The role of the DLPFC in inductive reasoning of MCI patients and normal agings: An fMRI study

Improving iconic memory through contrast detection training with HOA-corrected vision

Iconic memory and short-term memory are not only crucial for perception and cognition, but also of great importance to mental health. Here, we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning. Normal adults were trained in a contrast detection task for ten days, with their higher-order aberrations (HOA) corrected in real-time. We found that the training improved not only their contrast sensitivity function (CSF), but also their iconic memory and baseline information maintenance for short-term memory, and the relationship between memory and CSF improvements could be well-predicted by an observer model. These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition. They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.

Repetitive Transcranial Magnetic Stimulation (rTMS) in Mild Cognitive Impairment: Effects on Cognitive Functions-A Systematic Review

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique also used as a non-pharmacological intervention against cognitive impairment. The purpose of the present review was to summarize what is currently known about the effectiveness of rTMS intervention on different cognitive domains in patients with mild cognitive impairment (MCI) and to address potential neuromodulation approaches in combination with electroencephalography (EEG) and neuroimaging, especially functional magnetic resonance imaging (fMRI). In this systematic review, we consulted three main databases (PubMed, Science Direct, and Scopus), and Google Scholar was selected for the gray literature search. The PRISMA flowchart drove the studies' inclusion. The selection process ensured that only high-quality studies were included; after removing duplicate papers, explicit ratings were given based on the quality classification as high (A), moderate (B), or low (C), considering factors such as risks of bias, inaccuracies, inconsistencies, lack of direction, and publication bias. Seven full-text articles fulfilled the stated inclusion, reporting five double-blind, randomized, sham-controlled studies, a case study, and a randomized crossover trial. The results of the reviewed studies suggested that rTMS in MCI patients is safe and effective for enhancing cognitive functions, thus making it a potential therapeutic approach for MCI patients. Changes in functional connectivity within the default mode network (DMN) after targeted rTMS could represent a valuable indicator of treatment response. Finally, high-frequency rTMS over the dorsolateral prefrontal cortex (DLPFC) has been shown to significantly enhance cognitive functions, such as executive performance, together with the increase of functional connectivity within frontoparietal networks. The main limitations were the number of included studies and the exclusion of studies using intermittent theta-burst stimulation, used in studies on Alzheimer's disease. Therefore, neuroimaging techniques in combination with rTMS have been shown to be useful for future network-based, fMRI-guided therapeutic approaches.

BNLoop-GAN: a multi-loop generative adversarial model on brain network learning to classify Alzheimer's disease

Recent advancements in AI, big data analytics, and magnetic resonance imaging (MRI) have revolutionized the study of brain diseases such as Alzheimer's Disease (AD). However, most AI models used for neuroimaging classification tasks have limitations in their learning strategies, that is batch training without the incremental learning capability. To address such limitations, the systematic Brain Informatics methodology is reconsidered to realize evidence combination and fusion computing with multi-modal neuroimaging data through continuous learning. Specifically, we introduce the BNLoop-GAN (Loop-based Generative Adversarial Network for Brain Network) model, utilizing multiple techniques such as conditional generation, patch-based discrimination, and Wasserstein gradient penalty to learn the implicit distribution of brain networks. Moreover, a multiple-loop-learning algorithm is developed to combine evidence with better sample contribution ranking during training processes. The effectiveness of our approach is demonstrated through a case study on the classification of individuals with AD and healthy control groups using various experimental design strategies and multi-modal brain networks. The BNLoop-GAN model with multi-modal brain networks and multiple-loop-learning can improve classification performance.

