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Artificial Intelligence (AI) systems are precious support for decision-making, with many applications in the medical domain. However, there is little understanding of how human experts interact with AI. Health policy-makers fear flat reliance on AI advice. In this multicentric study, twenty-one endoscopists reviewed 504 videos of lesions from real colonoscopies, with and without the assistance of an AI support system. Endoscopists were influenced by AI (OR = 3.05), but not erratically: they followed the AI advice more when it was correct (OR = 3.48) than incorrect (OR = 1.85). Endoscopists achieved this outcome through a weighted integration of their and the AI opinions, considering the case-by-case estimations of the two reliabilities. This Bayesian-like rational behavior allowed the human-AI hybrid team to outperform both agents taken alone. We discuss the features of the interaction that determined this favorable outcome.

Body integrity dysphoria (BID), a long-lasting desire for the amputation of physically healthy limbs, is associated with reduced fMRI resting-state functional connectivity of somatosensory cortices. Here, we used fMRI to evaluate whether these findings could be replicated and expanded using a task-based paradigm. We measured brain activations during somatosensory stimulation and motor tasks for each of the four limbs in ten individuals with a life-long desire for the amputation of the left leg and fourteen controls. For the left leg, BID individuals had reduced brain activation in the right superior parietal lobule for somatosensory stimulation and in the right paracentral lobule for the motor task, areas where we previously found reduced resting-state functional connectivity. In addition, for somatosensory stimulation only, we found a robust reduction in activation of somatosensory areas SII bilaterally, mostly regardless of the stimulated body part. Areas SII were regions of convergent activations for signals from all four limbs in controls to a significantly greater extent than in subjects with BID. We conclude that BID is associated with altered integration of somatosensory and, to a lesser extent, motor signals, involving limb-specific cortical maps and brain regions where the first integration of body-related signals is achieved through convergence.

With practice, humans may improve their performance in a task by either optimizing a known strategy or discovering a novel, potentially more fruitful strategy. How does the brain support these two fundamental abilities? In the present experiment, subjects performed a simple perceptual decision-making task. They could either use and progressively optimize an instructed strategy based on stimulus position, or spontaneously devise and then use a new strategy based on stimulus color. We investigated how local and long-range BOLD coherence behave during these two types of strategy learning by applying a recently developed unsupervised fMRI analysis technique that was specifically designed to probe the presence of transient correlations. Converging evidence showed that the posterior portion of the default network, i.e. the precuneus and the angular gyrus bilaterally, has a central role in the optimization of the current strategy: these regions encoded the relevant spatial information, increased the level of local coherence and the strength of connectivity with other relevant regions in the brain (e.g. visual cortex, dorsal attention network). This increase was proportional to the task optimization achieved by subjects, as measured by the reduction of reaction times, and was transiently disrupted when subjects were forced to change strategy. By contrast, the anterior portion of the default network (i.e. medial prefrontal cortex) together with rostral portion of the fronto-parietal network showed an increase in local coherence and connectivity only in subjects that would at some point spontaneously choose the new strategy. Overall, our findings shed light on the dynamic interactions between regions related with attention and with cognitive control, underlying the balance between strategy exploration and exploitation. Results suggest that the default network, far from being “shut-down” during task performance, has a pivotal role in the background exploration and monitoring of potential alternative courses of action.

