- +49 30 314 73241
Doris Pischedda
University of Pavia, Brain and Behavioural Sciences, Faculty Member
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Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, our understanding of the way these networks are involved in intentions is still very limited. In this study, we... more
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, our understanding of the way these networks are involved in intentions is still very limited. In this study, we investigate two characteristics of these processes: context- and reason-dependence of the neural states associated with intentions. We ask whether these states depend on the context a person is in and the reasons they have for choosing an action. We used a combination of functional magnetic resonance imaging (fMRI) and multivariate decoding to directly assess the context- and reason-dependency of the neural states underlying intentions. We show that action intentions can be decoded from fMRI data based on a classifier trained in the same context and with the same reason, in line with previous decoding studies. Furthermore, we found that intentions can be decoded across different reasons for choosing an action. However, decoding across different contexts was not successful. We found anecdotal to moderate evidence against context-invariant information in all regions of interest and for all conditions but one. These results suggest that the neural states associated with intentions are modulated by the context of the action.
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Deciding the best action in social settings requires decision-makers to consider their and others’ preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior... more
Deciding the best action in social settings requires decision-makers to consider their and others’ preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior across individuals in strategic situations. While prosocial, moral, and emotional factors have been intensively investigated to explain this diversity, neuro-cognitive determinants of strategic decision-making and their relation with intelligence remain mostly unknown. This study presents a new model of the process of strategic decision-making in repeated interactions, first providing a precise measure of the environment’s complexity, and then analyzing how this complexity affects subjects’ performance and neural response. The results confirm the theoretical predictions of the model. The frequency of deviations from optimal behavior is explained by a combination of higher complexity of the strategic environment and cognitive skills of the individual...
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Surgical face masks reduce the spread of airborne pathogens but also disturb the flow of information between individuals. The risk of getting seriously ill after infection with SARS-COV-2 during the present COVID-19 pandemic amplifies... more
Surgical face masks reduce the spread of airborne pathogens but also disturb the flow of information between individuals. The risk of getting seriously ill after infection with SARS-COV-2 during the present COVID-19 pandemic amplifies with age, suggesting that face masks should be worn especially during face-to-face contact with and between older people. However, the ability to accurately perceive and understand communication signals decreases with age, and it is currently unknown whether face masks impair facial communication more severely in older people. We compared the impact of surgical face masks on dynamic facial emotion recognition in younger (18–30 years) and older (65–85 years) adults (N = 96) in an online study. Participants watched short video clips of young women who facially expressed anger, fear, contempt or sadness. Faces of half of the women were covered by a digitally added surgical face mask. As expected, emotion recognition accuracy declined with age, and face ma...
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Introduction: To investigate the processes and mechanism(s) underlying decision making in a group of Italian Air Force fighter pilots and navigators analyzing morphologic and functional MRI data to identify brain areas involved in... more
Introduction: To investigate the processes and mechanism(s) underlying decision making in a group of Italian Air Force fighter pilots and navigators analyzing morphologic and functional MRI data to identify brain areas involved in performing a series of cognitive tasks. The rationale for the study is to compare two groups of pilots and navigators differing in experience and number of flight hours to assess whether and how these elements influence cognitive performance. A control group will be also tested.
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STUDY’S OBJECT Most of real life interactions are repeated, rather than isolated, meetings. Such repeated strategic interactions are modeled in game theory (GT) as repeated (or stochastic) games, where the players play a sequence of the... more
STUDY’S OBJECT Most of real life interactions are repeated, rather than isolated, meetings. Such repeated strategic interactions are modeled in game theory (GT) as repeated (or stochastic) games, where the players play a sequence of the same (or different) single-shot game. The theory of repeated games assumes that players choose actions in a game according to strategies. Game theorists have formalized possible strategies for distinct economic games (Finkelstein & Whitley, 1981) and previous experimental studies have identified strategies that humans adopt in different repeated interactions (Fudenberg, Rand, & Dreber, 2012). The aim of this study is to characterize the neurobiological basis of the encoding and processing of critical game variables during strategic playing where either the game or the opponent player (i.e., strategy) may change during the interaction. METHODS Forty-two participants played a stochastic game while undergoing functional magnetic resonance imaging (fMRI). The game was defined by two parameters: the continuation probability (i.e., the probability of changing the current partner) and the probability of changing the stage game. Thus, during game playing subjects could stay with the same player and game as in the last round or they could change either the player or the game. Participants played with six virtual players (resembling the behavior of real people in analogous situations) two different stage games: the Prisoner’s Dilemma (PD) and the Battle of the Sexes (BoS). At the beginning of each trial, information about the opponent player (i.e., one of the six virtual players) and the game to be performed (either PD or BoS) was shown on the screen, followed by a delay in which the participant had to represent all pieces of information and make a choice. Finally, feedback about the choices made by both players was displayed on the screen. The fMRI data from the phase where the information about the player/game was displayed were analyzed. By contrasting trials in which the player (game) changed and trials in which the player (game) remained the same as in the previous round, we aimed to identify brain regions that implement the updating of player (game) information. RESULTS Preliminary results show that the same brain regions are involved in updating information either about the game or the player. This common network comprises the precuneus, the inferior frontal gyrus, the premotor cortex, and the anterior cingulate cortex. CONCLUSION These findings suggest that a single brain network implements the updating of both game and strategy information during strategic playing.