Acupuncture Treatment Modulate Regional Homogeneity of Dorsal Lateral Prefrontal Cortex in Patients with Amnesic Mild Cognitive Impairment

Background: Although acupuncture is widely used to improve cognitive and memory in the amnesic mild cognitive impairment (aMCI) patients with impressive effectiveness, its neural mechanism remains largely unclear. Objective: We aimed to explore functional magnetic resonance imaging (fMRI) mechanism of acupuncture for aMCI. Methods: A randomized, controlled, single-blind research was performed. A total of 46 aMCI patients were randomly assigned into verum and sham acupuncture group, who received a total of 24 times treatments (3 times/week, 8 weeks). Clinical evaluation and fMRI scanning were performed at baseline and after treatment for all aMCI patients. The interaction effects and inter-group effects of regional homogeneity (ReHo) were performed using mixed effect models, and the correlations between clinical improvement and neuroimaging changes before and after verum acupuncture treatment were analyzed using Pearson correlations. Results: As a result, interaction effects showed increased ReHo value in left dorsal lateral prefrontal cortex (DLPFC), increased functional connectivity between left DLPFC and left precuneus, and decreased functional connectivity between left DLPFC and left inferior temporal gyrus after verum acupuncture but inversely after sham acupuncture in the aMCI. Condition effects showed increased ReHo in right lingual gyrus, and bilateral post-central gyrus after verum and sham acupuncture in the aMCI. In addition, the changed Montreal Cognitive Assessment scores in verum acupuncture group were significantly correlated with changed ReHo values in left DLPFC. Conclusion: Together, our findings further confirmed that acupuncture could be used as a promising complementary therapy for aMCI by modulating function of left DLPFC to improve cognitive symptoms.

Transcranial Direct Current Stimulation Enhances Cognitive Function in Patients with Mild Cognitive Impairment and Early/Mid Alzheimer’s Disease: A Systematic Review and Meta-Analysis

Transcranial direct current stimulation (tDCS) i a non-invasive brain stimulation which is considered to have the potential to improve cognitive impairment in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). However, previous studies have been controversial on the therapeutic effect of tDCS. This meta-analysis aimed to evaluate the effects of tDCS on cognitive impairment in patients with MCI and mild-to-moderate AD. Five databases, namely PubMed, EMBASE, MEDLINE, Web of Science and The Cochrane Library, were searched with relative terms to extract the cognitive function changes measured by an objective cognitive scale in the included studies. The meta-analysis results showed that, compared with sham tDCS treatment, the overall cognitive function of patients with AD and MCI was significantly improved (weighted mean difference = 0.99; 95% confidence interval, 0.32 to 1.66; p = 0.004) after tDCS treatment, but the behavioral symptoms, recognition memory function, attention and executive function were not significantly improved. The subgroup analysis showed that the treatment would be more efficacious if the temporal-lobe-related brain areas were stimulated, the number of stimulations was greater than or equal to 10 and the current density was 2.5 mA/cm2. Among them, AD patients benefited more than MCI patients. No cognitive improvement was observed in patients with MCI or AD at different follow-up times after treatment. Our meta-analysis provided important evidence for the cognitive enhancement of tDCS in patients with MCI and mild-to-moderate AD and discussed its underlying mechanisms.

Progressive Prefrontal Cortex Dysfunction in Parkinson's Disease With Probable REM Sleep Behavior Disorder: A 3-Year Longitudinal Study

This study aimed to explore the disrupted prefrontal cortex activity specific to patients with Parkinson's disease (PD) with rapid eye movement sleep behavior disorder (RBD) compared with those without and to further examine the associations between these alterations and neuropsychological measurements. Ninety-six patients with early PD underwent both structural and functional MRI, and also neuropsychological assessments in the Parkinson's Progression Markers Initiative (PPMI) database. Of these, 46 patients who completed 1- and 3-year fMRI follow-up examinations were categorized as PD with probable RBD (PD-pRBD+) and without (PD-pRBD−). The left dorsolateral prefrontal cortex (DLPFC) seed-to-voxel functional connectivity analysis was conducted to evaluate the progressive neural alterations specific to PD-pRBD+ compared with PD-pRBD− over time. Furthermore, relationships between these alterations and neuropsychological performance were examined. Compared with patients with PD-pRBD−, patients with PD-pRBD+ initially exhibited connectivity deficits between the left DLPFC and the medial frontopolar cortex. Moreover, these patients further exhibited disrupted DLPFC connectivity in the lateral frontopolar cortex at the 3-year follow-up evaluation. Correlation analysis revealed that connectivity between the left DLPFC and frontopolar cortex was positively related to executive function in PD-pRBD+ after adjusting for nuisance variables. Progressive prefrontal cortex dysfunction associated with RBD in early PD may provide an effective subtype-specific biomarker of neurodegenerative progression, which may shed light on the neuropathological mechanisms underlying the clinical heterogeneity of this disease.

