Recomposing a fragmented literature: How conditional and relational arguments engage different neural systems for deductive reasoning

Examining the role and neural electrophysiological mechanisms of adjective cues in size judgment

Numerous influential theories have attempted to elucidate the relationship between language and thought. The debate persists on whether language and thought are distinct entities or if language is deeply embedded in individual cognitive processes. This study employs adjective cues combined with a mental imagery size judgment task as an experimental paradigm, utilizing neurophysiological techniques to preliminarily explore the role of adjectives in size judgment tasks and their underlying neurophysiological mechanisms. Findings reveal that performance is best when adjectives are congruent with the size of the object, with EEG microstate results indicating strong activity in Class A, related to language networks under this condition. Additionally, when adjectives conflict with object size, the discovery of the Ni component suggests that individuals monitor and inhibit the conflict between adjectives and object size, leading to decreased task performance in this condition. Moreover, when object size is ambiguous, individuals' size judgments do not benefit significantly from clear adjective cues. Event-related potentials and EEG microstate results suggest that under this condition, top-down cognitive resources are recruited more extensively. In conclusion, language plays a more crucial role in simpler judgment tasks; as tasks become more complex, judgment processes engage a greater number of distributed brain regions to collaborate, while the language system remains active. This study provides initial cognitive neuroscience evidence for understanding the relationship between language and simple forms of thought, offering preliminary insights for future investigations into the connection between language and thought.

A right frontal network for analogical and deductive reasoning

Two of the most well-studied types of reasoning are analogical reasoning (AR) and deductive reasoning (DR). Yet, our understanding of the relationship between reasoning abilities and their neuroanatomical basis remains surprisingly limited. We aimed to conduct fine-grained anatomical mapping of performance on tests of AR, DR and fluid intelligence (Gf), in a large sample of patients with unilateral focal frontal or posterior lesions and healthy controls. We assessed 247 prospectively recruited patients using two new tests: the Analogical Reasoning Test (ART) and the Deductive Reasoning Test (DRT); and the best-established measure of Gf: Raven's Advanced Progressive Matrices (RAPM). Non-parametric Bayesian stochastic block modelling was used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. ART and DRT performance was significantly impaired in patients with frontal lesions [ART: F(2,238) = 18.93; P < 0.001; Frontal group worse than Posterior group and healthy controls, both P < 0.001; DRT: F(2,387) = 18.491; P < 0.001; Frontal group worse than healthy controls, P < 0.01]. Right frontal effects were evident on both tests. Thus, on the ART, right frontal patients were more impaired than left (P < 0.05). On the DRT, right frontal patients were more impaired than left frontal patients on questions with indeterminate solutions (P < 0.05) but not on questions with determinate ones. Non-parametric Bayesian stochastic block modelling implicated a right frontal network in ART and DRT performance. Strikingly, we found that this network was also implicated in performance on RAPM. Our study represents the most robust investigation of AR and DR in the focally injured brain. Our findings imply that a right frontal network is critical. The ART and DRT appear to be promising new clinical tests, capable of evaluating reasoning abilities and identifying right frontal lobe dysfunction.

Distinctive Delta and Theta Responses in Deductive and Probabilistic Reasoning

INTRODUCTION

The neural substrates of reasoning, a cognitive ability we use constantly in daily life, are still unclear. Reasoning can be divided into two types according to how the inference process works and the certainty of the conclusions. In deductive reasoning, certain conclusions are drawn from premises by applying the rules of logic. On the other hand, in probabilistic reasoning, possible conclusions are drawn by interpreting the semantic content of arguments.

METHODS

We examined event-related oscillations associated with deductive and probabilistic reasoning. To better represent the natural use of reasoning, we adopted a design that required participants to choose what type of reasoning they would use. Twenty healthy participants judged the truth values of alternative conclusion propositions following two premises while the EEG was being recorded. We then analyzed event-related delta and theta power and phase-locking induced under two different conditions.

RESULTS

We found that the reaction time was shorter and the accuracy rate was higher in deductive reasoning than in probabilistic reasoning. High delta and theta power in the temporoparietal, parietal, and occipital regions of the brain were observed in deductive reasoning. As for the probabilistic reasoning, prolonged delta response in the right hemisphere and high frontal theta phase-locking were noted.

CONCLUSION

Our results suggest that the electrophysiological signatures of the two types of reasoning have distinct characteristics. There are significant differences in the delta and theta responses that are associated with deductive and probabilistic reasoning. Although our findings suggest that deductive and probabilistic reasoning have different neural substrates, consistent with most of the studies in the literature, there is not yet enough evidence to make a comprehensive claim on the subject. There is a need to diversify the growing literature on deductive and probabilistic reasoning with different methods and experimental paradigms.

Electrophysiological connectivity of logical deduction: Early cortical MEG study

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered "deductive" because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive processes has not been addressed yet. In this work we consider typically deductive logico-probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age = 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the differences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive "core" areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes.

Electrical analysis of logical complexity: an exploratory eeg study of logically valid/invalid deducive inference

INTRODUCTION

Logically valid deductive arguments are clear examples of abstract recursive computational procedures on propositions or on probabilities. However, it is not known if the cortical time-consuming inferential processes in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes.

