited.

Renal arteriolar hyalinosis, not intimal thickening in large arteries, is associated with cardiovascular events in people with biopsy-proven diabetic nephropathy

AIMS

Diabetic nephropathy, a pathologically diagnosed microvascular complication of diabetes, is a strong risk factor for cardiovascular events, which mainly involve arteries larger than those affected in diabetic nephropathy. However, the association between diabetic nephropathy pathological findings and cardiovascular events has not been well studied. We aimed to investigate whether the pathological findings in diabetic nephropathy are closely associated with cardiovascular event development.

METHODS

This retrospective cohort study analysed 377 people with type 2 diabetes and biopsy-proven diabetic nephropathy, with a median follow-up of 5.9 years (interquartile range 2.0 to 13.5). We investigated how cardiovascular events were impacted by two vascular diabetic nephropathy lesions, namely arteriolar hyalinosis and arterial intimal thickening, and by glomerular and interstitial lesions.

RESULTS

Of the 377 people with diabetic nephropathy, 331 (88%) and 295 (78%) had arteriolar hyalinosis and arterial intimal thickening, respectively. During the entire follow-up period, those with arteriolar hyalinosis had higher cardiovascular event rates in the crude Kaplan-Meier analysis than those without these lesions (P = 0.005, log-rank test). When fully adjusted for clinically relevant confounders, arteriolar hyalinosis independently predicted cardiovascular events [hazard ratio (HR) 1.99; 95% confidence interval (CI) 1.12, 3.86], but we did not find any relationship between arterial intimal thickening and cardiovascular events (HR 0.89; 95% CI 0.60, 1.37). Additionally, neither glomerular nor interstitial lesions were independently associated with cardiovascular events in the fully adjusted model.

CONCLUSIONS

Arteriolar hyalinosis, but not intimal thickening of large arteries, was strongly associated with cardiovascular events in people with diabetic nephropathy.

Neuronal Representation of Object Choice in the Striatum of the Monkey

According to a widely held view, the decision-making process can be conceptualized as a two-step process: “object choice,” which does not include physical actions, followed by “movement choice,” in which action is executed to obtain the object. Accumulating evidence in the field of decision neuroscience suggests that the cortico-basal ganglia circuits play a crucial role in decision-making. However, the underlying mechanisms of the object and movement choices remain poorly understood, mainly because the two processes occur simultaneously in most experiments. In this study, to uncover the neuronal basis of object choice in the striatum, the main input site of the basal ganglia, we designed a behavioral task in which the processes of object and movement choice were temporally separated, and recorded the single-unit activity of phasically active neurons (PANs) (n = 375) in the striatum of two monkeys. We focused our study mainly on neuronal representation during the object choice period, before movement choice, using a mutual information analysis. Population striatal activities significantly represented the information of the chosen object during the object choice period, which indicated that the monkeys actually made the object choice during the task. For the activity of each individual neuron during the object choice period, we identified offered object- and chosen object-type neurons, corresponding to pre- and post-decision signals, respectively. We also found the movement-type neurons during the movement period after the object choice. Most offered object- or chosen object-type neurons were not overlapped with movement-type neurons. The presence of object choice-related signals independent of movement signal in the striatum indicated that the striatum was part of the site where object choice was made within a cortico-basal ganglia circuit.

Distinct Functions of the Primate Putamen Direct and Indirect Pathways in Adaptive Outcome-Based Action Selection

Cortico-basal ganglia circuits are critical regulators of reward-based decision making. Reinforcement learning models posit that action reward value is encoded by the firing activity of striatal medium spiny neurons (MSNs) and updated upon changing reinforcement contingencies by dopamine (DA) signaling to these neurons. However, it remains unclear how the anatomically distinct direct and indirect pathways through the basal ganglia are involved in updating action reward value under changing contingencies. MSNs of the direct pathway predominantly express DA D1 receptors and those of the indirect pathway predominantly D2 receptors, so we tested for distinct functions in behavioral adaptation by injecting D1 and D2 receptor antagonists into the putamen of two macaque monkeys performing a free choice task for probabilistic reward. In this task, monkeys turned a handle toward either a left or right target depending on an asymmetrically assigned probability of large reward. Reward probabilities of left and right targets changed after 30–150 trials, so the monkeys were required to learn the higher-value target choice based on action–outcome history. In the control condition, the monkeys showed stable selection of the higher-value target (that more likely to yield large reward) and kept choosing the higher-value target regardless of less frequent small reward outcomes. The monkeys also made flexible changes of selection away from the high-value target when two or three small reward outcomes occurred randomly in succession. DA D1 antagonist injection significantly increased the probability of the monkey switching to the alternate target in response to successive small reward outcomes. Conversely, D2 antagonist injection significantly decreased the switching probability. These results suggest distinct functions of D1 and D2 receptor-mediated signaling processes in action selection based on action–outcome history, with D1 receptor-mediated signaling promoting the stable choice of higher-value targets and D2 receptor-mediated signaling promoting a switch in action away from small reward outcomes. Therefore, direct and indirect pathways appear to have complementary functions in maintaining optimal goal-directed action selection and updating action value, which are dependent on D1 and D2 DA receptor signaling.