tACS as a promising therapeutic option for improving cognitive function in mild cognitive impairment: A direct comparison between tACS and tDCS

Neuromodulation has gained attention as a potential non-pharmacological intervention for mild cognitive impairment (MCI). However, no studies have directly compared the effects of transcranial alternating current stimulation (tACS) with transcranial direct current stimulation (tDCS) on MCI patients. We aimed to identify the more promising and efficient therapeutic option between tACS and tDCS for cognitive enhancement in MCI patients. We compared the effects of gamma-tACS with tDCS on cognitive function and electroencephalography (EEG) in MCI patients. In this sham-controlled, double-blinded, repeated-measures study with the order of the stimulation counterbalanced across patients (n = 20), both gamma-tACS (40 H z) and tDCS were administered at the same intensity (2 mA) in the dorsolateral prefrontal cortex for 30 min. Cognitive tests (Stroop and Trail-Making-Test [TMT]) and EEG were performed before and after single-session stimulation. Gamma-tACS improved the Stroop-color in comparison with tDCS (p = .044) and sham (p = .010) and enhanced the TMT-B in comparison with sham (p = .021). However, tDCS was not significantly different from sham in changes of any cognitive test scores. In EEG analysis, gamma-tACS increased beta activity in comparison with sham and tDCS, whereas tDCS decreased delta and theta activity in comparison with sham. Gamma-tACS also increased beta 2 source activity in the anterior cingulate, compared to sham. The cognitive benefits of tACS in MCI patients appeared superior to those of tDCS. tACS facilitated cognitive function by increasing beta activity, while tDCS delayed the progression of MCI symptoms by decreasing slow-frequency activity. Thus, tACS could be used as a new therapeutic option for MCI.

Activation of Glucagon-Like Peptide-1 Receptor Ameliorates Cognitive Decline in Type 2 Diabetes Mellitus Through a Metabolism-Independent Pathway

Background

Patients with hypertension and diabetes mellitus are susceptible to dementia, but regular therapy fails to reduce the risk of dementia. Glucagon‐like peptide‐1 receptor agonists have neuroprotective effects in experimental studies. We aimed to assess the effect of liraglutide, a glucagon‐like peptide‐1 receptor agonist, on cognitive function and whether its effect was associated with metabolic changes in patients with type 2 diabetes mellitus.

Methods and Results

Fifty patients with type 2 diabetes mellitus were recruited in this prospective study. All patients underwent cognitive assessment and brain activation monitoring by functional near‐infrared spectroscopy. At 12 weeks, patients in the glucagon‐like peptide‐1 group acquired better scores in all cognitive tests and showed remarkable improvement in memory and attention (P=0.040) test compared with the control group after multivariable adjustment. Compared with the control group, liraglutide significantly increased activation of the dorsolateral prefrontal cortex and orbitofrontal cortex brain regions (P=0.0038). After liraglutide treatment, cognitive scores were significantly correlated with changes in these activating brain regions (P<0.05), but no correlation was observed between the changes in cognitive function and changes of body mass index, blood pressure, and glycemic levels.

Conclusions

We concluded that liraglutide improves cognitive decline in patients with type 2 diabetes mellitus. This beneficial effect is independent of its hypoglycemic effect and weight loss. The optimal intervention should be targeted to cognitive decline in the early stages of dementia.

