Complex Behavior Research Articles

Thrombin - A Molecular Dynamics Perspective.

Thrombin is a crucial enzyme involved in blood coagulation, essential for maintaining circulatory system integrity and preventing excessive bleeding. However, thrombin is also implicated in pathological conditions such as thrombosis and cancer. Despite the application of various experimental techniques, including X-ray crystallography, NMR spectroscopy, and HDXMS, none of these methods can precisely detect thrombin's dynamics and conformational ensembles at high spatial and temporal resolution. Fortunately, molecular dynamics (MD) simulation, a computational technique that allows the investigation of molecular functions and dynamics in atomic detail, can be used to explore thrombin behavior. This review summarizes recent MD simulation studies on thrombin and its interactions with other biomolecules. Specifically, the 17 studies discussed here provide insights into thrombin's switch between 'slow' and 'fast' forms, active and inactive forms, the role of Na+ binding, the effects of light chain mutation, and thrombin's interactions with other biomolecules. The findings of these studies have significant implications for developing new therapies for thrombosis and cancer. By understanding thrombin's complex behavior, researchers can design more effective drugs and treatments that target thrombin.

System reliability-based design of composite frames with concrete – filled steel plate shear walls

Nowadays, many high-rise buildings are constructed from concrete-filled steel tubular (CFST) columns and concrete-filled steel plate (CFSP) shear walls due to their superior merits. However, these composite buildings are still designed by traditional load and resistance factor design (LRFD) approach which is conservative and impossible to explicitly capture the complex behaviour of CFST structures. Hence, this paper develops an efficient framework for the system design of CFST structures utilizing nonlinear simulation and reliability analysis. Firstly, a C++ source code for a new material model is developed in OpenSees to capture the behaviour of semi-rigid connections. This material is implemented into the numerical model of CFST structures. Secondly, a framework based on subset simulation is developed for the reliability analysis. This code rigorously considers uncertainties of variables such as numerical model, geometric and material properties or applied loads of both American (US) and Australian (AS) standards. Finally, case study and parametric study are conducted by using the developed framework to propose resistance reduction factors for the investigated frames. The results of the study show that the resistance reduction factor can be taken as 0.8 for both AS and US codes. This proposed factor can be a great source of reference for the system design of CFST buildings with composite shear walls.

Backstepping synchronization control for four-dimensional chaotic system based on DNA strand displacement

Backstepping control is an important nonlinear control design method, which realizes the control of complex systems by constructing control law step by step, and has significant advantages for dealing with complex nonlinear systems. This article proposes a synchronization technique for four-dimensional chaotic systems using a combination of backstepping control method and DNA strand displacement technology. By relying on theoretical knowledge of DNA molecules, five basic chemical reaction modules such as trigger reaction, reference reaction, catalytic reaction, annihilation reaction and degradation reaction are given to construct a four-dimensional DNA chaotic system. On the basis of the relevant theory of chaotic dynamics, the constructed system is analyzed by Lyapunov exponent diagram and spectral entropy complexity algorithm, and the results come to the conclusion that the system reveals extremely complex and varied dynamic behaviors. Combining DNA strand displacement technology with backstepping control method, four controllers are developed to ensure that the trajectories of two homogeneous chaotic systems are synchronized. The numerical simulation results validate the feasibility and applicability of the proposed method. The method proposed in this paper may provide some references in the field of DNA molecular chaos synchronization control.

Spatiotemporal Distribution Characteristics and Influencing Factors of Dissolved Potentially Toxic Elements along Guangdong Coastal Water, South China

In this study, five potentially toxic elements (PTEs) (Hg, Pb, As, Zn, and Cu) and five physicochemical factors (pH, dissolved oxygen, salinity, chlorophyll a, and chemical oxygen demand) relating to surface seawater were measured along the coast of Guangdong Province (GD), China, during three seasons in 2019. Comprehensive analyses were conducted to explore the distribution characteristics, pollution degrees, and influencing factors of PTE. The results showed that the concentrations of PTE varied spatially and seasonally due to these elements’ complex sources and behaviors. Pb was the most abundant toxic element, reaching considerable contamination levels. Overall, the average pollution degrees of Cu, As, and Zn were higher around the east coast of GD, while Hg and Pb levels were higher in the west coast region of GD. The correlation analysis showed that the variation of different physicochemical parameters had different degrees of influence on PTE transport and transformation. This study can help environmental managers gain deeper insight into the influence of complex factors on PTE and improve the efficiency of pollution control in this significant subtropical coastal area.

