Neural Correlates of Opponent Processes for Financial Gains and Losses

Objective: Functional imaging studies offer alternative explanations for the neural correlates of monetary gain and loss related brain activity, and their opponents, omission of gains and losses. One possible explanation based on the psychology of opponent process theory suggests that successful avoidance of an aversive outcome is itself rewarding, and hence activates brain regions involved in reward processing. In order to test this hypothesis, we compared brain activation for successful avoidance of losses and receipt of monetary gains. Additionally, the brain regions involved in processing of frustrative neutral outcomes and actual losses were compared in order to test whether these two representations are coded in common or distinct brain regions. Methods: Using a 3 Tesla functional magnetic resonance imaging machine, fifteen healthy volunteers between the ages 22 to 28 were scanned for blood oxygen level dependent signal changes while they were performing a probabilistic learning task, wherein each trial a participant chose one of the two available options in order to win or avoid losing money. Results: The results confirmed, previous findings showing that medial frontal cortex and ventral striatum show significant activation (p<0.001) not only for monetary gains but also for successful avoidance of losses. A similar activation pattern was also observed for monetary losses and avoidance of gains in the medial frontal cortex, and posterior cingulate cortex, however, there was increased activation in amygdala specific to monetary losses (p<0.001). Further, subtraction analysis showed that regardless of the type of loss (i.e., frustrative neutral outcomes) posterior insula showed increased activation. Conclusion: This study provides evidence for a significant overlap not only between gains and losses, but also between their opponents. The results suggested that the overlapping activity pattern in the medial frontal cortex could be explained by a more abstract function of medial frontal cortex, such as outcome evaluation or performance monitoring, which possibly does not differentiate between winning and losing monetary outcomes.Peer reviewedFinal Published versio

Human Uniqueness, Cognition by Description, and Procedural Memory

Evidence will be reviewed suggesting a fairly direct link between the human ability to think about entities which one has never perceived — here called “cognition by description” — and procedural memory. Cognition by description is a uniquely hominid trait which makes religion, science, and history possible. It is hypothesized that cognition by description (in the manner of Bertrand Russell’s “knowledge by description”) requires variable binding, which in turn utilizes quantifier raising. Quantifier raising plausibly depends upon the computational core of language, specifically the element of it which Noam Chomsky calls “internal Merge”. Internal Merge produces hierarchical structures by means of a memory of derivational steps, a process plausibly involving procedural memory. The hypothesis is testable, predicting that procedural memory deficits will be accompanied by impairments in cognition by description. We also discuss neural mechanisms plausibly underlying procedural memory and also, by our hypothesis, cognition by description

Neurological Basis of Bodily Self-Consciousness and Related Psychopathologies

The change in the body awareness of people depending on the dynamic processing of the multisensory signals from the body has been revealed the bodily self-consciousness approach. Recent studies have proposed that the processing and integration of multisensory signals (i.e. vestibular, somatosensory) are fundamental requirement for bodily self-consciousness. Perception of body-parts and global aspect of whole body can dynamically change depending on the congruency between signals from multiple modalities (i.e. vestibular, somatosensory). The basic assumption of the studies investigating bodily self-consciousness is that the bodily experiences are related with the multisensory signal processing. The aim of the present article is to review how the bodily self-consciousness is studied experimentally and discuss the underlying sensory processes. In addition to that, we discussed the limitations of the previous experimental studies

Study protocol to examine the effects of spaceflight and a spaceflight analog on neurocognitive performance: extent, longevity, and neural bases

Abstract Background Long duration spaceflight (i.e., 22 days or longer) has been associated with changes in sensorimotor systems, resulting in difficulties that astronauts experience with posture control, locomotion, and manual control. The microgravity environment is an important causal factor for spaceflight induced sensorimotor changes. Whether spaceflight also affects other central nervous system functions such as cognition is yet largely unknown, but of importance in consideration of the health and performance of crewmembers both in- and post-flight. We are therefore conducting a controlled prospective longitudinal study to investigate the effects of spaceflight on the extent, longevity and neural bases of sensorimotor and cognitive performance changes. Here we present the protocol of our study. Methods/design This study includes three groups (astronauts, bed rest subjects, ground-based control subjects) for which each the design is single group with repeated measures. The effects of spaceflight on the brain will be investigated in astronauts who will be assessed at two time points pre-, at three time points during-, and at four time points following a spaceflight mission of six months. To parse out the effect of microgravity from the overall effects of spaceflight, we investigate the effects of seventy days head-down tilted bed rest. Bed rest subjects will be assessed at two time points before-, two time points during-, and three time points post-bed rest. A third group of ground based controls will be measured at four time points to assess reliability of our measures over time. For all participants and at all time points, except in flight, measures of neurocognitive performance, fine motor control, gait, balance, structural MRI (T1, DTI), task fMRI, and functional connectivity MRI will be obtained. In flight, astronauts will complete some of the tasks that they complete pre- and post flight, including tasks measuring spatial working memory, sensorimotor adaptation, and fine motor performance. Potential changes over time and associations between cognition, motor-behavior, and brain structure and function will be analyzed. Discussion This study explores how spaceflight induced brain changes impact functional performance. This understanding could aid in the design of targeted countermeasures to mitigate the negative effects of long-duration spaceflight.http://deepblue.lib.umich.edu/bitstream/2027.42/112560/1/12883_2013_Article_922.pd