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We investigated neural representations of task information while playing a collaborative game. Results showed that the identity of a subtask assigned to either the subject or their partner and task ownership information are represented in... more
We investigated neural representations of task information while playing a collaborative game. Results showed that the identity of a subtask assigned to either the subject or their partner and task ownership information are represented in distinct frontal and parietal regions, suggesting that task ownership determines where task information is represented.
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Despite recent developments in integrating autonomous and human-like robots into many aspects of everyday life, social interactions with robots are still a challenge. Here, we focus on a central tool for social interaction: verbal... more
Despite recent developments in integrating autonomous and human-like robots into many aspects of everyday life, social interactions with robots are still a challenge. Here, we focus on a central tool for social interaction: verbal communication. We assess the extent to which humans co-represent (simulate and predict) a robot’s verbal actions. During a joint picture naming task, participants took turns in naming objects together with a social robot (Pepper, Softbank Robotics). Previous findings using this task with human partners revealed internal simulations on behalf of the partner down to the level of selecting words from the mental lexicon, reflected in partner-elicited inhibitory effects on subsequent naming. Here, with the robot, the partner-elicited inhibitory effects were not observed. Instead, naming was facilitated, as revealed by faster naming of word categories co-named with the robot. This facilitation suggests that robots, unlike humans, are not simulated down to the le...
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The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience,... more
The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience, and Psychology as the three fields have quite different perspectives and approaches to offer. Nonetheless, aligning backgrounds and interdisciplinary expectations can present challenges due to varied research cultures and practices. Overcoming these challenges stands at the beginning of each productive collaboration and thus is a mandatory step in cognitive neurorobotics. In this article, we share eight lessons that we learned from our ongoing interdisciplinary project on human-robot and robot-robot interaction in social settings. These lessons provide practical advice for scientists initiating interdisciplinary research endeavors. Our advice can help to avoid early problems and deal with differences between research fields, prepare for and anticipate...
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ABSTRACTAdaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based... more
ABSTRACTAdaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various PFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive.Twenty-eight h...
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SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently... more
SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with ...
Research Interests:
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those... more
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those processes. We ask whether the neural representations of intentions are context- and reason-invariant, or whether these processes depend on the context we are in, and the reasons we have for choosing an action. We use a combination of functional magnetic resonance imaging and multivariate decoding to directly assess the context- and reason-dependency of the processes underlying intentional action. We were able to decode action decisions in the same context and for the same reasons from the fMRI data, in line with previous decoding studies. Furthermore, we could decode action decisions across different reasons for choosing an action. Importantly, though, decoding decisions across different contexts was at chance level. These results suggest that for volu...
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A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a... more
A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be combined in alternative ways using logical connectives: e.g., 'There is a fork AND there is a knife', 'There is a fork OR there is a knife', 'IF there is a fork, there is a knife'. How does the brain represent compounds based on different logical connectives, and how are compounds evaluated in relation to new facts? In the present study, participants had to maintain and evaluate conjunctive (AND), disjunctive (OR) or conditional (IF) compounds while undergoing functional MRI. Our results suggest that, during maintenance, the left posterior inferior frontal gyrus (pIFG, BA44, or Broca's area) represents the surface form of compounds. During evaluation, the left pIFG switches to processing the full logical meanin...
Research Interests: Computer Science, Logic, Cognition, Deductive reasoning, Medicine, and 15 morePrefrontal Cortex, FMRI, Brain Mapping, Humans, Concept Formation, Female, Neuroimage, Male, Knowledge Representation and Reasoning, Adult, Parietal Lobe, Multivariate Pattern Analysis, Neural Code Neuroscience, Academic, and Medical and Health Sciences
Nella vita quotidiana è frequente l’utilizzo di regole per organizzare pensieri ed azioni al fine di raggiungere obiettivi prefissati. Per le situazioni più semplici, singole regole condizionali (“se… allora…”) sono sufficienti.... more
Nella vita quotidiana è frequente l’utilizzo di regole per organizzare pensieri ed azioni al fine di raggiungere obiettivi prefissati. Per le situazioni più semplici, singole regole condizionali (“se… allora…”) sono sufficienti. Situazioni più complesse, tuttavia, richiedono la considerazione contemporanea di molteplici regole, organizzate sia in termini temporali che gerarchici. Studi precedenti hanno dimostrato che la corteccia prefrontale (PFC) laterale è una delle aree critiche per la rappresentazione di regole semplici. Rimane da chiarire tuttavia dove e come il nostro cervello rappresenti insiemi di regole più complessi. Abbiamo condotto quattro esperimenti, manipolando lo stesso paradigma di base. I soggetti sono preliminarmente istruiti a rappresentare e applicare più insiemi di regole. Le regole utilizzate nei diversi esperimenti si collocano a diversi livelli di complessità. In ciascuna prova sperimentale i soggetti devono rievocare, rappresentare e quindi applicare uno de...
