Dynamic changes of brain functional states during surgical skill acquisition.
Ontology highlight
ABSTRACT:
SUBMITTER: Shafiei SB
PROVIDER: S-EPMC6209154 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Dynamic changes of brain functional states during surgical skill acquisition.
Shafiei Somayeh B SB Hussein Ahmed Aly AA Guru Khurshid A KA
PloS one 20181031 10
There is lack of a standardized measure of technical proficiency and skill acquisition for robot-assisted surgery (RAS). Learning surgical skills, in addition to the interaction with the machine and the new surgical environment adds to the complexity of the learning process. Moreover, evaluation of surgeon performance in operating room is required to optimize patient safety. In this study, we investigated the dynamic changes of RAS trainee's brain functional states by practice. We also developed ...[more]
Similar Datasets
Project description:The learning of new skills is characterized by an initial phase of rapid improvement in performance and a phase of more gradual improvements as skills are automatized and performance asymptotes. Using in vivo striatal recordings, we observed region-specific changes in neural activity during the different phases of skill learning, with the associative or dorsomedial striatum being preferentially engaged early in training and the sensorimotor or dorsolateral striatum being engaged later in training. Ex vivo recordings from medium spiny striatal neurons in brain slices of trained mice revealed that the changes observed in vivo corresponded to regional- and training-specific changes in excitatory synaptic transmission in the striatum. Furthermore, the potentiation of glutamatergic transmission observed in dorsolateral striatum after extensive training was preferentially expressed in striatopallidal neurons, rather than striatonigral neurons. These findings demonstrate that region- and pathway-specific plasticity sculpts the circuits involved in the performance of the skill as it becomes automatized.
| S-EPMC2774785 | biostudies-literature
Project description:This study investigated the spatial, spectral, temporal and functional proprieties of functional brain connections involved in the concurrent execution of unrelated visual perception and working memory tasks. Electroencephalography data was analysed using a novel data-driven approach assessing source coherence at the whole-brain level. Three connections in the beta-band (18-24 Hz) and one in the gamma-band (30-40 Hz) were modulated by dual-task performance. Beta-coherence increased within two dorsofrontal-occipital connections in dual-task conditions compared to the single-task condition, with the highest coherence seen during low working memory load trials. In contrast, beta-coherence in a prefrontal-occipital functional connection and gamma-coherence in an inferior frontal-occipitoparietal connection was not affected by the addition of the second task and only showed elevated coherence under high working memory load. Analysis of coherence as a function of time suggested that the dorsofrontal-occipital beta-connections were relevant to working memory maintenance, while the prefrontal-occipital beta-connection and the inferior frontal-occipitoparietal gamma-connection were involved in top-down control of concurrent visual processing. The fact that increased coherence in the gamma-connection, from low to high working memory load, was negatively correlated with faster reaction time on the perception task supports this interpretation. Together, these results demonstrate that dual-task demands trigger non-linear changes in functional interactions between frontal-executive and occipitoparietal-perceptual cortices.
| S-EPMC3226683 | biostudies-literature
Project description:The acquisition of basic surgical skills is a key component of medical education and trainees in laparoscopic surgery typically begin developing their skills using simulation box trainers. However, despite the advantages of simulation surgical training, access can be difficult for many trainees. One technique that has shown promise to enhance the deliberate practice of motor skills is transcranial electric stimulation (tES). The purpose of this study was to assess the impact of transcranial direct current stimulation (tDCS) on training induced improvements and retention of traditional time and kinematic based laparoscopic surgical skill metrics. Forty-nine medical students were randomly allocated to a neurostimulation or sham group and completed 5 training sessions of a bead transfer and threading laparoscopic task. Participants in both the sham and stimulation groups significantly improved their time and kinematic performance on both tasks following training. Although we did find that participants who received M1 tDCS saw greater performance benefits in response to training on a bead transfer task compared to those receiving sham stimulation no effect of neurostimulation was found for the threading task. This finding raises new questions regarding the effect that motor task complexity has on the efficacy of neurostimulation to augment training induced improvement and contributes to a growing body of research investigating the effects of neurostimulation on the sensory-motor performance of laparoscopic surgical skill.