Characteristics of fast-spiking neurons in the striatum of behaving monkeys

Inhibitory interneurons are the fundamental constituents of neural circuits that organize network outputs. The striatum as part of the basal ganglia is involved in reward-directed behaviors. However, the role of the inhibitory interneurons in this process remains unclear, especially in behaving monkeys. We recorded the striatal single neuron activity while monkeys performed reward-directed hand or eye movements. Presumed parvalbumin-containing GABAergic interneurons (fast-spiking neurons, FSNs) were identified based on narrow spike shapes in three independent experiments, though they were a small population (4.2%, 42/997). We found that FSNs are characterized by high-frequency and less-bursty discharges, which are distinct from the basic firing properties of the presumed projection neurons (phasically active neurons, PANs). Besides, the encoded information regarding actions and outcomes was similar between FSNs and PANs in terms of proportion of neurons, but the discharge selectivity was higher in PANs than that of FSNs. The coding of actions and outcomes in FSNs and PANs was consistently observed under various behavioral contexts in distinct parts of the striatum (caudate nucleus, putamen, and anterior striatum). Our results suggest that FSNs may enhance the discharge selectivity of postsynaptic output neurons (PANs) in encoding crucial variables for a reward-directed behavior.

Impact of stimulus uncanniness on speeded response

In the uncanny valley phenomenon, the causes of the feeling of uncanniness as well as the impact of the uncanniness on behavioral performances still remain open. The present study investigated the behavioral effects of stimulus uncanniness, particularly with respect to speeded response. Pictures of fish were used as visual stimuli. Participants engaged in direction discrimination, spatial cueing, and dot-probe tasks. The results showed that pictures rated as strongly uncanny delayed speeded response in the discrimination of the direction of the fish. In the cueing experiment, where a fish served as a task-irrelevant and unpredictable cue for a peripheral target, we again observed that the detection of a target was slowed when the cue was an uncanny fish. Conversely, the dot-probe task suggested that uncanny fish, unlike threatening stimulus, did not capture visual spatial attention. These results suggested that stimulus uncanniness resulted in the delayed response, and importantly this modulation was not mediated by the feelings of threat.

Effects of depression on reward-based decision making and variability of action in probabilistic learning

BACKGROUND AND OBJECTIVES

Depression is characterized by low reward sensitivity in behavioral studies applying signal detection theory. We examined deficits in reward-based decision making in depressed participants during a probabilistic learning task, and used a reinforcement learning model to examine learning parameters during the task.

METHODS

Thirty-six nonclinical undergraduates completed a probabilistic selection task. Participants were divided into depressed and non-depressed groups based on Center for Epidemiologic Studies-Depression (CES-D) cut scores. We then applied a reinforcement learning model to every participant's behavioral data.

RESULTS

Depressed participants showed a reward-based decision making deficit and higher levels of the learning parameter τ, which modulates variability of action selection, as compared to non-depressed participants. Highly variable action selection is more random and characterized by difficulties with selecting a specific course of action.

CONCLUSION

These results suggest that depression is characterized by deficits in reward-based decision making as well as high variability in terms of action selection.

Photosensitive-polyimide based method for fabricating various neural electrode architectures

An extensive photosensitive-polyimide (PSPI)-based method for designing and fabricating various neural electrode architectures was developed. The method aims to broaden the design flexibility and expand the fabrication capability for neural electrodes to improve the quality of recorded signals and integrate other functions. After characterizing PSPI's properties for micromachining processes, we successfully designed and fabricated various neural electrodes even on a non-flat substrate using only one PSPI as an insulation material and without the time-consuming dry etching processes. The fabricated neural electrodes were an electrocorticogram (ECoG) electrode, a mesh intracortical electrode with a unique lattice-like mesh structure to fixate neural tissue, and a guide cannula electrode with recording microelectrodes placed on the curved surface of a guide cannula as a microdialysis probe. In vivo neural recordings using anesthetized rats demonstrated that these electrodes can be used to record neural activities repeatedly without any breakage and mechanical failures, which potentially promises stable recordings for long periods of time. These successes make us believe that this PSPI-based fabrication is a powerful method, permitting flexible design, and easy optimization of electrode architectures for a variety of electrophysiological experimental research with improved neural recording performance.

Stimulus-dependent adjustment of reward prediction error in the midbrain

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus-reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus.

