Biological Cybernetics最新文献

{"title":"Delay suppression control of β-oscillations: a proposal for dual-target adaptive deep brain stimulation on STN-GPe network model.","authors":"Jaderson G Polli, Florian Kolbl, M G E da Luz, P Lanusse","doi":"10.1007/s00422-025-01021-5","DOIUrl":"10.1007/s00422-025-01021-5","url":null,"abstract":"<p><p>Parkinson's Disease (PD) is a neurodegenerative disorder associated with Basal Ganglia (BG) dysfunction, where abnormal neuronal β-oscillations ([Formula: see text] Hz) have been shown to correlate with motor symptoms. Non-pharmacological therapies are based on Deep Brain Stimulation (DBS), delivering electric current waveform with constant frequency and amplitude to BG regions, commonly single targeting either the Subthalamic Nucleus (STN) or the Globus Palidus (GP). More recently, studies have also employed dual-target stimulation, which may synergistically increase therapeutic benefit. Additionally, novel designs of adaptive DBS (aDBS) with closed-loop feedback aim to further enhance efficiency when compared to open-loop procedures, while enabling it to deal with patient variability and disease progression. In this way, here we propose a dual-target aDBS controller, considering a computational model for STN-GPe circuit. Its goal is to suppress the mentioned oscillations at any stage of illness development and synaptic and connectivity parameters ranges, hence in principle adjustable to distinct patient conditions. The control method generally addresses the STN-GPe circuit as a nonlinear-delayed dynamical system, employing a robust technique of delay compensation. The controller architecture relies on recording and stimulating both STN and GPe, also using a straightforward predictor algorithm to select the external inputs for the STN-GPe circuit. The stimulation inputs consist of initial simple brief pulses that suppress or shift the onset of β-oscillations. Then, weak amplitude signals are enough to sustain the achieved stabilization. The protocol has been fully simulated considering an in silico model. Within such theoretical framework, it was shown to be extremely efficient if the processing time is not too long. The dual-target aDBS put forward here is based on implementable technologies, thus potentially amenable to novel strategies for biomedical close-loop approaches. But concrete challenges for doing so are also discussed.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"21"},"PeriodicalIF":1.6,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144746051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding human visual foraging: a review.","authors":"Tómas Kristjánsson, Árni Kristjánsson","doi":"10.1007/s00422-025-01020-6","DOIUrl":"10.1007/s00422-025-01020-6","url":null,"abstract":"<p><p>Visual foraging tasks provide great insights into how organisms orient within their visual environment. These tasks are useful for simultaneously investigating concepts often addressed separately, such as attentional guidance, working memory, and strategy. Foraging tasks enable the study of continuous real-world visual exploration and how information about the environment is gathered. They yield rich and multifaceted datasets and can provide insights into the mechanisms of visual attention, visual search, visual memory, and other cognitive factors in a setting more closely resembling how we employ those factors in the real world. We provide a review of the literature and discuss the pros and cons of different ways of understanding and explaining human foraging. A popular approach has been to test whether foraging performance fits certain mathematical rules, such as the marginal value theorem, or so-called Lévy flights. We question the usefulness of such approaches, in particular in the context human foraging (or the foraging of any organism with a sizeable nervous system). The goals and rewards that determine foraging behavior are multifaceted, and understanding those will bring us closer to understanding how humans interact with the world. The usefulness of assessing whether performance falls in line with a particular mathematical rule is, in our opinion, questionable and resources may have been wasted on trying to answer such questions, instead of focusing on the rich insights that foraging data provides about vision, attentional selection, visual short-term memory and the gathering of information.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"20"},"PeriodicalIF":1.