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In everyday life, humans use rules to organize their thoughts and actions in order to achieve specific goals (Bunge & Wallis, 2007). For simple situations, single rules can be used to link a sensory stimulus (the traffic light is green)... more
In everyday life, humans use rules to organize their thoughts and actions in order to achieve specific goals (Bunge & Wallis, 2007). For simple situations, single rules can be used to link a sensory stimulus (the traffic light is green) to its appropriate response (cross the road). More complex situations, however, require the application of multiple rules organized in hierarchies, where high level rules influence the selection or application of lower level rules. Previous studies have demonstrated that Prefrontal Cortex (PFC) is one of the key areas underlying rule processing and control of action. However, it is still unclear whether distinct brain regions within PFC systematically encode qualitatively different task features. In the present study we investigated whether different features defining a complex rule set are represented in different brain areas depending on the level of control they enforce. To this purpose, we devised an experiment in which participants (N = 20) lear...
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Women neuroscientists (please note that we refer to all who identify as such) are still underrepresented in various aspects of academic life. The efforts of the community to mitigate this issue are growing but can elicit adverse reactions... more
Women neuroscientists (please note that we refer to all who identify as such) are still underrepresented in various aspects of academic life. The efforts of the community to mitigate this issue are growing but can elicit adverse reactions (Moghaddam & Gur, 2016). In this opinion paper, we discuss the different approaches that have been taken at institutional, organizational and individual levels to counter gender bias and aim at addressing unfavorable comments. We base our reasoning on empirical data and on the feedback received after the release of the Women in Neuroscience Repository (WiNRepo, see Supplementary Table S1.a), an initiative we created to increase the visibility of women in neuroscience. While this feedback originated mainly from oral conversations and was not rigorously quantified, we believe the frequency of the comments justify their discussion, as performed in (Moghaddam & Gur, 2016). The aim of this piece (supported by a list of signatories, see Supplementary Tab...
Robots are getting increasingly more present in many spheres of human life, making the need for robots that can successfully engage in natural social interactions with humans paramount. Successful human-robot interaction could be achieved... more
Robots are getting increasingly more present in many spheres of human life, making the need for robots that can successfully engage in natural social interactions with humans paramount. Successful human-robot interaction could be achieved more effectively if robots could act predictably and could predict the humans' actions. If robots could represent human partners and generate behaviors that are in line with the partners' expectations based on human's mental models of interdependent action, human agents would be able to apply predictive and adaptive mechanisms acquired in human interactions to interact with robots effectively. How could robots be predictable and be capable of predicting human behavior? We propose that this could be achieved by having an internal representation of both oneself and the other agent, that is by equipping the robot with the ability to co-represent. Here, co-representation refers to the representation of the partner's actions alongside one's own actions. Although co-representation constitutes an essential process for successful human social interaction, as it supports understanding of others' actions, to date co-representation processes have only scarcely been integrated into robotic platforms. We highlight the state-of-the-art findings on co-representation in social robotics, discuss current research limitations and open issues for creating computational models of co-representation in robots, and put forward the idea that predictive learning might constitute a particularly promising framework to build models of co-representing robots. Overall, in this article, we offer an integrated view of the state-of-the-art findings in robotics literature on co-representation and outline directions for future research, with the aim to boost success in building robots equipped with co-representation models fit for smooth social interactions.
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Despite recent developments in integrating autonomous and human-like robots into many aspects of everyday life, social interactions with robots are still a challenge. Here, we focus on a central tool for social interaction: verbal... more
Despite recent developments in integrating autonomous and human-like robots into many aspects of everyday life, social interactions with robots are still a challenge. Here, we focus on a central tool for social interaction: verbal communication. We assess the extent to which humans co-represent (simulate and predict) a robot's verbal actions. During a joint picture naming task, participants took turns in naming objects together with a social robot (Pepper, Softbank Robotics). Previous findings using this task with human partners revealed internal simulations on behalf of the partner down to the level of selecting words from the mental lexicon, reflected in partner-elicited inhibitory effects on subsequent naming. Here, with the robot, the partner-elicited inhibitory effects were not observed. Instead, naming was facilitated, as revealed by faster naming of word categories co-named with the robot. This facilitation suggests that robots, unlike humans, are not simulated down to th...
