Coding Of Signals Research Articles

Low-Cost Conversion of Single-Zone HVAC Systems to Multi-Zone Control Systems Using Low-Power Wireless Sensor Networks.

This paper presents a novel approach to convert a conventional house air conditioning installation into a more efficient system that individually controls the temperature of each zone of the house through Wi-Fi technology. Each zone regulates the air flow depending on the detected temperature, providing energy savings and increasing the machine performance. Therefore, the first step was to examine the communication bus of the air conditioner and obtain the different signal codes. Thus, an alternative Controller module has been designed and developed to control and manage the requests on the communication bus (Bus–Wi-Fi gateway). A specific circuit has been designed to adapt the signal of the serial port of the Controller with the communication bus. For the acquisition of the temperature and humidity data in each zone, a Node module has been developed, which communicates with the Controller through the Wi-Fi interface using the Message Queuing Telemetry Transport (MQTT) protocol with Secure Sockets Layer / Transport Layer Security (SSL/TLS) certificates. It has been equipped with an LCD touch screen as a human-machine interface. The Controller and the Node modules have been developed with the ultra-low power consumption CC3200 microController of Texas Instruments and the code has been implemented under the TI-RTOS real-time operating system. An additional module based on the Raspberry Pi computer has been designed to create the Wi-Fi network and implement the required network functionalities. The developed system not only ensures that the temperature in each zone is the desired one, but also controls the fan velocity of the indoor unit and the opening area of the vent registers, which considerably improves the efficiency of the system. Compared with the single-zone system, the experiments carried out show energy savings between 75% and 94% when only one of the zones is selected, and 44% when the whole house is air-conditioned, in addition to considerably improving user comfort.

Neuronal On- and Off-type heterogeneities improve population coding of envelope signals in the presence of stimulus-induced noise

Understanding the mechanisms by which neuronal population activity gives rise to perception and behavior remains a central question in systems neuroscience. Such understanding is complicated by the fact that natural stimuli often have complex structure. Here we investigated how heterogeneities within a sensory neuron population influence the coding of a noisy stimulus waveform (i.e., the noise) and its behaviorally relevant envelope signal (i.e., the signal). We found that On- and Off-type neurons displayed more heterogeneities in their responses to the noise than in their responses to the signal. These differences in heterogeneities had important consequences when quantifying response similarity between pairs of neurons. Indeed, the larger response heterogeneity displayed by On- and Off-type neurons made their pairwise responses to the noise on average more independent than when instead considering pairs of On-type or Off-type neurons. Such relative independence allowed for better averaging out of the noise response when pooling neural activities in a mixed-type (i.e., On- and Off-type) than for same-type (i.e., only On-type or only Off-type), thereby leading to greater information transmission about the signal. Our results thus reveal a function for the combined activities of On- and Off-type neurons towards improving information transmission of envelope stimuli at the population level. Our results will likely generalize because natural stimuli across modalities are characterized by a stimulus waveform whose envelope varies independently as well as because On- and Off-type neurons are observed across systems and species.

Regulated Charge Pumps: A Comparative Study by Means of Verilog-AMS

This paper proposes a comparative study of regulation schemes for charge-pump-based voltage generators using behavioral models in Verilog- Analog Mixed Signal (AMS) code. An accurate and simple model of the charge pump is first introduced. It allows reducing the simulation time of complex electronic systems made up by both analog and digital circuits while maintaining a good agreement with transistor-level simulations. Finally, a comprehensive comparative study of the different regulation schemes for charge pumps is reported which allows the designer to choose the most suitable topology for a given application and Charge Pump (CP) operative zone.

MIMO radar signals with better correlation characteristics

Abstract MIMO radars employ multiple transmitting and receiving antennae. For each transmitting antenna, an independent and easily distinguishable signal is required, and appropriate filters must be used by the receiver. For this, the transmitted signals should have characteristics, enabling their effective separation. In this paper the correlation characteristics of selected signals are compared, and the appropriate signal coding is suggested. For differentiation, we address signals with basic linear or nonlinear frequency modulation (LFM or NLFM) multiplied by Gold, PRN, or frequency diversity (FD) codes. The analysis shows that better signal characteristics are achieved using the FD than the other codes. Using matched filters with filter length of 511, sidelobes and cross-correlations are suppressed by 40 dB with FD codes, while with the other codes only 20 dB was achieved. It was also proven, that the FD codes are more tolerant to the Doppler shift. On the other hand, the FD codes application leads to an extension of the overall transmitted signal bandwidth. This however, only represents a serious barrier for very broadband radar systems.

