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Synaptic Communication Engineering for Future Cognitive Brain–Machine Interfaces
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| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1425-1441 |
| Abstrak | : | Disease-affected nervous systems exhibit anatomical or physiological impairments that degrade processing, transfer, storage, and retrieval of neural information, leading to physical or intellectual disabilities. Brain implants may potentially promote clinical means for detecting and treating neurological symptoms by establishing direct communication between the nervous and artificial systems. Current technology can modify the neural function at the supracellular level as in Parkinson's disease, epilepsy, and depression. However, recent advances in nanotechnology, nanomaterials, and molecular communications have the potential to enable brain implants to preserve the neural function at the subcellular level, which could increase effectiveness, decrease energy consumption, and make the leadless devices chargeable from outside the body or by utilizing the body's own energy sources. In this paper, we focus on understanding the principles of elemental processes in synapses to enable diagnosis and treatment of brain diseases with pathological conditions using biomimetic synaptically interactive brain-machine interfaces (BMIs). First, we provide an overview of the synaptic communication system, followed by an outline of brain diseases that promote dysfunction in the synaptic communication system. Then, we discuss the technologies for brain implants and propose future directions for the design and fabrication of cognitive BMIs. The overarching goal of this paper is to summarize the status of engineering research at the interface between the technology and the nervous system and direct the ongoing research toward the point where synaptically interactive BMIs can be embedded in the nervous system. |
Redox Is a Global Biodevice Information Processing Modality
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1402-1424 |
| Abstrak | : | Biology is well known for its ability to communicate through molecularly specific signaling modalities and a globally acting electrical modality associated with ion flow across biological membranes. Emerging research suggests that biology uses a third type of communication modality associated with a “flow” of electrons through reduction/oxidation (redox) reactions. This redox signaling modality appears to act globally and has features of both molecular and electrical modalities: since free electrons do not exist in aqueous solution, the electrons must “flow” through molecular intermediates that can be switched between two states-with electrons (reduced) or without electrons (oxidized). Importantly, this global redox modality is easily accessible through its electrical features using convenient electrochemical instrumentation. In this review, we explain this redox modality, describe our electrochemical measurements, and provide four examples demonstrating that redox enables communication between biology and electronics. The first two examples illustrate how redox probing can acquire biologically relevant information. The last two examples illustrate how redox inputs can transduce biologically relevant transitions for patterning and the induction of a synthetic biology (synbio) “transceiver” for two-hop molecular communication. In summary, we believe redox provides a unique ability to bridge biodevice communication because simple electrochemical methods enable global access to biologically meaningful information. Furthermore, we envision that redox may facilitate the application of information theory to the biological sciences. |
Optogenomic Interfaces: Bridging Biological Networks With the Electronic Digital World
| Pengarang | : | Josep Miquel Jornet |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1387-1401 |
| Abstrak | : | The development of optical nano-bio interfaces is a fundamental step toward connecting biological networks and traditional electronic computing systems. Compared to conventional chemical and electrical nano-bio interfaces, the use of light as a mediator enables new type of interfaces with unprecedented spatial and temporal resolutions. In this paper, the state of the art and future research directions in optogenomic interfaces are discussed. Optogenomic interfaces are light-mediated nano-bio interfaces that allow the control of the genome, i.e., the genes and their interactions in the cell nucleus (and, thus, of all the cell functionalities) with (sub) cellular resolution and high temporal accuracy. Given its fundamental role in the process of cell development, the study is focused on the interactions with the fibroblast growth factor receptor 1 (FGFR1) gene and the integrative nuclear FGFR1 signaling (INFS) module in stem cells and in neuronal cells, whose control opens the door to transformative applications, including reconstructive medicine and cancer therapy. Three stages of optogenomic interfaces are described, ranging from already experimentally validated interfaces activating broad cellular responses and expressing individual genes to more advanced interfaces able to regulate and correct DNA topology, chromatin structure, and cellular development. |
The Effect of Loads in Molecular Communications
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1369-1386 |