Tailoring 3D Star-Shaped Auxetic Structures for Enhanced Mechanical Performance

Auxetic lattice structures are three-dimensionally designed intricately repeating units with multifunctionality in three-dimensional space, especially with the emergence of additive manufacturing (AM) technologies. In aerospace applications, these structures have potential for use in high-performance lightweight components, contributing to enhanced efficiency. This paper investigates the design, numerical simulation, manufacturing, and testing of three-dimensional (3D) star-shaped lattice structures with tailored mechanical properties. Finite element analysis (FEA) was employed to examine the effect of a lattice unit’s vertex angle and strut diameter on the lattice structure’s Poisson’s ratio and effective elastic modulus. The strut diameter was altered from 0.2 to 1 mm, while the star-shaped vertex angle was adjusted from 15 to 90 degrees. Laser powder bed fusion (LPBF), an AM technique, was employed to experimentally fabricate 3D star-shaped honeycomb structures made of Ti6Al4V alloy, which were then subjected to compression testing to verify the modelling results. The effective elastic modulus was shown to decrease when increasing the vertex angle or decreasing the strut diameter, while the Poisson’s ratio had a complex behaviour depending on the geometrical characteristics of the structure. By tailoring the unit vertex angle and strut diameter, the printed structures exhibited negative, zero, and positive Poisson’s ratios, making them applicable across a wide range of aerospace components such as impact absorption systems, aircraft wings, fuselage sections, landing gear, and engine mounts. This optimization will support the growing demand for lightweight structures across the aerospace sector.

Control of the chaotic dynamics of the RCLSJ model of the Josephson junction by the frequency of an excitation currentand the internal resistance of a coil

Abstract Abstract In this paper, we controlled the chaotic dynamics of the RCLSJ model of the Josephson junction by the frequency of an excitation current and the internal resistance of an coil. We have used an alternating current source and the internal resistance of the coil of the inductive circuit is considered. The assembly is coupled to a shunted inductive junction (RCLSJ) model where the non-harmonic dynamics of the model is taken into account. The fixed points of the system are determined and are analyzed from the differential equations which govern its dynamics. The numerical results showed that the model studied can be used in direct and alternating conditions depending on the value of the frequency of the excitation current and the phase difference of the junction. In continuous mode, the model exhibits chaotic behavior at the beginning and is regular thereafter. This initial chaotic behavior has become stable due to the internal resistance of the coil. In the alternative regime, the model presents more complex dynamic behaviors. The system behaves like a current adapter depending on the frequency and phase difference conditions of the junction. Comprehensive study of the system reveals many new forks and pathways leading to chaos that have been verified using hardware experiments in addition to numerical calculations.

Chain mail structures in architecture: a systematic, multi-scalar design exploration

