Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person’s brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model’s stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications

Author Correction: Real-time Acute Stress Facilitates Allocentric Spatial Processing in a Virtual Fire Disaster

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper

Real-time Acute Stress Facilitates Allocentric Spatial Processing in a Virtual Fire Disaster

Abstract Prior studies have shown that spatial cognition is influenced by stress prior to task. The current study investigated the effects of real-time acute stress on allocentric and egocentric spatial processing. A virtual reality-based spatial reference rule learning (SRRL) task was designed in which participants were instructed to make a location selection by walking to one of three poles situated around a tower. A selection was reinforced by either an egocentric spatial reference rule (leftmost or rightmost pole relative to participant) or an allocentric spatial reference rule (nearest or farthest pole relative to the tower). In Experiment 1, 32 participants (16 males, 16 females; aged from 18 to 27) performed a SRRL task in a normal virtual reality environment (VRE). The hit rates and rule acquisition revealed no difference between allocentric and egocentric spatial reference rule learning. In Experiment 2, 66 participants (32 males, 34 females; aged from 19 to 30) performed the SRRL task in both a low-stress VRE (a mini virtual arena) and a high-stress VRE (mini virtual arena with a fire disaster). Allocentric references facilitated learning in the high-stressful VRE. The results suggested that acute stress facilitate allocentric spatial processing

Effects of zero-valent iron and enzymes on the anaerobic co-digestion of sewage sludge and corn silage

Anaerobic co-digestion of sewage sludge and corn silage with zero-valent iron powder (Fe0), cellulase, and papain as reinforcement means was conducted. COD-based feeding ratio of sewage sludge to corn silage was set to 2:1, the solids retention time (SRT) 20 day, digestion temperature 35 °C, and mixing speed 60 rpm. Removal rates of total COD during the control group, and Fe0, papain, cellulase, and papain, Fe0, and the two kinds of enzyme-added tests were 38.04, 41.02, 34.62, 34.55, 35.42, and 48.21%, respectively. The corresponding biogas production was 2.12, 2.62, 2.22, 2.41, 2.25, and 2.81 dm3/day, respectively. The results indicated the addition of cellulase, and papain could maximize the decomposition and hydrolysis of organic matter in sewage sludge and corn silage to volatile fatty acids. Fe0 could reduce the redox potentials of the anaerobic co-digestion, optimize the circumstances of the methanogenesis stage, accelerate biogas production, and improve biogas components. Fe0 and enzymes played a synergistic role in the anaerobic co-digestion system. Life cycle assessment indicated that the anaerobic co-digestion of sludge and corn silage co-substrates could benefit the economy, environment, and social development under the synergistic action of Fe0 and enzymes

Distribution and behavior of plutonium isotopes in Western Pacific marginal Seas

Due to the worldwide atmospheric nuclear weapon tests and the U.S. ground-level test series conducted in the 1950s at Bikini and Enewetak Atolls, marine environments have been extensively contaminated by plutonium (Pu) over the China Seas (CHS). The released Pu isotopes can serve as an excellent geochemical tracer for various physical and biogeochemical ocean processes, such as sediment mixing rate, particle scavenging, biological productivity and water mass circulation. In this critical review, a database of Pu activity concentrations, Pu isotope ratio, and inventories in marine environment in the CHS is established based on previous studies. In addition, the source term, spatial distribution and environmental behavior of Pu isotopes in seawater and sediments in the CHS are summarized and discussed, and are further compared to these in the neighboring seas for a better understanding of the transport and fate of Pu isotopes. Finally, the future research needs for Pu in marine environment are discussed

Effects of zero-valent iron and enzymes on the anaerobic co-digestion of sewage sludge and corn silage

Anaerobic co-digestion of sewage sludge and corn silage with zero-valent iron powder (Fe0), cellulase, and papain as reinforcement means was conducted. COD-based feeding ratio of sewage sludge to corn silage was set to 2:1, the solids retention time (SRT) 20 day, digestion temperature 35 °C, and mixing speed 60 rpm. Removal rates of total COD during the control group, and Fe0, papain, cellulase, and papain, Fe0, and the two kinds of enzyme-added tests were 38.04, 41.02, 34.62, 34.55, 35.42, and 48.21%, respectively. The corresponding biogas production was 2.12, 2.62, 2.22, 2.41, 2.25, and 2.81 dm3/day, respectively. The results indicated the addition of cellulase, and papain could maximize the decomposition and hydrolysis of organic matter in sewage sludge and corn silage to volatile fatty acids. Fe0 could reduce the redox potentials of the anaerobic co-digestion, optimize the circumstances of the methanogenesis stage, accelerate biogas production, and improve biogas components. Fe0 and enzymes played a synergistic role in the anaerobic co-digestion system. Life cycle assessment indicated that the anaerobic co-digestion of sludge and corn silage co-substrates could benefit the economy, environment, and social development under the synergistic action of Fe0 and enzymes

DataSheet_1_Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility.docx

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person’s brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model’s stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.</p

Data_Sheet_1_Targeting the pathological network: Feasibility of network-based optimization of transcranial magnetic stimulation coil placement for treatment of psychiatric disorders.docx

It has been recognized that the efficacy of TMS-based modulation may depend on the network profile of the stimulated regions throughout the brain. However, what profile of this stimulation network optimally benefits treatment outcomes is yet to be addressed. The answer to the question is crucial for informing network-based optimization of stimulation parameters, such as coil placement, in TMS treatments. In this study, we aimed to investigate the feasibility of taking a disease-specific network as the target of stimulation network for guiding individualized coil placement in TMS treatments. We present here a novel network-based model for TMS targeting of the pathological network. First, combining E-field modeling and resting-state functional connectivity, stimulation networks were modeled from locations and orientations of the TMS coil. Second, the spatial anti-correlation between the stimulation network and the pathological network of a given disease was hypothesized to predict the treatment outcome. The proposed model was validated to predict treatment efficacy from the position and orientation of TMS coils in two depression cohorts and one schizophrenia cohort with auditory verbal hallucinations. We further demonstrate the utility of the proposed model in guiding individualized TMS treatment for psychiatric disorders. In this proof-of-concept study, we demonstrated the feasibility of the novel network-based targeting strategy that uses the whole-brain, system-level abnormity of a specific psychiatric disease as a target. Results based on empirical data suggest that the strategy may potentially be utilized to identify individualized coil parameters for maximal therapeutic effects.</p