Causal Circuits Research Articles

From Sweet Spots to Causal Circuits: Navigating Deep Brain Stimulation Targeting Through Anatomic, Connectomic, and Personalized Approaches

From Sweet Spots to Causal Circuits: Navigating Deep Brain Stimulation Targeting Through Anatomic, Connectomic, and Personalized Approaches

Electroconvulsive Therapy-Induced Volumetric Brain Changes Converge on a Common Causal Circuit in Depression

Electroconvulsive Therapy-Induced Volumetric Brain Changes Converge on a Common Causal Circuit in Depression

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = −2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Low-threshold, high-resolution, chronically stable intracortical microstimulation by ultraflexible electrodes

Intracortical microstimulation (ICMS) enables applications ranging from neuroprosthetics to causal circuit manipulations. However, the resolution, efficacy, and chronic stability of neuromodulation are often compromised by adverse tissue responses to the indwelling electrodes. Here we engineer ultraflexible stim-nanoelectronic threads (StimNETs) and demonstrate low activation threshold, high resolution, and chronically stableICMS in awake, behaving mouse models. Invivo two-photon imaging reveals that StimNETs remain seamlessly integrated with the nervous tissue throughout chronic stimulation periods and elicit stable, focal neuronal activation at low currents of 2μA. Importantly, StimNETs evoke longitudinally stable behavioral responses for over 8months at a markedly low charge injection of 0.25 nC/phase. Quantified histological analyses show that chronic ICMS by StimNETs induces no neuronal degeneration or glial scarring. These results suggest that tissue-integrated electrodes provide a path for robust, long-lasting, spatially selective neuromodulation at low currents, which lessens risk of tissue damage or exacerbation of off-target side effects.

Risk Propagation Model and Simulation of an Assembled Building Supply Chain Network

In recent years, the prefabricated building supply chain has received strong support from the government and has developed rapidly, but there are various risks in the operation process. In this paper, on the basis of considering asymptomatic infections and relapse, this paper establishes a risk transmission model that considers a recurrent Susceptible–Exposed–Asymptomatic–Infectious–Recovered (abbr. SEAIR) model, systematically analyses the risks in the supply chain, and calculates the risk balance point to conclude that the risks can exist in the supply chain for a long time. By drawing a causal circuit diagram, the relationship between the influencing factors in the process of risk transmission is found, establishing a stock flow map to explore the law of risk propagation. The simulation results using Vensim PLE software show that the five influencing factors of infection rate, transmission rate, government financial support, government policy supervision, and immunity loss ratio have an important impact on the number of risk-unknown enterprises, risk-latent enterprises, risk transmission enterprises, and infection rehabilitation enterprises in risk transmission, and relevant countermeasures to deal with risk transmission in the supply chain are proposed. Theoretically, this paper broadens the ideas for improving infectious disease models. From the management point of view, it reveals how the prefabricated building supply chain enables enterprises to improve their ability to deal with risks through the risk propagation model, providing reference and helping to manage the risks faced by the prefabricated building supply chain.

Concurrent- and After-Effects of Medial Temporal Lobe Stimulation on Directed Information Flow to and from Prefrontal and Parietal Cortices during Memory Formation.

Electrical stimulation of the medial temporal lobe (MTL) has the potential to uncover causal circuit mechanisms underlying memory function. However, little is known about how MTL stimulation alters information flow with frontoparietal cortical regions implicated in episodic memory. We used intracranial EEG recordings from humans (14 participants, 10 females) to investigate how MTL stimulation alters directed information flow between MTL and PFC and between MTL and posterior parietal cortex (PPC). Participants performed a verbal episodic memory task during which they were presented with words and asked to recall them after a delay of ∼20 s; 50 Hz stimulation was applied to MTL electrodes on selected trials during memory encoding. Directed information flow was examined using phase transfer entropy. Behaviorally, we observed that MTL stimulation reduced memory recall. MTL stimulation decreased top-down PFC→MTL directed information flow during both memory encoding and subsequent memory recall, revealing aftereffects more than 20 s after end of stimulation. Stimulation suppressed top-down PFC→MTL influences to a greater extent than PPC→MTL. Finally, MTL→PFC information flow on stimulation trials was significantly lower for successful, compared with unsuccessful, memory recall; in contrast, MTL→ventral PPC information flow was higher for successful, compared with unsuccessful, memory recall. Together, these results demonstrate that the effects of MTL stimulation are behaviorally, regionally, and directionally specific, that MTL stimulation selectively impairs directional signaling with PFC, and that causal MTL-ventral PPC circuits support successful memory recall. Findings provide new insights into dynamic casual circuits underling episodic memory and their modulation by MTL stimulation.SIGNIFICANCE STATEMENT The medial temporal lobe (MTL) and its interactions with prefrontal and parietal cortices (PFC and PPC) play a critical role in human memory. Dysfunctional MTL-PFC and MTL-PPC circuits are prominent in psychiatric and neurologic disorders, including Alzheimer's disease and schizophrenia. Brain stimulation has emerged as a potential mechanism for enhancing memory and cognitive functions, but the underlying neurophysiological mechanisms and dynamic causal circuitry underlying bottom-up and top-down signaling involving the MTL are unknown. Here, we use intracranial EEG recordings to investigate the effects of MTL stimulation on causal signaling in key episodic memory circuits linking the MTL with PFC and PPC. Our findings have implications for translational applications aimed at realizing the promise of brain stimulation-based treatment of memory disorders.

