Hemispheric asymmetry in the prefrontal cortex for complex cognition

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults

Impulsive traits (i.e., the tendency to act without forethought regardless of negative outcomes) are frequently found in healthy populations. When exposed to risk factors, individuals may develop debilitating disorders of impulse control (addiction, substance abuse, gambling) characterized by behavioral and cognitive deficits, eventually leading to huge socioeconomic costs. With the far-reaching aim of preventing the onset of impulsive disorders, it is relevant to investigate the topological organization of functional brain networks associated with impulsivity in sub-clinical populations. Taking advantage of the open-source LEMON dataset, we investigated the topological features of resting-state functional brain networks associated with impulsivity in younger (n = 146, age: 20-35) and older (n = 61, age: 59-77) individuals, using a graph-theoretical approach. Specifically, we computed indices of segregation and integration at the level of specific circuits and nodes known to be involved in impulsivity (frontal, limbic, and striatal networks). In younger individuals, results revealed that impulsivity was associated with a more widespread, less clustered and less efficient functional organization, at all levels of analyses and in all selected networks. Conversely, impulsivity in older individuals was associated with reduced integration and increased segregation of striatal regions. Speculatively, such alterations of functional brain networks might underlie behavioral and cognitive abnormalities associated with impulsivity, a working hypothesis worth being tested in future research. Lastly, differences between younger and older individuals might reflect the implementation of age-specific adaptive strategies, possibly accounting for observed differences in behavioral manifestations. Potential interpretations, limitations and implications are discussed.

Lateralisation of nasal cycle is not reflected in the olfactory bulb volumes and cerebral activations

Nasal cycle (NC) is a rhythmic change of lateralised nasal airflow mediated by the autonomous nervous system. Previous studies reported the dependence of NC dominance or more patent side on handedness and hemispheric cerebral activity. We aimed to investigate firstly the possible lateralised effect of NC on olfactory bulb volume and secondly the association of NC with the lateralised cerebral dominance in terms of olfactory processing. Thirty-five subjects (22 women and 13 men, mean age 26 ± 3 years) participated in the study. NC was ascertained using a portable rhino-flowmeter. Structural and functional brain measurements were assessed using a 3T MR scanner. Vanillin odorant was presented during functional scans using a computer-controlled olfactometer. NC was found to be independent of the olfactory bulb volumes. Also, cerebral activations were found independent of the NC during odorant perception. NC potency is not associated with lateralised structural or functional differences in the cerebral olfactory system.

Altered asymmetry of functional connectome gradients in major depressive disorder

Introduction

Major depressive disorder (MDD) is a debilitating disease involving sensory and higher-order cognitive dysfunction. Previous work has shown altered asymmetry in MDD, including abnormal lateralized activation and disrupted hemispheric connectivity. However, it remains unclear whether and how MDD affects functional asymmetries in the context of intrinsic hierarchical organization.

Methods

Here, we evaluate intra- and inter-hemispheric asymmetries of the first three functional gradients, characterizing unimodal-transmodal, visual-somatosensory, and somatomotor/default mode-multiple demand hierarchies, to study MDD-related alterations in overarching system-level architecture.

Results

We find that, relative to the healthy controls, MDD patients exhibit alterations in both primary sensory regions (e.g., visual areas) and transmodal association regions (e.g., default mode areas). We further find these abnormalities are woven in heterogeneous alterations along multiple functional gradients, associated with cognitive terms involving mind, memory, and visual processing. Moreover, through an elastic net model, we observe that both intra- and inter-asymmetric features are predictive of depressive traits measured by BDI-II scores.

Discussion

Altogether, these findings highlight a broad and mixed effect of MDD on functional gradient asymmetry, contributing to a richer understanding of the neurobiological underpinnings in MDD.

