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adaptive coding of reward in schizophrenia, its change over time and relationship to apathy

BRAIN 2024年第7期147卷 2459-2470页

作者： Kaliuzhna, Mariia Carruzzo, Fabien Kuenzi, Noemie Tobler, Philippe N. Kirschner, Matthias Geffen, Tal Katthagen, Teresa Boege, Kerem Zierhut, Marco M. Schlagenhauf, Florian Kaiser, Stefan Univ Geneva Dept Psychiat Clin & Expt Psychopathol Lab CH-1205 Geneva Switzerland Geneva Univ Hosp Dept Psychiat CH-1205 Geneva Switzerland Univ Zurich Dept Econ Lab Social & Neural Syst Res CH-8006 Zurich Switzerland Charite Univ Med Berlin Dept Psychiat & Psychotherapy D-10117 Berlin Germany Batiment Voirons Chemin Petit Bel Air 2 CH-1226 Thonex Switzerland

adaptive coding of reward is the process by which neurons adapt their response to the context of available compensations. Higher rewards lead to a stronger brain response, but the increase of the response depends on the range of available rewards. A steeper increase is observed in a narrow range and a more gradual slope in a wider range. In schizophrenia, adaptive coding appears to be affected in different domains, especially in the reward domain. Here, we tested adaptive coding of reward in a large group of patients with schizophrenia (n = 86) and control subjects (n = 66). We assessed: (i) the association between adaptive coding deficits and symptoms;(ii) the longitudinal stability of deficits (the same task was performed 3 months apart);and (iii) the stability of results between two experimental *** used functional MRI and the monetary incentive delay task to assess adaptation of participants to two different reward ranges: a narrow range and a wide range. We used a region-of-interest analysis to evaluate adaptation within striatal and visual regions. Patients and control subjects underwent a full demographic and clinical *** found reduced adaptive coding in patients, with a decreased slope in the narrow reward range with respect to that of control participants, in striatal but not visual regions. This pattern was observed at both research sites. Upon retesting, patients increased their narrow-range slopes, showing improved adaptive coding, whereas control subjects slightly reduced them. At retesting, patients with overly steep slopes in the narrow range also showed higher levels of negative *** data confirm deficits in reward adaptation in schizophrenia and reveal an effect of practice in patients, leading to improvement, with steeper slopes upon retesting. However, in some patients, an excessively steep slope may result in poor discriminability of larger rewards, owing to early saturation of the brain response. Together, the loss of prec

关键词： adaptive coding schizophrenia reward functional MRI monetary incentive delay task negative symptoms

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adaptive coding and Ordered-Index Extended Scrambling Based RDH in Encrypted Images

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IEEE TRANSACTIONS ON MULTIMEDIA 2023年 25卷 2864-2875页

作者： Chen, Fan Yang, Yaolin He, Hongjie Yuan, Yuan Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 611756 Peoples R China

Reversible data hiding in encrypted images (RDHEI) technique can be used to realize privacy protection and management in the image outsourcing scenario. Most existing RDHEI schemes focus on increasing the maximum embedding rate (Max-ER), but not paying much attention to the security improvement under various attacks. In this paper, a RDHEI method based on the adaptive bit-plane (ABP) coding is proposed to improve the Max-ER. The order-index extended scrambling (OIES) encryption scheme is also developed to strengthen the RDHEI's ability of thwarting various attacks. The effectiveness of ABP coding is achieved by proper selections of the threshold. The OIES enables the design of a novel scramble-key (SK) generation method to greatly reduce the probability of generating the same SK by the same user-key. This significantly improves the ability of resisting various attacks in that the attack on the scrambling encryption is mainly via the SK rather than the user-key estimation. Analysis shows that the probability of OIES obtaining the same SK is reduced from 1.0 to 0.01 for different images and to 1/2(a) for the same image. Simulation results demonstrate that the proposed ABP coding and OIES schemes outperform the state-of-the-art RDHEI algorithms in terms of the Max-ER and ability against various attacks.