Research Interests:
Adaptive coding of stimuli is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it... more
Adaptive coding of stimuli is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various mPFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive. Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in one-half of the trials participants received partial feedback, whereas in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions. We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in its ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information enhances context-dependent outcome encoding. This study offers a systematic investigation of the effect of the amount of feedback information (partial vs complete) on uni-variate and multivariate outcome value encoding, within multiple regions in mPFC and cingulate cortex that are critical for value-based decisions and behavioral adaptation. Moreover, we provide the first comparison of three possible models of neu-ral coding (i.e., absolute, partially-adaptive, and fully-adaptive coding) of value signal in these regions, by using commensura-ble measures of prediction accuracy. Taken together, our results help build a more comprehensive picture of how the human brain encodes and processes outcome value. In particular, our results suggest that simultaneous presentation of obtained and foregone outcomes promotes relative value representation.
Robots are getting increasingly more present in many spheres of human life, making the need for robots that can successfully engage in natural social interactions with humans paramount. Successful human-robot interaction could be achieved... more
Robots are getting increasingly more present in many spheres of human life, making the need for robots that can successfully engage in natural social interactions with humans paramount. Successful human-robot interaction could be achieved more effectively if robots could act predictably and could predict the humans' actions. If robots could represent human partners and generate behaviors that are in line with the partners' expectations based on human's mental models of interdependent action, human agents would be able to apply predictive and adaptive mechanisms acquired in human interactions to interact with robots effectively. How could robots be predictable and be capable of predicting human behavior? We propose that this could be achieved by having an internal representation of both oneself and the other agent, that is by equipping the robot with the ability to co-represent. Here, co-representation refers to the representation of the partner's actions alongside one's own actions. Although co-representation constitutes an essential process for successful human social interaction , as it supports understanding of others' actions, to date co-representation processes have only scarcely been integrated into robotic platforms. We highlight the state-of-the-art findings on co-representation in social robotics, discuss current research limitations and open issues for creating computational models of co-representation in robots, and put forward the idea that predictive learning might constitute a particularly promising framework to build models of co-representing robots. Overall, in this article, we offer an integrated view of the state-of-the-art findings in robotics literature on co-representation and outline directions for future research, with the aim to boost success in building robots equipped with co-representation models fit for smooth social interactions.
Research Interests:
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to... more
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2,3,4,5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
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Adaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based... more
Adaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various PFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive.
Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in half of the trials participants received partial feedback, while in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.
We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information promotes context-dependent outcome encoding.
Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in half of the trials participants received partial feedback, while in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.
We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information promotes context-dependent outcome encoding.
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A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be... more
A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be combined in alternative ways using logical connectives: e.g., 'There is a fork AND there is a knife', 'There is a fork OR there is a knife', 'IF there is a fork, there is a knife'. How does the brain represent compounds based on different logical connectives, and how are compounds evaluated in relation to new facts? In the present study, participants had to maintain and evaluate conjunctive (AND), disjunctive (OR) or conditional (IF) compounds while undergoing functional MRI. Our results suggest that, during maintenance, the left posterior inferior frontal gyrus (pIFG, BA44, or Broca's area) represents the surface form of compounds. During evaluation, the left pIFG switches to processing the full logical meaning of compounds, and two additional areas are recruited: the left anterior inferior frontal gyrus (aIFG, BA47) and the left intraparietal sulcus (IPS, BA40). The aIFG shows a pattern of activation similar to pIFG, and compatible with processing the full logical meaning of compounds, whereas activations in IPS differ with alternative interpretations of conditionals: logical vs conjunctive. These results uncover the functions of a basic cortical network underlying human compositional thought, and provide a shared neural foundation for the cognitive science of language and reasoning.
Humans use rules to organize their actions to achieve specific goals. While simple rules that link a sensory stimulus to one response may suffice in some situations, often the application of multiple, hierarchically-organized rules is... more
Humans use rules to organize their actions to achieve specific goals. While simple rules that link a sensory stimulus to one response may suffice in some situations, often the application of multiple, hierarchically-organized rules is required. Recent theories suggest that progressively higher level rules are encoded along an anterior-to-posterior gradient within PFC. While some work supports the existence of such a functional gradient, other studies argue for a lesser degree of specialization within PFC. We used fMRI to investigate whether rules at different hierarchical levels are represented at distinct locations in the brain or encoded by a single system. Thirty-seven male and female participants represented and applied hierarchical rule sets containing one lower-level stimulus-response rule and one higher-level selection rule. We used multivariate pattern analysis to directly investigate the representation of rules at each hierarchical level in absence of information about rules from other levels or other task-related information, thus providing a clear identification of low- and high-level rule representations. We could decode low- and high-level rules from local patterns of brain activity within a wide frontoparietal network. However, no significant difference existed between regions encoding representations of rules from both levels, except for precentral gyrus that represented only low-level rule information. Our findings show that the brain represents conditional rules irrespective of their level in the explored hierarchy, and thus that the human control system did not organize task representation according to this dimension. Our paradigm represents a promising approach to identify critical principles that shape this control system.