METHODS

In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and invalid inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth-functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two-condition paradigm (100 trials for each condition). After the initial general analysis, a trial-by-trial approach in beta-2 band allowed to uncover not only evoked but also phase asynchronous activity between trials.

RESULTS

showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta-2 activations (p-value < 0,01, Wilcoxon signed rank test).

CONCLUSION

We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events.

Probabilistic and Deductive Reasoning in the Human Brain

Reasoning is a process of inference from given premises to new conclusions. Deductive reasoning is truth-preserving and conclusions can only be either true or false. Probabilistic reasoning is based on degrees of belief and conclusions can be more or less likely. While deductive reasoning requires people to focus on the logical structure of the inference and ignore its content, probabilistic reasoning requires the retrieval of prior knowledge from memory. Recently, however, some researchers have denied that deductive reasoning is a faculty of the human mind. What looks like deductive inference might actually also be probabilistic inference, only with extreme probabilities. We tested this assumption in an fMRI experiment with two groups of participants: one group was instructed to reason deductively, the other received probabilistic instructions. They could freely choose between a binary and a graded response to each problem. The conditional probability and the logical validity of the inferences were systematically varied. Results show that prior knowledge was only used in the probabilistic reasoning group. These participants gave graded responses more often than those in the deductive reasoning group and their reasoning was accompanied by activations in the hippocampus. Participants in the deductive group mostly gave binary responses and their reasoning was accompanied by activations in the anterior cingulate cortex, inferior frontal cortex, and parietal regions. These findings show that (1) deductive and probabilistic reasoning rely on different neurocognitive processes, (2) people can suppress their prior knowledge to reason deductively, and (3) not all inferences can be reduced to probabilistic reasoning.

Dissociating Language and Thought in Human Reasoning

What is the relationship between language and complex thought? In the context of deductive reasoning there are two main views. Under the first, which we label here the language-centric view, language is central to the syntax-like combinatorial operations of complex reasoning. Under the second, which we label here the language-independent view, these operations are dissociable from the mechanisms of natural language. We applied continuous theta burst stimulation (cTBS), a form of noninvasive neuromodulation, to healthy adult participants to transiently inhibit a subregion of Broca's area (left BA44) associated in prior work with parsing the syntactic relations of natural language. We similarly inhibited a subregion of dorsomedial frontal cortex (left medial BA8) which has been associated with core features of logical reasoning. There was a significant interaction between task and stimulation site. Post hoc tests revealed that performance on a linguistic reasoning task, but not deductive reasoning task, was significantly impaired after inhibition of left BA44, and performance on a deductive reasoning task, but not linguistic reasoning task, was decreased after inhibition of left medial BA8 (however not significantly). Subsequent linear contrasts supported this pattern. These novel results suggest that deductive reasoning may be dissociable from linguistic processes in the adult human brain, consistent with the language-independent view.

Neural correlates of transitive inference: An SDM meta-analysis on 32 fMRI studies

Transitive inference (TI) is a critical capacity involving the integration of relevant information into prior knowledge structure for drawing novel inferences on unobserved relationships. To date, the neural correlates of TI remain unclear due to the small sample size and heterogeneity of various experimental tasks from individual studies. Here, the meta-analysis on 32 fMRI studies was performed to detect brain activation patterns of TI and its three paradigms (spatial inference, hierarchical inference, and associative inference). We found the hippocampus, prefrontal cortex (PFC), putamen, posterior parietal cortex (PPC), retrosplenial cortex (RSC), supplementary motor area (SMA), precentral gyrus (PreCG), and median cingulate cortex (MCC) were engaged in TI. Specifically, the RSC was implicated in the associative inference, whereas PPC, SMA, PreCG, and MCC were implicated in the hierarchical inference. In addition, the hierarchical inference and associative inference both evoked activation in the hippocampus, medial PFC, and PCC. Although the meta-analysis on spatial inference did not generate a reliable result due to insufficient amount of investigations, the present work still offers a new insight for better understanding the neural basis underlying TI.

Set-shifting and inhibition interplay affect the rule-matching bias occurrence during conditional reasoning task

The rule-matching bias is a common error during conditional reasoning tasks, which refers to a tendency to match responses with the lexical context in the conditional rule and leads to incorrect responses. Conditional reasoning is one of the higher-level cognitive abilities affected by many cognitive skills. We aimed to determine whether inhibition and set-shifting skills with rule-matching bias occurrence could be related and, if so, to what quantitative, at a statistically significant level. A total of 30 healthy university students aged 18 to 30 participated in this study. We used the Wason's Selection Task (WST) to measure conditional reasoning and investigated their inhibition and set-shifting skills with the Stroop and Wisconsin Card Sorting Test, respectively. Results showed a significant positive correlation between the number of correct responses to the Stroop test and the Wason Selection Card Test (p=0.614). There was a positive correlation between the number of correct responses to the Wisconsin Card Sorting Test and the Wason Selection Card Test (p=0.423). Participants with higher inhibition and set-shifting abilities showed better performance in the conditional reasoning test and lower rule-matching bias errors.