Registration

URL: https://www.ClinicalTrials.gov; Unique identifier: NCT03707171.

Serial Reaction Time Task Performance in Older Adults with Neuropsychologically Defined Mild Cognitive Impairment

BACKGROUND

Studies have found that individuals with mild cognitive impairment (MCI) exhibit a range of deficits outside the realm of primary explicit memory, yet the role of response speed and implicit learning in older adults with MCI have not been established.

OBJECTIVE

The current study aims to explore and document response speed and implicit learning in older adults with neuropsychologically defined MCI using a simple serial reaction (SRT) task. In addition, the study aims to explore the feasibility of a novel utilization of the simple cognitive task using machine learning procedures as a proof of concept.

METHOD

Participants were 22 cognitively healthy older adults and 20 older adults with MCI confirmed through comprehensive neuropsychological evaluation. Two-sample t-test, multivariate regression, and mixed-effect models were used to investigate group difference in response speed and implicit learning on the SRT task. We also explored the potential utility of SRT feature analysis through random forest classification.

RESULTS

With demographic variables controlled, the MCI group showed overall slower reaction time and higher error rate compared to the cognitively healthy volunteers. Both groups showed significant simple motor learning and implicit learning. The learning patterns were not statistically different between the two groups. Random forest classification achieved overall accuracy of 80.9%.

CONCLUSIONS

Individuals with MCI demonstrated slower reaction time and higher error rate compared to cognitively healthy volunteers but demonstrated largely preserved motor learning and implicit sequence learning. Preliminary results from random forest classification using features from SRT performance supported further research in this area.

Neural correlates of improved inductive reasoning ability in abacus-trained children: A resting state fMRI study

Abacus-based mental calculation (AMC) training may improve mathematics-related abilities and transfer to other cognitive domains. Thus, it was hypothesized that inductive reasoning abilities can be improved by AMC training given the overlapping cognitive processes and neural correlates between AMC and inductive reasoning. The aim of the current study was to examine the underlying neurobiological mechanisms of this possible adaption by resting-state functional magnetic resonance imaging (rs-fMRI). Sixty-three children were randomly assigned to either the AMC-trained or the nontrained group. The AMC-trained group was required to perform abacus training for 2 hours per week for 5 years whereas the nontrained group was not required to perform any abacus training. Each participant's rs-fMRI data were collected after abacus training, and regional homogeneity (ReHo) analysis was performed to determine the neural activity differences between groups. The participants' posttraining mathematical ability, intelligence quotients, and inductive reasoning ability were recorded and evaluated. The results revealed that AMC-trained children exhibited a significantly higher mathematical ability and inductive reasoning performance and higher ReHo in the rostrolateral prefrontal cortex (RLPFC) compared to the nontrained group. In particular, the increased ReHo in the RLPFC was found to be positively correlated with improved inductive reasoning performance. Our findings suggest that rs-fMRI may reflect the modulation of training in task-related networks.

Involvement of the Right Dorsolateral Prefrontal Cortex in Numerical Rule Induction: A Transcranial Direct Current Stimulation Study