Cerebral dominance representation of directed connectivity within and between left-right hemispheres and frontal-posterior lobes in mild cognitive impairment

Electroencephalography can assess connectivity between brain hemispheres, potentially influencing cognitive functions. Much of the existing electroencephalography research primarily focuses on undirected connectivity, leaving uncertainties about directed connectivity alterations between left-right brain hemispheres or frontal-posterior lobes in mild cognitive impairment. We analyzed resting-state electroencephalography data from 34 mild cognitive impairment individuals and 23 normal controls using directed transfer function and graph theory for directed network analysis. Concerning the dominance within left-right hemispheres or frontal-posterior lobes, the mild cognitive impairment group exhibited decreased connectivity within the frontal compared with posterior brain regions in the delta and theta bands. Regarding the dominance between the brain hemispheres or lobes, the mild cognitive impairment group showed reduced connectivity from the posterior to the frontal regions versus the reverse direction in the same bands. Among all participants, the intra-lobe frontal-posterior dominance correlated positively with executive function in the delta and alpha bands. Inter-lobe dominance between frontal and posterior regions also positively correlated with executive function, attention, and language in the delta band. Additionally, interhemispheric dominance between the left and right hemispheres positively correlated with attention in delta and theta bands. These findings suggest altered cerebral dominance in mild cognitive impairment, potentially serving as electrophysiological markers for neurocognitive disorders.

Measuring cognitively demanding activities in pediatric out-of-hospital cardiac arrest

BACKGROUND

This methodological intersection article demonstrates a method to measure cognitive load in clinical simulations. Researchers have hypothesized that high levels of cognitive load reduce performance and increase errors. This phenomenon has been studied primarily by experimental designs that measure responses to predetermined stimuli and self-reports that reduce the experience to a summative value. Our goal was to develop a method to identify clinical activities with high cognitive burden using physiologic measures.

METHODS

Teams of emergency medical responders were recruited from local fire departments to participate in a scenario with a shockable pediatric out-of-hospital cardiac arrest (POHCA) patient. The scenario was standardized with the patient being resuscitated after receiving high-quality CPR and 3 defibrillations. Each team had a person in charge (PIC) who wore a functional near-infrared spectroscopy (fNIRS) device that recorded changes in oxygenated and deoxygenated hemoglobin concentration in their prefrontal cortex (PFC), which was interpreted as cognitive activity. We developed a data processing pipeline to remove nonneural noise (e.g., motion artifacts, heart rate, respiration, and blood pressure) and detect statistically significant changes in cognitive activity. Two researchers independently watched videos and coded clinical tasks corresponding to detected events. Disagreements were resolved through consensus, and results were validated by clinicians.

RESULTS

We conducted 18 simulations with 122 participants. Participants arrived in teams of 4 to 7 members, including one PIC. We recorded the PIC's fNIRS signals and identified 173 events associated with increased cognitive activity. [Defibrillation] (N = 34); [medication] dosing (N = 33); and [rhythm checks] (N = 28) coincided most frequently with detected elevations in cognitive activity. [Defibrillations] had affinity with the right PFC, while [medication] dosing and [rhythm checks] had affinity with the left PFC.

CONCLUSIONS

FNIRS is a promising tool for physiologically measuring cognitive load. We describe a novel approach to scan the signal for statistically significant events with no a priori assumptions of when they occur. The events corresponded to key resuscitation tasks and appeared to be specific to the type of task based on activated regions in the PFC. Identifying and understanding the clinical tasks that require high cognitive load can suggest targets for interventions to decrease cognitive load and errors in care.