Brain Functional Networks Involved in Different Premise Order in Conditional Reasoning: A Dynamic Causal Model Study

In conditional reasoning, the reasoner must draw a conclusion based on a conditional or "If…, then…" proposition. Previous studies have reported that reversing the premises can effectively promote modus tollens reasoning (a form of conditional reasoning), but subsequent experimental studies have found no such effect. Therefore, to further examine this issue and reveal the cognitive mechanism of conditional reasoning, we asked two groups of healthy volunteers (traditional and inverted premise order groups) to evaluate a set of visually presented conditional tasks (modus ponens/modus tollens) under fMRI. The results indicated that the inverted condition activated more brain regions associated with working memory, including the angular gyrus (BA 39), precuneus (BA 7), inferior parietal lobe, and middle frontal gyrus. The resulting common activation map was used to define the ROIs and perform dynamic causal modeling for the effective connectivity analysis, containing the medial frontal gyrus, hippocampus, cerebellum, and middle occipital gyrus in the right hemisphere and the inferior occipital gyrus in the left hemisphere. The results of intrinsic connections in the optimal model selected by Bayesian model selection showed that the connection strength was stronger in the inverted group rather than in the traditional group, which may indicate that the reversal of the premise order promotes connectivity between brain regions. Despite the lack of a premise order effect, we did discover a neuronal separation between the inverted and traditional conditions, which lends support to the mental model theory to some extent.

Neural Correlates of Causal Inferences in Discourse Understanding and Logical Problem-Solving: A Meta-Analysis Study

In discourse comprehension, we need to draw inferences to make sense of discourse. Previous neuroimaging studies have investigated the neural correlates of causal inferences in discourse understanding. However, these findings have been divergent, and how these types of inferences are related to causal inferences in logical problem-solving remains unclear. Using the activation likelihood estimation (ALE) approach, the current meta-analysis analyzed 19 experiments on causal inferences in discourse understanding and 20 experiments on those in logical problem-solving to identify the neural correlates of these two cognitive processes and their shared and distinct neural correlates. We found that causal inferences in discourse comprehension recruited a left-lateralized frontotemporal brain system, including the left inferior frontal gyrus, the left middle temporal gyrus (MTG), and the bilateral medial prefrontal cortex (MPFC), while causal inferences in logical problem-solving engaged a nonoverlapping brain system in the frontal and parietal cortex, including the left inferior frontal gyrus, the bilateral middle frontal gyri, the dorsal MPFC, and the left inferior parietal lobule (IPL). Furthermore, the pattern similarity analyses showed that causal inferences in discourse understanding were primarily related to the terms about language processing and theory-of-mind processing. Both types of inferences were found to be related to the terms about memory and executive function. These findings suggest that causal inferences in discourse understanding recruit distinct neural bases from those in logical problem-solving and rely more on semantic knowledge and social interaction experiences.

The Influence of Language on Spatial Reasoning: Reading Habits Modulate the Formulation of Conclusions and the Integration of Premises

In the present study, we explore how reading habits (e.g., reading from left to right in French or reading from right to left in Arabic) influence the scanning and the construction of mental models in spatial reasoning. For instance, when participants are given a problem like A is to the left of B; B is to the left of C, what is the relation between A and C? They are assumed to construct the model: A B C. If reading habits influence the scanning process, then readers of French should inspect models from left to right, whereas readers of Arabic should inspect them from right to left. The prediction following this analysis is that readers of French should be more inclined to produce "left" conclusions (i.e., A is to the left of C), whereas readers of Arabic should be more inclined to produce "right" conclusions (i.e., C is to the right of A). Furthermore, one may expect that readers of French show a greater ease in constructing models following a left-to-right direction than models following a right-to-left direction, whereas an opposite pattern might be expected for readers of Arabic. We tested these predictions in two experiments involving French and Yemeni participants. Experiment 1 investigated the formulation of conclusions from spatial premises, and Experiment 2, which was based on non-linguistic stimuli, examined the time required to construct mental models from left to right and from right to left. Our results show clear differences between the two groups. As expected, the French sample showed a strong left-to-right bias, but the Yemeni sample did not show the reverse bias. Results are discussed in terms of cultural influences and universal mechanisms.

Brain electrical traits of logical validity

Neuroscience has studied deductive reasoning over the last 20 years under the assumption that deductive inferences are not only de jure but also de facto distinct from other forms of inference. The objective of this research is to verify if logically valid deductions leave any cerebral electrical trait that is distinct from the trait left by non-valid deductions. 23 subjects with an average age of 20.35 years were registered with MEG and placed into a two conditions paradigm (100 trials for each condition) which each presented the exact same relational complexity (same variables and content) but had distinct logical complexity. Both conditions show the same electromagnetic components (P3, N4) in the early temporal window (250-525 ms) and P6 in the late temporal window (500-775 ms). The significant activity in both valid and invalid conditions is found in sensors from medial prefrontal regions, probably corresponding to the ACC or to the medial prefrontal cortex. The amplitude and intensity of valid deductions is significantly lower in both temporal windows (p = 0.0003). The reaction time was 54.37% slower in the valid condition. Validity leaves a minimal but measurable hypoactive electrical trait in brain processing. The minor electrical demand is attributable to the recursive and automatable character of valid deductions, suggesting a physical indicator of computational deductive properties. It is hypothesized that all valid deductions are recursive and hypoactive.

Deductive-reasoning brain networks: A coordinate-based meta-analysis of the neural signatures in deductive reasoning

OBJECTIVE

Deductive reasoning is a complex and poorly understood concept in the field of psychology. Many cognitive neuroscience studies have been published on deductive reasoning but have yielded inconsistent findings.