Causal dynamics and information flow in parietal-temporal-hippocampal circuits during mental arithmetic revealed by high-temporal resolution human intracranial EEG

Mental arithmetic involves distributed brain regions spanning parietal and temporal cortices, yet little is known about the neural dynamics of causal functional circuits that link them. Here we use high-temporal resolution (1000 Hz sampling rate) intracranial EEG from 35 participants, 362 electrodes, and 1727 electrode pairs, to investigate dynamic causal circuits linking posterior parietal cortex (PPC) with ventral temporal-occipital cortex and hippocampal regions which constitute the perceptual, visuospatial, and mnemonic building blocks of mental arithmetic. Nonlinear phase transfer entropy measures capable of capturing information flow identified dorsal PPC as a causal inflow hub during mental arithmetic, with strong causal influences from fusiform gyrus in ventral temporal-occipital cortex as well as the hippocampus. Net causal inflow into dorsal PPC was significantly higher during mental arithmetic, compared to both resting-state and verbal memory recall. Our analysis also revealed functional heterogeneity of casual signaling in the PPC, with greater net causal inflow into the dorsal PCC, compared to ventral PPC. Additionally, the strength of causal influences was significantly higher on dorsal, compared to ventral, PPC from the hippocampus, and ventral temporal-occipital cortex during mental arithmetic, when compared to both resting-state and verbal memory recall. Our findings provide novel insights into dynamic neural circuits and hubs underlying numerical problem solving and reveal neurophysiological circuit mechanisms by which both the visual number form processing and declarative memory systems dynamically engage the PPC during mental arithmetic.

Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation

BackgroundMotor impairment after stroke is due not only to direct tissue loss but also to disrupted connectivity within the motor network. Mixed results from studies attempting to enhance motor recovery with Transcranial Magnetic Stimulation (TMS) highlight the need for a better understanding of both connectivity after stroke and the impact of TMS on this connectivity. This study used TMS-EEG to map the causal information flow in the motor network of healthy adult subjects and define how stroke alters these circuits.MethodsFourteen stroke patients and 12 controls received TMS to two sites (bilateral primary motor cortices) during two motor tasks (paretic/dominant hand movement vs. rest) while EEG measured the cortical response to TMS pulses. TMS-EEG based connectivity measurements were derived for each hemisphere and the change in connectivity (ΔC) between the two motor tasks was calculated. We analyzed if ΔC for each hemisphere differed between the stroke and control groups or across TMS sites, and whether ΔC correlated with arm function in stroke patients.ResultsRight hand movement increased connectivity in the left compared to the right hemisphere in controls, while hand movement did not significantly change connectivity in either hemisphere in stroke. Stroke patients with the largest increase in healthy hemisphere connectivity during paretic hand movement had the best arm function.ConclusionsTMS-EEG measurements are sensitive to movement-induced changes in brain connectivity. These measurements may characterize clinically meaningful changes in circuit dynamics after stroke, thus providing specific targets for trials of TMS in post-stroke rehabilitation.

Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease.

Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine if these circuits converge, we studied depression severity after brain lesions (n=461, five datasets), transcranial magnetic stimulation (TMS) (n=151, four datasets), and deep brain stimulation (DBS) (n=101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets (p<0.001). Circuits derived from lesions, DBS, and TMS were similar (p<0.0005), as were circuits derived from patients with major depression versus other diagnoses (p<0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of TMS and DBS sites (p<0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson’s disease (p<0.05). We conclude that lesions, TMS, and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders.