Agonist-induced phosphorylation bar code and differential post-activation signaling of the delta opioid receptor revealed by phosphosite-specific antibodies

The δ-opioid receptor (DOP) is an attractive pharmacological target due to its potent analgesic, anxiolytic and anti-depressant activity in chronic pain models. However, some but not all selective DOP agonists also produce severe adverse effects such as seizures. Thus, the development of novel agonists requires a profound understanding of their effects on DOP phosphorylation, post-activation signaling and dephosphorylation. Here we show that agonist-induced DOP phosphorylation at threonine 361 (T361) and serine 363 (S363) proceeds with a temporal hierarchy, with S363 as primary site of phosphorylation. This phosphorylation is mediated by G protein-coupled receptor kinases 2 and 3 (GRK2/3) followed by DOP endocytosis and desensitization. DOP dephosphorylation occurs within minutes and is predominantly mediated by protein phosphatases (PP) 1α and 1β. A comparison of structurally diverse DOP agonists and clinically used opioids demonstrated high correlation between G protein-dependent signaling efficacies and receptor internalization. In vivo, DOP agonists induce receptor phosphorylation in a dose-dependent and agonist-selective manner that could be blocked by naltrexone in DOP-eGFP mice. Together, our studies provide novel tools and insights for ligand-activated DOP signaling in vitro and in vivo and suggest that DOP agonist efficacies may determine receptor post-activation signaling.

Deep back propagation–long short-term memory network based upper-limb sEMG signal classification for automated rehabilitation

Autonomous rehabilitation training for assisted patients with injured upper-limbs promotes the regenerative communication between muscle signals and brain consciousness. Surface electromyographic (sEMG) is a type of electrical signals of neuromuscular activity recorded by electrodes on the surface of the human body, which is widely applied for detecting gestures and stimuli reactions. Experimental results proved the importance of the sEMG signals for extracting such reactions, in which, the segmentation and classification of the sEMG are vital tasks. The objective of the present work is to segment and classify the sEMG signals of patients to assist the design of clinical rehabilitation devices based on the classification of sEMG signals. In the pre-processing stage, a dual-tone multi-frequency signaling is designed for signal coding; subsequently, the pre-processed sEMG signal is transformed by the Fast Fourier Transfer. Afterward, a time-series frequency analysis is performed by applying Hidden Markov Models. A basic traditional long short-term memory (LSTM) model is addressed for waveform-based classification to be compared to the proposed improved deep BP (back-propagation)–LSTM for sEMG signal classification. Seventeen performance features are selected for evaluating the proposed multi-classification, deep learning model for classifying six actions, namely moving gesture of grip, slowly moving, flexor, straight lift, stretch, and up-high lift; which were proposed by rehabilitation physician. The experiment results indicated the superiority of the proposed method compared to other well-known classifiers, such as the neural network, support vector machine, decision trees, Bayes inference, and recurrent neural network. The proposed deep BP–LSTM network achieved 92% accuracy, 89% specificity, 91% precision, and 96% F1-score, in the multi-classification of the sEMG signals.

On the adequacy of the frequency-symbolic method for linear parametric circuits analysis

A frequency-symbolic method (FS-method) of the analysis of steady-state mode of linear parametric circuits is intended for forming their transfer functions in the frequency domain. Transfer functions are approximated by Fourier polynomials and contain a complex variable, time variable and parameters of circuit elements in the form of symbols. The coefficients of such Fourier polynomials by the FS-method are unknown in the symbolic systems of linear algebraic equations (SSLAE), and are defined as their solutions in symbolic form. In the paper we present a method of forming an approximation expression which ensures the adequacy of calculations. Examples and results of computer experiments are given. The system of functions MAOPCs based on a frequency-symbolic method is used for the optimal design of electronic devices of noise-immune hidden radio engineering systems using code signals.