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coding odor modality in piriform cortex efficiently with low-dimensional subspaces: a shared covariance decoding approach.","authors":"Delaney M Selb, Andrea K Barreiro, Shree Hari Gautam, Woodrow L Shew, Cheng Ly","doi":"10.1007/s00422-025-01015-3","DOIUrl":"10.1007/s00422-025-01015-3","url":null,"abstract":"<p><p>A fundamental question in neuroscience is how sensory signals are decoded from noisy cortical activity. We address this question in the olfactory system, decoding the route by which odorants arrive into the nasal cavity: through the nostrils (orthonasal), or through the back of the throat (retronasal). We recently showed with modeling and novel experiments on anesthetized rats that orthonasal versus retronasal modality information is encoded in the olfactory bulb (OB, a pre-cortical region). However, key questions remain: is modality information transmitted from OB to anterior piriform cortex (aPC)? How can this information be extracted from a much noisier cortical population with overall less firing? With simultaneous spike recordings of populations of neurons in OB and aPC, we show that an unsupervised and biologically plausible algorithm, Shared Covariance Decoding (SCD), can indeed linearly encode modality in low dimensional subspaces. Specifically, SCD improves encoding of ortho/retro in aPC compared to Fisher's linear discriminant analysis (LDA). Consistent with our theoretical analysis, when noise correlations between OB and aPC are low and OB well-encodes modality, modality in aPC tends to be encoded optimally with SCD. We observe that with several algorithms (LDA, SCD, optimal) the decoding accuracy distributions are invariant when GABA[Formula: see text] (ant-)agonists (bicuculline and muscimol) are applied to OB, which is consistent with invariance in population firing in aPC. Overall, we show modality information can be encoded efficiently in piriform cortex.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"19"},"PeriodicalIF":1.6,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144592989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Basal ganglia: an amplifier for preparatory activity in motor control.","authors":"Serhat Çağdaş, Neslihan Serap Şengör","doi":"10.1007/s00422-025-01016-2","DOIUrl":"10.1007/s00422-025-01016-2","url":null,"abstract":"<p><p>The basal ganglia make a significant contribution to the generation of motor behavior through their involvement in the descending motor pathways. Gaining insight into how the motor cortex produces motor patterns is also a key to understanding the function of the basal ganglia. The population dynamics approach is convenient for the reevaluation of the behavior of the motor cortex and also the roles of other components in the motor system. Here, it is proposed that the basal ganglia amplify preparatory activity in the motor cortex with the modulatory effect of phasic dopamine release. The influence of the basal ganglia is tested with a computational model on a center-out-reaching task. The results show that the basal ganglia facilitate movement initiation and increase the robustness of the behavior. These results, based on the perspective of population dynamics, may improve our understanding of the role of the basal ganglia in motor control and the symptoms of dopamine-related conditions in neurodegenerative diseases of motor control.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"18"},"PeriodicalIF":1.6,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144576994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating buccal mass planar mechanics and anatomical features improves neuromechanical modeling of Aplysia feeding behavior.","authors":"Michael J Bennington, Ashlee S Liao, Ravesh Sukhnandan, Bidisha Kundu, Stephen M Rogers, Jeffrey P Gill, Jeffrey M McManus, Gregory P Sutton, Hillel J Chiel, Victoria A Webster-Wood","doi":"10.1007/s00422-025-01017-1","DOIUrl":"10.1007/s00422-025-01017-1","url":null,"abstract":"<p><p>To understand how behaviors arise in animals, it is necessary to investigate both the neural circuits and the biomechanics of the periphery. A tractable model system for studying multifunctional control is the feeding apparatus of the marine mollusk Aplysia californica. Previous in silico and in roboto models have investigated how the nervous and muscular systems interact in this system. However, these models are still limited in their ability to match in vivo data both qualitatively and quantitatively. We introduce a new neuromechanical model of Aplysia feeding that combines a modified version of a previously developed neural model with a novel biomechanical model that better reflects the anatomy and kinematics of Aplysia feeding. The model was calibrated using a combination of previously measured biomechanical parameters and hand-tuning to behavioral data. Using this model, simulated feeding experiments were conducted, and the resulting behavioral metrics were compared to animal data. The model successfully produces three key behaviors seen in Aplysia and demonstrates a good quantitative agreement with biting and swallowing behaviors. Additional work is needed to match rejection behavior quantitatively and to reflect qualitative observations related to the relative contributions of two key muscles, the hinge and I3. Future improvements will focus on incorporating the effects of deformable 3D structures in the simulated buccal mass.