Programming ability prediction: Applying an attention-based convolutional neural network to functional near-infrared spectroscopy analyses of working memory

Although theoretical studies have suggested that working-memory capacity is crucial for academic achievement, few empirical studies have directly investigated the relationship between working-memory capacity and programming ability, and no direct neural evidence has been reported to support this relationship. The present study aimed to fill this gap in the literature. Using a between-subject design, 17 programming novices and 18 advanced students performed an n-back working-memory task. During the experiment, their prefrontal hemodynamic responses were measured using a 48-channel functional near-infrared spectroscopy (fNIRS) device. The results indicated that the advanced students had a higher working-memory capacity than the novice students, validating the relationship between programming ability and working memory. The analysis results also showed that the hemodynamic responses in the prefrontal cortex can be used to discriminate between novices and advanced students. Additionally, we utilized an attention-based convolutional neural network to analyze the spatial domains of the fNIRS signals and demonstrated that the left prefrontal cortex was more important than other brain regions for programming ability prediction. This result was consistent with the results of statistical analysis, which in turn improved the interpretability of neural networks.

Alteration of a brain network with stable and strong functional connections in subjects with schizophrenia

It is widely accepted that there are some common network patterns in the human brain. However, the existence of stable and strong functional connections in the human brain and whether they change in schizophrenia is still a question. By setting 1% connections with the smallest coefficient of variation, we found a widespread brain functional network (frame network) in healthy people(n = 380, two datasets from public databases). We then explored the alterations in a medicated group (60 subjects with schizophrenia vs 71 matched controls) and a drug-naive first-episode group (68 subjects with schizophrenia vs 45 matched controls). A linear support vector classifier (SVC) was constructed to distinguish patients and controls using the medicated patients' frame network. We found most frame connections of healthy people had high strength, which were symmetrical and connected the left and right hemispheres. Conversely, significant differences in frame connections were observed in both patient groups, which were positively correlated with negative symptoms (mainly language dysfunction). Additionally, patients' frame network were more left-lateralized, concentrating on the left frontal lobe, and was quite accurate at distinguishing medicated patients from controls (classifier accuracy was 78.63%, sensitivity was 86.67%, specificity was 76.06%, and the area under the curve (AUC) was 0.83). Furthermore, the results were repeated in the drug-naive set (accuracy was 84.96%, sensitivity was 85.29%, specificity was 88.89%, and AUC was 0.93). These findings indicate that the abnormal pattern of frame network in subjects with schizophrenia might provide new insights into the dysconnectivity in schizophrenia.

Presence or absence of a prefrontal sulcus is linked to reasoning performance during child development

The relationship between structural variability in late-developing association cortices like the lateral prefrontal cortex (LPFC) and the development of higher-order cognitive skills is not well understood. Recent findings show that the morphology of LPFC sulci predicts reasoning performance; this work led to the observation of substantial individual variability in the morphology of one of these sulci, the para-intermediate frontal sulcus (pimfs). Here, we sought to characterize this variability and assess its behavioral significance. To this end, we identified the pimfs in a developmental cohort of 72 participants, ages 6-18. Subsequent analyses revealed that the presence or absence of the ventral component of the pimfs was associated with reasoning, even when controlling for age. This finding shows that the cortex lining the banks of sulci can support the development of complex cognitive abilities and highlights the importance of considering individual differences in local morphology when exploring the neurodevelopmental basis of cognition.

Topographically organized representation of space and context in the medial prefrontal cortex

The neocortex is composed of areas with specialized functions (e.g., sensory versus associational). Despite this functional diversity, emerging evidence suggests that the encoding of space might be a universal feature of cortical circuits. Here, we identified a gradient of spatial tuning depth along the dorsoventral axis. A complex topography of spatial tuning properties might support a division of labor among medial prefrontal cortical subnetworks to support local circuit computation relevant for the execution of context-dependent behavioral outcomes.