Vip1 is a kinase and pyrophosphatase switch that regulates inositol diphosphate signaling

Inositol diphosphates (PP-IPs), also known as inositol pyrophosphates, are high-energy cellular signaling codes involved in nutrient and regulatory responses. We report that the evolutionarily conserved gene product, Vip1, possesses autonomous kinase and pyrophosphatase domains capable of synthesis and destruction of D-1 PP-IPs. Our studies provide atomic-resolution structures of the PP-IP products and unequivocally define that the Vip1 gene product is a highly selective 1-kinase and 1-pyrophosphatase enzyme whose activities arise through distinct active sites. Kinetic analyses of kinase and pyrophosphatase parameters are consistent with Vip1 evolving to modulate levels of 1-IP7 and 1,5-IP8 Individual perturbations in kinase and pyrophosphatase activities in cells result in differential effects on vacuolar morphology and osmotic responses. Analogous to the dual-functional key energy metabolism regulator, phosphofructokinase 2, Vip1 is a kinase and pyrophosphatase switch whose 1-PP-IP products play an important role in a cellular adaptation.

Common-View Time Transfer Using Geostationary Satellite.

The National Time Service Center (NTSC), Chinese Academy of Sciences (CAS), Xi'an, China, has developed a method for common-view time transfer using Geostationary Earth Orbit (GEO) satellite (GCV) applicable to the time and frequency transfer at distant stations. This method is independent of Global Navigation Satellite System (GNSS) time and frequency transfer, as well as two-way satellite time and frequency transfer (TWSTFT). A master clock at the time laboratory transmits pseudorandom code signals to a GEO telecommunication satellite, and the time signals are retransmitted by the satellite. Receivers at the time laboratory and user locations coincidentally receive the time signals, and the offsets between the user clocks and the master clock of the time laboratory are determined with high precision if the precise coordinates of the user locations are known. For this technology, only a parabolic antenna with receiver devices and a demodulator are required at each user station, but the coordinates and precise orbits need to be obtained in advance. The key features of GCV include 1) continuous coverage of the signal from GEO communication satellites; 2) differential observations to reduce the effects of orbit error and the imprecision of the propagation delay model; 3) using a very small aperture terminal (VSAT) to enhance high signal ratio to noise to obtain precise ranging accuracy and antimultipath ability; and 4) utilizing the C-band or Ku-band to decrease the impact of the ionosphere. Experiments based on the TWSTFT network of CAS showed that the performance of GCV was at the same level as that of TWSTFT, and the rms of the residuals of GCV was less than 1.5 ns with respect to TWSTFT.

Traffic Surveillance Using Smart Drone

Day by day the number of vehicles is increasing very fast as the demand is increasing. So, the details of the vehicles are very important to maintain for the government of a country. Information like ownership, insurance, emission, road tax etc., need to be maintained and accessed very efficiently and easily. Even for crime purpose the vehicles are used. So, depending on the demand of the requirements we have proposed this model for real time vehicle monitoring and intimating for violation of traffic rules using drone. In our proposed system, the drone is fitted with cameras and Raspberry Pi. The drone will keep on monitoring the non-parking areas from above the level of ground. The drone will capture the image and detect the vehicle and if the vehicle is not moving after two minutes, transmit the vehicle image to the server along with the road signal code.

Gastric Distension‐induced Nodose Ganglionic Cell Responses Using a High‐throughput Multi‐electrode Array in the Ferret

The nodose ganglion (NG) contains cell bodies of gastrointestinal afferents, which play critical roles in metabolic and feeding disorders and gastrointestinal and inflammatory diseases. To further understand the population coding of nodose ganglionic signals, we used a 32‐chan multi‐electrode array (MEA; 4×8, 400 μm pitch; Blackrock Microsystems) to record single‐unit responses with 3 main objectives: (1) determine the stability of multiple single‐unit responses during several hours of in vivo electrophysiological recording; (2) measure the activation patterns of these neurons to prototypical stimulation, such as gastric distension; and (3) investigate the phenotypes of nodose neurons using mechanical probing and vagus nerve electrical stimulation to determine conduction velocities. Acute experiments were performed in anesthetized ferrets using inhalational isoflurane (~2.5%) anesthesia. MEAs were inserted in the nodose ganglion using a pneumatic inserter, and a balloon‐catheter was advanced into the stomach through a small incision on the lateral edge of the gastric fundus. Two volumes of saline, 10 and 20 ml, were infused into the balloon to provide distension. Nerve cuff electrodes were placed on the abdominal vagus trunk to determine conduction velocity. Ganglionic single‐unit activity was successfully recorded from the NG for up to 5.3 h. In our preliminary analysis using spike sorting on each channel (MKsort, https://github.com/ripple‐neuro/mksort; Matlab), we were able to identify a total of 233 units in 6 animals (16 to 55 units per animal). Gastric balloon distension produced >20% increase in neuronal activity in an average of 48% of units to 10 ml inflation and 56% of units to 20 ml inflation. These results demonstrate the feasibility to record multiple single‐unit responses from the ferret NG to provide insight into gastric‐related population coding. Future effort could focus on delineating the physiological roles of these gastric neurons for the design of neuromodulation devices, which could be used to treat diseases involving vagal sensory input such as obesity and the chronic nausea associated with gastroparesis.Support or Funding InformationThis research was supported by funding from the NIH SPARC Common Fund Program (award #U18TR002205).