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A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be... more
A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be combined in alternative ways using logical connectives: e.g., 'There is a fork AND there is a knife', 'There is a fork OR there is a knife', 'IF there is a fork, there is a knife'. How does the brain represent compounds based on different logical connectives, and how are compounds evaluated in relation to new facts? In the present study, participants had to maintain and evaluate conjunctive (AND), disjunctive (OR) or conditional (IF) compounds while undergoing functional MRI. Our results suggest that, during maintenance, the left posterior inferior frontal gyrus (pIFG, BA44, or Broca's area) represents the surface form of compounds. During evaluation, the left pIFG switches to processing the full logical meaning of compounds, and two additional areas are recruited: the left anterior inferior frontal gyrus (aIFG, BA47) and the left intraparietal sulcus (IPS, BA40). The aIFG shows a pattern of activation similar to pIFG, and compatible with processing the full logical meaning of compounds, whereas activations in IPS differ with alternative interpretations of conditionals: logical vs conjunctive. These results uncover the functions of a basic cortical network underlying human compositional thought, and provide a shared neural foundation for the cognitive science of language and reasoning.
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Focusing on relevant information while suppressing the irrelevant one are critical abilities for different cognitive processes. However, their functioning has been scarcely investigated in the working memory (WM) domain, in both healthy... more
Focusing on relevant information while suppressing the irrelevant one are critical abilities for different cognitive processes. However, their functioning has been scarcely investigated in the working memory (WM) domain, in both healthy and pathological conditions. The present research aimed to study these abilities in aging and Parkinson’s disease (PD), testing three groups of healthy participants (young, older and elderly) and one of PD patients, employing a new experimental paradigm. Results showed that the transient storing of irrelevant information in WM causes substantial interference effects, which were remarkable in elderly individuals on both response latency and accuracy. Interestingly, PD patients responded faster and were equally accurate compared to a matched control group. Taken together, findings confirm the existence of similar mechanisms for orienting attention inwards to WM contents or outwards to perceptual stimuli, and suggest the suitability of our task to assess WM functioning in both healthy aging and PD.
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We investigated whether two basic forms of deductive inference, Modus Ponens and Disjunctive Syllogism, occur automatically and without awareness. In Experiment 1, we used a priming paradigm with a set of conditional and disjunctive... more
We investigated whether two basic forms of deductive inference, Modus Ponens and Disjunctive Syllogism, occur automatically and without awareness. In Experiment 1, we used a priming paradigm with a set of conditional and disjunctive problems. For each trial, two premises were shown. The second premise was presented at a rate designed to be undetectable. After each problem, participants had to evaluate whether a newly-presented target number was odd or even. The target number matched or did not match a conclusion endorsed by the two previous premises. We found that when the target matched the conclusion of a Modus Ponens inference, the evaluation of the target number was reliably faster than baseline even when participants reported that they were not aware of the second premise. This priming effect did not occur for any other valid or invalid inference that we tested, including the Disjunctive Syllogism. In Experiment 2, we used a forced-choice paradigm in which we found that some participants were able to access some information on the second premise when their attention was explicitly directed to it. In Experiment 3, we showed that the priming effect for Modus Ponens was present also in subjects who could not access any information about P2. In Experiment 4 we explored whether spatial relations (e.g., “a before b”) or sentences with quantifiers (e.g., “all a with b”) could generate a priming effect similar to the one observed for Modus Ponens. A priming effect could be found for Modus Ponens only, but not for the other relations tested. These findings show that the Modus Ponens inference, in contrast to other deductive inferences, can be carried out automatically and unconsciously. Furthermore, our findings suggest that critical deductive inference schemata can be included in the range of high-level cognitive activities that are carried out unconsciously.
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STUDY’S OBJECT Most of real life interactions are repeated, rather than isolated, meetings. Such repeated strategic interactions are modeled in game theory (GT) as repeated (or stochastic) games, where the players play a sequence of the... more
STUDY’S OBJECT
Most of real life interactions are repeated, rather than isolated, meetings. Such repeated strategic interactions are modeled in game theory (GT) as repeated (or stochastic) games, where the players play a sequence of the same (or different) single-shot game. The theory of repeated games assumes that players choose actions in a game according to strategies. Game theorists have formalized possible strategies for distinct economic games (Finkelstein & Whitley, 1981) and previous experimental studies have identified strategies that humans adopt in different repeated interactions (Fudenberg, Rand, & Dreber, 2012). The aim of this study is to characterize the neurobiological basis of the encoding and processing of critical game variables during strategic playing where either the game or the opponent player (i.e., strategy) may change during the interaction.
METHODS
Forty-two participants played a stochastic game while undergoing functional magnetic resonance imaging (fMRI). The game was defined by two parameters: the continuation probability (i.e., the probability of changing the current partner) and the probability of changing the stage game. Thus, during game playing subjects could stay with the same player and game as in the last round or they could change either the player or the game. Participants played with six virtual players (resembling the behavior of real people in analogous situations) two different stage games: the Prisoner’s Dilemma (PD) and the Battle of the Sexes (BoS). At the beginning of each trial, information about the opponent player (i.e., one of the six virtual players) and the game to be performed (either PD or BoS) was shown on the screen, followed by a delay in which the participant had to represent all pieces of information and make a choice. Finally, feedback about the choices made by both players was displayed on the screen.