Background Famous face and voice recognition is reported to be impaired both in semantic dementia (SD) and in Alzheimer's Disease (AD), although more severely in the former. In AD a coexistence of perceptual impairment in face and voice processing has also been reported and this could contribute to the altered performance in complex semantic tasks. On the other hand, in SD both face and voice recognition disorders could be related to the prevalence of atrophy in the right temporal lobe (RTL). Objective The aim of the present study was twofold: (1) to investigate famous faces and voices recognition in SD and AD to verify if the two diseases show a differential pattern of impairment, resulting from disruption of different cognitive mechanisms; (2) to check if face and voice recognition disorders prevail in patients with atrophy mainly affecting the RTL. Materials To avoid the potential influence of primary perceptual problems in face and voice recognition, a pool of patients suffering from early SD and AD were administered a detailed set of tests exploring face and voice perception. Thirteen SD (8 with prevalence of right and 5 with prevalence of left temporal atrophy) and 25 CE patients, who did not show visual and auditory perceptual impairment, were finally selected and were administered an experimental battery exploring famous face and voice recognition and naming. Twelve SD patients underwent cerebral PET imaging and were classified in right and left SD according to the onset modality and to the prevalent decrease in FDG uptake in right or left temporal lobe respectively. Correlation of PET imaging and famous face and voice recognition was performed. Results Results showed a differential performance profile in the two diseases, because AD patients were significantly impaired in the naming tests, but showed preserved recognition, whereas SD patients were profoundly impaired both in naming and in recognition of famous faces and voices. Furthermore, face and voice recognition disorders prevailed in SD patients with RTL atrophy, who also showed a conceptual impairment on the Pyramids and Palm Trees test more important in the pictorial than in the verbal modality. Finally, in 12SD patients in whom PET was available, a strong correlation between FDG uptake and face-to-name and voice-to-name matching data was found in the right but not in the left temporal lobe. Discussion The data support the hypothesis of a different cognitive basis for impairment of face and voice recognition in the two dementias and suggest that the pattern of impairment in SD may be due to a loss of semantic representations, while a defect of semantic control, with impaired naming and preserved recognition might be hypothesized in AD. Furthermore, the correlation between face and voice recognition disorders and RTL damage are consistent with the hypothesis assuming that in the RTL person-specific knowledge may be mainly based upon non-verbal representations.

There is growing interest in the description of short-lived patterns in the spatiotemporal cortical activity monitored via neuroimaging. Most traditional analysis methods, designed to estimate relatively long-term brain dynamics, are not always appropriate to capture these patterns. Here we introduce a novel data-driven approach for detecting short-lived fMRI brain activity patterns. Exploiting Density Peak Clustering (Rodriguez and Laio [2014]), our approach reveals well localized clusters by identifying and grouping together voxels whose time-series are similar, irrespective of their brain location, even when very short time windows (∼10 volumes) are used. The method, which we call Coherence Density Peak Clustering (CDPC), is first tested on simulated data and compared with a standard unsupervised approach for fMRI analysis, independent component analysis (ICA). CDPC identifies activated voxels with essentially no false-positives and proves more reliable than ICA, which is troubled by a number of false positives comparable to that of true positives. The reliability of the method is demonstrated on real fMRI data from a simple motor task, containing brief iterations of the same movement. The clusters identified are found in regions expected to be involved in the task, and repeat synchronously with the paradigm. The methodology proposed is especially suitable for the study of short-time brain dynamics and single trial experiments, where the event or task of interest cannot be repeated for the same subject, as happens, for instance, in problem-solving, learning and decision-making. A GUI implementation of our method is available for download at https://github.com/micheleallegra/CDPC. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

As they approach a traffic light, drivers and pedestrians monitor the color (instructed stimulus feature) and/or the position of the signal (covarying stimulus feature) for response selection. Many studies have pointed out that instructions can effectively determine the stimulus features used for response selection in a task. This leaves open whether and how practice with a correlating alternative stimulus feature can lead to a strategy change from an instructed to a learned variant of performing the task. To address this question, we instructed participants to respond to the position of a stimulus within a reference frame, at the same time, during task performance, an unmentioned second stimulus feature, the color, covaried with stimulus position and allowed the use of an alternative response strategy. To assess the impact of the non-instructed stimulus feature of color on response selection throughout practice, the spatial position of the stimulus was ambiguous on some trials. Group average increases in color usage were based on a mixture of (1) participants who, despite extended practice on the covariation, exclusively relied on the instructed stimulus feature and (2) those who abruptly started to rely heavily on stimulus color to select responses in ambiguous trials. When the instructed and uninstructed feature predicted different actions, choices were still biased by the uninstructed color feature, albeit more weakly. A second experiment showed that the influence of color generalized across frequently and infrequently presented combinations of position and color. Strategy changes were accompanied by awareness in both experiments. The results suggest that incidental covariation learning can trigger spontaneous voluntary strategy change involving a re-configuration of the instructed task set.