METHODS

In this study, we analyzed collected data from 38 articles using a recently proposed activation likelihood estimation (ALE) approach and used conjunction analysis to better determine the intersection of the results of meta-analyses.

RESULTS

First, the left hemispheres in the inferior parietal lobule (Brodmann area 40 [BA40]), middle frontal gyrus (BA6), medial frontal gyrus (BA8), inferior frontal gyrus (BA45/46), caudate, and insula (BA47) were revealed to be significant brain regions via simple-effect analysis (deductive reasoning versus baseline). Furthermore, IFG, insula, and cingulate (the key neural hubs of the cingulo-opercular network) were highlighted in overlapped functional connectivity maps.

CONCLUSION

The findings of the current study are consistent with the view that deductive reasoning requires a succession of stages, which included decoding of linguistic information, conversion and correction of rules, and transformation of inferential results into conclusive outputs, all of which are putatively processed via a distributed network of brain regions encompassing frontal/parietal cortices, as well as the caudate and other subcortical structures, which suggested that in the process of deductive reasoning, the coding and integration of premise information is indispensable, and it is also crucial to the execution and monitoring of the cognitive processing of reasoning.

Enhancing cognitive training effects in Alzheimer's disease: rTMS as an add-on treatment

The treatment of Alzheimer's disease (AD) in the field of non-pharmacological interventions is a challenging issue, given the limited benefits of the available drugs. Cognitive training (CT) represents a commonly recommended strategy in AD. Recently, repetitive transcranial magnetic stimulation (rTMS) has gained increasing attention as a promising therapeutic tool for the treatment of AD, given its ability of enhancing neuroplasticity. In the present randomized, double-blind, sham-controlled study, we aimed at investigating the add-on effect of a high frequency rTMS protocol applied over the left dorsolateral prefrontal cortex (DLPFC) combined with a face-name associative memory CT in the continuum of AD pathology. Fifty patients from a very early to a moderate phase of dementia were randomly assigned to one of two groups: CT plus real rTMS or CT plus placebo rTMS. The results showed that the improvement in the trained associative memory induced with rTMS was superior to that obtained with CT alone. Interestingly, the extent of the additional improvement was affected by disease severity and levels of education, with less impaired and more educated patients showing a greater benefit. When testing for generalization to non-trained cognitive functions, results indicated that patients in CT-real group showed also a greater improvement in visuospatial reasoning than those in the CT-sham group. Interestingly, this improvement persisted over 12 weeks after treatment beginning. The present study provides important hints on the promising therapeutic use of rTMS in AD.

The neural bases of argumentative reasoning

Most reasoning tasks used in behavioral and neuroimaging studies are abstract, triggering slow, effortful processes. By contrast, most of everyday life reasoning is fast and effortless, as when we exchange arguments in conversation. Recent behavioral studies have shown that reasoning tasks with the same underlying logic can be solved much more easily if they are embedded in an argumentative context. In the present article, we study the neural bases of this type of everyday, argumentative reasoning. Such reasoning is both a social and a metarepresentational process, suggesting it should share some mechanisms, and thus some neural bases, with other social, metarepresentational process such as pragmatics, metacognition, or theory of mind. To isolate the neural bases of argumentative reasoning, we measured fMRI activity of participants who read the same statement presented either as the conclusion of an argument, or as an assertion. We found that conclusions of arguments, compared to assertions, were associated with greater activity in a region of the medial prefrontal cortex that was identified in quantitative meta-analyses of studies on theory of mind. This study shows that it is possible to use more ecologically valid tasks to study the neural bases of reasoning, and that using such tasks might point to different neural bases than those observed with the more abstract and artificial tasks typically used in the neuroscience of reasoning. Specifically, we speculate that reasoning in an argumentative context might rely on mechanisms supporting metarepresentational processes in the medial prefrontal cortex.

Cognitive Enhancement via Network-Targeted Cortico-cortical Associative Brain Stimulation

Fluid intelligence (gf) represents a crucial component of human cognition, as it correlates with academic achievement, successful aging, and longevity. However, it has strong resilience against enhancement interventions, making the identification of gf enhancement approaches a key unmet goal of cognitive neuroscience. Here, we applied a spike-timing-dependent plasticity (STDP)-inducing brain stimulation protocol, named cortico-cortical paired associative stimulation (cc-PAS), to modulate gf in 29 healthy young subjects (13 females-mean ± standard deviation, 25.43 years ± 3.69), based on dual-coil transcranial magnetic stimulation (TMS). Pairs of neuronavigated TMS pulses (10-ms interval) were delivered over two frontoparietal nodes of the gf network, based on individual functional magnetic resonance imaging data and in accordance with cognitive models of information processing across the prefrontal and parietal lobe. cc-PAS enhanced accuracy at gf tasks, with parieto-frontal and fronto-parietal stimulation significantly increasing logical and relational reasoning, respectively. Results suggest the possibility of using SPTD-inducing TMS protocols to causally validate cognitive models by selectively engaging relevant networks and manipulating inter-regional temporal dynamics supporting specific cognitive functions.