Numerical inductive reasoning has been considered as one of the most important higher cognitive functions of the human brain. Importantly, previous behavioral studies have consistently reported that one critical component of numerical inductive reasoning is checking, which often occurs when a discrepant element is discovered, and reprocessing is needed to determine whether the discrepancy is an error of the original series. However, less is known about the neural mechanism underlying the checking process. Given that the checking effect involves cognitive control processes, such as the incongruent resolution, that are linked to the right dorsolateral prefrontal cortex (DLPFC), this study hypothesizes that the right DLPFC may play a specific role in the checking process. To test the hypothesis, this study utilized the transcranial direct current stimulation (tDCS), a non-invasive brain stimulation method that could modulate cortical excitability, and examined whether and how the stimulation of the right DLPFC via tDCS could modulate the checking effect during a number-series completion problem task. Ninety healthy participants were allocated to one of the anodal, cathodal, and sham groups. Subjects were required to verify whether number sequences formed rule-based series, and checking effect was assessed by the difference in performance between invalid and valid conditions. It was found that significantly longer response times (RTs) were exhibited in invalid condition compared with valid condition in groups of anodal, cathodal, and sham tDCS. Furthermore, the anodal tDCS significantly shortened the checking effect than those of the cathodal and sham groups, whereas no significantly prolonged checking effect was detected in the cathodal group. The current findings indicated that anodal tDCS affected the process of checking, which suggested that the right DLPFC might play a critical role in the checking process of numerical inductive reasoning by inhibiting incongruent response.

A Brain Network Constructed on an L1-Norm Regression Model Is More Sensitive in Detecting Small World Network Changes in Early AD

Most previous imaging studies have used traditional Pearson correlation analysis to construct brain networks. This approach fails to adequately and completely account for the interaction between adjacent brain regions. In this study, we used the L1-norm linear regression model to test the small-world attributes of the brain networks of three groups of patients, namely, those with mild cognitive impairment (MCI), Alzheimer's disease (AD), and healthy controls (HCs); we attempted to identify the method that may detect minor differences in MCI and AD patients. Twenty-four AD patients, 33 MCI patients, and 27 HC elderly subjects were subjected to functional MRI (fMRI). We applied traditional Pearson correlation and the L1-norm to construct the brain networks and then tested the small-world attributes by calculating the following parameters: clustering coefficient (Cp), path length (Lp), global efficiency (Eg), and local efficiency (Eloc). As expected, L1 could detect slight changes, mainly in MCI patients expressing higher Cp and Eloc; however, no statistical differences were found between MCI patients and HCs in terms of Cp, Lp, Eg, and Eloc, using Pearson correlation. Compared with HCs, AD patients expressed a lower Cp, Eloc, and Lp and an increased Eg using both connectivity metrics. The statistical differences between the groups indicated the brain networks constructed by the L1-norm were more sensitive to detect slight small-world network changes in early stages of AD.

Reality Status Judgments of Real and Fantastical Events in Children's Prefrontal Cortex: An fNIRS Study

The present study aimed to examine neural mechanisms underlying the ability to differentiate reality from fantasy. Using functional near-infrared spectroscopy (fNIRS), we measured prefrontal activations in children and adults while they performed a reality judgment task. Participants’ task was to judge the reality status of events in fantastical and realistic videos. Behavioral data revealed that, although there was no accuracy difference, children showed significantly longer reaction times in making the judgments than did adults. The fNIRS data consistently revealed higher prefrontal activations in children than in adults when watching the videos and judging the reality of the events. These results suggest that when making judgments of event reality, children may require more cognitive resources and also mainly rely on their own personal experiences.

New Perspective for Non-invasive Brain Stimulation Site Selection in Mild Cognitive Impairment: Based on Meta- and Functional Connectivity Analyses

Background

Non-invasive brain stimulation (NIBS) has been widely used to treat mild cognitive impairment (MCI). However, there exists no consensus on the best stimulation sites.

Objective

To explore potential stimulation locations for NIBS treatment in patients with MCI, combining meta- and resting state functional connectivity (rsFC) analyses.

Methods

The meta-analysis was conducted to identify brain regions associated with MCI. Regions of interest (ROIs) were extracted based on this meta-analysis. The rsFC analysis was applied to 45 MCI patients to determine brain surface regions that are functionally connected with the above ROIs.

Results

We found that the dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) were the overlapping brain regions between our results and those of previous studies. In addition, we recommend that the temporoparietal junction (including the angular gyrus), which was found in both the meta- and rsFC analysis, should be considered in NIBS treatment of MCI. Furthermore, the bilateral orbital prefrontal gyrus, inferior temporal gyrus, medial superior frontal gyrus, and right inferior occipital gyrus may be potential brain stimulation sites for NIBS treatment of MCI.