Luzzi, Simona Fabi, Katia Cafazzo, Viviana Fringuelli, Fabio M Reverberi, Carlo Baldinelli, Sara Silvestrini, Mauro Provinciali, Leandro Ascoli, Giorgio Pickering-Brown, Stuart Mann, David Neary, David Snowden, Julie S 089701/Wellcome Trust/United Kingdom G0701441/Medical Research Council/United Kingdom Alzheimer Dis Assoc Disord. 2015 Oct-Dec;29(4):360-3. doi: 10.1097/WAD.0000000000000064.

We report the case of a 48 year old men who developed a selective impairment in famous voice recognition after ischemic stroke in right subcortical structures (lenticular nucleus and head of the caudate) and right anterior temporal lobe. He underwent fibrinolytic treatment. During the following days he progressively recovered and was discharged without neurological focal sign. Patent foramen ovale was found. When he got back to his house he noticed that he was unable to recognize the voice of his favoured singers and needed to ask who was the singer to his relatives. Neuropsychological examination revealed a selective impairment in famous voice recognition in the absence of alteration of voice perception, face perception and famous face recognition. All other neuropsychological domains were spared. In particular language, memory and executive functions were intact. Neuroimaging carried out by means of PET and MRI revealed two small ischemic lesions in the right subcortical region, involving lenticular and caudate nuclei and in the right temporal pole. To our knowledge, this is the first case described in literature of a patient showing a selective associative phonagnosia after right anterior temporal stroke. The present case helps to clarify the brain circuits underlying famous voice recognition and adds evidence in favour of a right hemisphere involvement in processing knowledge of familiar voices. These findings are discussed in relation to current models of brain organization of person-specific and general semantic knowledge.

Background Although there is a growing body of research on driving and Alzheimer9s disease (AD), focal dementias have been understudied. Moreover, driving has never been explored in semantic dementia (SD). Methods An experimental battery exploring road sign knowledge and route learning was applied to patients with SD and AD selected in the early-moderate stage of disease and to a group of healthy participants. Neuropsychological data were correlated to cerebral hypometabolism distribution, investigated by means of positron emission tomography. Results The two dementias showed opposite profiles. Patients with SD showed poor road sign knowledge and normal performance in route learning. By contrast, patients with AD showed low performance in route learning test with preservation of semantic knowledge of road signs. In SD, there was a correlation of semantic knowledge impairment with hypometabolism in the left temporolateral cortex. No correlation between the AD region of interests (ROIs) and the relevant behavioural indices was found, while in the whole-brain analysis there was a significant correlation between route learning and the superior frontal gyrus. Discussion and conclusions For the first time, driving skills were explored in SD, and it is showed a differential profile from the one detected in AD. We demonstrate that the left anterior temporal cortex is implicated in road sign knowledge, while a distributed cortical network, including the frontal cortex, is likely to process route learning.

Humans use rules to organize their actions to achieve specific goals. Although 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. Although some evidence 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 investigate directly 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, which represented only low-level rule information. Our findings show that the brain represents conditional rules regardless of their level in the explored hierarchy, so the human control system did not organize task representation according to this dimension. Our paradigm represents a promising approach to identifying critical principles that shape this control system.SIGNIFICANCE STATEMENTSeveral recent studies investigating the organization of the human control system propose that rules at different control levels are organized along an anterior-to-posterior gradient within PFC. In this study, we used multivariate pattern analysis to explore independently the representation of formally identical conditional rules belonging to different levels of a cognitive hierarchy and provide for the first time a clear identification of low- and high-level rule representations. We found no major spatial differences between regions encoding rules from different hierarchical levels. This suggests that the human brain does not use levels in the investigated hierarchy as a topographical organization principle to represent rules controlling our behavior. Our paradigm represents a promising approach to identifying which principles are critical.

Humans are able to flexibly devise and implement rules to reach their desired goals. For simple situations, we can use single rules, such as “if traffic light is green then cross the street.” In most cases, however, more complex rule sets are required, involving the integration of multiple layers of control. Although it has been shown that prefrontal cortex is important for rule representation, it has remained unclear how the brain encodes more complex rule sets. Here, we investigate how the brain represents the order in which different parts of a rule set are evaluated. Participants had to follow compound rule sets that involved the concurrent application of two single rules in a specific order, where one of the rules always had to be evaluated first. The rules and their assigned order were independently manipulated. By applying multivariate decoding to fMRI data, we found that the identity of the current rule was encoded in a frontostriatal network involving right ventrolateral prefrontal cortex, right superior frontal gyrus, and dorsal striatum. In contrast, rule order could be decoded in the dorsal striatum and in the right premotor cortex. The nonhomogeneous distribution of information across brain areas was confirmed by follow-up analyses focused on relevant regions of interest. We argue that the brain encodes complex rule sets by “decomposing” them in their constituent features, which are represented in different brain areas, according to the aspect of information to be maintained.