Optical 4D signal detection in turbid water by multi-dimensional integral imaging using spatially distributed and temporally encoded multiple light sources.

We propose an underwater optical signal detection system based on multi-dimensional integral imaging with spatially distributed multiple light sources and four-dimensional (4D) spatial-temporal correlation. We demonstrate our system for the detection of optical signals in turbid water. A 4D optical signal is generated from a three-dimensional (3D) spatial distribution of underwater light sources, which are temporally encoded using spread spectrum techniques. The optical signals are captured by an array of cameras, and 3D integral imaging reconstruction is performed, followed by multi-dimensional correlation to detect the optical signal. Inclusion of multiple light sources located at different depths allows for successful signal detection at turbidity levels not feasible using only a single light source. We consider the proposed system under varied turbidity levels using both Pseudorandom and Gold Codes for temporal signal coding. We also compare the effectiveness of the proposed underwater optical signal detection system to a similar system using only a single light source and compare between conventional and integral imaging-based signal detection. The underwater signal detection capabilities are measured through performance-based metrics such as receiver operating characteristic (ROC) curves, the area under the curve (AUC), and the number of detection errors. Furthermore, statistical analysis, including Kullback-Leibler divergence and Bhattacharya distance, shows improved performance of the proposed multi-source integral imaging underwater system. The proposed integral-imaging based approach is shown to significantly outperform conventional imaging-based methods.

Fast phase retrieval with a combined method between interferometry and non-interferometry in the holographic data storage

Non-interferometric phase retrieval is a fundamental technique for phase-modulated holographic data storage due to its advantages of easy implementation, simple system setup, and robust noise tolerance. Usually, the iterative algorithm of non-interferometry needs hundreds of iteration numbers to retrieve phase accurately, which decreased the data transfer rate severely. Strong constraint conditions, such as embedded data, can be used on the phase data page to reduce the iteration numbers. However, introducing embedded data will reduce the code rate of the system. We proposed a method that combined the single-shot interferometric method with the non-interferometric iterative Fourier transform algorithm method. We used the phase decoding result by single-shot interferometry as the embedded data in the process of non-interferometry. Therefore, no extra embedded data are needed in the signal code. We realized the code rate improvement as well as keeping fast data transfer rate. In the demonstration, we recorded a four-level phase pattern and retrieved the phase correctly. The bit error rate of phase retrieval is less than 1% within 20 iterations, which proves our approach is practical. In our case, the code rate is increased by two times.

The Effect of Counterfactual Information on Outcome Value Coding in Medial Prefrontal and Cingulate Cortex: From an Absolute to a Relative Neural Code

Adaptive coding of stimuli is well documented in perception, where it supports efficient encoding over a broad range of possible percepts. Recently, a similar neural mechanism has been reported also in value-based decision, where it allows optimal encoding of vast ranges of values in PFC: neuronal response to value depends on the choice context (relative coding), rather than being invariant across contexts (absolute coding). Additionally, value learning is sensitive to the amount of feedback information: providing complete feedback (both obtained and forgone outcomes) instead of partial feedback (only obtained outcome) improves learning. However, it is unclear whether relative coding occurs in all PFC regions and how it is affected by feedback information. We systematically investigated univariate and multivariate feedback encoding in various mPFC regions and compared three modes of neural coding: absolute, partially-adaptive and fully-adaptive.Twenty-eight human participants (both sexes) performed a learning task while undergoing fMRI scanning. On each trial, they chose between two symbols associated with a certain outcome. Then, the decision outcome was revealed. Notably, in one-half of the trials participants received partial feedback, whereas in the other half they got complete feedback. We used univariate and multivariate analysis to explore value encoding in different feedback conditions.We found that both obtained and forgone outcomes were encoded in mPFC, but with opposite sign in its ventral and dorsal subdivisions. Moreover, we showed that increasing feedback information induced a switch from absolute to relative coding. Our results suggest that complete feedback information enhances context-dependent outcome encoding.SIGNIFICANCE STATEMENT This study offers a systematic investigation of the effect of the amount of feedback information (partial vs complete) on univariate and multivariate outcome value encoding, within multiple regions in mPFC and cingulate cortex that are critical for value-based decisions and behavioral adaptation. Moreover, we provide the first comparison of three possible models of neural coding (i.e., absolute, partially-adaptive, and fully-adaptive coding) of value signal in these regions, by using commensurable measures of prediction accuracy. Taken together, our results help build a more comprehensive picture of how the human brain encodes and processes outcome value. In particular, our results suggest that simultaneous presentation of obtained and foregone outcomes promotes relative value representation.