Conclusion

Our results provide several potential sites for NIBS, such as the DLFPC and IFG, and may shed light on the locations of NIBS sites in the treatment of patients with MCI.

Transcranial direct current stimulation (tDCS) in elderly with mild cognitive impairment: A pilot study

Transcranial direct current stimulation (tDCS) is a non-invasive, painless and easy-to use-technology. It can be used in depression, schizophrenia and other neurological disorders. There are no studies about longer usage protocols regarding the ideal duration and weekly frequency of tDCS.

OBJECTIVE

to study the use of tDCS twice a week for longer periods to improve memory in elderly with MCI.

METHODS

a randomized double-blind controlled trial of anodal tDCS on cognition of 58 elderly aged over 60 years was conducted. A current of 2.0 mA was applied for 30 minutes for 10 sessions, twice a week. The anode was placed over the left dorsolateral prefrontal cortex (LDLFC). Subjects were evaluated before and after 10 sessions by the following tests: CAMCOG, Mini-Mental State Examination (MMSE), Trail Making, Semantic Verbal Fluency (Animals), Boston naming, Clock Drawing Test, Word list memory (WLMT), Direct and Indirect Digit Order (WAIS-III and WMS-III) and N-back.

RESULTS

After 10 sessions of tDCS, significant group-time interactions were found for the CAMCOG - executive functioning (χ2 = 3.961, p = 0.047), CAMCOG - verbal fluency (χ2 = 3.869, p = 0.049), CAMCOG - Memory recall (χ2 = 9.749, p = 0.004), and WMLT - recall (χ2 = 7.254, p = 0.007). A decline in performance on the CAMCOG - constructional praxis (χ2 = 4.371, p = 0.037) was found in the tDCS group after intervention. No significant differences were observed between the tDCS and Sham groups for any other tasks.

CONCLUSION

tDCS at 2 mA for 30 min twice a week over 5 consecutive weeks proved superior to placebo (Sham) for improving memory recall, verbal fluency and executive functioning in elderly with MCI.

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.

Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer's Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer's Disease Neuroimaging Initiative

Purpose

To detect changes in brain lateralization in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using resting-state functional magnetic resonance imaging (fMRI).

Materials and methods

Data from 61 well-matched right-handed subjects were obtained from the Alzheimer’s Disease Neuroimaging Initiative, including 19 healthy controls (HCs), 25 patients with MCI, and 17 patients with AD. First, we divided 256 pairs of seed regions from each hemisphere covering the entire cerebral gray matter. Then, we used the intrinsic laterality index (iLI) approach to quantify the functional laterality using fMRI. One-way ANOVA was employed to estimate the differences in iLI among the three groups. The sum, number and mean value of the iLI were calculated within the thresholds of 0 < |iLI| < 0.2, 0.2 ≤ |iLI| < 0.4, 0.4 ≤ |iLI| < 0.8, and |iLI| ≥ 0.8, to explore the changes in the lateralization of resting-state brain function in patients with MCI and AD.

Results

One-way ANOVA revealed that the iLIs of the three groups were significantly different. The HCs showed a significant leftward interhemispheric difference within |iLI| ≥ 0.8. Compared with the HCs, the patients with MCI manifested a distinct abnormal rightward interhemispheric asymmetry, mainly within the thresholds of 0.2 ≤ |iLI| < 0.4 and 0.4 ≤ |iLI| < 0.8; in the patients with AD, the normal leftward lateralization that was observed in the HCs disappeared, and an abnormal rightward laterality was expressed within 0.4 ≤ |iLI| < 0.8. By directly comparing the patients with MCI with the patients with AD, an exclusive abnormal rightward laterality was observed in the patients with MCI within the 0.2 ≤ |iLI| < 0.4 threshold, and the normal leftward asymmetry vanished in the patients with AD within the |iLI| ≥ 0.8 threshold.