关键词： Reversible data hiding image encryption adaptive coding extended scrambling chosen plaintext attack (CPA)

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adaptive coding IN WIRELESS ACOUSTIC SENSOR NETWORKS FOR DISTRIBUTED BLIND SYSTEM IDENTIFICATION 57

ADAPTIVE CODING IN WIRELESS ACOUSTIC SENSOR NETWORKS FOR DIS...

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57th Asilomar Conference on Signals, Systems and Computers

作者： Blochberger, M. Ostergaard, J. Ali, R. Moonen, M. Elvander, F. Jensen, J. van Waterschoot, T. Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS Leuven Belgium Aalborg Univ Dept Elect Syst Aalborg Denmark Univ Surrey Dept Mus & Media Guildford Surrey England Aalto Univ Dept Informat & Commun Engn Espoo Finland

ISBN: (纸本)9798350325744

With distributed signal processing gaining traction in the audio and speech processing landscape through the utilization of interconnected devices constituting wireless acoustic sensor networks, additional challenges arise, including optimal data transmission between devices. In this paper, we extend an adaptive distributed blind system identification algorithm by introducing a residual-based adaptive coding scheme to minimize communication costs within the network. We introduce a coding scheme that takes advantage of the convergence of estimates, i.e., vanishing residuals, to minimize information being sent. The scheme is adaptive, i.e., tracks changes in the estimated system and utilizes entropy coding and adaptive gain to fit the time-varying residual variance to pre-trained codebooks. We use a low-complexity approach for gain adaptation, based on a recursive variance estimate. We demonstrate the approach's effectiveness with numerical simulations and its performance in various scenarios.

关键词： adaptive coding blind system identification alternating direction method of multipliers

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Comparing adaptive coding of reward in bipolar I disorder and schizophrenia

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HUMAN BRAIN MAPPING 2023年第2期44卷 523-534页

作者： Kaliuzhna, Mariia Kirschner, Matthias Tobler, Philippe N. Kaiser, Stefan Univ Geneva Dept Psychiat Clin & Expt Psychopathol Grp Geneva Switzerland McGill Univ Montreal Neurol Inst Montreal PQ Canada Univ Zurich Dept Econ Lab Social & Neural Syst Res Zurich Switzerland Univ Zurich Psychiat Hosp Dept Psychiat Psychotherapy & Psychosomat Zurich Switzerland

Deficits in neural processing of reward have been described in both bipolar disorder (BD) and schizophrenia (SZ), but it remains unclear to what extent these deficits are caused by similar mechanisms. Efficient reward processing relies on adaptive coding which allows representing large input spans by limited neuronal encoding ranges. Deficits in adaptive coding of reward have previously been observed across the SZ spectrum and correlated with total symptom severity. In the present work, we sought to establish whether adaptive coding is similarly affected in patients with BD. Twenty-five patients with BD, 27 patients with SZ and 25 healthy controls performed a variant of the Monetary Incentive Delay task during functional magnetic resonance imaging in two reward range conditions. adaptive coding was impaired in the posterior part of the right caudate in BD and SZ (trend level). In contrast, BD did not show impaired adaptive coding in the anterior caudate and right precentral gyrus/insula, where SZ showed deficits compared to healthy controls. BD patients show adaptive coding deficits that are similar to those observed in SZ in the right posterior caudate. adaptive coding in BD appeared more preserved as compared to SZ participants especially in the more anterior part of the right caudate and to a lesser extent also in the right precentral gyrus. Thus, dysfunctional adaptive coding could constitute a fundamental deficit in severe mental illnesses that extends beyond the SZ spectrum.

关键词： adaptive coding bipolar disorder fMRI monetary incentive delay task reward processing schizophrenia

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adaptive coding Strategy for User-side Resource and Power Grid Interaction Service 12

Adaptive Coding Strategy for User-side Resource and Power Gr...