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"17"},"PeriodicalIF":1.6,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234631/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144576995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence meets brain theory (again).","authors":"Michael A Arbib","doi":"10.1007/s00422-025-01013-5","DOIUrl":"10.1007/s00422-025-01013-5","url":null,"abstract":"<p><p>After noting the cybernetic origins of Kybernetik/ Biological Cybernetics, we respond to the Editorial by Fellous et al. (2025) and then analyze talks from the NIH BRAIN NeuroAI 2024 Workshop to get one \"snapshot\" of the state of the conversation between Artificial intelligence (AI) and brain theory (BT). Key recommendations going beyond the earlier Editorial are that: (i) Successes in fitting ANNs to increasingly large neuroscience datasets must not distract us from the quixotic but demanding quest to understand \"how the brain works\" and discover underlying brain (and AI) operating principles. (ii) We must integrate functional and structural analyses in exploring systems of systems, integrating structures (e.g., brain regions, cortical modules) and functions (e.g., schemas for perception, action and cognition) that bridge between neural circuitry and patterns of behavior. (iii) We must study the diversity of intelligences exhibited by animals in their strategies for survival and not only the disembodied employment of language and reasoning. Finally and briefly, we note the urgency of assessing the societal implications of an age of increasingly pervasive human-machine symbiosis.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 4-6","pages":"16"},"PeriodicalIF":1.6,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204934/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144512793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationships between the degrees of freedom in the affine Gaussian derivative model for visual receptive fields and 2-D affine image transformations with application to covariance properties of simple cells in the primary visual cortex.","authors":"Tony Lindeberg","doi":"10.1007/s00422-025-01014-4","DOIUrl":"10.1007/s00422-025-01014-4","url":null,"abstract":"<p><p>When observing the surface patterns of objects delimited by smooth surfaces, the projections of the surface patterns to the image domain will be subject to substantial variabilities, as induced by variabilities in the geometric viewing conditions, and as generated by either monocular or binocular imaging conditions, or by relative motions between the object and the observer over time. To first order of approximation, the image deformations of such projected surface patterns can be modelled as local linearizations in terms of local 2-D spatial affine transformations. This paper presents a theoretical analysis of relationships between the degrees of freedom in 2-D spatial affine image transformations and the degrees of freedom in the affine Gaussian derivative model for visual receptive fields. For this purpose, we first describe a canonical decomposition of 2-D affine transformations on a product form, closely related to a singular value decomposition, while in closed form, and which reveals the degrees of freedom in terms of (i) uniform scaling transformations, (ii) an overall amount of global rotation, (iii) a complementary non-uniform scaling transformation and (iv) a relative normalization to a preferred symmetry orientation in the image domain. Then, we show how these degrees of freedom relate to the degrees of freedom in the affine Gaussian derivative model. Finally, we use these theoretical results to consider whether we could regard the biological receptive fields in the primary visual cortex of higher mammals as being able to span the degrees of freedom of 2-D spatial affine transformations, based on interpretations of existing neurophysiological experimental results.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 2-3","pages":"15"},"PeriodicalIF":1.7,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12176974/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-Inspired spiking tactile sensing system for robust texture recognition across varying scanning speeds in passive touch.","authors":"Fatemeh Yavari, Ali Motie Nasrabadi, Fereidoun Nowshiravan Rahatabad, Mahmood Amiri","doi":"10.1007/s00422-025-01012-6","DOIUrl":"10.1007/s00422-025-01012-6","url":null,"abstract":"<p><p>Tactile sensing plays a crucial role in texture recognition, but variations in scanning speed pose a significant challenge for accurate discrimination. Previous studies have demonstrated that scanning speed alters the frequency of texture-induced vibrations, necessitating methods for speed encoding. In this study, we propose a bio-inspired spiking tactile sensing system that integrates mechanoreceptor responses with coincidence