Neural representations of transitive relations predict current and future math calculation skills in children

A large body of evidence suggests that math learning in children is built upon innate mechanisms for representing numerical quantities in the intraparietal sulcus (IPS). Learning math, however, is about more than processing quantitative information. It is also about understanding relations between quantities and making inferences based on these relations. Consistent with this idea, recent behavioral studies suggest that the ability to process transitive relations (A > B, B > C, therefore A > C) may contribute to math skills in children. Here we used fMRI coupled with a longitudinal design to determine whether the neural processing of transitive relations in children could predict their current and future math skills. At baseline (T₁), children (n = 31) processed transitive relations in an MRI scanner. Math skills were measured at T₁ and again 1.5 years later (T₂). Using a machine learning approach with cross-validation, we found that activity associated with the representation of transitive relations in the IPS predicted math calculation skills at both T₁ and T₂. Our study highlights the potential of neurobiological measures of transitive reasoning for forecasting math skills in children, providing additional evidence for a link between this type of reasoning and math learning.

The Neurocognitive Correlates of Human Reasoning: A Meta-analysis of Conditional and Syllogistic Inferences

Inferring knowledge is a core aspect of human cognition. We can form complex sentences connecting different pieces of information, such as in conditional statements like "if someone drinks alcohol, then they must be older than 18." These are relevant for causal reasoning about our environment and allow us to think about hypothetical scenarios. Another central aspect to forming complex statements is to quantify about sets, such as in "some apples are green." Reasoning in terms of the ability to form these statements is not yet fully understood, despite being an active field of interdisciplinary research. On a theoretical level, several conceptual frameworks have been proposed, predicting diverging brain activation patterns during the reasoning process. We present a meta-analysis comprising the results of 32 neuroimaging experiments about reasoning, which we subdivided by their structure, content, and requirement for world knowledge. In conditional tasks, we identified activation in the left middle and rostrolateral pFC and parietal regions, whereas syllogistic tasks elicit activation in Broca's complex, including the BG. Concerning the content differentiation, abstract tasks exhibit activation in the left inferior and rostrolateral pFC and inferior parietal regions, whereas content tasks are in the left superior pFC and parieto-occipital regions. The findings clarify the neurocognitive mechanisms of reasoning and exhibit clear distinctions between the task's type and content. Overall, we found that the activation differences clarify inconsistent results from accumulated data and serve as useful scaffolding differentiations for theory-driven interpretations of the neuroscientific correlates of human reasoning.

The Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies

It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.

Developmental grey matter changes in superior parietal cortex accompany improved transitive reasoning

The neural basis of developmental changes in transitive reasoning in parietal regions was examined, using voxel-based morphometry. Young adolescents and adults performed a transitive reasoning task, subsequent to undergoing anatomical magnetic resonance imaging (MRI) brain scans. Behaviorally, adults reasoned more accurately than did the young adolescents. Neural results showed (i) less grey matter density in superior parietal cortex in the adults than in the young adolescents, possibly due to a developmental period of synaptic pruning; (ii) improved performance in the reasoning task was negatively correlated with grey matter density in superior parietal cortex in the adolescents, but not in the adult group; and (iii) the latter results were driven by the more difficult trials, requiring greater spatial manipulation. Taken together, the results support the idea that during development, regions in superior parietal cortex are fine-tuned, to support more robust spatial manipulation, resulting in greater accuracy and efficiency in transitive reasoning.

At the core of reasoning: Dissociating deductive and non-deductive load

In recent years, neuroimaging methods have been used to investigate how the human mind carries out deductive reasoning. According to some, the neural substrate of language is integral to deductive reasoning. According to others, deductive reasoning is supported by a language-independent distributed network including left frontopolar and frontomedial cortices. However, it has been suggested that activity in these frontal regions might instead reflect non-deductive factors such as working memory load and general cognitive difficulty. To address this issue, 20 healthy volunteers participated in an fMRI experiment in which they evaluated matched simple and complex deductive and non-deductive arguments in a 2 × 2 design. The contrast of complex versus simple deductive trials resulted in a pattern of activation closely matching previous work, including frontopolar and frontomedial "core" areas of deduction as well as other "cognitive support" areas in frontoparietal cortices. Conversely, the contrast of complex and simple non-deductive trials resulted in a pattern of activation that does not include any of the aforementioned "core" areas. Direct comparison of the load effect across deductive and non-deductive trials further supports the view that activity in the regions previously interpreted as "core" to deductive reasoning cannot merely reflect non-deductive load, but instead might reflect processes specific to the deductive calculus. Finally, consistent with previous reports, the classical language areas in left inferior frontal gyrus and posterior temporal cortex do not appear to participate in deductive inference beyond their role in encoding stimuli presented in linguistic format.

Multiple neural representations of elementary logical connectives

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.

Uncertain relational reasoning in the parietal cortex

The psychology of reasoning is currently transitioning from the study of deductive inferences under certainty to inferences that have degrees of uncertainty in both their premises and conclusions; however, only a few studies have explored the cortical basis of uncertain reasoning. Using transcranial magnetic stimulation (TMS), we show that areas in the right superior parietal lobe (rSPL) are necessary for solving spatial relational reasoning problems under conditions of uncertainty. Twenty-four participants had to decide whether a single presented order of objects agreed with a given set of indeterminate premises that could be interpreted in more than one way. During the presentation of the order, 10-Hz TMS was applied over the rSPL or a sham control site. Right SPL TMS during the inference phase disrupted performance in uncertain relational reasoning. Moreover, we found differences in the error rates between preferred mental models, alternative models, and inconsistent models. Our results suggest that different mechanisms are involved when people reason spatially and evaluate different kinds of uncertain conclusions.