Correlation Analysis of Runoff-Electricity Price-Load in Cascade Hydropower Spot Market

Runoff, electricity price, and load are the main random variables in the cascade hydropower spot market. The inter-influence, intertwining and coupling relationship among the three increase the difficulty of power market operation. For this reason, this study first used the system dynamics method to draw the causal circuit diagram of the correlation between power station runoff, discharge price and full network load in the spot market, revealed the correlation mechanism of the three, and analyzed the correlation between the three based on the actual data of the spot market. The results show that there is a significant correlation between the three variables. The price of clearing electricity is positively correlated with the load of the whole network, the correlation coefficient is as high as 0.5238, and the price of clearing electricity is negatively correlated with the reservoir runoff, showing a certain degree of complementarity.

“Multiplied without Number”: Lynching, Statistics, and Visualization in Ida B. Wells, Mark Twain, and W. E. B. Du Bois

AbstractQuantification has long played a vexed role in efforts to record and resist racial violence. Building from Ida B. Wells’s antilynching crusade, this essay examines the risks and power of calculating life and death at the close of the nineteenth century. For her part, Wells pushed mere counting past itself to a profound mode of ethical accounting. Two of her contemporaries, Mark Twain and W. E. B. Du Bois, sustained a similarly supraquantitative thrust; each attempted to harness the antilynching potential of numbers by enlisting data visualization. Twain falls short in a telling fashion, as his unpublished satire “The United States of Lyncherdom” (written in 1901) exacerbates the dehumanizing tendencies of quantification. Du Bois, however, pursues a more generative experiment, creating statistical graphics in 1900 that indict and outstrip the causal circuit that yoked scientific numbering to lynching and racial violence more broadly. This latter achievement resonates with scholarly efforts to access Black life from within a desolately tabulated archive of loss and erasure. Specifically, as triangulated with Wells and Twain, Du Bois’s graphics proffer a counterintuitive means to register life as a future-oriented, aggregate abstraction that is neither wholly conditioned by, nor separate from, a past whose violent legacies endure.

Resting fMRI-guided TMS results in subcortical and brain network modulation indexed by interleaved TMS/fMRI.

Traditional non-invasive imaging methods describe statistical associations of functional co-activation over time. They cannot easily establish hierarchies in communication as done in non-human animals using invasive methods. Here, we interleaved functional MRI (fMRI) recordings with non-invasive transcranial magnetic stimulation (TMS) to map causal communication between the frontal cortex and subcortical target structures including the subgenual anterior cingulate cortex (sgACC) and the amygdala. Seed-based correlation maps from each participant's resting fMRI scan determined individual stimulation sites with high temporal correlation to targets for the subsequent TMS/fMRI session(s). The resulting TMS/fMRI images were transformed to quantile responses, so that regions of high-/low-quantile response corresponded to the areas of the brain with the most positive/negative evoked response relative to the global brain response. We then modeled the average quantile response for a given region (e.g., structure or network) to determine whether TMS was effective in the relative engagement of the downstream targets. Both the sgACC and amygdala were differentially influenced by TMS. Furthermore, we found that the sgACC distributed brain network was modulated in response to fMRI-guided TMS. The amygdala, but not its distributed network, also responded to TMS. Our findings suggest that individual targeting and brain response measurements reflect causal circuit mapping to the sgACC and amygdala in humans. These results set the stage to further map circuits in the brain and link circuit pathway integrity to clinical intervention outcomes, especially when the intervention targets specific pathways and networks as is possible with TMS.

Anxiety and Stress Alter Decision-Making Dynamics and Causal Amygdala-Dorsolateral Prefrontal Cortex Circuits During Emotion Regulation in Children