Spatial tuning of neocortical pyramidal cells has been observed in diverse cortical regions and is thought to rely primarily on input from the hippocampal formation. Despite the well-studied hippocampal place code, many properties of the neocortical spatial tuning system are still insufficiently understood. In particular, it has remained unclear how the topography of direct anatomical connections from hippocampus to neocortex affects spatial tuning depth, and whether the dynamics of spatial coding in the hippocampal output region CA1, such as remapping in novel environments, is transmitted to the neocortex. Using mice navigating through virtual environments, we addressed these questions in the mouse medial prefrontal cortex, which receives direct input from the hippocampus. We found a rapidly emerging prefrontal representation of space in the absence of task rules, which discriminates familiar from novel environments and is reinstated upon reexposure to the same familiar environment. Topographical analysis revealed a dorsoventral gradient in the representation of the own position, which runs opposite to the innervation density of hippocampal inputs. Jointly, these results reveal a dynamically emerging and topographically organized prefrontal place code during spontaneous locomotion.

Developmental Brain Asymmetry. The Good and the Bad Sides

Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.

Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization

Autism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing vs. empathizing cognitive styles, with resemblances to male vs. female average sex differences. Left-right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness, and subcortical volume measures in 32,256 participants from the UK Biobank. Polygenic risks for the two disorders were positively correlated (r = 0.08, p = 7.13 × 10-50) and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each polygenic risk score was associated with multivariate brain asymmetry after adjusting for sex, ASD r = 0.03, p = 2.17 × 10-9, and schizophrenia r = 0.04, p = 2.61 × 10-11, but the multivariate patterns were mostly distinct for the two polygenic risks and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both polygenic risks were associated with asymmetries of regions important for language and executive functions, consistent with behavioral associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risks for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies.

The Quest for Hemispheric Asymmetries Supporting and Predicting Executive Functioning

This narrative review addresses the neural bases of two executive functions: criterion setting, that is, the capacity to flexibly set up and select task rules and associations between stimuli, responses, and nonresponses, and monitoring, that is, the process of continuously evaluating whether task rules are being applied optimally. There is a documented tendency for criterion setting and monitoring to differentially recruit left and right lateral prefrontal regions and connected networks, respectively, above and beyond the specific task context. This model, known as the ROtman-Baycrest Battery to Investigate Attention (ROBBIA) model, initially sprung from extensive neuropsychological work led by Don Stuss. In subsequent years, multimodal lines of empirical investigation on both healthy individuals and patients with brain damage, coming from functional neuroimaging, EEG, neurostimulation, individual difference approaches, and, again, neuropsychology, so to "complete the circle," corroborated the functional mapping across the two hemispheres as predicted by the model. More recent electrophysiological evidence has further shown that hemispheric differences in intrinsic prefrontal dynamics are able to predict cognitive performance in tasks tapping these domain-general functions. These empirical contributions will be presented together with contrasting evidence, limits, and possible future directions to better fine-tune this model and extend its scope to new fields.

Repetitive Transcranial Magnetic Stimulation in the Treatment of Alzheimer's Disease and Other Dementias

Dementia is a debilitating impairment of cognitive functions that affects millions of people worldwide. There are several diseases belonging to the dementia spectrum, most prominently Alzheimer’s disease (AD), vascular dementia (VD), Lewy body dementia (LBD) and frontotemporal dementia (FTD). Repetitive transcranial magnetic stimulation (rTMS) is a safe, non-invasive form of brain stimulation that utilizes a magnetic coil to generate an electrical field and induce numerous changes in the brain. It is considered efficacious for the treatment of various neuropsychiatric disorders. In this paper, we review the available studies involving rTMS in the treatment of these dementia types. The majority of studies have involved AD and shown beneficial effects, either as a standalone, or as an add-on to standard-of-care pharmacological treatment and cognitive training. The dorsolateral prefrontal cortex seems to hold a central position in the applied protocols, but several parameters still need to be defined. In addition, rTMS has shown potential in mild cognitive impairment as well. Regarding the remaining dementias, research is still at preliminary phases, and large, randomized studies are currently lacking.

How does hemispheric specialization contribute to human-defining cognition?