Focal Gray Matter Plasticity as a Function of Long Duration Head-down Tilt Bed Rest

Long duration spaceflight (i.e., 22 days or longer) has been associated with changes in sensorimotor systems, resulting in difficulties that astronauts experience with posture control, locomotion, and manual control. The microgravity environment is an important causal factor for spaceflight induced sensorimotor changes. Whether these sensorimotor changes may be related to structural and functional brain changes is yet unknown. However, increased intracranial pressure that by itself has been related to microgravity-induced bodily fluid shifts: [1] has been associated with white matter microstructural damage, [2] Thus, it is possible that spaceflight may affect brain structure and thereby cognitive functioning. Long duration head-down tilt bed rest has been suggested as an exclusionary analog to study microgravity effects on the sensorimotor system, [3] Bed rest mimics microgravity in body unloading and bodily fluid shifts. In consideration of the health and performance of crewmembers both in- and post-flight, we are conducting a prospective longitudinal 70-day bed rest study as an analog to investigate the effects of microgravity on brain structure, and [4] Here we present results of the first eight subjects

Computational Model-Based Functional Magnetic Resonance Imaging of Reinforcement Learning in Humans

The aim of this thesis is to determine the changes in BOLD signal of the human brain during various stages of reinforcement learning. In order to accomplish that goal two probabilistic reinforcement-learning tasks were developed and assessed with healthy participants by using functional magnetic resonance imaging (fMRI). For both experiments the brain imaging data of the participants were analysed by using a combination of univariate and model–based techniques. In Experiment 1 there were three types of stimulus-response pairs where they predict either a reward, a neutral or a monetary loss outcome with a certain probability. The Experiment 1 tested the following research questions: Where does the activity occur in the brain for expecting and receiving a monetary reward and a punishment ? Does avoiding a loss outcome activate similar brain regions as gain outcomes and vice a verse does avoiding a reward outcome activate similar brain regions as loss outcomes? Where in the brain prediction errors, and predictions for rewards and losses are calculated? What are the neural correlates of reward and loss predictions for reward and loss during early and late phases in learning? The results of the Experiment 1 have shown that expectation for reward and losses activate overlapping brain areas mainly in the anterior cingulate cortex and basal ganglia but outcomes of rewards and losses activate separate brain regions, outcomes of losses mainly activate insula and amygdala whereas reward activate bilateral medial frontal gyrus. The model-based analysis also revealed early versus late learning related changes. It was found that predicted-value in early trials is coded in the ventro-medial orbito frontal cortex but later in learning the activation for the predicted value was found in the putamen. The second experiment was designed to find out the differences in processing novel versus familiar reward-predictive stimuli. The results revealed that dorso-lateral prefrontal cortex and several regions in the parietal cortex showed greater activation for novel stimuli than for familiar stimuli. As an extension to the fourth research question of Experiment 1, reward predictedvalues of the conditional stimuli and prediction errors of unconditional stimuli were also assessed in Experiment 2. The results revealed that during learning there is a significant activation of the prediction error mainly in the ventral striatum with extension to various cortical regions but for familiar stimuli no prediction error activity was observed. Moreover, predicted values for novel stimuli activate mainly ventro-medial orbito frontal cortex and precuneus whereas the predicted value of familiar stimuli activates putamen. The results of Experiment 2 for the predictedvalues reviewed together with the early versus later predicted values in Experiment 1 suggest that during learning of CS-US pairs activation in the brain shifts from ventro-medial orbito frontal structures to sensori-motor parts of the striatum

Computational model-based functional magnetic resonance imaging of reinforcement learning in humans