BackgroundAnxiety and stress reactivity are risk factors for the development of affective disorders. However, the behavioral and neurocircuit mechanisms that potentiate maladaptive emotion regulation are poorly understood. Neuroimaging studies have implicated the amygdala and dorsolateral prefrontal cortex (DLPFC) in emotion regulation, but how anxiety and stress alter their context-specific causal circuit interactions is not known. Here, we use computational modeling to inform affective pathophysiology, etiology, and neurocircuit targets for early intervention. MethodsForty-five children (10–11 years of age; 25 boys) reappraised aversive stimuli during functional magnetic resonance imaging scanning. Clinical measures of anxiety and stress were acquired for each child. Drift-diffusion modeling of behavioral data and causal circuit analysis of functional magnetic resonance imaging data, with a National Institute of Mental Health Research Domain Criteria approach, were used to characterize latent behavioral and neurocircuit decision-making dynamics driving emotion regulation. ResultsChildren successfully reappraised negative responses to aversive stimuli. Drift-diffusion modeling revealed that emotion regulation was characterized by increased initial bias toward positive reactivity during viewing of aversive stimuli and increased drift rate, which captured evidence accumulation during emotion evaluation. Crucially, anxiety and stress reactivity impaired latent behavioral dynamics associated with reappraisal and decision making. Anxiety and stress increased dynamic casual influences from the right amygdala to DLPFC. In contrast, DLPFC, but not amygdala, reactivity was correlated with evidence accumulation and decision making during emotion reappraisal. ConclusionsOur findings provide new insights into how anxiety and stress in children impact decision making and amygdala-DLPFC signaling during emotion regulation, and uncover latent behavioral and neurocircuit mechanisms of early risk for psychopathology.

Study on sustainable development of Tibetan medicine resources on Qinghai-Tibet Plateau

Through using the theoretical research results of traditional Chinese medicine resource management and sustainable utilization as references,this article systematically analyzes the relationship between economic subsystems for utilization of wild renewable resources in Tibetan medicine,resources,environment and social systems. It sorts out and designs the relationship diagram of the sustainable utilization system for Tibetan medicine resources,input and output relationship diagrams of economics subsystems for Tibetan medicine resources,development model diagram for Tibetan medical industrial chain,market development flow chart of wild herb resources of Tibetan medicine,causal circuit diagram of sustainable use mechanism for Tibetan medicine resources,cause tree of the stock and function for Tibetan medicine resources,cause tree of total income for Tibetan medicine resource utilization and tree diagram of compensation fund usage of Tibetan medicine resources. It provides an innovative research method for Tibetan medicine resources,and theoretical basis and relevant countermeasure for constructing sustainable approaches to development of wild renewable resources in Tibetan medicine.

Deconstructing ARDS Variability: Platelet Count, an ARDS Intermediate Phenotype and Novel Mediator of Genetic Effects in ARDS.

Genome-wide association studies (GWASs) in acute respiratory distress syndrome (ARDS) have been hampered by the heterogeneity of the clinical phenotypes and the large sample size requirement. As the limitations of these studies to uncover the complex genetic architecture of ARDS are evident, new approaches intended to reduce data complexity need to be applied. Intermediate phenotypes are mechanism-related manifestations of the disease, located closer to the genetic substrate than to disease phenotype, and therefore able to reflect more directly and more strongly the effect of causal genes. The dissection of complex phenotypes into less complex intermediate phenotypes is a valuable strategy to facilitate the discovery of those genetic variants whose effect is not strong enough to be detected as markers of disease in traditional GWASs. Genetic causal inference methodologies can be then applied to estimate the implication of the intermediate trait in the causal circuit between genes and disease. By following this strategy, platelet count, a relevant intermediate quantitative trait in ARDS, has been recently identified as a novel mediator in the genetic contribution to ARDS risk and mortality. The use of intermediate phenotypes and causal inference are emerging methodological and statistical strategies that can help to overcome the limitations of traditional GWASs in ARDS. Moreover, these approaches can provide evidence for the mechanisms linking genes to ARDS and help to prioritize therapeutic targets for the treatment of this devastating syndrome.

Interacting neural ensembles in orbitofrontal cortex for social and feeding behaviour.

Categorically distinct basic drives (for example, for social versus feeding behaviour1-3) can exert potent influences on each other; such interactions are likely to have important adaptive consequences (such as appropriate regulation of feeding in the context of social hierarchies) and can become maladaptive (such as in clinical settings involving anorexia). It is known that neural systems regulating natural and adaptive caloric intake, and those regulating social behaviours, involve related circuitry4-7, butthe causal circuit mechanisms of these drive adjudications are not clear. Here we investigate the causal role in behaviour of cellular-resolution experience-specific neuronal populations in the orbitofrontal cortex, a major reward-processing hub thatcontains diverse activity-specific neuronal populations that respond differentially to various aspects of caloric intake8-13 and social stimuli14,15. We coupled genetically encoded activity imaging with thedevelopment and application of methods for optogenetic control of multiple individually defined cells, to both optically monitor and manipulate the activity of many orbitofrontal cortex neurons at the single-cell level in real time during rewarding experiences (caloric consumption and socialinteraction). We identified distinct populations within the orbitofrontal cortex that selectively responded to either caloric rewards or social stimuli, and found that activity of individually specified naturally feeding-responsive neurons was causally linked to increased feeding behaviour; this effect was selective as, by contrast, single-cell resolution activation of naturally social-responsive neurons inhibited feeding, and activation of neurons responsive to neither feeding nor social stimuli did not alter feeding behaviour. These results reveal the presence of potent cellular-level subnetworks within the orbitofrontal cortex that can be precisely engaged to bidirectionally control feeding behaviours subject to, for example, social influences.