МЕТОД ЗАБЕЗПЕЧЕННЯ ЗАВАДОСТІЙКОСТІ РУХОМОГО ЗВ’ЯЗКУ ПРИ ВИНИКНЕННІ ВНУТРІШНЬОСИСТЕМНИХ ЗАВАД

Предметом вивчення є процеси забезпечення безпроводової завадостійкої передачі дискретної інформації на грунті надширокосмугових сигналів з високою інформаційною ємністю. Мета – розробка рекомендацій щодо забезпечення електромагнітної сумісності надширокосмугової системи зв’язку при передачі дискретних повідомлень каналом зв’язку з аддитивним гаусовим шумом. Задача – забезпечення усталеної та надійної роботи надширокосмугової системи зв’язку в умовах внутрішньосистемних завад. Використані методи: методи аналітичного, імітаційного моделювання та цифрового кодування сигналів. Отримані наступні результати. Показано, що випадкові зміни енергії та автокореляційної функції прийнятих надширокосмугових сигналів в потоці бітів інформації є причиною виникнення внутрішньосистемних завад. У свою чергу це викликає збільшення бітової похибки та деградацію імовірнісних характеристик системи зв’язку. Отримані характеристики бітової похибки свідчать про високий рівень прихованості та електромагнітної сумісності надширокосмугової системи зв’язку при передачі дискретних повідомлень в каналі зв’язку з адитивним гаусовом білим шумом. Причому, за умов використання некратних затримок кодуючих імпульсів в процесі кодової спектральної модуляції, отримуємо імовірність бітової похибки на рівні 10(-5) – 10(-6) при суттєво менших одиниці відношеннях сигнал/шум. Висновки. Використання технології надширокосмугових сигналів дозволяє здійснити безпроводову приховану передачу інформації з малою потужністю випромінювання на швидкості 1-2 Мб/с з імовірністю похибки на біт менш, ніж 10 . Таким чином система надширокосмугового радіозв’язку з кодовою модуляцією в передавачі та спектральною обробкою в приймачі має високу завадостійкість, що дозволяє здійснювати надійну передачу цифрової інформації при появі внутрішньосистемних завад

MASS: Microphone Array Speech Simulator in Room Acoustic Environment for Multi-Channel Speech Coding and Enhancement

Multi-channel speech coding and enhancement is an indispensable technology in speech communication. In order to verify the effectiveness of multi-channel speech coding and enhancement methods in the research and development, a microphone array speech simulator (MASS) used in room acoustic environment is proposed. The proposed MASS is the improvement and extension of the existing multi-channel speech simulator. It aims to simulate clean speech, noisy speech, clean speech with reverberation, noisy speech with reverberation, and noise signals by microphone array used for multi-channel coding and enhancement of speech signal in room acoustic environment. The experimental results of the multi-channel speech coding and enhancement prove that the MASS could well simulate the signals used in real room acoustic environment and can be applied to the research of the related fields.

Neural Synchrony Gives Rise to Amplitude- and Duration-Invariant Encoding Consistent With Perception of Natural Communication Stimuli.