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12th International Conference on Power, Energy and Electrical Engineering (CPEEE)

作者： Gong, Feixiang Chen, Songsong Tian, Shiming Hao, Yihao Li, Bin China Elect Power Res Inst Co Ltd Beijing 100192 Peoples R China

ISBN: (纸本)9781665420495

Demand response (DR) continues to deepen the practice, the future needs to rely on highly reliable information interaction to support fine DR control. Aiming at the communication optimization problem of DR wireless communication, this paper designs a double-layer adaptive coding strategy based on real-time monitoring of signal-to-noise ratio and real-time acquisition of broadcast messages from DR master station on the premise of analyzing the quality of service requirements of all kinds of DR services. The proposed strategy uses adaptive precoding technology to optimize DR wireless communication, classifies the communication quality of service according to the specific period of time during the implementation of DR, and considers the computational cost introduced by the algorithm. The simulation results show that the strategy has a good optimization effect in the system bit error rate and processing delay control.

关键词： demand response information exchange precoding adaptive coding

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adaptive coding and Bit-Power Loading Algorithms for Underwater Acoustic Transmissions

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2021年第9期20卷 5798-5811页

作者： Zhang, Rongxin Ma, Xiaoli Wang, Deqing Yuan, Fei Cheng, En Xiamen Univ Sch Elect Sci & Engn Natl Model Microelect Coll Xiamen 361005 Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Xiamen Univ Key Lab Underwater Acoust Commun & Marine Informa Minist Educ Xiamen 361005 Peoples R China

Underwater acoustic channel (UAC) is featured as fast time-varying characteristic, and challenges the transmission designs. To countermine the time variation effect, we propose an adaptive design for orthogonal frequency division multiplexing (OFDM) transmission systems by utilizing the long-term stability of the second-order statistics of the channel state information (CSI). We derive the analytical expression of signal-to-interference-plus-noise-ratio (SINR) at each subcarrier to reach the target error performance based on the statistical information of the CSI. Thereafter, a new adaptive coding and bit-power loading algorithm with low computational complexity is proposed to pursuit the highest achievable bit rate with fixed error rate. The validity of SINR calculations and the effectiveness of the proposed adaptive algorithm are demonstrated under various conditions, wherein both simulated and measured channels have been tested.

关键词： Loading Signal to noise ratio OFDM Covariance matrices Wireless communication Modulation Gaussian distribution adaptive coding bit loading power loading underwater transmissions statistical channel state information

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Selective Weighted adaptive coding

Selective Weighted Adaptive Coding

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Data Compression Conference (DCC)

作者： Gross, Yoav Klein, Shmuel T. Opalinsky, Elina Shapira, Dana Ariel Univ Dept Comp Sci IL-40700 Ariel Israel Bar Ilan Univ Dept Comp Sci IL-52900 Ramat Gan Israel

ISBN: (纸本)9781665478939

Unlike the uniform treatment of symbols in different locations of an input file, a new approach is taken in the weighted dynamic compression method suggested in [1], which assigns higher priority to closer to be encoded symbols by means of an increasing weight function. The weighted method is especially suited for the encoding of files with locally skewed distributions. Empirical results have shown that weighted techniques can improve beyond the lower bound given by the entropy for static encoding.

关键词： Symbols Encoding Entropy adaptive coding

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A convolutional spiking neural network with adaptive coding for motor imagery classification

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NEUROCOMPUTING 2023年第1期549卷

作者： Liao, Xiaojian Wu, Yuli Wang, Zi Wang, Deheng Zhang, Hongmiao Soochow Univ Sch Mech & Elect Engn Jiangsu Prov Key Lab Adv Robot Suzhou 215000 Peoples R China Shanghai Univ Tradit Chinese Med Sch Basic Med Sci Shanghai 201203 Peoples R China