The fMRI data from the phase where the information about the player/game was displayed were analyzed. By contrasting trials in which the player (game) changed and trials in which the player (game) remained the same as in the previous round, we aimed to identify brain regions that implement the updating of player (game) information.
RESULTS
Preliminary results show that the same brain regions are involved in updating information either about the game or the player. This common network comprises the precuneus, the inferior frontal gyrus, the premotor cortex, and the anterior cingulate cortex.
CONCLUSION
These findings suggest that a single brain network implements the updating of both game and strategy information during strategic playing.
Most of real life interactions are repeated, rather than isolated, meetings. Such repeated strategic interactions are modeled in game theory (GT) as repeated (or stochastic) games, where the players play a sequence of the same (or different) single-shot game. The theory of repeated games assumes that players choose actions in a game according to strategies. Game theorists have formalized possible strategies for distinct economic games (Finkelstein & Whitley, 1981) and previous experimental studies have identified strategies that humans adopt in different repeated interactions (Fudenberg, Rand, & Dreber, 2012). The aim of this study is to characterize the neurobiological basis of the encoding and processing of critical game variables during strategic playing where either the game or the opponent player (i.e., strategy) may change during the interaction.
METHODS
Forty-two participants played a stochastic game while undergoing functional magnetic resonance imaging (fMRI). The game was defined by two parameters: the continuation probability (i.e., the probability of changing the current partner) and the probability of changing the stage game. Thus, during game playing subjects could stay with the same player and game as in the last round or they could change either the player or the game. Participants played with six virtual players (resembling the behavior of real people in analogous situations) two different stage games: the Prisoner’s Dilemma (PD) and the Battle of the Sexes (BoS). At the beginning of each trial, information about the opponent player (i.e., one of the six virtual players) and the game to be performed (either PD or BoS) was shown on the screen, followed by a delay in which the participant had to represent all pieces of information and make a choice. Finally, feedback about the choices made by both players was displayed on the screen.
The fMRI data from the phase where the information about the player/game was displayed were analyzed. By contrasting trials in which the player (game) changed and trials in which the player (game) remained the same as in the previous round, we aimed to identify brain regions that implement the updating of player (game) information.
RESULTS
Preliminary results show that the same brain regions are involved in updating information either about the game or the player. This common network comprises the precuneus, the inferior frontal gyrus, the premotor cortex, and the anterior cingulate cortex.
CONCLUSION
These findings suggest that a single brain network implements the updating of both game and strategy information during strategic playing.
Research Interests:
Humans use rules to organize their actions to achieve specific goals. While simple rules that link a sensory stimulus to one response may suffice in some situations, often the application of multiple, hierarchically organized rules is... more
Humans use rules to organize their actions to achieve specific goals. While simple rules that link a sensory stimulus to one response may suffice in some situations, often the application of multiple, hierarchically organized rules is required. Recent theories suggest that progressively higher level rules are encoded along an anterior-to-posterior gradient within PFC. While some work supports the existence of such a functional gradient, other studies argue for a lesser degree of specialization within PFC. We used fMRI to investigate whether rules at different hierarchical levels are represented at distinct locations in the brain or encoded by a single system. Participants (N = 37) had to represent and apply hierarchical rule sets containing one lower-level stimulus-response rule and one higher-level selection rule. We used multivariate pattern analysis to directly investigate the representation of rules at each hierarchical level in absence of information about rules from other levels or other task-related information, thus providing for the first time a clear identification of low- and high-level rule representations. We could decode low- and high-level rules from local patterns of brain activity within a wide frontoparietal network. However, no significant difference existed between regions encoding representations of rules from both levels, except for precentral gyrus that represented only low-level rule information. Our findings suggest that the brain represents conditional rules irrespective of their hierarchical level and thus that the human control system is not organized according to this dimension.
Research Interests:
Introduction: To investigate the processes and mechanism(s) underlying decision making in a group of Italian Air Force fighter pilots and navigators analyzing morphologic and functional MRI data to identify brain areas involved in... more
Introduction: To investigate the processes and mechanism(s) underlying decision making in a group of Italian Air Force fighter pilots and navigators analyzing morphologic and functional MRI data to identify brain areas involved in performing a series of cognitive tasks. The rationale for the study is to compare two groups of pilots and navigators differing in experience and number of flight hours to assess whether and how these elements influence cognitive performance. A control group will be also tested.
Research Interests:
We investigated neural representations of task information while playing a collaborative game. Results showed that the identity of a subtask assigned to either the subject or their partner and task ownership information are represented in... more
We investigated neural representations of task information while playing a collaborative game. Results showed that the identity of a subtask assigned to either the subject or their partner and task ownership information are represented in distinct frontal and parietal regions, suggesting that task ownership determines where task information is represented.