| S-EPMC10447451 | biostudies-literature
Project description:BackgroundChanges in medical education may limit opportunities for trainees to gain proficiency in surgical skills. Transcranial direct-current stimulation (tDCS) can augment motor skill learning and may enhance surgical procedural skill acquisition. The aim of this study was to determine the effects of tDCS on simulation-based laparoscopic surgical skill acquisition.MethodsIn this double-blind, sham-controlled randomized trial, participants were randomized to receive 20 min of anodal tDCS or sham stimulation over the dominant primary motor cortex, concurrent with Fundamentals of Laparoscopic Surgery simulation-based training. Primary outcomes of laparoscopic pattern-cutting and peg transfer tasks were scored at baseline, during repeated performance over 1 h, and again at 6 weeks. Intent-to-treat analysis examined the effects of treatment group on skill acquisition and retention.ResultsOf 40 participants, those receiving tDCS achieved higher mean(s.d.) final pattern-cutting scores than participants in the sham group (207·6(30·0) versus 186·0(32·7) respectively; P = 0·022). Scores were unchanged at 6 weeks. Effects on peg transfer scores were not significantly different (210·2(23·5) in the tDCS group versus 201·7(18·1) in the sham group; P = 0·111); the proportion achieving predetermined proficiency levels was higher for tDCS than for sham stimulation. Procedures were well tolerated with no serious adverse events and no decreases in motor measures.ConclusionThe addition of tDCS to laparoscopic surgical training may enhance skill acquisition. Trials of additional skills and translation to non-simulated performance are required to determine the potential value in medical education and impact on patient outcomes. Registration number: NCT02756052 (https://clinicaltrials.gov/).
| S-EPMC5989997 | biostudies-literature
Project description:ImportanceThe human patient simulators that are currently used in multidisciplinary operating room team training scenarios cannot simulate surgical tasks because they lack a realistic surgical anatomy. Thus, they eliminate the surgeon's primary task in the operating room. The surgical trainee is presented with a significant barrier when he or she attempts to suspend disbelief and engage in the scenario.ObjectiveTo develop and test a simulation-based operating room team training strategy that challenges the communication abilities and teamwork competencies of surgeons while they are engaged in realistic operative maneuvers.Design, setting, and participantsThis pre-post educational intervention pilot study compared the gains in teamwork skills for midlevel surgical residents at Wake Forest Baptist Medical Center after they participated in a standardized multidisciplinary team training scenario with 3 possible levels of surgical realism: (1) SimMan (Laerdal) (control group, no surgical anatomy); (2) "synthetic anatomy for surgical tasks" mannequin (medium-fidelity anatomy), and (3) a patient simulated by a deceased donor (high-fidelity anatomy).InterventionsParticipation in the simulation scenario and the subsequent debriefing.Main outcomes and measuresTeamwork competency was assessed using several instruments with extensive validity evidence, including the Nontechnical Skills assessment, the Trauma Management Skills scoring system, the Crisis Resource Management checklist, and a self-efficacy survey instrument. Participant satisfaction was assessed with a Likert-scale questionnaire.ResultsScenario participants included midlevel surgical residents, anesthesia providers, scrub nurses, and circulating nurses. Statistical models showed that surgical residents exposed to medium-fidelity simulation (synthetic anatomy for surgical tasks) team training scenarios demonstrated greater gains in teamwork skills compared with control groups (SimMan) (Nontechnical Skills video score: 95% CI, 1.06-16.41; Trauma Management Skills video score: 95% CI, 0.61-2.90) and equivalent gains in teamwork skills compared with high-fidelity simulations (deceased donor) (Nontechnical Skills video score: 95% CI, -8.51 to 6.71; Trauma Management Skills video score: 95% CI, -1.70 to 0.49).Conclusions and relevanceIncluding a surgical task in operating room team training significantly enhanced the acquisition of teamwork skills among midlevel surgical residents. Incorporating relatively inexpensive, medium-fidelity synthetic anatomy in human patient simulators was as effective as using high-fidelity anatomies from deceased donors for promoting teamwork skills in this learning group.
