The orbitofrontal cortex (OFC) has been described as signaling outcome expectancies or value. Evidence for the latter comes from the studies showing that neural signals in the OFC correlate with value across features. Yet features can co-vary with value, and individual units may participate in multiple ensembles coding different features. Here we used unblocking to test whether OFC neurons would respond to a predictive cue signaling a ‘valueless’ change in outcome flavor. Neurons were recorded as the rats learned about cues that signaled either an increase in reward number or a valueless change in flavor. We found that OFC neurons acquired responses to both predictive cues. This activity exceeded that exhibited to a ‘blocked’ cue and was correlated with activity to the actual outcome. These results show that OFC neurons fire to cues with no value independent of what can be inferred through features of the predicted outcome.DOI: http://dx.doi.org/10.7554/eLife.02653.001
Objective: The human brain adjusts its level of effort in coping with various life stressors as a partial function of perceived access to social resources. We examined whether people who avoid social ties maintain a higher fasting basal level of glucose in their bloodstream and consume more sugar-rich food, reflecting strategies to draw more on personal resources when threatened. Methods: In Study 1 (N = 60), we obtained fasting blood glucose and adult attachment orientations data. In Study 2 (N = 285), we collected measures of fasting blood glucose and adult attachment orientations from older adults of mixed gender, using a measure of attachment style different from Study 1. In Study 3 (N = 108), we examined the link between trait-like attachment avoidance, manipulation of an asocial state, and consumption of sugar-rich food. In Study 4 (N = 115), we examined whether manipulating the social network will moderate the effect of attachment avoidance on consumption of sugar-rich food. Results: In Study 1, fasting blood glucose levels corresponded with higher attachment avoidance scores after statistically adjusting for time of assessment and interpersonal anxiety. For Study 2, fasting blood glucose continued to correspond with higher adult attachment avoidance even after statistically adjusting for interpersonal anxiety, stress indices, age, gender, social support and body mass. In Study 3, people high in attachment avoidance consume more sugar-rich food, especially when reminded of asocial tendencies. Study 4 indicated that after facing a stressful task in the presence of others, avoidant people gather more sugar-rich food than more socially oriented people. Conclusion: Results are consistent with the suggestion that socially avoidant individuals upwardly adjust their basal glucose levels and consume more glucose-rich food with the expectation of increased personal effort because of limited access to social resources. Further investigation of this link is warranted.
Nicotine has strong addictive as well as procognitive properties. While a large body of research on nicotine continues to inform us about mechanisms related to its reinforcing effects, less is known about clinically relevant mechanisms that subserve its cognitive-enhancing properties. Understanding the latter is critical for developing optimal strategies for treating cognitive deficits. The primary brain region implicated in cognitive functions improved by nicotine is the prefrontal cortex (PFC). Here we assessed the impact of nicotine on unit activity and local field potential oscillations in the PFC of behaving rats. An acute dose of nicotine produced a predominantly inhibitory influence on population activity, a small increase in gamma oscillations, and a decrease in theta and beta oscillations. After a daily dosing regimen, a shift to excitatory–inhibitory balance in single-unit activity and stronger gamma oscillations began to emerge. This pattern of plasticity was specific to the gamma band as lower frequency oscillations were suppressed consistently across daily nicotine treatments. Gamma oscillations are associated with enhanced attentional capacity. Consistent with this mechanism, the repeat dosing regimen in a separate cohort of subjects led to improved performance in an attention task. These data suggest that procognitive effects of nicotine may involve development of enhanced gamma oscillatory activity and a shift to excitatory–inhibitory balance in PFC neural activity. In the context of the clinical use of nicotine and related agonists for treating cognitive deficits, these data suggest that daily dosing may be critical to allow for development of robust gamma oscillations.