Research Interests:
A defining trait of cognition is the capacity to combine information into compound concepts. This ability relies, among others, on the logical connectives 'and', 'or' and 'if-then'. Simple sentences, such as 'there is a fork on the table'... more
A defining trait of cognition is the capacity to combine information into compound concepts. This ability relies, among others, on the logical connectives 'and', 'or' and 'if-then'. Simple sentences, such as 'there is a fork on the table' (A) or 'there is a knife' (B), can be combined in different ways using different connectives. No evidence is available to date on how and where the brain represents different concept combinations produced by different connectives, and how these are evaluated against new facts. Here, participants learned associations between graphic cues and conjunctive (A and B), disjunctive (A or B) or conditional (If A then B) sentences. During fMRI scanning, a cue was presented, followed by a delay, during which participants had to represent the sentence associated to the cue; finally, a visual scene had to be evaluated for compatibility with the sentence. Two participant groups were recruited so that conditionals (If A then B) were interpreted in either of two alternative ways (thus, same form, different semantics). Multivariate decoding applied to the delay period revealed that the active sentence was encoded in left inferior frontal gyrus (BA44). During the delay, no difference was found between participant groups. During the target phase, we found higher activations in rostral regions of left inferior frontal cortex (BA47), for disjunctions and conditionals relative to conjunctions. Activation of BA47 was modulated by the interpretation of conditionals. We suggest BA44 represents the surface form of a compound sentence, while BA47 is involved in deriving its logical consequences.
Research Interests:
Nella vita quotidiana è frequente l’utilizzo di regole per organizzare pensieri ed azioni al fine di raggiungere obiettivi prefissati. Per le situazioni più semplici, singole regole condizionali (“se… allora…”) sono sufficienti.... more
Nella vita quotidiana è frequente l’utilizzo di regole per organizzare pensieri ed azioni al fine di raggiungere obiettivi prefissati. Per le situazioni più semplici, singole regole condizionali (“se… allora…”) sono sufficienti. Situazioni più complesse, tuttavia, richiedono la considerazione contemporanea di molteplici regole, organizzate sia in termini temporali che gerarchici. Studi precedenti hanno dimostrato che la corteccia prefrontale (PFC) laterale è una delle aree critiche per la rappresentazione di regole semplici. Rimane da chiarire tuttavia dove e come il nostro cervello rappresenti insiemi di regole più complessi.
Abbiamo condotto quattro esperimenti, manipolando lo stesso paradigma di base. I soggetti sono preliminarmente istruiti a rappresentare e applicare più insiemi di regole. Le regole utilizzate nei diversi esperimenti si collocano a diversi livelli di complessità. In ciascuna prova sperimentale i soggetti devono rievocare, rappresentare e quindi applicare uno degli insiemi di regole appresi. I soggetti sono sottoposti a scansione fMRI. I dati sono analizzati con tecniche multivariate per identificare quali aree cerebrali siano coinvolte nella rappresentazione di specifiche regole.
Dalle analisi è emerso, come atteso, che la PFC laterale è coinvolta nella rappresentazione di regole. E’ inoltre emerso come informazioni relative a un'unica regola complessa non siano rappresentate tutte nella stessa regione cerebrale. Al contrario, le diverse caratteristiche che concorrono a costruire una regola complessa sono ripartite in aree cerebrali diverse, in funzione del tipo di informazione da rappresentare.
I risultati della nostra serie sperimentale suggeriscono che la rappresentazione di regole complesse è “composizionale”. Gli elementi base delle regole complesse sono identificati e rappresentati separatamente dal nostro cervello. La segregazione dell’informazione avviene in aree cerebrali appropriate alla tipologia di contenuto da rappresentare.
Abbiamo condotto quattro esperimenti, manipolando lo stesso paradigma di base. I soggetti sono preliminarmente istruiti a rappresentare e applicare più insiemi di regole. Le regole utilizzate nei diversi esperimenti si collocano a diversi livelli di complessità. In ciascuna prova sperimentale i soggetti devono rievocare, rappresentare e quindi applicare uno degli insiemi di regole appresi. I soggetti sono sottoposti a scansione fMRI. I dati sono analizzati con tecniche multivariate per identificare quali aree cerebrali siano coinvolte nella rappresentazione di specifiche regole.
Dalle analisi è emerso, come atteso, che la PFC laterale è coinvolta nella rappresentazione di regole. E’ inoltre emerso come informazioni relative a un'unica regola complessa non siano rappresentate tutte nella stessa regione cerebrale. Al contrario, le diverse caratteristiche che concorrono a costruire una regola complessa sono ripartite in aree cerebrali diverse, in funzione del tipo di informazione da rappresentare.
I risultati della nostra serie sperimentale suggeriscono che la rappresentazione di regole complesse è “composizionale”. Gli elementi base delle regole complesse sono identificati e rappresentati separatamente dal nostro cervello. La segregazione dell’informazione avviene in aree cerebrali appropriate alla tipologia di contenuto da rappresentare.