Uniquely human cognitive faculties arise from flexible interplay between specific local neural modules, with hemispheric asymmetries in functional specialization. Here, we discuss how these computational design principles provide a scaffold that enables some of the most advanced cognitive operations, such as semantic understanding of world structure, logical reasoning, and communication via language. We draw parallels to dual-processing theories of cognition by placing a focus on Kahneman's System 1 and System 2. We propose integration of these ideas with the global workspace theory to explain dynamic relay of information products between both systems. Deepening the current understanding of how neurocognitive asymmetry makes humans special can ignite the next wave of neuroscience-inspired artificial intelligence.

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.

The transcranial direct current stimulation over prefrontal cortex combined with the cognitive training reduced the cue-induced craving in female individuals with methamphetamine use disorder: A randomized controlled trial

BACKGROUND

Craving and cognitive deficits are potential treatment targets for methamphetamine use disorder (MUD). Previous studies implied that transcranial direct current stimulation (tDCS) and cognitive training respectively improve these symptoms, but the combined effect is unknown. In this study, we investigated the combined effects of tDCS over dorsolateral prefrontal cortex (DLPFC) and computerized cognitive addiction therapy (CCAT) on cue-induced craving and cognitive functions among female individuals with MUD.

METHODS

Seventy-five patients with MUD were randomly assigned to three groups: CCAT + tDCS group, CCAT + sham tDCS group and the control group. The former two groups received 20 sessions of cognitive training combined 1.5 mA active/sham tDCS over DLPFC (20min/session, 5times/week), while the control group received usual care which includes routine medical care, health education, physical exercises and psychological support related to relapse prevention. The cue-induced craving and cognitive functions were tested at the baseline, the end of 2nd week and 4th week.

RESULTS

The CCAT + tDCS group showed a significant reduction in cue-induced craving after 4-week intervention. Moreover, the craving score of the real CCAT + tDCS group was significantly lower than that of the CCAT + sham tDCS group and that of the control group at the end of 4th week. A significant improvement in accuracy of TWOB task was only observed in the CCAT + tDCS group at the end of 4th week when compared to baseline. Unexpectedly, participants who received CCAT plus active or sham tDCS did not change their discounting, whereas those in the control group performed more impulsively over time.

CONCLUSIONS

The study found that the intervention of tDCS over DLPFC combined with CCAT may have potential benefit in improving treatment outcome in patients with MUD. More research is needed to explore the underlying mechanism.

Brain functional changes in perimenopausal women: an amplitude of low-frequency fluctuation study

Objective:

To evaluate the effects of sex hormones on amplitude of low-frequency fluctuation (ALFF) in brain regions related to cognition in perimenopausal women.

Methods:

This cross-sectional study involved 25 perimenopausal women and 25 premenopausal women who underwent behavioral evaluations, sex hormone level measurements, and functional magnetic resonance imaging (fMRI). All data and ALFF analyses were preprocessed using the Data Processing Assistant for Resting-State fMRI. Statistical analyses were performed using the Resting-State fMRI Data Analysis Toolkit to explore the differences in ALFF between perimenopausal and premenopausal women. The gray matter volume (GMV) values extracted from brain regions (regions of interest) with significantly different ALFF values between the perimenopausal and premenopausal groups were compared. We analyzed the correlations of the ALFF and GMV values of these regions of interest with the results of behavioral evaluations and sex hormone levels in the two groups.

Results:

Compared with the premenopausal group, the perimenopausal group showed significant ALFF increase in the left gyrus rectus. Regions with decreased ALFF in the perimenopausal group included the left superior temporal gyrus, left inferior frontal gyrus, and left insula. The GMV values of the left gyrus rectus and left superior temporal gyrus were reduced in perimenopausal women. Furthermore, the estradiol level was negatively correlated with the ALFF value of the left gyrus rectus in perimenopausal women.

Conclusions:

The ALFF and GMV values of certain brain regions related to cognitive function were changed in perimenopausal women. Such functional brain alterations may provide more information regarding the mechanism of cognitive dysfunction in perimenopausal women.