Chain mail structures, known for flexibility and adaptability, hold increasing promise for architectural applications, including transportable and reconfigurable systems. However, there is a dearth of knowledge on both systematic methods to design them, and complex behaviours of interlocking modules that comprise the structure. Preliminary studies, in response to this research gap, demonstrate the chain mail’s structural potential as programmable architecture. Nevertheless, to validate our models, we must move from the small scale to recognisably viable structures at an architectural scale.Acknowledging the multiscale prototype’s significance for developing new architectural systems, this study scales up chain mail structures from a small 1:10 scale to larger 1:2 and 1:1 scales. Employing a Research-Through-Design approach, we systematically addressed the challenges, focusing on module fabrication and prototype construction through analogue computation. Fabrication adjustments involve changing materials and modifying designs to suit manufacturing techniques. Additional design elements and process steps are needed to facilitate programming the larger scale structures due to the increased weight during construction. The research culminated in a full-scale saddle-like structure, illustrating the feasibility of direct scaling from smaller to larger scales and the expansive architectural potential of chain mail structures.In conclusion, the study successfully identified and responded to specific challenges related to the fabrication and construction of upscaled chain mail prototypes, aligning solutions with practical contexts. In doing so, this research contributes a set of considerations to enable more systematic design approaches for chain mail structural systems in architecture. At the same time, scaling up uncovers the inherent intelligence of these structures, providing a foundation for both empirical testing through analogue experimentation, and developing a predictive framework for their development and application in the field.

Systems genetics analyses reveals key genes related to behavioral traits in the striatum of CFW mice.

The striatum plays a central role in directing many complex behaviors ranging from motor control to action choice and reward learning. In our study, we used 55 CFW mice with rapid decay linkage disequilibrium to systematically mine the striatum-related behavioral functional genes by analyzing their striatal transcriptomes and 79 measured behavioral phenotypic data. By constructing a gene co-expression network, we clustered the genes into 13 modules, with most of them being positively correlated with motor traits. Based on functional annotations as well as Fisher's exact and hypergeometric distribution tests, brown and magenta modules were identified as core modules. They were significantly enriched for striatal-related functional genes. Subsequent Mendelian randomization analysis verified the causal relationship between the core modules and dyskinesia. Through the intra-modular gene connectivity analysis, Adcy5 and Kcnma1 were identified as brown and magenta module hub genes, respectively. Knockouts of both Adcy5 and Kcnma1 lead to motor dysfunction in mice, and KCNMA1 acts as a risk gene for schizophrenia and smoking addiction in humans. We also evaluated the cellular composition of each module and identified oligodendrocytes in the striatum to have a positive role in motor regulation.Significance Statement The striatum plays a central role in guiding many complex behaviours from motor control to action selection and reward learning. Clinically, striatal dysfunction contributes to a variety of neurodegenerative diseases, including the well-known Alzheimer's disease and Huntington's disease. In our study, we systematically mined striatum-associated behavioural function genes using 55 CFW mice. And we validated our findings in multiple ways. We found that Adcy5 and Kcnma1 knockouts in mice lead to motor dysfunction in mice and that Kcnma1 is associated with schizophrenia, a finding that holds true in humans. Finally, we also assessed the role of different cells in the regulation of striatal behaviour and found that oligodendrocytes in the striatum play an active role in movement regulation.

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories.

Cascade Mesophase Transitions of Multi-enzyme Responsive Polymeric Formulations.

Studying how synthetic polymer assemblies respond to sequential enzymatic stimuli can uncover intricate interactions in biological systems. Using amidase- and esterase-responsive PEG-based diblock (DBA) and triblock amphiphiles (TBAs), we created two distinct formulations: amidase-responsive DBA with esterase-responsive TBA and vice versa. We studied their cascade responses to the two enzymes and the sequence of their introduction. These formulations underwent cascade mesophase transitions upon the addition of the DBA-degrading enzyme, transitioning from (i) coassembled micelles to (ii) triblock-based hydrogel, and ultimately to (iii) dissolved polymers when exposed to the TBA hydrolyzing enzyme. The specific pathway of the two mesophase transitions depended on the compositions of the formulations and the enzyme introduction sequence. The results highlight the potential for designing polymeric formulations with programmable multistep enzymatic responses, mimicking the complex behavior of biological macromolecules.

