Comparing Knee Kinetics and Kinematics in Healthy Individuals and Those With Knee Osteoarthritis, With and Without Flat Feet.

Individuals with knee osteoarthritis (KOA) and flat feet are more likely to experience increased pain and cartilage damage. This study aimed to investigate the knee kinetics, kinematics, pain, and physical function in individuals with moderate symptomatic KOA, in comparison to asymptomatic control participants. Thirty volunteers with moderate KOA (with flat feet n = 15, with normal feet n = 15) and 30 asymptomatic people (with flat feet n = 15, with normal feet n = 15) were evaluated. The knee adduction angular impulse, knee flexion moment, knee flexion angular impulse, and knee flexion angle were measured during level walking. The pain was assessed in patients with KOA. The study found that individuals with KOA had a significant increase in the knee adduction angular impulse compared with the asymptomatic people (P < .05). The KOA with flat feet group had significantly lower knee flexion moment, knee flexion angular impulse, and knee flexion angle values than the KOA with normal feet group (P < .05). Furthermore, the KOA with flat feet group had a higher pain score than the KOA with normal feet group. Individuals with osteoarthritis and flat feet had lower knee flexion moments which may indicate reduced knee force exerted through compensatory mechanisms. Despite this reduction, they reported significantly higher levels of pain compared with those without flat feet, a finding that warrants further investigation in future studies.

Exploring the dynamic interplay between learning and working memory within various cognitive contexts.

Introduction: The intertwined relationship between reinforcement learning and working memory in the brain is a complex subject, widely studied across various domains in neuroscience. Research efforts have focused on identifying the specific brain areas responsible for these functions, understanding their contributions in accomplishing the related tasks, and exploring their adaptability under conditions such as cognitive impairment or aging. Methods: Numerous models have been introduced to formulate either these two subsystems of reinforcement learning and working memory separately or their combination and relationship in executing cognitive tasks. This study adopts the RLWM model as a computational framework to analyze the behavioral parameters of subjects with varying cognitive abilities due to age or cognitive status. A related RLWM task is employed to assess a group of subjects across different age groups and cognitive abilities, as measured by the Montreal Cognitive Assessment tool (MoCA). Results: Analysis reveals a decline in overall performance accuracy and speed with differing age groups (young vs. middle-aged). Significant differences are observed in model parameters such as learning rate, WM decay, and decision noise. Furthermore, among the middle-aged group, distinctions emerge between subjects categorized as normal vs. MCI based on MoCA scores, notably in speed, performance accuracy, and decision noise.

A biological and a mathematical model of SLE treated by mesenchymal stem cells covering all the stages of the disease.

In this study, we proposed a biological model explaining the progress of autoimmune activation along different stages of systemic lupus erythematosus (SLE). For any upcoming stage of SLE, any new component is introduced, when it is added to the model. Particularly, the interaction of mesenchymal stem cells, with the components of the model, is specified in a way that both the inflammatory and anti-inflammatory functions of these cells would be covered. The biological model is then recapitulated to a model with less complexity that explains the main features of the problem. Later, a 7th-order mathematical model for SLE is proposed, based on this simplified model. Finally, the range of validity of the proposed mathematical model was assessed. For this purpose, we simulated the model and analyzed the simulation results in case of some known behaviors of the disease, such as tolerance breach, the appearance of systemic inflammation, development of clinical signs, and occurrence of flares and improvements. The model was able to reproduce these events, qualitatively.

Virtual Reality Exergaming Capability to Change Muscle Strategy During the Limits of Stability Test and Reduce Fear of Falling in Primary Osteoporotic Women.