Rules are widely used in everyday life to organize actions and thoughts in accordance with our internal goals. At the simplest level, single rules can be used to link individual sensory stimuli to their appropriate responses. However, most tasks are more complex and require the concurrent application of multiple rules. Experiments on humans and monkeys have shown the involvement of a frontoparietal network in rule representation. Yet, a fundamental issue still needs to be clarified: Is the neural representation of multiple rules compositional, that is, built on the neural representation of their simple constituent rules? Subjects were asked to remember and apply either simple or compound rules. Multivariate decoding analyses were applied to functional magnetic resonance imaging data. Both ventrolateral frontal and lateral parietal cortex were involved in compound representation. Most importantly, we were able to decode the compound rules by training classifiers only on the simple rules they were composed of. This shows that the code used to store rule information in prefrontal cortex is compositional. Compositional coding in rule representation suggests that it might be possible to decode other complex action plans by learning the neural patterns of the known composing elements.

Zusammenfassung Seit dem Aufkommen der funktionellen Magnetresonanztomografie (fMRT) vor 20 Jahren steht eine neue Methode zur nicht invasiven Messung von Gehirnfunktionen zur Verfügung, welche in den kognitiven Neurowissenschaften inzwischen weit verbreitet ist. Traditionell wurden fMRT-Daten vor allem verwendet, um globale Änderungen der Aktivität in bestimmten Gehirnregionen zu messen, wie sie etwa während einer kognitiven Verarbeitung auftreten. Die Entwicklung neuer Methoden ermöglicht nun einen verfeinerten, inhaltsbasierten Ansatz. Das „multivariate Decoding“ erlaubt es, die kognitive Information zu untersuchen, die in feinkörnigen fMRT-Aktivitätsmustern enthalten ist. Damit lässt sich die Kodierung spezifischer kognitiver Inhalte und Repräsentationen im Gehirn näher bestimmen. Hier wird ein Überblick über verschiedene Entwicklungen des multivariaten Decoding gegeben von der Anwendung in den kognitiven Neurowissenschaften (Wahrnehmung, Aufmerksamkeit, Belohnung, Entscheidungsfindung, emotionale Kommunikation) über neuere methodische Entwicklungen (Informationsfluss, oberflächenbasiertes Searchlight-Decoding) bis hin zur medizinischen Diagnostik gegeben.

The advent of functional magnetic resonance imaging (fMRI) of brain function 20 years ago has provided a new methodology for non-in­vasive measurement of brain function that is now widely used in cognitive neurosci­ence. Traditionally, fMRI data has been an­alyzed looking for overall activity chang­es in brain regions in response to a stimu­lus or a cognitive task. Now, recent develop­ments have introduced more elaborate, con­tent-based analysis techniques. When mul­tivariate decoding is applied to the detailed patterning of regionally-specific fMRI signals, it can be used to assess the amount of infor­mation these encode about specific task-vari­ables. Here we provide an overview of sev­eral developments, spanning from applica­tions in cognitive neuroscience (perception, attention, reward, decision making, emotion­al communication) to methodology (informa­tion flow, surface-based searchlight decod­ing) and medical diagnostics.

Two experiments investigated whether dealing with a homogeneous subset of syllogisms with time-constrained responses encouraged participants to develop and use heuristics for abstract (Experiment 1) and thematic (Experiment 2) syllogisms. An atmosphere-based heuristic accounted for most responses with both abstract and thematic syllogisms. With thematic syllogisms, a weaker effect of a belief heuristic was also observed, mainly where the correct response was inconsistent with the atmosphere of the premises. Analytic processes appear to have played little role in the time-constrained condition, whereas their involvement increased in a self-paced, unconstrained condition. From a dual-process perspective, the results further specify how task demands affect the recruitment of heuristic and analytic systems of reasoning. Because the syllogisms and experimental procedure were the same as those used in a previous neuroimaging study by Goel, Buchel, Frith, and Dolan (2000), the result also deepen our understanding of the cognitive processes investigated by that study.