Conclusion

Global brain lateralization was different among three groups. The abnormal rightward dominance observed in the patients with MCI and AD may indicate that these patients use additional brain resources to compensate for the loss of cognitive function, and the observed disappearance of the leftward laterality in the patients with AD was likely associated with the damage in the left hemisphere. The observed disappearance of the rightward asymmetry in the patients with AD using the 0.2 ≤ |iLI| < 0.4 threshold was likely a sign of decompensation. Our study provides new insights that may improve our understanding of MCI and AD.

Dissociable roles of medial and lateral PFC in rule learning

INTRODUCTION

Although the neural basis of rule learning is of great interest to cognitive neuroscientists, the pattern of transient brain activation during rule discovery remains to be investigated.

METHOD

In this study, we measured event-related functional magnetic resonance imaging (fMRI) during distinct phases of rule learning. Twenty-one healthy human volunteers were presented with a series of cards, each containing a clock-like display of 12 circles numbered sequentially. Participants were instructed that a fictitious animal would move from one circle to another either in a regular pattern (according to a rule hidden in consecutive trials) or randomly. Participants were then asked to judge whether a given step followed a rule.

RESULTS

While the rule-search phase evoked more activation in the posterior lateral prefrontal cortex (LPFC), the rule-following phase caused stronger activation in the anterior medial prefrontal cortex (MPFC). Importantly, the intermediate phase, the rule-discovery phase evoked more activations in MPFC and dorsal anterior cingulate cortex (dACC) than rule search, and more activations in LPFC than rule following.

CONCLUSION

Therefore, we can conclude that the medial and lateral PFC have dissociable contributions in rule learning.

Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model

Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the fronto-parietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network.

Hemispheric lateralization in reasoning

A growing body of evidence suggests that reasoning in humans relies on a number of related processes whose neural loci are largely lateralized to one hemisphere or the other. A recent review of this evidence concluded that the patterns of lateralization observed are organized according to two complementary tendencies. The left hemisphere attempts to reduce uncertainty by drawing inferences or creating explanations, even at the cost of ignoring conflicting evidence or generating implausible explanations. Conversely, the right hemisphere aims to reduce conflict by rejecting or refining explanations that are no longer tenable in the face of new evidence. In healthy adults, the hemispheres work together to achieve a balance between certainty and consistency, and a wealth of neuropsychological research supports the notion that upsetting this balance results in various failures in reasoning, including delusions. However, support for this model from the neuroimaging literature is mixed. Here, we examine the evidence for this framework from multiple research domains, including an activation likelihood estimation analysis of functional magnetic resonance imaging studies of reasoning. Our results suggest a need to either revise this model as it applies to healthy adults or to develop better tools for assessing lateralization in these individuals.

The interaction of process and domain in prefrontal cortex during inductive reasoning

Inductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left-right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain.

Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model

In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning.

Different strategies in solving series completion inductive reasoning problems: an fMRI and computational study

Neural correlate of human inductive reasoning process is still unclear. Number series and letter series completion are two typical inductive reasoning tasks, and with a common core component of rule induction. Previous studies have demonstrated that different strategies are adopted in number series and letter series completion tasks; even the underlying rules are identical. In the present study, we examined cortical activation as a function of two different reasoning strategies for solving series completion tasks. The retrieval strategy, used in number series completion tasks, involves direct retrieving of arithmetic knowledge to get the relations between items. The procedural strategy, used in letter series completion tasks, requires counting a certain number of times to detect the relations linking two items. The two strategies require essentially the equivalent cognitive processes, but have different working memory demands (the procedural strategy incurs greater demands). The procedural strategy produced significant greater activity in areas involved in memory retrieval (dorsolateral prefrontal cortex, DLPFC) and mental representation/maintenance (posterior parietal cortex, PPC). An ACT-R model of the tasks successfully predicted behavioral performance and BOLD responses. The present findings support a general-purpose dual-process theory of inductive reasoning regarding the cognitive architecture.