The neuronal underpinning of learning cause-and-effect associations in the adolescent brain remains poorly understood. Two fundamental forms of associative learning are Pavlovian (classical) conditioning, where a stimulus is followed by an outcome, and operant (instrumental) conditioning, where outcome is contingent on action execution. Both forms of learning, when associated with a rewarding outcome, rely on midbrain dopamine neurons in the ventral tegmental area (VTA) and substantia nigra (SN). We find that in adolescent male rats, reward-guided associative learning is encoded differently by midbrain dopamine neurons in each conditioning paradigm. Whereas simultaneously recorded VTA and SN adult neurons have a similar phasic response to reward delivery during both forms of conditioning, adolescent neurons display a muted reward response during operant but a profoundly larger reward response during Pavlovian conditioning suggesting that adolescent neurons assign a different value to reward when it is not gated by action. The learning rate of adolescents and adults during both forms of conditioning was similar further supporting the notion that differences in reward response in each paradigm are due to differences in motivation and independent of state versus action value learning. Static characteristics of dopamine neurons such as dopamine cell number and size were similar in the VTA and SN but there were age differences in baseline firing rate, stimulated release and correlated spike activity suggesting that differences in reward responsiveness by adolescent dopamine neurons are not due to differences in intrinsic properties of these neurons but engagement of different networks.
Neuronal underpinning of learning cause-and-effect associations in the adolescent brain remains poorly understood. Two fundamental forms of associative learning are Pavlovian (classical) conditioning, where a stimulus is followed by an outcome, and operant (instrumental) conditioning, where outcome is contingent on action execution. Both forms of learning, when associated with a rewarding outcome, rely on midbrain dopamine neurons in the ventral tegmental area (VTA) and substantia nigra (SN). We find that, in adolescent male rats, reward-guided associative learning is encoded differently by midbrain dopamine neurons in each conditioning paradigm. Whereas simultaneously recorded VTA and SN adult neurons have a similar phasic response to reward delivery during both forms of conditioning, adolescent neurons display a muted reward response during operant but a profoundly larger reward response during Pavlovian conditioning. These results suggest that adolescent neurons assign a different value to reward when it is not gated by action. The learning rate of adolescents and adults during both forms of conditioning was similar, supporting the notion that differences in reward response in each paradigm may be because of differences in motivation and independent of state versus action value learning. Static characteristics of dopamine neurons, such as dopamine cell number and size, were similar in the VTA and SN of both ages, but there were age-related differences in stimulated dopamine release and correlated spike activity, suggesting that differences in reward responsiveness by adolescent dopamine neurons are not because of differences in intrinsic properties of these neurons but engagement of different dopaminergic networks.SIGNIFICANCE STATEMENTReckless behavior and impulsive decision-making by adolescents suggest that motivated behavioral states are encoded differently by the adolescent brain. Motivated behavior, which is dependent on the function of the dopamine system, follows learning of cause-and-effect associations in the environment. We find that dopamine neurons in adolescents encode reward differently depending on the cause-and-effect relationship of the means to receive that reward. Compared with adults, reward contingent on action led to a muted response, whereas reward that followed a cue but was not gated by action produced an augmented phasic response. These data demonstrate an age-related difference in dopamine neuron response to reward that is not uniform and is guided by processes that differentiate between state and action values.
Extracting single-unit activity from in vivo extracellular neural electrophysiology data requires sorting spikes from background noise and action potentials from multiple cells in order to identify the activity of individual neurons. Typically this has been achieved by algorithms that employ principal component analyses followed by manual allocation of spikes to individual clusters based on visual inspection of the waveform shape. This method of manual sorting can give varying results between human operators and is highly time-consuming, especially in recordings with higher levels of background noise. To address these problems, automatic sorting algorithms have begun to gain popularity as viable methods for sorting electrophysiological data, although little is known about the use of these algorithms with neural data from midbrain recordings. KiloSort is a relatively new algorithm that automatically clusters raw data which can then be manually curated. In this report, we compare results of manually-sorted and KiloSort-processed recordings from the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). Sorting with KiloSort required substantially less time to complete, while yielding comparable and consistent results. We conclude that the use of KiloSort to identify single units from multi-channel recording in the VTA and SNc is accurate and efficient.
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