Zooming into the Complex Dynamics of Electrodermal Activity Recorded during Emotional Stimuli: A Multiscale Approach

Physiological phenomena exhibit complex behaviours arising at multiple time scales. To investigate them, techniques derived from chaos theory were applied to physiological signals, providing promising results in distinguishing between healthy and pathological states. Fractal-like properties of electrodermal activity (EDA), a well-validated tool for monitoring the autonomic nervous system state, have been reported in previous literature. This study proposes the multiscale complexity index of electrodermal activity (MComEDA) to discern different autonomic responses based on EDA signals. This method builds upon our previously proposed algorithm, ComEDA, and it is empowered with a coarse-graining procedure to provide a view at multiple time scales of the EDA response. We tested MComEDA’s performance on the EDA signals of two publicly available datasets, i.e., the Continuously Annotated Signals of Emotion (CASE) dataset and the Affect, Personality and Mood Research on Individuals and Groups (AMIGOS) dataset, both containing physiological data recorded from healthy participants during the view of ultra-short emotional video clips. Our results highlighted that the values of MComEDA were significantly different (p-value < 0.05 after Wilcoxon signed rank test with Bonferroni’s correction) when comparing high- and low-arousal stimuli. Furthermore, MComEDA outperformed the single-scale approach in discriminating among different valence levels of high-arousal stimuli, e.g., showing significantly different values for scary and amusing stimuli (p-value = 0.024). These findings suggest that a multiscale approach to the nonlinear analysis of EDA signals can improve the information gathered on task-specific autonomic response, even when ultra-short time series are considered.

Unveiling the cognitive network organization through cognitive performance

The evaluation of cognitive functions interactions has become increasingly implemented in the cognition exploration. In the present study, we propose to examine the organization of the cognitive network in healthy participants through the analysis of behavioral performances in several cognitive domains. Specifically, we aim to explore cognitive interactions profiles, in terms of cognitive network, and as a function of participants’ handedness. To this end, we proposed several behavioral tasks evaluating language, memory, executive functions, and social cognition performances in 175 young healthy right-handed and left-handed participants and we analyzed cognitive scores, from a network perspective, using graph theory. Our results highlight the existence of intricate interactions between cognitive functions both within and beyond the same cognitive domain. Language functions are interrelated with executive functions and memory in healthy cognitive functioning and assume a central role in the cognitive network. Interestingly, for similar high performance, our findings unveiled differential organizations within the cognitive network between right-handed and left-handed participants, with variations observed both at a global and nodal level. This original integrative network approach to the study of cognition provides new insights into cognitive interactions and modulations. It allows a more global understanding and consideration of cognitive functioning, from which complex behaviors emerge.

Consensus Paper: Cerebellum and Reward.

Cerebellum is a key-structure for the modulation of motor, cognitive, social and affective functions, contributing to automatic behaviours through interactions with the cerebral cortex, basal ganglia and spinal cord. The predictive mechanisms used by the cerebellum cover not only sensorimotor functions but also reward-related tasks. Cerebellar circuits appear to encode temporal difference error and reward prediction error. From a chemical standpoint, cerebellar catecholamines modulate the rate of cerebellar-based cognitive learning, and mediate cerebellar contributions during complex behaviours. Reward processing and its associated emotions are tuned by the cerebellum which operates as a controller of adaptive homeostatic processes based on interoceptive and exteroceptive inputs. Lobules VI-VII/areas of the vermis are candidate regions for the cortico-subcortical signaling pathways associated with loss aversion and reward sensitivity, together with other nodes of the limbic circuitry. There is growing evidence that the cerebellum works as a hub of regional dysconnectivity across all mood states and that mental disorders involve the cerebellar circuitry, including mood and addiction disorders, and impaired eating behaviors where the cerebellum might be involved in longer time scales of prediction as compared to motor operations. Cerebellar patients exhibit aberrant social behaviour, showing aberrant impulsivity/compulsivity. The cerebellum is a master-piece of reward mechanisms, together with the striatum, ventral tegmental area (VTA) and prefrontal cortex (PFC). Critically, studies on reward processing reinforce our view that a fundamental role of the cerebellum is to construct internal models, perform predictions on the impact of future behaviour and compare what is predicted and what actually occurs.