Objective: Muscle strength and balance impairment change the control strategy and increase the probability of falling. This study aimed to investigate the effect of 6-week strength-balance training through virtual reality exergaming (VRE) on muscle strategy during the limits of stability (LOS) test, fear of falling, and quality of life (QOL) in osteoporotic women. Materials and Methods: Twenty volunteer postmenopausal women with osteoporosis were randomly allocated to the VRE (n = 10) and traditional training (TRT as control, n = 10) groups. The VRE and TRT strength-balance training was performed for 6 weeks and three sessions per week. Before and after exercise, the muscle activity (onset time, peak root means square [PRMS]) and hip/ankle activity ratio were assessed by the wireless electromyography system. The muscle activities of the dominant leg were recorded during LOS functional test. The fall efficacy scale and QOL were assessed. Paired t-test was used to compare results within groups, and an independent t-test was used to compare the percentage changes in parameters between the two groups. Results: The VRE improved the onset time and PRMS. The VRE significantly reduced the hip/ankle activity ratio in the LOS test's forward, backward, and right directions (P < 0.05). No significant change was seen in all directions of the LOS functional test in the TRT group (P > 0.05). VRE reduced the fall efficacy scale (P = 0.042). Both VRT and TRT improved the total QOL score (P = 0.010). Conclusion: VRE was more effective in decreasing the onset time and hip/ankle ratio of muscle activation. The VRE is recommended to induce a better ability to reduce the fear of falling and control balance during functional activity in osteoporotic women. Clinical Trial Registration number: IRCT20101017004952N9.

Dysconnection and cognition in schizophrenia: A spectral dynamic causal modeling study.

Schizophrenia (SZ) is a severe mental disorder characterized by failure of functional integration (aka dysconnection) across the brain. Recent functional connectivity (FC) studies have adopted functional parcellations to define subnetworks of large-scale networks, and to characterize the (dys)connection between them, in normal and clinical populations. While FC examines statistical dependencies between observations, model-based effective connectivity (EC) can disclose the causal influences that underwrite the observed dependencies. In this study, we investigated resting state EC within seven large-scale networks, in 66 SZ and 74 healthy subjects from a public dataset. The results showed that a remarkable 33% of the effective connections (among subnetworks) of the cognitive control network had been pathologically modulated in SZ. Further dysconnection was identified within the visual, default mode and sensorimotor networks of SZ subjects, with 24%, 20%, and 11% aberrant couplings. Overall, the proportion of discriminative connections was remarkably larger in EC (24%) than FC (1%) analysis. Subsequently, to study the neural correlates of impaired cognition in SZ, we conducted a canonical correlation analysis between the EC parameters and the cognitive scores of the patients. As such, the self-inhibitions of supplementary motor area and paracentral lobule (in the sensorimotor network) and the excitatory connection from parahippocampal gyrus to inferior temporal gyrus (in the cognitive control network) were significantly correlated with the social cognition, reasoning/problem solving and working memory capabilities of the patients. Future research can investigate the potential of whole-brain EC as a biomarker for diagnosis of brain disorders and for neuroimaging-based cognitive assessment.

The simultaneous changes in motor performance and EEG patterns in beta band during learning dart throwing skill in dominant and non-dominant hand.

Background: Although changes in performance during the learning of various sports skills have been studied, however, how these changes at the brain level is still unknown. The aim of this study was to investigate simultaneous changes in motor performance and EEG patterns in beta band during learning dart throwing skill in dominant and non-dominant hand. Methodology: The samples consisted of 14 non-athlete students with an average age of 23 ± 2.5, which were divided into two group dominant hand (7) and non-dominant hand (7). Repeated measures ANOVA were used to measure data at the execution level and changes in EEG activity. Results: The results of this study at the performance level showed a significant reduction in the absolute error of dart throwing and at the same time at the brain level increased EEG activity in frontal and parietal-posterior regions along with decreased central area activity in acquisition and retention stages in both groups (P<.05). Also, there was a significant difference between the activity of EEG pattern in the dominant and non-dominant hand groups except for two channels AF3 and PO4 (P<.05). Conclusion: In general, the results of this study showed that along with relatively constant changes in performance during dart skill learning, relatively constant changes in EEG activity pattern occur, so that the concept of motor learning is also visible at the brain level. Also, the results of this study supported the existence of the different motor program for dominant and non-dominant hand control in the conditions of bilateral transfer control.

The effect of six week virtual reality training on the improvement of functional balance in women with type-I osteoporosis: A preliminary study.