Visual Evidence Accumulation Guides Decision-Making in Unrestrained Mice.

The ability to manipulate neural activity with precision is an asset in uncovering neural circuits for decision-making. Diverse tools for manipulating neurons are available for mice, but their feasibility remains unclear, especially when decisions require accumulating visual evidence. For example, whether mice' decisions reflect leaky accumulation is unknown, as are the relevant/irrelevant factors that influence decisions. Further, causal circuits for visual evidence accumulation are poorly understood. To address this, we measured decisions in mice judging the fluctuating rate of a flash sequence. An initial analysis (>500,000 trials, 29 male and female mice) demonstrated that information throughout the 1000 ms trial influenced choice, with early information most influential. This suggests that information persists in neural circuits for ∼1000 ms with minimal accumulation leak. Next, in a subset of animals, we probed strategy more extensively and found that although animals were influenced by stimulus rate, they were unable to entirely suppress the influence of stimulus brightness. Finally, we identified anteromedial (AM) visual area via retinotopic mapping and optogenetically inhibited it using JAWS. Light activation biased choices in both injected and uninjected animals, demonstrating that light alone influences behavior. By varying stimulus-response contingency while holding stimulated hemisphere constant, we surmounted this obstacle to demonstrate that AM suppression biases decisions. By leveraging a large dataset to quantitatively characterize decision-making behavior, we establish mice as suitable for neural circuit manipulation studies. Further, by demonstrating that mice accumulate visual evidence, we demonstrate that this strategy for reducing uncertainty in decision-making is used by animals with diverse visual systems.SIGNIFICANCE STATEMENT To connect behaviors to their underlying neural mechanism, a deep understanding of behavioral strategy is needed. This understanding is incomplete for mice. To surmount this, we measured the outcome of >500,000 decisions made by 29 mice trained to judge visual stimuli and performed behavioral/optogenetic manipulations in smaller subsets. Our analyses offer new insights into mice' decision-making strategies and compares them with those of other species. We then disrupted neural activity in a candidate neural structure and examined the effect on decisions. Our findings establish mice as suitable for visual accumulation of evidence decisions. Further, the results highlight similarities in decision-making strategies across very different species.

Causal Analysis of Databases Concerning Electromagnetism and Health

In this article, we conducted a causal analysis of a system extracted from a database of current data in the telecommunications domain, namely the Eurobarometer 73.3 database arose from a survey of 26,602 citizens EU on the potential health effects that electromagnetic fields can produce. To determine the cause-effect relationships between variables, we represented these data by a directed graph that can be applied to a qualitative version of the theory of discrete chaos to highlight causal circuits and attractors, as these are basic elements of system behavior.

Optogenetics and the circuit dynamics of psychiatric disease.

Optogenetics and the circuit dynamics of psychiatric disease.

Naturalizing Institutions: Evolutionary Principles and Application on the Case of Money

Summary In recent extensions of Darwinism into economics, the replicator-interactor duality looms large. I propose a naturalistic approach to this duality in the context of the theory of institutions, which means that its use is necessarily dependent on identifying a physical realization. I introduce a general framework, which synthesizes Searle’s and Aoki’s theories, especially with regard to the role of public representations (signs) in the coordination of actions, and the function of cognitive processes that underlie rule-following as a behavioural disposition. Institutions are causal circuits that connect the population-level dynamics of interactions with cognitive phenomena on the individual level which ultimately root in neuronal structures. I propose a new conceptualization of the replicator in the context of institutions: the replicator is a causal conjunction between (physical) signs and neuronal structures which undergirds the dispositions that generate rule-following actions. Signs, in turn, are outcomes of population-level interactions. I apply this framework on the case of money, analysing the emotions that go along with the use of money, and presenting a stylized account of the emergence of money in terms of the naturalized Searle-Aoki model. In this view, money is a neuronally anchored sign for emotions relating with social exchange and reciprocity. The money replicator is physically realized in a causal conjunction of money artefacts and money emotions.