Altered causal connectivity of resting state brain networks in amnesic MCI

Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI) have concentrated on functional connectivity (FC) based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN), hippocampal cortical memory network (HCMN), dorsal attention network (DAN) and fronto-parietal control network (FPCN). Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE), and California verbal learning test (CVLT) scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

Age-related functional reorganization, structural changes, and preserved cognition

Although healthy aging is associated with general cognitive decline, there is considerable variability in the extent to which cognitive functions decline or are preserved. Preserved cognitive function in the context of age-related neuroanatomical and functional changes, has been attributed to compensatory mechanisms. However, the existing sparse evidence is largely focused on functions associated with the frontal cortex, leaving open the question of how wider age-related brain changes relate to compensation. We evaluated relationships between age-related neural and functional changes in the context of preserved cognitive function by combining measures of structure, function, and cognitive performance during spoken language comprehension using a paradigm that does not involve an explicit task. We used a graph theoretical approach to derive cognitive activation-related functional magnetic resonance imaging networks. Correlating network properties with age, neuroanatomical variations, and behavioral data, we found that decreased gray matter integrity was associated with decreased connectivity within key language regions but increased overall functional connectivity. However, this network reorganization was less efficient, suggesting that engagement of a more distributed network in aging might be triggered by reduced connectivity within specialized networks.

Functional disconnection and compensation in mild cognitive impairment: evidence from DLPFC connectivity using resting-state fMRI

The known regional abnormality of the dorsolateral prefrontal cortex (DLPFC) and its role in various neural circuits in mild cognitive impairment (MCI) has given prominence to its importance in studies on the disconnection associated with MCI. The purpose of the current study was to examine the DLPFC functional connectivity patterns during rest in MCI patients and the impact of regional grey matter (GM) atrophy on the functional results. Structural and functional MRI data were collected from 14 MCI patients and 14 age, gender-matched healthy controls. We found that both the bilateral DLPFC showed reduced functional connectivity with the inferior parietal lobule (IPL), superior/medial frontal gyrus and sub-cortical regions (e.g., thalamus, putamen) in MCI patients when compared with healthy controls. Moreover, the DLPFC connectivity with the IPL and thalamus significantly correlated with the cognitive performance of patients as measured by mini-mental state examination (MMSE), clock drawing test (CDT), and California verbal learning test (CVLT) scores. When taking GM atrophy as covariates, these results were approximately consistent with those without correction, although there may be a decrease in the statistical power. These results suggest that the DLPFC disconnections may be the substrates of cognitive impairments in MCI patients. In addition, we also found enhanced functional connectivity between the left DLPFC and the right prefrontal cortex in MCI patients. This is consistent with previous findings of MCI-related increased activation during cognitive tasks, and may represent a compensatory mechanism in MCI patients. Together, the present study demonstrated the coexistence of functional disconnection and compensation in MCI patients using DLPFC functional connectivity analysis, and thus might provide insights into biological mechanism of the disease.

A dissociation between social mentalizing and general reasoning

It has recently been suggested that brain areas crucial for mentalizing, including the medial prefrontal cortex (mPFC), are not activated exclusively during mentalizing about the intentions, beliefs, morals or traits of the self or others, but also more generally during cognitive reasoning including relational processing about objects. Contrary to this notion, a meta-analysis of cognitive reasoning tasks demonstrates that the core mentalizing areas are not systematically recruited during reasoning, but mostly when these tasks describe some human agency or general evaluative and enduring traits about humans, and much less so when these social evaluations are absent. There is a gradient showing less mPFC activation as less mentalizing content is contained in the stimulus material used in reasoning tasks. Hence, it is more likely that cognitive reasoning activates the mPFC because inferences about social agency and mind are involved.