Purpose: This preliminary study aimed to investigate the effects of exergames in a virtual reality environment to improve functional balance during goal-directed functional tasks in postmenopausal women with osteoporosis. Methods: Twelve volunteer postmenopausal women with osteoporosis were randomly assigned to virtual reality (VRT, n = 6) and conventional multimodal (CMT, n = 6) training groups. The exercise was performed for 6 weeks, 3 days weekly, and 18 sessions. Using a force platform, functional balance assessments were made through four dynamic tasks, including performance-based limits of stability (LOS), curve tracking (CT), sit-to-stand (STS), and turning before and after 18 sessions of treatment. Each task's time-dependent center of pressure (COP) variables was separately calculated via Kistler-Mars software. Results: The COP variables of LOS and CT tasks were significantly improved after 6 weeks of CMT and VRT (P ≤ 0.05). In the VRT group, the rising index (P < 0.00), COP sway velocity in STS, and Turn sway were significantly reduced (P < 0.05). Following the VRT, the mean difference of forwarding maximum COP excursion increased (P = 0.03), and errors in CT (P = 0.03) significantly decreased. Conclusion: The VRT and CMT improved the COP sway parameters during weight-shifting tasks. The VRT was more effective than CMT in increasing the ability to control weight-shifting and dynamic functional tasks in postmenopausal women with osteoporosis. This approach in training has suitable potential to provide convenient error feedback learning.

Gait modification with subject-specific foot progression angle in people with moderate knee osteoarthritis: Investigation of knee adduction moment and muscle activity.

BACKGROUND: Subject-specific foot progression angle (SSFPA) as a personalized gait modification is a novel approach to specifically reducing knee adduction. OBJECTIVE: This study aimed to investigate the effect of gait modification with SSFPA on the knee adduction moment and muscle activity in people with moderate knee osteoarthritis (KOA). METHODS: In this clinical trial, nineteen volunteers with moderate KOA were instructed to walk in four different foot progression angle conditions (5° toe-out, 10° toe-out, 5° toe-in, and 10° toe-in) to determine SSFPA that caused the greatest reduction in the greater peak of the knee adduction moment (PKAM). Immediately and after 30 minutes of gait modification with SSFPA, peak root means square (PRMS) and medial and lateral co-contraction index (CCI) were evaluated in the knee muscles. RESULT: Walking with 10° toe-in showed the most reduction in the greater PKAM (17.52 ± 15.39%) compared to 5° toe-in (7.1 ± 19.14%), 10° toe-out (1.26 ± 23.13%), and 5° toe-out (7.64 ± 16.71%). As the immediate effect, walking with SSFPA caused a 20.71 ± 12.07% reduction in the greater PKAM than the basic FPA (p < 0.001). After 30 minutes of gait retraining, the greater PKAM decreased by 10.36 ± 26.24%, but this reduction was not significant (p = 0.17). In addition, PRMS of lateral gastrocnemius increased (p = 0.04), and lateral CCI increased 10.72% during late stance (p = 0.04). CONCLUSION: Our findings suggest the immediate effect of gait modification with SSFPA on decreasing the knee adduction moment. After gait retraining with SSFPA, the increase of lateral muscle co-contraction may enhance lateral knee muscle co-activity to unload the medial knee compartment. Clinical Trial Register Number: IRCT20101017004952N8.

Human balance control in 3D running based on virtual pivot point concept.

Balance control is one of the crucial challenges in bipedal locomotion. Humans need to maintain their trunk upright while the body behaves like an inverted pendulum which is inherently unstable. As an alternative, the virtual pivot point (VPP) concept introduced a new virtual pendulum model to the human balance control paradigm by analyzing the ground reaction forces (GRFs) in the body coordinate frame. This paper presents novel VPP-based analyses of the postural stability of human running in 3D space. We demonstrate the relationship between the VPP position and the gait speed. The experimental results suggest different control strategies in frontal and sagittal planes. The GRFs intersect below the center of mass in the sagittal plane and above the center of mass in the frontal plane. These VPP locations are found for the sagittal and frontal planes at all running speeds. We introduced a 3D VPP-based model which can replicate the kinematic and kinetic behavior of human running. The similarity between the experimental and simulation results indicates the ability of the VPP concept to predict human balance control in running and support its applicability for gait assistance.

From a biological template model to gait assistance with an exosuit.