Individual differences and specificity of prefrontal gamma frequency-tACS on fluid intelligence capabilities

Emerging evidence suggests that transcranial alternating current stimulation (tACS) is an effective, frequency-specific modulator of endogenous brain oscillations, with the potential to alter cognitive performance. Here, we show that reduction in response latencies to solve complex logic problem indexing fluid intelligence is obtained through 40 Hz-tACS (gamma band) applied to the prefrontal cortex. This improvement in human performance depends on individual ability, with slower performers at baseline receiving greater benefits. The effect could have not being explained by regression to the mean, and showed task and frequency specificity: it was not observed for trials not involving logical reasoning, as well as with the application of low frequency 5 Hz-tACS (theta band) or non-periodic high frequency random noise stimulation (101-640 Hz). Moreover, performance in a spatial working memory task was not affected by brain stimulation, excluding possible effects on fluid intelligence enhancement through an increase in memory performance. We suggest that such high-level cognitive functions are dissociable by frequency-specific neuromodulatory effects, possibly related to entrainment of specific brain rhythms. We conclude that individual differences in cognitive abilities, due to acquired or developmental origins, could be reduced during frequency-specific tACS, a finding that should be taken into account for future individual cognitive rehabilitation studies.

Deductive Versus Probabilistic Reasoning in Healthy Adults: An EEG Analysis of Neural Differences

This study examined the electrophysiological signatures of deductive and probabilistic reasoning. Deduction is defined as the case in which a conclusion can be found to be true or false due to validity of argument. In probabilistic reasoning, however, conclusions can be considered to be likely or unlikely, but not with certainty due to the lack of validity in the form of the argument. 16 participants were presented with both types of arguments while response times and ERPs were carried out. Participants had to decide with the presentation of each argument, what type of reasoning was appropriate and which of four responses (certainly yes, probably yes, probably no and certainly no) was the most appropriate. Response times indicated faster processing of deductive arguments. N2 amplitude distinguished between positive and negative responses in the deductive condition, but not in the probabilistic one, suggesting partial differentiation between the cognitive processes required for the two types of reasoning.

Brain imaging, forward inference, and theories of reasoning

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

Distributed neural representations of logical arguments in school-age children

Children's understanding of linear-order (e.g., Dan is taller than Lisa, Lisa is taller than Jess) and set-inclusion (i.e., All tulips are flowers, All flowers are plants) relationships is critical for the acquisition of deductive reasoning, that is, the ability to reach logically valid conclusions from given premises. Behavioral and neuroimaging studies in adults suggest processing differences between these relations: While arguments that involve linear-orders may be preferentially associated with spatial processing, arguments that involve set-inclusions may be preferentially associated with verbal processing. In this study, we used functional magnetic resonance imaging to investigate whether these processing differences appear during the period of elementary school in development. Consistent with previous studies in adults, we found that arguments that involve linear-order and set-inclusion relationships preferentially involve spatial and verbal brain mechanisms (respectively) in school-age children (9-14 year olds). Because this neural sensitivity was not related to age, it likely emerges before the period of elementary education. However, the period of elementary education might play an important role in shaping the neural processing of logical reasoning, as indicated by developmental changes in frontal and parietal regions that were dependent on the type of relation.

Neural interaction between logical reasoning and pragmatic processing in narrative discourse

Logical connectives (e.g., or, if, and not) are central to everyday conversation, and the inferences they generate are made with little effort in pragmatically sound situations. In contrast, the neural substrates of logical inference-making have been studied exclusively in abstract tasks where pragmatic concerns are minimal. Here, we used fMRI in an innovative design that employed narratives to investigate the interaction between logical reasoning and pragmatic processing in natural discourse. Each narrative contained three premises followed by a statement. In Fully-deductive stories, the statement confirmed a conclusion that followed from two steps of disjunction-elimination (e.g., Xavier considers Thursday, Friday, or Saturday for inviting his girlfriend out; he removes Thursday before he rejects Saturday and declares "I will invite her out for Friday"). In Implicated-premise stories, an otherwise identical narrative included three premises that twice removed a single option from consideration (i.e., Xavier rejects Thursday for two different reasons). The conclusion therefore necessarily prompts an implication (i.e., Xavier must have removed Saturday from consideration as well). We report two main findings. First, conclusions of Implicated-premise stories are associated with more activity than conclusions of Fully-deductive stories in a bilateral frontoparietal system, suggesting that these regions play a role in inferring an implicated premise. Second, brain connectivity between these regions increases with pragmatic abilities when reading conclusions in Implicated-premise stories. These findings suggest that pragmatic processing interacts with logical inference-making when understanding arguments in narrative discourse.

Reasoning from transitive premises: an EEG study

Neuroimaging studies have contributed to a major advance in understanding the neural and cognitive mechanisms underpinning deductive reasoning. However, the dynamics of cognitive events associated with inference making have been largely neglected. Using electroencephalography, the present study aims at describing the rapid sequence of processes involved in performing transitive inference (A B; B C therefore "A C"; with AB meaning "A is to the left of B"). The results indicate that when the second premise can be integrated into the first one (e.g. A B; B C) its processing elicits a P3b component. In contrast, when the second premise cannot be integrated into the first premise (e.g. A B; D C), a P600-like components is elicited. These ERP components are discussed with respect to cognitive expectations.