Research Interests:
In everyday life, humans use rules to organize their thoughts and actions in order to achieve specific goals (Bunge & Wallis, 2007). For simple situations, single rules can be used to link a sensory stimulus (the traffic light is green)... more
In everyday life, humans use rules to organize their thoughts and actions in order to achieve specific goals (Bunge & Wallis, 2007). For simple situations, single rules can be used to link a sensory stimulus (the traffic light is green) to its appropriate response (cross the road). More complex situations, however, require the application of multiple rules organized in hierarchies, where high level rules influence the selection or application of lower level rules.
Previous studies have demonstrated that Prefrontal Cortex (PFC) is one of the key areas underlying rule processing and control of action. However, it is still unclear whether distinct brain regions within PFC systematically encode qualitatively different task features.
In the present study we investigated whether different features defining a complex rule set are represented in different brain areas depending on the level of control they enforce. To this purpose, we devised an experiment in which participants (N = 20) learnt complex rule sets composed by rules at two different levels of control: low (e.g., “if you see a banana, then press left”) and high (e.g., “If you see a star, then only consider red targets”). The task required participants to retrieve, maintain, and apply two rule sets (one low and one high level) to target stimuli. At the beginning of each trial two cues associated with low (or high) level rules were displayed, followed by a delay (delay 1). Then a second pair of cues standing for high (or low) level rules were presented followed by a second delay (delay 2), after which the target was shown. Participants had to apply all the rules to the target stimuli and respond accordingly. The paradigm allowed us to: (i) independently assess the encoding of high and low level rules, (ii) evaluate the difference between the encoding of the two types of rules (comparing high vs. low level rule representations during delay 1, when only one type of rule was maintained), and (iii) decode rule integration (by comparing rule representations during delay 1 vs. delay 2, in which the two levels of rules had to be integrated in order to respond).
We applied multivariate decoding analysis (e.g., Haynes et al., 2007) to functional magnetic resonance imaging data to perform the above-described comparisons. Behavioral as well as preliminary decoding results suggest that rules at different levels of abstraction are indeed processed differently in distinct brain regions within a large-scale brain network comprising parietal and prefrontal areas.
Previous studies have demonstrated that Prefrontal Cortex (PFC) is one of the key areas underlying rule processing and control of action. However, it is still unclear whether distinct brain regions within PFC systematically encode qualitatively different task features.
In the present study we investigated whether different features defining a complex rule set are represented in different brain areas depending on the level of control they enforce. To this purpose, we devised an experiment in which participants (N = 20) learnt complex rule sets composed by rules at two different levels of control: low (e.g., “if you see a banana, then press left”) and high (e.g., “If you see a star, then only consider red targets”). The task required participants to retrieve, maintain, and apply two rule sets (one low and one high level) to target stimuli. At the beginning of each trial two cues associated with low (or high) level rules were displayed, followed by a delay (delay 1). Then a second pair of cues standing for high (or low) level rules were presented followed by a second delay (delay 2), after which the target was shown. Participants had to apply all the rules to the target stimuli and respond accordingly. The paradigm allowed us to: (i) independently assess the encoding of high and low level rules, (ii) evaluate the difference between the encoding of the two types of rules (comparing high vs. low level rule representations during delay 1, when only one type of rule was maintained), and (iii) decode rule integration (by comparing rule representations during delay 1 vs. delay 2, in which the two levels of rules had to be integrated in order to respond).
We applied multivariate decoding analysis (e.g., Haynes et al., 2007) to functional magnetic resonance imaging data to perform the above-described comparisons. Behavioral as well as preliminary decoding results suggest that rules at different levels of abstraction are indeed processed differently in distinct brain regions within a large-scale brain network comprising parietal and prefrontal areas.
Research Interests:
Adaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based... more
Adaptive coding of stimuli in visual cortex is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various PFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive.
Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in half of the trials participants received partial feedback, while in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.
We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information promotes context-dependent outcome encoding.
Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in half of the trials participants received partial feedback, while in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.
We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information promotes context-dependent outcome encoding.
Research Interests:
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently... more
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.
Research Interests:
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those... more
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those processes. We ask whether the neural representations of intentions are context- and reason-invariant, or whether these processes depend on the context we are in, and the reasons we have for choosing an action. We use a combination of functional magnetic resonance imaging and multivariate decoding to directly assess the context- and reason dependency of the processes underlying intentional action. We were able to decode action decisions in the same context and for the same reasons from the fMRI data, in line with previous decoding studies. Furthermore, we could decode action decisions across different reasons for choosing an action. Importantly, though, decoding decisions across different contexts was at chance level. These results suggest that for voluntary action,
there is considerable context-dependency in intention representations. This suggests that established invariance in neural processes may not reflect an essential feature of a certain process, but that this stable character could be dependent on invariance in the experimental setup, in line with predictions from situated cognition theory.
there is considerable context-dependency in intention representations. This suggests that established invariance in neural processes may not reflect an essential feature of a certain process, but that this stable character could be dependent on invariance in the experimental setup, in line with predictions from situated cognition theory.