Carlo Reverberi

Specific impairments of rule induction in different frontal lobe subgroups

The neural correlates of inductive reasoning are still poorly understood. In order to explore them, we administered a revised version of the Brixton test, 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.

Compositionality of Rule Representations in Human Prefrontal Cortex

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.

Distributed representations of rule identity and rule order in human frontal cortex and striatum

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.

Qualitative features of semantic fluency performance in mesial and lateral frontal patients

Semantic verbal fluency is widely used in clinical and experimental studies. This task is highly sensitive to the presence of brain pathology and is frequently impaired after frontal lesions. Besides the total number of words generated, a qualitative analysis of their sequence can add valuable information about the impaired cognitive components. Thirty-four frontal patients and a group of matched controls were examined. Besides the number of words and subcategories retrieved by each group, we analysed two distinct aspects of the word sequence: the search strategy through a semantically organised store and the ability to switch from one subcategory to another. We checked whether the pattern of impairment changed according to the lesion site within the frontal lobe. Overall, patients produced fewer words than controls. However, only lateral frontal patients presented a reduced semantic relatedness between contiguously produced words and a specifically increased proportion of switches to different subcategories. The performance of lateral frontal patients was in line with the hypothesis of a search strategy impairment and cannot be attributed to a switching deficit. The performance of mesial frontal patients could be ascribed to a general deficit of activation.

Medial prefrontal cortex predicts internally driven strategy shifts.

Many 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.

Conditional and syllogistic deductive tasks dissociate functionally during premise integration.

Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event‐related fMRI, in the same group of subjects, to compare reasoning‐related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning‐related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto‐lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro‐lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations. Hum Brain Mapp, 2010.

Large scale brain activations predict reasoning profiles

Deduction is the ability to draw necessary conclusions from previous knowledge. Here we propose a novel approach to understanding the neural basis of deduction, which exploits fine-grained inter-participant variability in such tasks. Participants solved deductive problems and were grouped by the behavioral strategies employed, i.e., whether they were sensitive to the logical form of syllogistic premises, whether the problems were solved correctly, and whether heuristic strategies were employed. Differential profiles of neural activity can predict membership of the first two of these groups. The predictive power of activity profiles is distributed non-uniformly across the brain areas activated by deduction. Activation in left ventro-lateral frontal (BA47) and lateral occipital (BA19) cortices predicts whether logically valid solutions are sought. Activation of left inferior lateral frontal (BA44/45) and superior medial frontal (BA6/8) cortices predicts sensitivity to the logical structure of problems. No specific pattern of activation was associated with the use of a non-logical heuristic strategy. Not only do these findings corroborate the hypothesis that left BA47, BA44/45 and BA6/8 are critical for making syllogistic deductions, but they also imply that they have different functional roles as components of a dedicated network. We propose that BA44/45 and BA6/8 are involved in the extraction and representation of the formal structure of a problem, while BA47 is involved in the selection and application of relevant inferential rules. Finally, our findings suggest that deductive reasoning can be best described as a cascade of cognitive processes requiring the concerted operation of several, functionally distinct, brain areas.

Critical Dimensions Affecting Imitation Performance of Patients with Ideomotor Apraxia

The conceptualisation of apraxia has often been linked to the clinicalassessment of the disorder (Rothi et al., 1997). Thus Ideomotor Apraxia(hereafter IMA) has been described as a failure to imitate actions. One of thetasks more widely employed by clinicians is that devised by De Renzi et al.,(1980). The 24 gestures of this test vary according to a 2x2x2 design, the threefactors being (i) gestures composed of a single posture (‘positions’) vs. asequence of postures (‘sequences’); (ii) involving hand and/or arm vs. fingers;(iii) symbolic vs. non-symbolic (see De Renzi and Faglioni, 1999, for detailsabout the items). Specific predictions involving all these gestures were madebased on a model that comprises a Long-Term Memory (LTM), a ‘MotorProgramming’ (MP) component, and a Working Memory (WM) (Baddeley,1986) including a Short-Term Memory component specific for gestures (STM;Smyth and Pendleton, 1988; Rumiati and Tessari, in press) and the SupervisoryAttentional System (SAS, Norman and Shallice, 1986) (Fig. 1).The gesture to be imitated is temporarily held in the STM (while the SASselects, whenever necessary, alternative strategies for the gesture encoding), andthen transferred to the MP system. When a gesture is symbolic, the WM loadcan be reduced by accessing its LTM representation. IMA per sewouldcorrespond to a breakdown at MP level, while damage to the WM componentwould produce an inability to maintain the gesture (STM) or to selectappropriate strategies (SAS) beforethe MP stage.The WM and LTM components have an overall probability wof maintainingand transferring to MP an accurate copy of the input gesture. When a non-

The Neural Representation of Voluntary Task-Set Selection in Dynamic Environments

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.

Generation and recognition of abstract rules in different frontal lobe subgroups

The Left Lateral cortex is known to have a role in inductive reasoning tasks. A more specific hypothesis on its role is that it is crucial in the generation of new abstract rules, rather than in the selection and implementation of a specific rule among a set of previously learned ones. Two new tests - the Generation of Hypotheses test and the Recognition of the Rule test - were administered to 46 patients with focal damage to the frontal cortex. Patients were divided in three frontal subgroups: Left Lateral, Right Lateral and Medial. On the basis of the new hypothesis, it was predicted that (i) the Left Lateral subgroup would fail in the Generation of Hypotheses test but would show spared performance on the Recognition of the Rule test and that (ii) the other frontal subgroups would perform normally on both tests. The findings on the Left Lateral and Right Lateral frontal subgroup were consistent with the predictions. This suggests that the Left Lateral frontal cortex is critical specifically for the generation of hypotheses in inductive reasoning. The Medial frontal subgroup, in contrast with our expectations, was impaired on Generation test; two hypotheses have been raised to explain this finding.