The aim of this thesis is to determine the changes in BOLD signal of the human brain during various stages of reinforcement learning. In order to accomplish that goal two probabilistic reinforcement-learning tasks were developed and assessed with healthy participants by using functional magnetic resonance imaging (fMRI). For both experiments the brain imaging data of the participants were analysed by using a combination of univariate and model–based techniques. In Experiment 1 there were three types of stimulus-response pairs where they predict either a reward, a neutral or a monetary loss outcome with a certain probability. The Experiment 1 tested the following research questions: Where does the activity occur in the brain for expecting and receiving a monetary reward and a punishment ? Does avoiding a loss outcome activate similar brain regions as gain outcomes and vice a verse does avoiding a reward outcome activate similar brain regions as loss outcomes? Where in the brain prediction errors, and predictions for rewards and losses are calculated? What are the neural correlates of reward and loss predictions for reward and loss during early and late phases in learning? The results of the Experiment 1 have shown that expectation for reward and losses activate overlapping brain areas mainly in the anterior cingulate cortex and basal ganglia but outcomes of rewards and losses activate separate brain regions, outcomes of losses mainly activate insula and amygdala whereas reward activate bilateral medial frontal gyrus. The model-based analysis also revealed early versus late learning related changes. It was found that predicted-value in early trials is coded in the ventro-medial orbito frontal cortex but later in learning the activation for the predicted value was found in the putamen. The second experiment was designed to find out the differences in processing novel versus familiar reward-predictive stimuli. The results revealed that dorso-lateral prefrontal cortex and several regions in the parietal cortex showed greater activation for novel stimuli than for familiar stimuli. As an extension to the fourth research question of Experiment 1, reward predictedvalues of the conditional stimuli and prediction errors of unconditional stimuli were also assessed in Experiment 2. The results revealed that during learning there is a significant activation of the prediction error mainly in the ventral striatum with extension to various cortical regions but for familiar stimuli no prediction error activity was observed. Moreover, predicted values for novel stimuli activate mainly ventro-medial orbito frontal cortex and precuneus whereas the predicted value of familiar stimuli activates putamen. The results of Experiment 2 for the predictedvalues reviewed together with the early versus later predicted values in Experiment 1 suggest that during learning of CS-US pairs activation in the brain shifts from ventro-medial orbito frontal structures to sensori-motor parts of the striatum.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Ödülün, bağlamın ve belirsizliğin olasılıksal öğrenmeye olan etkisi.

In this thesis, the learning of probabilistic relationships between stimulus-action pairs is investigated under the probability learning paradigm. The effect of reward is investigated in the first three experiments. Additionally, the effect of context and uncertainty is investigated in the second and third experiments, respectively. The fourth experiment is the replication of the second experiment with a group of Parkinson patients where the effect of dopamine medication on probability learning is studied. In Experiment 1, we replicate the classical probability learning task by comparing monetary and non-monetary reward feedback. Probability learning behavior is observed in both monetary and non-monetary rewarding feedback conditions. However, no significant difference between the monetary and non-monetary feedback conditions is observed. In Experiment 2, a variation of the probability learning task which includes irrelevant contextual information is applied. Probability learning behavior is observed, and a significant effect is found between monetary and non-monetary feedback conditions. In Experiment 3; a probability learning task similar to that in Experiment 2 is applied, however, in this experiment, stimulus included relevant contextual information. As expected, due to the utilization of the relevant contextual information from the start of the experiment, no significant effect is found for probability learning behavior. The effect of uncertainty observed in this experiment is a replication of the reports in literature. Experiment 4 is identical to Experiment 2; except that the subject population is a group of dopamine medicated Parkinson patients and a group of age matched controls. This experiment is introduced to test the suggestions in the literature regarding the enhancement effect of dopamine medication in probability learning based on positive feedback conditions. In Experiment 4, probability learning behavior is observed in both groups, but the difference in learning performance between Parkinson patients and controls was not significant, probably due to the low number of subject recruited in the experiment. In addition to these investigations, learning mechanisms are also examined in Experiments 1 and 4. Our results indicate that subjects initially search for patterns which lead to probability learning. At the end of Experiments 1 and 4, upon learning the winning frequencies, subjects change their behavior and demonstrate maximization behavior, which makes them prefer continuously one option over the other.M.S. - Master of Scienc

The Influence of Wobble Board on Spatial Learning and Navigation: Sex Differences in Learning Performance

In order to determine how postural control affects spatial memory performance, the present study looked at the interaction between postural control on a wobble board and performance in a concurrent spatial navigation task (virtual Morris water maze) in 68 participants. Participants in dual task condition navigated the virtual maze on a wobble board, while participants in single task condition navigated in the normal standing way. Postural sway errors on wobble board, path length and duration to find platform were measured during the experiment. The main effect of the condition showed that participants in the dual task condition took longer paths to find the hidden platform, and were slower compared to participants in the single task condition. In terms of sex differences, the results showed that male participants found the hidden platform faster and used shorter paths than females in both conditions

Sağlıklı Yetişkinlerde Sinirsel Geribildirim Eğitiminin Dikkat Değişkenleri Üzerindeki Etkisi

The aim of present study is to examine the effect of neurofeedback training on attentional processes in two groups of healthy adult participants. During the experiment, participants in the experimental group were required to complete two puzzles displayed on the computer screen while having neu-rofeedback training. During this procedure, performance on the puzzles was based on participants’ brain activity that was recorded from the Cz area. Moreover, before and after completion of seven neurofeedback sessions, Stroop task was used to measure selective attention performance. Results for the Stroop task showed that although there was a significant reaction time difference before and after the neurofeedback training, there was no significant main effect of group (experimental vs. control group). Furthermore, the reaction time to complete the puzzles across the sessions did not differ significantly between the experimental and the control group. Improving the training program by increasing the number of training sessions and employing a more attention-demanding task in the training sessions might have resulted in an expected effect of neurofeedback