Elementary deduction is the ability of unreflectively drawing conclusions from explicit or implicit premises, on the basis of their logical forms. This ability is involved in many aspects of human cognition and interactions. To date, limited evidence exists on its cortical bases. We propose a model of elementary deduction in which logical inferences, memory, and meta-logical control are separable subcomponents. We explore deficits in patients with left, medial and right frontal lesions, by both studying patients' deductive abilities and providing measures of their meta-logical sensitivity for proof difficulty. We show that lesions to left lateral and medial frontal cortex impair abilities at solving elementary deductive problems, but not so lesions to right frontal cortex. Furthermore, we show that memory deficits differentially affect patients according to the locus of the lesion. Left lateral patients with working memory deficits had defective deductive abilities, but not so left lateral patients with spared working memory. In contrast, in medial patients both deductive and meta-deductive abilities were affected regardless of the presence of memory deficits. Overall, the results are compatible with a componential view of elementary deduction, and call for the elaboration of more fine-grained models of deductive abilities.

When choosing actions, humans have to balance carefully between different task demands. On the one hand, they should perform tasks repeatedly to avoid frequent and effortful switching between different tasks. On the other hand, subjects have to retain their flexibility to adapt to changes in external task demands such as switching away from an increasingly difficult task. Here, we developed a difficulty-based choice task to investigate how subjects voluntarily select task-sets in predictably changing environments. Subjects were free to choose 1 of the 3 task-sets on a trial-by-trial basis, while the task difficulty changed dynamically over time. Subjects self-sequenced their behavior in this environment while we measured brain responses with functional magnetic resonance imaging (fMRI). Using multivariate decoding, we found that task choices were encoded in the medial prefrontal cortex (dorso-medial prefrontal cortex, dmPFC, and dorsal anterior cingulate cortex, dACC). The same regions were found to encode task difficulty, a major factor influencing choices. Importantly, the present paradigm allowed us to disentangle the neural code for task choices and task difficulty, ensuring that activation patterns in dmPFC/dACC independently encode these 2 factors. This finding provides new evidence for the importance of the dmPFC/dACC for task-selection and motivational functions in highly dynamic environments.

Rewards obtained from specific behaviors can and do change across time. To adapt to such conditions, humans need to represent and update associations between behaviors and their outcomes. Much previous work focused on how rewards affect the processing of specific tasks. However, abstract associations between multiple potential behaviors and multiple rewards are an important basis for adaptation as well. In this experiment, we directly investigated which brain areas represent associations between multiple tasks and rewards, using time-resolved multivariate pattern analysis of functional magnetic resonance imaging data. Importantly, we were able to dissociate neural signals reflecting task-reward associations from those related to task preparation and reward expectation processes, variables that were often correlated in previous research. We hypothesized that brain regions involved in processing tasks and/or rewards will be involved in processing associations between them. Candidate areas included the dorsal anterior cingulate cortex, which is involved in associating simple actions and rewards, and the parietal cortex, which has been shown to represent task rules and action values. Our results indicate that local spatial activation patterns in the inferior parietal cortex indeed represent task-reward associations. Interestingly, the parietal cortex flexibly changes its content of representation within trials. It first represents task-reward associations, later switching to process tasks and rewards directly. These findings highlight the importance of the inferior parietal cortex in associating behaviors with their outcomes and further show that it can flexibly reconfigure its function within single trials. Significance statement: Rewards obtained from specific behaviors rarely remain constant over time. To adapt to changing conditions, humans need to continuously update and represent the current association between behavior and its outcomes. However, little is known about the neural representation of behavior-outcome associations. Here, we used multivariate pattern analysis of functional magnetic resonance imaging data to investigate the neural correlates of such associations. Our results demonstrate that the parietal cortex plays a central role in representing associations between multiple behaviors and their outcomes. They further highlight the flexibility of the parietal cortex, because we find it to adapt its function to changing task demands within trials on relatively short timescales.

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.