The invention of soft wearable assistive devices, known as exosuits, introduced a new aspect in assisting unimpaired subjects. In this study, we designed and developed an exosuit with compliant biarticular thigh actuators called BATEX. Unlike the conventional method of using rigid actuators in exosuits, the BATEX is made of serial elastic actuators (SEA) resembling artificial muscles. This bioinspired design is complemented by the novel control concept of using the ground reaction force to adjust the artificial muscles' stiffness in the stance phase. By locking the motors in the swing phase, the SEAs will be simplified to passive biarticular springs, which is sufficient for leg swinging. The key concept in our design and control approach is to synthesize human locomotion to develop an assistive device instead of copying human motor control outputs. Analyzing human walking assistance using experiment-based OpenSim simulations demonstrates the advantages of the proposed design and control of BATEX, such as 9.4% reduction in metabolic cost during normal walking condition. This metabolic reduction increases to 10.4% when the subjects carry a 38 kg load. The adaptability of our proposed model-based control to such an unknown condition outperforms the assistance level of the model-free optimal controller. Moreover, increasing the assistive system's efficiency by adjusting the actuator compliance with the force feedback supports our previous findings on the LOPES II exoskeleton.

Are weight shifting and dynamic control strategies different in postmenopausal women with and without type-I osteoporosis?

OBJECTIVE: Tracking postural control processes at dynamic conditions might help develop an appropriate rehabilitation program in osteoporotic women. This study aimed to investigate the differences in center of pressure (COP) control at weight shifting and dynamic tasks between postmenopausal women with and without type-I osteoporosis. Also, we investigated the correlations between bone mineral density (BMD), the activity-specific balance confidence questionnaire (ABC-Q) score, and postural control parameters. METHOD: A total of 62 volunteer postmenopausal women participated in this study. The participants were classified into non-osteoporotic (NOP, T-score >1, n = 35, age = 60.04± 5.33 years) and osteoporotic (OP, T-score < -2.5, n = 27, age = 61.88 ± 5.34 years) groups. The COP sway was recorded using a Kistler force plate during performance-based Limits of Stability (LOS), Curve Tracking (CT), Sit to Stand (STS), and Turn tasks. In addition, the level of balance confidence in daily activities was evaluated by ABC-Q. RESULTS: In the LOS task, COP sway velocity in the anterior direction (P = 0.02) and COP maximum excursion in the side-to-side direction (right-side P = 0.027 and left-side P = 0.044) were significantly lower in the OP than the NOP group. In the CT task, all the quantified parameters, including errors and area, showed significantly lower values in the OP group than the NOP group (P < 0.05). In the STS task, the rising index score was significantly higher in the OP group than the NOP group (P = 0.014). The two groups had an equal ABC-Q score (P = 0.175). The COP sway variables correlated significantly with the lumbar and femoral neck T-score (P < 0.05). CONCLUSION: BMD decline can change weight shifting and dynamic postural control in postmenopausal women.

The Critical Modulatory Role of Spiny Stellate Cells in Seizure Onset Based on Dynamic Analysis of a Neural Mass Model.

Growing evidence suggests that excitatory neurons in the brain play a significant role in seizure generation. Nonetheless, spiny stellate cells are cortical excitatory non-pyramidal neurons in the brain, whose basic role in seizure occurrence is not well understood. In the present research, we study the critical role of spiny stellate cells or the excitatory interneurons (EI), for the first time, in epileptic seizure generation using an extended neural mass model inspired by a thalamocortical model originally introduced by another research group. Applying bifurcation analysis on this modified model, we investigated the rich dynamics corresponding to the epileptic seizure onset and transition between interictal and ictal states caused by EI connectivity to other cell types. Our results indicate that the transition between interictal and ictal states (preictal signal) corresponds to a supercritical Hopf bifurcation, and thus, the extended model suggests that before seizure onset, the amplitude and frequency of neural activities gradually increase. Moreover, we showed that (1) the altered function of GABAergic and glutamatergic receptors of EI can cause seizure, and (2) the pathway between the thalamic relay nucleus and EI facilitates the transition from interictal to ictal activity by decreasing the preictal period. Thereafter, we considered both sensory and cortical periodic inputs to study model responses to various harmonic stimulations. Bifurcation analysis of the model, in this case, suggests that the initial state of the model might be the main cause for the transition between interictal and ictal states as the stimulus frequency changes. The extended thalamocortical model shows also that the amplitude jump phenomenon and non-linear resonance behavior result from the preictal state of the modified model. These results can be considered as a step forward to a deeper understanding of the mechanisms underlying the transition from normal activities to epileptic activities.

3D human arm reaching movement planning with principal patterns in successive phases.