What MEG can reveal about inference making: the case of if...then sentences

Characterizing the neural substrate of reasoning has been investigated with regularity over the last 10 years or so while relying on measures that come primarily from positron emission tomography and functional magnetic resonance imaging. To some extent, these techniques—as well as those from electroencephalography—have shown that time course is equally worthwhile for revealing the way reasoning processes work in the brain. In this work, we employ magnetoencephalography while investigating Modus Ponens (If P then Q; P//Therefore, Q) in order to simultaneously derive time course and the source of this fundamental logical inference. The present results show that conditional reasoning involves several successive cognitive processes, each of which engages a distinct cerebral network over the course of inference making, and as soon as a conditional sentence is processed.

Frequency-dependent enhancement of fluid intelligence induced by transcranial oscillatory potentials

Everyday problem solving requires the ability to go beyond experience by efficiently encoding and manipulating new information, i.e., fluid intelligence (Gf) [1]. Performance in tasks involving Gf, such as logical and abstract reasoning, has been shown to rely on distributed neural networks, with a crucial role played by prefrontal regions [2]. Synchronization of neuronal activity in the gamma band is a ubiquitous phenomenon within the brain; however, no evidence of its causal involvement in cognition exists to date [3]. Here, we show an enhancement of Gf ability in a cognitive task induced by exogenous rhythmic stimulation within the gamma band. Imperceptible alternating current [4] delivered through the scalp over the left middle frontal gyrus resulted in a frequency-specific shortening of the time required to find the correct solution in a visuospatial abstract reasoning task classically employed to measure Gf abilities (i.e., Raven's matrices) [5]. Crucially, gamma-band stimulation (γ-tACS) selectively enhanced performance only on more complex trials involving conditional/logical reasoning. The present finding supports a direct involvement of gamma oscillatory activity in the mechanisms underlying higher-order human cognition.

Processing counterfactual and hypothetical conditionals: an fMRI investigation

Counterfactual thinking is ubiquitous in everyday life and an important aspect of cognition and emotion. Although counterfactual thought has been argued to differ from processing factual or hypothetical information, imaging data which elucidate these differences on a neural level are still scarce. We investigated the neural correlates of processing counterfactual sentences under visual and aural presentation. We compared conditionals in subjunctive mood which explicitly contradicted previously presented facts (i.e. counterfactuals) to conditionals framed in indicative mood which did not contradict factual world knowledge and thus conveyed a hypothetical supposition. Our results show activation in right occipital cortex (cuneus) and right basal ganglia (caudate nucleus) during counterfactual sentence processing. Importantly the occipital activation is not only present under visual presentation but also with purely auditory stimulus presentation, precluding a visual processing artifact. Thus our results can be interpreted as reflecting the fact that counterfactual conditionals pragmatically imply the relevance of keeping in mind both factual and supposed information whereas the hypothetical conditionals imply that real world information is irrelevant for processing the conditional and can be omitted. The need to sustain representations of factual and suppositional events during counterfactual sentence processing requires increased mental imagery and integration efforts. Our findings are compatible with predictions based on mental model theory.

Transitive inference reasoning is impaired by focal lesions in parietal cortex rather than rostrolateral prefrontal cortex

Transitive inference reasoning involves the examination and comparison of a given number of relational pairs in order to understand overall group hierarchy (e.g., A>B, B>C, C>D; therefore is A>D?). A number of imaging studies have demonstrated the role of the parietal cortex for resolving transitive inferences. Some studies also identify the rostrolateral prefrontal cortex as being critical for "relational integration" processes supporting transitive reasoning. To clarify this issue, we carried out a transitive inference study involving neurological patients with focal lesions to the rostrolateral prefrontal (n=5) or parietal cortices (n=7), as well as normal controls (n=6). The patients and controls were statistically matched on age, education, pre-injury IQ, general memory, working memory, and performance/full IQ, though the rostrolateral patients did score significantly higher than the normal controls on verbal IQ. Results indicate that patients with focal lesions to the parietal cortex were impaired in the task relative to both the patients with focal lesions to rostrolateral prefrontal cortex and the control group, and there was no difference in task performance between the rostrolateral prefrontal and the control groups. This result continued to hold after controlling for verbal IQ as a covariate. These findings point to a critical role for the parietal cortex, rather than the rostrolateral prefrontal, in transitive inference. Since the groups performed similarly on a working memory task, working memory cannot fully account for the result, suggesting a specific role of parietal cortex in transitive inference.