Motor imagery (MI) signal classification is crucial for brain-computer interfaces (BCI). The third-generation neural network, spiking neural network (SNN), has rich neurodynamic properties in the spa-tiotemporal domain, and therefore it is more suitable for processing EEG signals. However, the feature extraction capability of the SNN previously applied to MI signal classification is limited by its structure, and the model's classification accuracy is not comparable to the state-of-the-art algorithms. In this paper, we propose a spiking neural network model called SCNet, which combines the feature extraction capa-bility of CNN with the biological interpretability of SNN, making the model structurally closer to the bio-logical neuronal dynamical system and improving the classification accuracy. SCNet reduces information loss by adaptive coding with learnability and solves the training difficulties of spiking neural networks by surrogate gradient learning. We evaluated the performance of the proposed SCNet on three typically rep-resentative motor imagery datasets. The validation shows that the model outperforms state-of-the-art SNN-based MI classification methods and various ANN and machine learning methods. The experimental results demonstrate the generality and effectiveness of the proposed motor imagery EEG signal classifi-cation model. Better classification results can be obtained by designing a well-structured spiking neural network.& COPY;2023 Elsevier B.V. All rights reserved.

关键词： Spiking neural network Motor imagery adaptive coding

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Reversible Data Hiding With Secret Encrypted Image Sharing and adaptive coding

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IEEE Internet of Things Journal 2025年

作者： Fang, Guangtian Wang, Feng Zhao, Chenbin Qin, Chuan Chang, Ching-Chun Chang, Chin-Chen Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Fujian University of Technology College of Computer Science and Mathematics Key Laboratory of Big Data Mining and Applications Fuzhou350118 China Monash University Faculty of IT Department of Software Systems and Cybersecurity VIC3800 Australia Ministry of Education School of Cyber Science and Engineering Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan430072 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Feng Chia University Information and Communication Security Research Center Taichuang 40724 Taiwan Feng Chia University Department of Information Engineering and Computer Science Taichung40724 Taiwan

To ensure the security of image information and facilitate efficient management in the cloud, the utilization of reversible data hiding in encrypted images (RDHEI) has emerged as pivotal. However, most existing RDHEI schemes suffer from lower security and limited embedding capacity. To tackle these challenges, we propose a reversible data hiding with secret encrypted image sharing and adaptive coding scheme. Specifically, in the encryption phase, we introduce an improved secret sharing (SS) encryption method based on the chinese remainder theorem for polynomials (CRTP). This method not only improves the security of encrypted images but also vacates a larger room for embedding. In the embedding phase, we introduce an adaptive coding embedding approach using XOR preservation (XORP) and huffman coding, which provides high embedding capacity. Experimental results and security analysis demonstrate that our proposed encryption method achieves optimal values in security indicators for encrypted images, such as information entropy, histograms, NPCR and UACI. The proposed embedding method is superior to some state-of-the-art schemes in terms of embedding capacity. Furthermore, in datasets BOSSBase and BOWS2, the average embedding rates of the proposed embedding approach can reach 2.1745 bpp and 2.0656 bpp, respectively. © 2025 IEEE.

关键词： adaptive coding chinese remainder theorem for polynomials encrypted images Reversible data hiding secret sharing

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Research on Multimodal Data Fusion Based on Optimal adaptive coding

Research on Multimodal Data Fusion Based on Optimal Adaptive...

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Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Yanhong Ma Yijie Qin Hong Zhang Kun Jiang State Grid Gansu Electric Power Company Lanzhou Gansu China School of Computer & Communication Lanzhou University of Technology Lanzhou Gansu China Changzhou Xingyu Automotive Lighting Systems Co. Ltd

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

In order to solve the problems of low accuracy and poor robustness of existing multimodal data fusion models, this paper proposes a multimodal data fusion model based on adaptive coding. The model maps different modal data into the same subspace through LSTM, and adaptively learns the weights of different modal data, which helps the model to more accurately use the information of each modal data. To fully explore the interaction information among multimodal data and improve the accuracy of the model by extracting consistency and complementary features from multimodal data using a Transformer-based encoder. The uncertainty of the prediction distribution is quantified by an improved loss function to improve the anti-interference ability of the model. Experimentally evaluated on two publicly available datasets, CMU-MOSI and CMU-MOSEI, the results show that the model performs better.

关键词： Adaptation models Uncertainty Computational modeling Data integration Predictive models Feature extraction Transformers Data models Robustness adaptive coding

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