There are observations indicating that the central nervous system (CNS) decomposes a movement into several successive sub-movements as an effective strategy to control the motor task. In this study, we propose an algorithm in which, Arm Reaching Movement (ARM) in 3D space is decomposed into several successive phases using zero joint angle jerk features of the arm kinematic data. The presented decomposition algorithm for 3D motions is, in fact, an improved and generalized version of the decomposition method proposed earlier by Emadi and Bahrami in 2012 for 2D movements. They assumed that the motion is coordinated by minimum jerk characteristics in joint angles space in each phase. However, at the first glance, it seems that in 3D ARM joint angles are not coordinated based on the minimum jerk features. Therefore, we defined a resultant variable in the joint space and showed that one can use its jerk properties together with those of the elbow joint in movement decomposition. We showed that phase borders determined with the proposed algorithm in 3D ARM, are defined with jerk characteristics of ARM's performance variable. We observed the same results in the Sit-to-Stand (STS) movement, too. Thus, based on our results, we suggested that any 3D motion can be decomposed into several phases, such that in each phase a set of principal patterns (PPs) extracted by Principal Component Analysis (PCA) method are linearly recruited to regenerate angle trajectories of each joint. Our results also suggest that the CNS, as the primary policy, may simplify the control of the ARMs by reducing the dimension of the control space. This dimension reduction might be accomplished by decomposing the movement into successive phases in which the movement satisfies the minimum joint angle jerk constraint. Then, in each phase, a set of PPs are recruited in the joint space to regenerate angle trajectory of each joint. Then, the dimension of the control space will be the number of the recruitment coefficients.

Deep Temporal Organization of fMRI Phase Synchrony Modes Promotes Large-Scale Disconnection in Schizophrenia.

Itinerant dynamics of the brain generates transient and recurrent spatiotemporal patterns in neuroimaging data. Characterizing metastable functional connectivity (FC) - particularly at rest and using functional magnetic resonance imaging (fMRI) - has shaped the field of dynamic functional connectivity (DFC). Mainstream DFC research relies on (sliding window) correlations to identify recurrent FC patterns. Recently, functional relevance of the instantaneous phase synchrony (IPS) of fMRI signals has been revealed using imaging studies and computational models. In the present paper, we identify the repertoire of whole-brain inter-network IPS states at rest. Moreover, we uncover a hierarchy in the temporal organization of IPS modes. We hypothesize that connectivity disorder in schizophrenia (SZ) is related to the (deep) temporal arrangement of large-scale IPS modes. Hence, we analyze resting-state fMRI data from 68 healthy controls (HC) and 51 SZ patients. Seven resting-state networks (and their sub-components) are identified using spatial independent component analysis. IPS is computed between subject-specific network time courses, using analytic signals. The resultant phase coupling patterns, across time and subjects, are clustered into eight IPS states. Statistical tests show that the relative expression and mean lifetime of certain IPS states have been altered in SZ. Namely, patients spend (45%) less time in a globally coherent state and a subcortical-centered state, and (40%) more time in states reflecting anticoupling within the cognitive control network, compared to the HC. Moreover, the transition profile (between states) reveals a deep temporal structure, shaping two metastates with distinct phase synchrony profiles. A metastate is a collection of states such that within-metastate transitions are more probable than across. Remarkably, metastate occupation balance is altered in SZ, in favor of the less synchronous metastate that promotes disconnection across networks. Furthermore, the trajectory of IPS patterns is less efficient, less smooth, and more restricted in SZ subjects, compared to the HC. Finally, a regression analysis confirms the diagnostic value of the defined IPS measures for SZ identification, highlighting the distinctive role of metastate proportion. Our results suggest that the proposed IPS features may be used for classification studies and for characterizing phase synchrony modes in other (clinical) populations.

How does the CNS control arm reaching movements? Introducing a hierarchical nonlinear predictive control organization based on the idea of muscle synergies.