Neural bases of falsification in conditional proposition testing: evidence from an fMRI study

The ability of testing the validity of a conditional statement is important in our everyday life. However, the brain mechanisms underlying this process, especially falsification process which is important in daily life, but especially crucial to scientific reasoning and research is not as yet completely clear. Therefore, in the present study, we used event-related functional magnetic resonance imaging (fMRI) to examine the neural bases of the falsification process in testing the validity of a conditional statement as used in Wason's (1966) selection task. Our fMRI results showed that: (1) compared with the baseline condition, both Falsification (by using Modus Ponens, and Modus Tollens) and Non-Falsification conditions (affirming the consequent, and denying the antecedent) activated the left frontal areas (BA44/45, or BA6), and basal ganglia, the areas previously found in the rule-guided conditional reasoning operations; the parietal area (BA40, BA7) for recruiting cognitive resources to represent and maintain the different evidential information in working memory. (2) The left middle frontal gyrus (BA9) and cerebellum were shown to be activated in the contrast of Falsification condition versus Non-Falsification condition and in the contrast of MT versus Non-Falsification condition. These results indicated that the left middle frontal gyrus (BA9) might be the key brain region involved in the falsification process of conditional statement for which abstracting and integrating logical relationships, and inhibiting the distraction of the irrelevant information were the essential processes. Moreover, the cerebellum was found to be responsible for constructing an internal working model. In addition, our brain imaging results might support the dual-process theory of reasoning.

Fractionating the neural substrates of transitive reasoning: task-dependent contributions of spatial and verbal representations

It has long been suggested that transitive reasoning relies on spatial representations in the posterior parietal cortex (PPC). Previous neuroimaging studies, however, have always focused on linear arguments, such as "John is taller than Tom, Tom is taller than Chris, therefore John is taller than Chris." Using functional magnetic resonance imaging (fMRI), we demonstrate here that verbal representations contribute to transitive reasoning when it involves set-inclusion relations (e.g., "All Tulips are Flowers, All Flowers are Plants, therefore All Tulips are Plants"). In the present study, such arguments were found to engage verbal processing regions of the left inferior frontal gyrus (IFG) and left PPC that were identified in an independent localizer task. Specifically, activity in these verbal regions increased as the number of relations increased in set-inclusion arguments. Importantly, this effect was specific to set-inclusion arguments because left IFG and left PPC were not differentially engaged when the number of relations increased in linear arguments. Instead, such an increase was linked to decreased activity in a spatial processing region of the right PPC that was identified in an independent localizer task. Therefore, both verbal and spatial representations can underlie transitive reasoning, but their engagement depends upon the structure of the argument.

Deduction without awareness

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 P(2). 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.

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.

Evaluating the roles of the inferior frontal gyrus and superior parietal lobule in deductive reasoning: an rTMS study

This study used off-line repetitive transcranial magnetic stimulation (rTMS) to examine the roles of the superior parietal lobule (SPL) and inferior frontal gyrus (IFG) in a deductive reasoning task. Subjects performed a categorical syllogistic reasoning task involving congruent, incongruent, and abstract trials. Twenty four subjects received magnetic stimulation to the SPL region prior to the task. In the other 24 subjects, TMS was administered to the IFG region before the task. Stimulation lasted for 10min, with an inter-pulse frequency of 1Hz. We found that bilateral SPL (Brodmann area (BA) 7) stimulation disrupted performance on abstract and incongruent reasoning. Left IFG (BA 45) stimulation impaired congruent reasoning performance while paradoxically facilitating incongruent reasoning performance. This resulted in the elimination of the belief-bias. In contrast, right IFG stimulation only impaired incongruent reasoning performance, thus enhancing the belief-bias effect. These findings are largely consistent with the dual-process theory of reasoning, which proposes the existence of two different human reasoning systems: a belief-based heuristic system; and a logic-based analytic system. The present findings suggest that the left language-related IFG (BA 45) may correspond to the heuristic system, while bilateral SPL may underlie the analytic system. The right IFG may play a role in blocking the belief-based heuristic system for solving incongruent reasoning trials. This study could offer an insight about functional roles of distributed brain systems in human deductive reasoning by utilizing the rTMS approach.

Logic, language and the brain

What is the role of language in human cognition? Within the domain of deductive reasoning, the issue has been the focus of numerous investigations without the emergence of a consensus view. Here we consider some of the reasons why neuroimaging studies of deductive reasoning have generated mixed results. We then review recent evidence suggesting that the role of language in deductive reasoning is confined to an initial stage in which verbally presented information is encoded as non-verbal representations. These representations are then manipulated by mental operations that are not based on the neural mechanisms of natural language. This article is part of a Special Issue entitled "The Cognitive Neuroscience".

The brain network for deductive reasoning: a quantitative meta-analysis of 28 neuroimaging studies

Over the course of the past decade, contradictory claims have been made regarding the neural bases of deductive reasoning. Researchers have been puzzled by apparent inconsistencies in the literature. Some have even questioned the effectiveness of the methodology used to study the neural bases of deductive reasoning. However, the idea that neuroimaging findings are inconsistent is not based on any quantitative evidence. Here, we report the results of a quantitative meta-analysis of 28 neuroimaging studies of deductive reasoning published between 1997 and 2010, combining 382 participants. Consistent areas of activations across studies were identified using the multilevel kernel density analysis method. We found that results from neuroimaging studies are more consistent than what has been previously assumed. Overall, studies consistently report activations in specific regions of a left fronto-parietal system, as well as in the left BG. This brain system can be decomposed into three subsystems that are specific to particular types of deductive arguments: relational, categorical, and propositional. These dissociations explain inconstancies in the literature. However, they are incompatible with the notion that deductive reasoning is supported by a single cognitive system relying either on visuospatial or rule-based mechanisms. Our findings provide critical insight into the cognitive organization of deductive reasoning and need to be accounted for by cognitive theories.