| S-EPMC5710460 | biostudies-literature
Project description:Significance: Surgical simulators, both virtual and physical, are increasingly used as training tools for teaching and assessing surgical technical skills. However, the metrics used for assessment in these simulation environments are often subjective and inconsistent. Aim: We propose functional activation metrics, derived from brain imaging measurements, to objectively assess the correspondence between brain activation with surgical motor skills for subjects with varying degrees of surgical skill. Approach: Cortical activation based on changes in the oxygenated hemoglobin (HbO) of 36 subjects was measured using functional near-infrared spectroscopy at the prefrontal cortex (PFC), primary motor cortex, and supplementary motor area (SMA) due to their association with motor skill learning. Inter-regional functional connectivity metrics, namely, wavelet coherence (WCO) and wavelet phase coherence were derived from HbO changes to correlate brain activity to surgical motor skill levels objectively. Results: One-way multivariate analysis of variance found a statistically significant difference in the inter-regional WCO metrics for physical simulator based on Wilk's Λ for expert versus novice, F(10,1)=7495.5 , p<0.01 . Partial eta squared effect size for the inter-regional WCO metrics was found to be highest between the central prefrontal cortex (CPFC) and SMA, CPFC-SMA ( η2=0.257 ). Two-tailed Mann-Whitney U tests with a 95% confidence interval showed baseline equivalence and a statistically significant ( p<0.001 ) difference in the CPFC-SMA WPCO metrics for the physical simulator training group ( 0.960±0.045 ) versus the untrained control group ( 0.735±0.177 ) following training for 10 consecutive days in addition to the pretest and posttest days. Conclusion: We show that brain functional connectivity WCO metric corresponds to surgical motor skills in the laparoscopic physical simulators. Functional connectivity between the CPFC and the SMA is lower for subjects that exhibit expert surgical motor skills than untrained subjects in laparoscopic physical simulators.
| S-EPMC7927423 | biostudies-literature
Project description:Currently, there is a dearth of objective metrics for assessing bi-manual motor skills, which are critical for high-stakes professions such as surgery. Recently, functional near-infrared spectroscopy (fNIRS) has been shown to be effective at classifying motor task types, which can be potentially used for assessing motor performance level. In this work, we use fNIRS data for predicting the performance scores in a standardized bi-manual motor task used in surgical certification and propose a deep-learning framework 'Brain-NET' to extract features from the fNIRS data. Our results demonstrate that the Brain-NET is able to predict bi-manual surgical motor skills based on neuroimaging data accurately ( R2=0.73). Furthermore, the classification ability of the Brain-NET model is demonstrated based on receiver operating characteristic (ROC) curves and area under the curve (AUC) values of 0.91. Hence, these results establish that fNIRS associated with deep learning analysis is a promising method for a bedside, quick and cost-effective assessment of bi-manual skill levels.
| S-EPMC8265734 | biostudies-literature
Project description:Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (µECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states.
| S-EPMC5562766 | biostudies-literature
Project description:Data-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellations are not highly reproducible at the level of individual subjects, even with very long acquisitions. Some brain areas are also more difficult to parcellate than others, with association heteromodal cortices being the most challenging. An important limitation of classical parcellations is that they are static, that is, they neglect dynamic reconfigurations of brain networks. In this paper, we proposed a new method to identify dynamic states of parcellations, which we hypothesized would improve reproducibility over static parcellation approaches. For a series of seed voxels in the brain, we applied a cluster analysis to regroup short (3 min) time windows into "states" with highly similar seed parcels. We split individual time series of the Midnight scan club sample into two independent sets of 2.5 hr (test and retest). We found that average within-state parcellations, called stability maps, were highly reproducible (over 0.9 test-retest spatial correlation in many instances) and subject specific (fingerprinting accuracy over 70% on average) between test and retest. Consistent with our hypothesis, seeds in heteromodal cortices (posterior and anterior cingulate) showed a richer repertoire of states than unimodal (visual) cortex. Taken together, our results indicate that static functional parcellations are incorrectly averaging well-defined and distinct dynamic states of brain parcellations. This work calls to revisit previous methods based on static parcellations, which includes the majority of published network analyses of fMRI data. Our method may, thus, impact how researchers model the rich interactions between brain networks in health and disease.
| S-EPMC7935036 | biostudies-literature
Project description:Current models of motor learning posit that skill acquisition involves both the formation and decay of multiple motor memories that can be engaged in different contexts. Memory formation is assumed to be context dependent, so that errors most strongly update motor memories associated with the current context. In contrast, memory decay is assumed to be context independent, so that movement in any context leads to uniform decay across all contexts. We demonstrate that for both object manipulation and force-field adaptation, contrary to previous models, memory decay is highly context dependent. We show that the decay of memory associated with a given context is greatest for movements made in that context, with more distant contexts showing markedly reduced decay. Thus, both memory formation and decay are strongest for the current context. We propose that this apparently paradoxical organization provides a mechanism for optimizing performance. While memory decay tends to reduce force output, memory formation can correct for any errors that arise, allowing the motor system to regulate force output so as to both minimize errors and avoid unnecessary energy expenditure. The motor commands for any given context thus result from a balance between memory formation and decay, while memories for other contexts are preserved.
| S-EPMC3688072 | biostudies-literature