Ethical Considerations in AI Simulations for Designing Assistive Technologies

Current ethical debates on the use of artificial intelligence (AI) in healthcare approach AI technology in three primary ways. First, they assess the risks and potential benefits of current AI-enabled products using ethical checklists. Second, they propose ex ante lists of ethical values relevant to the design and development of assistive technologies. Third, they advocate for incorporating moral reasoning into AI's automation processes. These three perspectives dominate the discourse, as evidenced by a brief literature summary. We propose a fourth approach: viewing AI as a methodological tool to aid ethical reflection. This involves an AI simulation concept informed by three elements: 1) stochastic human behavior models based on behavioral data for simulating realistic scenarios, 2) qualitative empirical data on value statements regarding internal policy, and 3) visualization components to illustrate the impact of variable changes. This approach aims to inform an interdisciplinary field about anticipated ethical challenges or trade-offs in specific settings, prompting a re-evaluation of design and implementation plans. This is particularly useful for applications involving complex values and behaviors or limited communication resources, such as dementia care or care for individuals with cognitive impairments. While simulation does not replace ethical reflection, it allows for detailed, context-sensitive analysis during the design process and before implementation.Finally, we discuss the quantitative analysis methods enabled by stochastic simulations and the potential for these simulations to enhance traditional thought experiments and future-oriented technology assessments.

Oscillating latent dynamics in robot systems during walking and reaching.

Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditionally employ hierarchical optimisation approaches or black-box policies, recent results in systems neuroscience suggest that complex behaviours such as locomotion and reaching are correlated with limit cycles in the primate motor cortex. A recent result suggests that, when applied to a learned latent space, oscillating patterns of activation can be used to control locomotion in a physical robot. While reminiscent of limit cycles observed in primate motor cortex, these dynamics are unsurprising given the cyclic nature of the robot's behaviour (walking). In this preliminary investigation, we consider how a similar approach extends to a less obviously cyclic behaviour (reaching). This has been explored in prior work using computational simulations. But simulations necessarily make simplifying assumptions that do not necessarily correspond to reality, so do not trivially transfer to real robot platforms. Our primary contribution is to demonstrate that we can infer and control real robot states in a learnt representation using oscillatory dynamics during reaching tasks. We further show that the learned latent representation encodes interpretable movements in the robot's workspace. Compared to robot locomotion, the dynamics that we observe for reaching are not fully cyclic, as they do not begin and end at the same position of latent space. However, they do begin to trace out the shape of a cycle, and, by construction, they are driven by the same underlying oscillatory mechanics.

Introducing Chiro-optical Activities in Photonic Synapses for Neuromorphic Computing and In-Memory Logic Operations.

In artificial synaptic devices aimed at mimicking neuromorphic computing systems, electrical or optical pulses, or both, are generally used as stimuli. In this work, we introduce chiral materials for tailoring the characteristics of photonic synaptic devices to achieve handedness-dependent neuromorphic computing and in-memory logic gates. In devices based on a pair of chiral perovskites, the use of circularly polarized light (CPL) as the optical stimuli mimicked a series of electrical and opto-synaptic functionalities in order to emulate the multifunctional complex behavior of the human brain. Upon illumination in this two-terminal device, anisotropy in current has been observed due to the out-of-plane carrier transport, originating from spin-selective carrier transport. More importantly, the logic gate achieved in devices based on optoelectronic memristors turned out to be chirality-dependent; while an R-device functioned as an AND gate, the device based on the same perovskite of the opposite chirality (S-device) acted as a NOR gate toward in-memory logic operations. These findings in chiral perovskite-based artificial synapses can identify further strategies for future neuromorphic computing, vision simulation, and artificial intelligence.