The neural correlates of inductive reasoning are still poorly understood. In order to explore them, we administered a revised version of the Brixton test [Cortex 32 (2) (1996a) 241], a rule attainment task, to a group of 40 patients with a focal frontal brain lesion of mixed aetiology and to 43 control subjects. To interpret an impairment on the test as suggesting an inductive reasoning deficit a number of alternative hypotheses need first to be considered, namely whether the Brixton impairment could be explained by: (i) a working memory deficit; (ii) a monitoring deficit; (iii) a difficulty in applying an already induced rule; (iv) greater impulsivity. The patients with left lateral (LL) frontal lesions were significantly impaired on the Brixton test; more importantly they were the only group in which none of the alternative hypotheses we explored proved able to explain the flawed performance. In sharp contrast, right lateral lesion patients did not make significantly more errors on the Brixton test than controls, but they produced three times more capture errors (a sign of impaired monitoring processes). The results were interpreted as suggesting functional dissociations between inductive reasoning, monitoring and working memory and a localisation of key processes for induction in left lateral frontal cortex and in right lateral cortex for monitoring and checking.

SummaryMany daily behaviors require us to actively focus on the current task and ignore all other distractions. Yet, ignoring everything else might hinder the ability to discover new ways to achieve the same goal. Here, we studied the neural mechanisms that support the spontaneous change to better strategies while an established strategy is executed. Multivariate neuroimaging analyses showed that before the spontaneous change to an alternative strategy, medial prefrontal cortex (MPFC) encoded information that was irrelevant for the current strategy but necessary for the later strategy. Importantly, this neural effect was related to future behavioral changes: information encoding in MPFC was changed only in participants who eventually switched their strategy and started before the actual strategy change. This allowed us to predict spontaneous strategy shifts ahead of time. These findings suggest that MPFC might internally simulate alternative strategies and shed new light on the organization of PFC.

Bilinguals require a high degree of cognitive control to select the language intended for speaking and inhibit the unintended. Previous neuroimaging studies have not teased apart brain regions for generating the intention to use a given language, and those for speaking in that language. Separating these two phases can clarify at what stage competition between languages occurs. In this fMRI study German–English bilinguals were first cued to use German or English. After a delay, they named a picture in the cued language. During the intention phase, the precuneus, right superior lateral parietal lobule, and middle temporal gyrus were more activated when participants had to update the currently active language. During language execution activation was higher for English compared to German in brain areas associated with cognitive control, most notably the anterior cingulate and the caudate. Our results suggest two different systems enabling cognitive control during bilingual language production.

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.

Semantic fluency is widely used both as a clinical test and as a basic tool for understanding how humans extract information from the semantic store. Recently, major efforts have been made to devise fine-grained scoring procedures to measure the multiple cognitive processes underlying fluency performance. Nevertheless, it is still unclear how many and which independent components are necessary to thoroughly describe performance on the fluency task. Furthermore, whether a combination of multiple indices can improve the diagnostic performance of the test should be assessed. In this study, we extracted multiple indices of performance on the semantic fluency test from a large sample of healthy controls (n = 307) and patients (n = 145) suffering from three types of focal dementia or Alzheimer's Disease (AD). We found that five independent components underlie semantic fluency performance. We argue that these components functionally map onto the generation and application of a search strategy (component 2), to the monitoring of the overall sequence to avoid repetitions (component 3) and out-of-category items (component 4), and to the full integrity of the semantic store (component 5). The integrated and effective work of all these components would relate to a “general effectiveness” component (component 1). Importantly, while all the focal dementia groups were equally impaired on general effectiveness measures, they showed differential patterns of failure in the other components. This finding suggests that the cognitive deficit that impairs fluency differs among the three focal dementia groups: a semantic store deficit in the semantic variant of primary progressive aphasia (sv-PPA), a strategy deficit in the non-fluent variant of primary progressive aphasia (nfv-PPA), and an initiation deficit in the behavioural variant of fronto-temporal dementia (bv-FTD). Finally, we showed that the concurrent use of multiple fluency indices improves the diagnostic accuracy of semantic fluency both for focal dementias and for AD. More generally, our study suggests that a formal evaluation of fine-grained patterns of performance would improve the diagnostic accuracy of neuropsychological tests.