In this study, we introduce a hierarchical and modular computational model to explain how the CNS (Central Nervous System) controls arm reaching movement (ARM) in the frontal plane and under different conditions. The proposed hierarchical organization was established at three levels: 1) motor planning, 2) command production, and 3) motor execution. Since in this work we are not discussing motion learning, no learning procedure was considered in the model. Previous models mainly assume that the motor planning level produces the desired trajectories of the joints and feeds it to the next level to be tracked. In the proposed model, the motion control is described based on a regulatory control policy, that is, the output of the motor planning level is a step function defining the initial and final desired position of the hand. For the command production level, a nonlinear predictive model was developed to explain how the time-invariant muscle synergies (MSs) are recruited. We used the same computational model to explain the arm reaching motion for a combined ARM task. The combined ARM is defined as two successive ARM such that it starts from point A and reaches to point C via point B. To develop the model, kinematic and kinetic data from six subjects were recorded and analyzed during ARM task performance. The subjects used a robotic manipulator while moving their hand in the frontal plane. The EMG data of 15 muscles were also recorded. The MSs used in the model were extracted from the recorded EMG data. The proposed model explains two aspects of the motor control system by a novel computational approach: 1) the CNS reduces the dimension of the control space using the notion of MSs and thereby, avoids immense computational loads; 2) at the level of motor planning, the CNS generates the desired position of the hand at the starting, via and the final points, and this amounts to a regulatory and non-tracking structure.

The Efficacy of Treadmill Training on Walking and Quality of Life of Adults with Spastic Cerebral Palsy: A Randomized Controlled Trial.

OBJECTIVES: We aimed to evaluate the efficacy of treadmill training on walking speed and endurance and quality of life in ambulatory adults with spastic cerebral palsy (CP) versus traditional physiotherapy. MATERIALS & METHODS: Participants (17 men, 13 women; mean (SD) age 25 yr, 9 m (7 yr, 10m) range 18-45) with Gross Motor Function Classification System (GMFCS) levels below IV (I, II, and III) from the Ra'ad Rehabilitation Goodwill Complex, Tehran, Iran randomly were allocated to the experimental and the control groups each with 15 persons in 2014. The training (treadmill for experimental group and conventional physiotherapy for control group) was conducted two times a week for 8 weeks. Statistical analysis was made by Repeated Measures of ANOVA for changes within the group during the time and Independent t and Mann-Whitney U tests for the differences between the groups. RESULTS: Although the experimental group showed a significant improve in the gait speed [1.08(0.47) m/s to 1.22(0.50) m/s] (P=0.002) and in the gait endurance [291.13(160.28) m to 342.63 (174.62) m] (P=0.002), however the changes of the outcome measures of walking and quality of life the between groups were not significant. CONCLUSION: The treadmill training without body weight support would improve walking speed and endurance in adults with spastic CP. It would not be however more effective than the traditional physiotherapy to increase the gait performances and function and the quality of life in adults with CP.

The Concept of Transmission Coefficient Among Different Cerebellar Layers: A Computational Tool for Analyzing Motor Learning.

High-fidelity regulation of information transmission among cerebellar layers is mainly provided by synaptic plasticity. Therefore, determining the regulatory foundations of synaptic plasticity in the cerebellum and translating them to behavioral output are of great importance. To date, many experimental studies have been carried out in order to clarify the effect of synaptic defects, while targeting a specific signaling pathway in the cerebellar function. However, the contradictory results of these studies at the behavioral level further add to the ambiguity of the problem. Information transmission through firing rate changes in populations of interconnected neurons is one of the most widely accepted principles of neural coding. In this study, while considering the efficacy of synaptic interactions among the cerebellar layers, we propose a firing rate model to realize the concept of transmission coefficient. Thereafter, using a computational approach, we test the effect of different values of transmission coefficient on the gain adaptation of a cerebellar-dependent motor learning task. In conformity with the behavioral data, the proposed model can accurately predict that disruption in different forms of synaptic plasticity does not have the same effect on motor learning. Specifically, impairment in training mechanisms, like in the train-induced LTD in parallel fiber-Purkinje cell synapses, has a significant negative impact on all aspects of learning, including memory formation, transfer, and consolidation, although it does not disrupt basic motor performance. In this regard, the overinduction of parallel fiber-molecular layer interneuron LTP could not prevent motor learning impairment, despite its vital role in preserving the robustness of basic motor performance. In contrast, impairment in plasticity induced by interneurons and background activity of climbing fibers is partly compensable through overinduction of train-induced parallel fiber-Purkinje cell LTD. Additionally, blockade of climbing fiber signaling to the cerebellar cortex, referred to as olivary system lesion, shows the most destructive effect on both motor learning and basic motor performance. Overall, the obtained results from the proposed computational framework are used to provide a map from procedural motor memory formation in the cerebellum. Certainly, the generalization of this concept to other multi-layered networks of the brain requires more physiological and computational researches.

Postural instability and position of the center of pressure into the base of support in postmenopausal osteoporotic and nonosteoporotic women with and without hyperkyphosis.