When confronted with a highly variable environment, it remains poorly understood how neural populations encode and classify natural stimuli to give rise to appropriate and consistent behavioral responses. Here we investigated population coding of natural communication signals with different attributes (i.e., amplitude and duration) in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. Our results show that, while single peripheral neurons encode the detailed timecourse of different stimulus waveforms, measures of population synchrony are effectively unchanged because of coordinated increases and decreases in activity. A phenomenological mathematical model reproduced this invariance and shows that this can be explained by considering homogeneous populations whose responses are solely determined by single neuron firing properties. Moreover, recordings from downstream central neurons reveal that synchronous afferent activity is actually decoded and thus most likely transmitted to higher brain areas. Finally, we demonstrate that the associated behavioral responses at the organism level are invariant. Our results provide a mechanism by which amplitude- and duration-invariant coding of behaviorally relevant sensory input emerges across successive brain areas thereby presumably giving rise to invariant behavioral responses. Such mechanisms are likely to be found in other systems that share anatomical and functional features with the electrosensory system (e.g., auditory, visual, vestibular).

200 Gbps/Lane IM/DD Technologies for Short Reach Optical Interconnects

Client-side optics are facing an ever-increasing upgrading pace, driven by upcoming 5G related services and datacenter applications. The demand for a single lane data rate is soon approaching 200 Gbps. To meet such high-speed requirement, all segments of traditional intensity modulation direct detection (IM/DD) technologies are being challenged. The characteristics of electrical and optoelectronic components and the performance of modulation, coding, and digital signal processing (DSP) techniques are being stretched to their limits. In this context, we witnessed technological breakthroughs in several aspects, including development of broadband devices, novel modulation formats and coding, and high-performance DSP algorithms for the past few years. A great momentum has been accumulated to overcome the aforementioned challenges. In this article, we focus on IM/DD transmissions, and provide an overview of recent research and development efforts on key enabling technologies for 200 Gbps per lane and beyond. Our recent demonstrations of 200 Gbps short-reach transmissions with 4-level pulse amplitude modulation (PAM) and discrete multitone signals are also presented as examples to show the system requirements in terms of device characteristics and DSP performance. Apart from digital coherent technologies and advanced direct detection systems, such as Stokes–vector and Kramers–Kronig schemes, we expect high-speed IM/DD systems will remain advantageous in terms of system cost, power consumption, and footprint for short reach applications in the short- to mid- term perspective.

Combined expectancies: the role of expectations for the coding of salient bottom-up signals

The visual system forms predictions about upcoming visual features based on previous visual experiences. Such predictions impact on current perception, so that expected stimuli can be detected faster and with higher accuracy. A key question is how these predictions are formed and on which levels of processing they arise. Particularly, predictions could be formed on early levels of processing, where visual features are represented separately, or might require higher levels of processing, with predictions formed based on full object representations that involve combinations of visual features. In four experiments, the present study investigated whether the visual system forms joint prediction errors or whether expectations about different visual features such as color and orientation are formed independently. The first experiment revealed that task-irrelevant and implicitly learned expectations were formed independently when the features were separately bound to different objects. In a second experiment, no evidence for a mutual influence of both types of task-irrelevant and implicitly formed feature expectations was observed, although both visual features were assigned to the same objects. A third experiment confirmed the findings of the previous experiments for explicitly rather than implicitly formed expectations. Finally, no evidence for a mutual influence of different feature expectations was observed when features were assigned to a single centrally presented object. Overall, the present results do not support the view that object feature binding generates joint feature-based expectancies of different object features. Rather, the results suggest that expectations for color and orientation are processed and resolved independently at the feature level.

Cracking the context-specific PI3K signaling code.

Specificity in signal transduction is determined by the ability of cells to "encode" and subsequently "decode" different environmental signals. Akin to computer software, this "signaling code" governs context-dependent execution of cellular programs through modulation of signaling dynamics and can be corrupted by disease-causing mutations. Class IA phosphoinositide 3-kinase (PI3K) signaling is critical for normal growth and development and is dysregulated in human disorders such as benign overgrowth syndromes, cancer, primary immune deficiency, and metabolic syndrome. Despite decades of PI3K research, understanding of context-dependent regulation of the PI3K pathway and of the underlying signaling code remains rudimentary. Here, we review current knowledge on context-specific PI3K signaling and how technological advances now make it possible to move from a qualitative to quantitative understanding of this pathway. Insight into how cellular PI3K signaling is encoded or decoded may open new avenues for rational pharmacological targeting of PI3K-associated diseases. The principles of PI3K context-dependent signal encoding and decoding described here are likely applicable to most, if not all, major cell signaling pathways.