detector neurons to encode both texture and velocity without relying on external speed sensors. Our method enables speed and texture recognition in both active and passive touch scenarios by leveraging spike timing information from mechanoreceptors. We evaluated the robustness of our approach by introducing Gaussian noise into the neural encoding process, demonstrating that the model maintains stable accuracy with minimal degradation across different noise levels. The proposed artificial tactile system achieves an impressive 93% accuracy in jointly classifying texture and speed. Compared to prior methods, our model provides a biologically plausible solution to real-world tactile sensing challenges. This research offers a robust framework for texture recognition in prosthetic devices, robotic hands, and autonomous systems operating in unstructured environments.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 2-3","pages":"14"},"PeriodicalIF":1.7,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144295433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian Dynamical Modeling of Fixational Eye Movements.","authors":"Lisa Schwetlick, Sebastian Reich, Ralf Engbert","doi":"10.1007/s00422-025-01010-8","DOIUrl":"10.1007/s00422-025-01010-8","url":null,"abstract":"<p><p>Humans constantly move their eyes, even during visual fixations, where miniature (or fixational) eye movements occur involuntarily. Fixational eye movements comprise slow components (physiological drift and tremor) and fast components (microsaccades). The complex dynamics of physiological drift can be modeled qualitatively as a statistically self-avoiding random walk (SAW model, Engbert et al., 2011). In this study, we implement a data assimilation approach for the SAW model to explain statistics of fixational eye movements and microsaccades in experimental data obtained from high-resolution eye-tracking. We discuss and analyze the likelihood function for the SAW model, which allows us to apply Bayesian parameter estimation at the level of individual human observers. Based on model fitting, we find a relationship between the activation predicted by the SAW model and the occurrence of microsaccades. The model's latent activation relative to microsaccade onsets and offsets using experimental data lends support to the existence of a triggering mechanism for microsaccades. Our findings suggest that the SAW model can capture individual differences and serve as a tool for exploring the relationship between physiological drift and microsaccades as the two most essential components of fixational eye movements. Our results contribute to understanding individual variability in microsaccade behaviors and the role of fixational eye movements in visual information processing.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 2-3","pages":"13"},"PeriodicalIF":1.7,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12149266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decreased spinal inhibition leads to undiversified locomotor patterns.","authors":"Myriam Lauren de Graaf, Heiko Wagner, Luis Mochizuki, Charlotte Le Mouel","doi":"10.1007/s00422-025-01011-7","DOIUrl":"10.1007/s00422-025-01011-7","url":null,"abstract":"<p><p>During walking and running, animals display rich and coordinated motor patterns that are generated and controlled within the central nervous system. Previous computational and experimental results suggest that the balance between excitation and inhibition in neural circuits may be critical for generating such structured motor patterns. In this paper, we explore the influence of this balance on the ability of a reservoir computing artificial neural network to learn human locomotor patterns, using mean-field theory and simulations. We created networks with varying neuron numbers, connection percentages and connection strengths for the excitatory and inhibitory neuron populations, and introduced the anatomical imbalance that quantifies the overall effect of the two populations. We trained the networks to reproduce muscle activation patterns derived from human recordings and evaluated their performance. Our results indicate that network dynamics and performance depend critically on the anatomical imbalance in the network. Excitation-dominated networks lead to saturated firing rates, thereby reducing the firing rate heterogeneity and leading to muscle coactivation and inflexible motor patterns. Inhibition-dominated networks, on the other hand, perform well, displaying balanced input to the neurons and sufficient heterogeneity in the neuron firing rate patterns. This suggests that motor pattern generation may be robust to increased inhibition but not increased excitation in neural networks.</p>","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"119 2-3","pages":"12"},"PeriodicalIF":1.7,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137539/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}