In postmenopausal women, thoracic hyperkyphosis affects postural instability in the sagittal plane, whereas osteoporosis affects it in the frontal plane. Decrease of hip muscle strength can be changed the center of pressure distance to the center of base of support. These results may be important to design the therapeutic exercise for decreasing the postural instability. PURPOSE: In this study, we investigated the effect of bone mineral density (BMD) and thoracic kyphosis on the center of pressure (CoP) sway and its location related to the base of support (BoS). METHODS: Ten young and 39 postmenopausal women voluntarily participated in this study. Postmenopausal women were divided into four groups according to the thoracic kyphosis angle (normal kyphotic < 50° ≤ hyperkyphotic) and T-score values. The isometric strength of the trunk and lower limb muscles were measured. The CoP postural sway was measured in a comfortable double stance position, and the location of the CoP was then determined related to the BoS. RESULTS: In both hyperkyphotic groups (osteoporotic and normal BMD), the strength of back extension and hip adduction showed a significant decrease compared to the normal kyphotic groups. In the osteoporotic groups (hyper- and normal kyphotic), hip abduction and ankle plantar flexion were significantly weaker than those in the nonosteoporotic groups. In both hyperkyphotic groups, velocity of the CoP displacement in the anterior-posterior (AP) direction was significantly higher than that in the young group, while, in both of the osteoporotic groups, velocity of the CoP displacement in the medio-lateral (ML) direction was significantly higher than that in the young group. In postmenopausal women, hip extensor strength negatively and significantly correlated with the CoP distance to the center of the BoS. CONCLUSION: It appears that thoracic hyperkyphosis affects postural instability in the AP direction and that a decrease of BMD affects postural instability in the ML direction.

Assessing the Effects of Opioids on Pathological Memory by a Computational Model.

INTRODUCTION: Opioids hijack learning and memory formation mechanisms of brain and induce a pathological memory in the hippocampus. This effect is mainly mediated by modifications in glutamatergic system. Speaking more precisely, Opioids presence in a synapse inhibits blockage of N-Methyl-D-Aspartate Receptor (NMDAR) by Mg2+, enhances conductance of NMDAR and thus, induces false Long-Term Potentiation (LTP). METHODS: Based on experimental observations of different researchers, we developed a mathematical model for a pyramidal neuron of the hippocampus to study this false LTP. The model contains a spine of the pyramidal neuron with NMDAR, α-Amino-3-hydroxy-5-Methyl-4-isoxazole Propionic Acid Receptors (AMPARs), and Voltage-Gated Calcium Channels (VGCCs). The model also describes Calmodulin-dependent protein Kinase II (CaMKII) and AMPAR phosphorylation processes which are assumed to be the indicators of LTP induction in the synapse. RESULTS: Simulation results indicate that the effect of inhibition of blockage of NMDARs by Mg2+ on the false LTP is not as crucial as the effect of NMDAR's conductance modification by opioids. We also observed that activation of VGCCs has a dominant role in inducing pathological LTP. CONCLUSION: Our results confirm that preventing this pathological LTP is possible by three different mechanisms: 1. By decreasing NMDAR's conductance; and 2. By attenuating VGCC's mediated current; and 3. By enhancing glutamate clearance rate from the synapse.

A modified particle swarm optimization algorithm for parameter estimation of a biological system.

BACKGROUND: Mathematical modeling has achieved a broad interest in the field of biology. These models represent the associations among the metabolism of the biological phenomenon with some mathematical equations such that the observed time course profile of the biological data fits the model. However, the estimation of the unknown parameters of the model is a challenging task. Many algorithms have been developed for parameter estimation, but none of them is entirely capable of finding the best solution. The purpose of this paper is to develop a method for precise estimation of parameters of a biological model. METHODS: In this paper, a novel particle swarm optimization algorithm based on a decomposition technique is developed. Then, its root mean square error is compared with simple particle swarm optimization, Iterative Unscented Kalman Filter and Simulated Annealing algorithms for two different simulation scenarios and a real data set related to the metabolism of CAD system. RESULTS: Our proposed algorithm results in 54.39% and 26.72% average reduction in root mean square error when applied to the simulation and experimental data, respectively. CONCLUSION: The results show that the metaheuristic approaches such as the proposed method are very wise choices for finding the solution of nonlinear problems with many unknown parameters.