Debris‐flow entrainment modelling under climate change: Considering antecedent moisture conditions along the flow path

AbstractDebris‐flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris‐flow properties available at a Swiss debris‐flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process‐based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris‐flow entrainment is then predicted using the RAMMS debris‐flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel‐bed erodibility for single‐surge debris‐flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris‐flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris‐flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation‐dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Left and Right‐Handed Light Reflection and Emission in Ultrathin Cellulose Nanocrystals Films with Printed Helicity

AbstractNatural polymers, particularly plant‐derived nanocelluloses, self‐organize into hierarchical structures, enabling mechanical robustness, bright iridescence, emission, and polarized light reflection. These biophotonic properties are facilitated by the assembly of individual components during evaporation, such as cellulose nanocrystals (CNCs), which exhibit a left‐handed helical pitch in a chiral nematic state. This work demonstrates how optically active films with pre‐programmed opposite handedness (left or right) can be constructed via shear‐induced twisted printing with clockwise and counter‐clockwise shearing vectors. The resulting large‐area thin films are transparent yet exhibit pre‐determined mirror‐symmetrical optical activity, enabling the distinction of absorbed and emitted circularly polarized light. This processing method allows for sequential printing of thin and ultrathin films with twisted layered organization and on‐demand helicity. The complex light polarization behavior is due to step‐like changes in linear birefringence within each deposited layer and circular birefringence, different from that of conventional CNC films as revealed with Muller matrix analysis. Furthermore, intercalating an achiral organic dye into printed structures induces circularly polarized luminescence while preserving high transmittance and controlled handedness. These results suggest that twisted sequential printing can facilitate the construction of chiroptical metamaterials with tunable circular polarization, absorption, and emission for optical filters, encryption, photonic coatings, and chiral sensors.

Growth and addition in a herding model with fractional orders of derivatives

Abstract This work involves an investigation of the mechanics of the herding behaviour using a non-linear timescale, with the aim to generalize the herding model which helps to explain frequently occurring complex behaviour in the real world, such as the financial markets. A herding model with fractional order of derivatives was developed. This model involves the use of derivatives of order α where 0<α ≤1. We have found the generalized result that the number of groups of agents with size k increases linearly with time as nk={p(2p-1)(2-α)/[p(1-α)+1]}Γ(α+(2-α)/(1-p){Γ(k)/[Γ(k-1+α+(2-α)/(1-p))}t for α ∈ (0,1], where p is a growth parameter. The result reduces to that in a previous herding model with derivative order of 1 for α=1. The results corresponding to various values of α and p are presented. The group size distribution at long time is found to decay as a generalized power law, with an exponent depending on both α and p, thereby demonstrating that the scale invariance property of a complex system holds regardless of the order of the derivatives. The physical interpretation of fractional differentiation and fractional integration is also explored based on the results of this work.

Eye-specific detection and a multi-eye integration model of biological motion perception.

'Biological motion' refers to the distinctive kinematics observed in many living organisms, where visually-observable points on the animal move at fixed distances from each other. Across the animal kingdom, many species have developed specialized visual circuitry to recognize such biological motion and to discriminate it from other patterns. Recently, this ability has been observed in the distributed visual system of jumping spiders. These eight-eyed animals usesix eyes to perceive motion, while the remaining two (the principal anterior-medial eyes) are shifted across the visual scene to further inspect detected objects. When presented with a biologically moving stimulus and a random one, jumping spiders turn to face the latter, clearly demonstrating the ability to discriminate between them. However, it remains unclear if the principal eyes are necessary for this behavior, whether all secondary eyes can perform this discrimination, or if a single eye-pair is specialized for this task. Here, we systematically tested the ability of jumping spiders to discriminate between biological and random visual stimuli by testing each eye-pair alone. Spiders were able to discriminate stimuli only when the anterior-lateral eyes were unblocked, and performed at chance levels in other configurations. Interestingly, spiders showed a preference for biological motion over random stimuli-unlike in past work. We therefore propose a new model describing how specialization of the anterior-lateral eyes for detecting biological motion contributes to multi-eye integration in this system. This integration generates more complex behavior through the combination of simple, single-eye responses. We posit that this in-built modularity may be a solution to the limited resources of these invertebrates' brains-constituting a novel approach to visual processing.