Development of a BCI master switch based on single-trial detection of contingent negative variation related potentials

To control the startup/shutdown of a conventional brain-computer interface (BCI) that is always running for daily use, we proposed and developed a new BCI system called a BCI master switch. We designed it with on/off switching functions by detecting the contingent negative variation (CNV)--related potentials. We chose CNV to improve the single-trial discrimination of user intentions to switch because CNV had a high signal-to-noise ratio and needed high concentration for its elicitation. We also applied a support vector machine (SVM) to improve the single-trial detection of CNV-related potentials. As the best parameters of SVM were estimated and applied, the offline evaluation's best performance achieved a CNV detection rate of 99.3% for the intention to switch and 2.1% for the intention not to switch. Remarkably, this performance was achieved from single-trial detection, imaginary response of user's intention without physical reaction, and the data from only one recording electrode. These results suggest that our proposed BCI system might work as a master switch by single-trial detection.

Multiple representations of belief states and action values in corticobasal ganglia loops

Reward-related neural activities have been found in a variety of cortical and subcortical areas by neurophysiological and neuroimaging experiments. Here we present a unified view on how three subloops of the corticobasal ganglia network are involved in reward prediction and action selection using different types of information. The motor/premotor-posterior striatum loop is specialized for action-based value representation and movement selection. The orbitofrontal-ventral striatum loop is specialized for object-based value representation and target selection. The lateral prefrontal-anterior striatum loop is specialized for context-based value representation and context estimation. Furthermore, the medial prefrontal cortex (MPFC) coordinates these multiple value representations and actions at different levels of hierarchy by monitoring the error in predictions.

Efficient reinforcement learning: computational theories, neuroscience and robotics

Reinforcement learning algorithms have provided some of the most influential computational theories for behavioral learning that depends on reward and penalty. After briefly reviewing supporting experimental data, this paper tackles three difficult theoretical issues that remain to be explored. First, plain reinforcement learning is much too slow to be considered a plausible brain model. Second, although the temporal-difference error has an important role both in theory and in experiments, how to compute it remains an enigma. Third, function of all brain areas, including the cerebral cortex, cerebellum, brainstem and basal ganglia, seems to necessitate a new computational framework. Computational studies that emphasize meta-parameters, hierarchy, modularity and supervised learning to resolve these issues are reviewed here, together with the related experimental data.

Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics

In learning goal-directed behaviors, an agent has to consider not only the reward given at each state but also the consequences of dynamic state transitions associated with action selection. To understand brain mechanisms for action learning under predictable and unpredictable environmental dynamics, we measured brain activities by functional magnetic resonance imaging (fMRI) during a Markov decision task with predictable and unpredictable state transitions. Whereas the striatum and orbitofrontal cortex (OFC) were significantly activated both under predictable and unpredictable state transition rules, the dorsolateral prefrontal cortex (DLPFC) was more strongly activated under predictable than under unpredictable state transition rules. We then modelled subjects' choice behaviours using a reinforcement learning model and a Bayesian estimation framework and found that the subjects took larger temporal discount factors under predictable state transition rules. Model-based analysis of fMRI data revealed different engagement of striatum in reward prediction under different state transition dynamics. The ventral striatum was involved in reward prediction under both unpredictable and predictable state transition rules, although the dorsal striatum was dominantly involved in reward prediction under predictable rules. These results suggest different learning systems in the cortico-striatum loops depending on the dynamics of the environment: the OFC-ventral striatum loop is involved in action learning based on the present state, while the DLPFC-dorsal striatum loop is involved in action learning based on predictable future states.

Representation of Action-Specific Reward Values in the Striatum

The estimation of the reward an action will yield is critical in decision-making. To elucidate the role of the basal ganglia in this process, we recorded striatal neurons of monkeys who chose between left and right handle turns, based on the estimated reward probabilities of the actions. During a delay period before the choices, the activity of more than one-third of striatal projection neurons was selective to the values of one of the two actions. Fewer neurons were tuned to relative values or action choice. These results suggest representation of action values in the striatum, which can guide action selection in the basal ganglia circuit.

Microbiological and chemical quality of ground beef treated with sodium lactate and sodium chloride during refrigerated storage

The effects of sodium lactate (NaL) and sodium chloride (NaCl), either alone (30 g/kg) or in combination (20+20 g/kg), on the microbiological and chemical quality of raw ground beef during vacuum-packaged storage at 2 degrees C were investigated. The results showed that addition of NaL alone or in combination with NaCl significantly delayed the proliferation of aerobic plate counts, psychrotrophic counts, lactic acid bacteria and Enterobacteriaceae and extended the shelf life of the product up to 15 and 21 days, respectively, versus 8 days only for control. Over the storage time (21 days), NaL maintained the ground beef at almost constant pH, while the pH of control or NaCl-treated samples significantly decreased. Lipid oxidation (TBA value) was not affected by addition of NaL. At storage day 21 however, TBA values of both NaL-treated (0.309) and control (0.318) samples were significantly lower than those of samples treated with NaCl (0.463). The combination of NaCl with NaL significantly reduced the oxidative changes caused by NaCl (0.384 versus 0.463). Therefore, NaL alone or in combination with NaCl could be utilized successfully to reduce the microbial growth, maintain the chemical quality, and extend the shelf life of ground beef during refrigerated storage.