| Abstrak | : | The ability of cells to sense and respond to their environment is encoded in biomolecular reaction networks, in which information travels through processes such as production, modification, and removal of biomolecules. Recent advances in biotechnology have made it possible to reengineer these physical processes to the point where synthetic biomolecular circuits can be inserted into cells to program cell behavior for useful functionalities. These circuits are often designed in a bottom-up fashion with smaller components connected to form complex systems. In a bottom-up approach to design, it is highly desirable that circuit components behave modularly, that is, the input-output behavior of a module characterized in isolation remains unchanged when the context changes. Unfortunately, due to the physical processes by which information is communicated from one biomolecular circuit module to the other, the lack of modularity is often a problem. In fact, the input-output behavior of a module depends on both direct connectivity to other modules, due to loading effects, and indirect connectivity arising from loads applied to shared cellular resources. In this paper, we summarize the published work illustrating how the means of molecular communication lead to these problems. Specifically, we review the concept of retroactivity, which has been proposed to capture loading problems within a “signals and systems” framework, allowing for engineering solutions that restore modularity. |
Design of Asynchronous Genetic Circuits
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1356-1368 |
| Abstrak | : | Most digital electronic circuits utilize a timing reference to synchronize the progression of signals and enable sequential memory elements. These designs may not be realizable in biological substrates due to the lack of a reliable high-frequency clock signal. Asynchronous designs eliminate the need for a clock with data encodings and request/acknowledge handshake protocols. This paper proposes a workflow to automate the design of asynchronous genetic circuits. This workflow extends genetic design tools by leveraging asynchronous logic design methods customized for this technology. This workflow is demonstrated on a genetic sensor that uses filtering and cellular communication to improve its reliability. |
Capacity Bounds on Point-to-Point Communication Using Molecules
| Pengarang | : | Christopher Rose |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1342-1355 |
| Abstrak | : | Recent years have shown a rapid increase in the amount of study devoted to communication systems where molecules are information carriers. The reasons for such interest are varied, from seeking to understand the ubiquity of molecular communication in biology to the search for communication methods in media where electromagnetic and acoustic methods are inappropriate, to exploring the energy efficiency of methods where some delivery latency can be allowed. With this tutorial on recent discrete molecular communication research, we seek to organize the work into broad categories and thence under the umbrella of what can be called “inscribed matter communication,” where information is conveyed through assemblage, release, and capture of matter as opposed to the transmission of photons or phonons. We will begin by considering discrete passage of molecules between senders and receivers, and argue that matter emission and detection, even at Avogadrian levels, are a subset of the discrete problem, all with a focus on point-to-point communication. In this way, we hope to contextualize current work within a larger fundamental framework, illuminate the hard boundaries of what is known, and then stimulate further research on this fascinating topic. |
Transmitter and Receiver Architectures for Molecular Communications: A Survey on Physical Design With Modulation, Coding, and Detection Techniques
| Pengarang | : | Murat Kuscu |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1302-1341 |
| Abstrak | : | Inspired by nature, molecular communications (MC), i.e., the use of molecules to encode, transmit, and receive information, stands as the most promising communication paradigm to realize the nanonetworks. Even though there has been extensive theoretical research toward nanoscale MC, there are no examples of implemented nanoscale MC networks. The main reason for this lies in the peculiarities of nanoscale physics, challenges in nanoscale fabrication, and highly stochastic nature of the biochemical domain of envisioned nanonetwork applications. This mandates developing novel device architectures and communication methods compatible with MC constraints. To that end, various transmitter and receiver designs for MC have been proposed in the literature together with numerable modulation, coding, and detection techniques. However, these works fall into domains of a very wide spectrum of disciplines, including, but not limited to, information and communication theory, quantum physics, materials science, nanofabrication, physiology, and synthetic biology. Therefore, we believe it is imperative for the progress of the field that an organized exposition of cumulative knowledge on the subject matter can be compiled. Thus, to fill this gap, in this comprehensive survey, we review the existing literature on transmitter and receiver architectures toward realizing MC among nanomaterial-based nanomachines and/or biological entities and provide a complete overview of modulation, coding, and detection techniques employed for MC. Moreover, we identify the most significant shortcomings and challenges in all these research areas and propose potential solutions to overcome some of them. |
Channel Modeling for Diffusive Molecular Communication—A Tutorial Review
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1256-1301 |
| Abstrak | : | Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications, such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide the channel models for time-varying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate the simulation- and experiment-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems. |
An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 7) |
| Halaman | : | 1230-1255 |
| Abstrak | : | Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline. |
Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
| Pengarang | : | Zhi Zhou |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 107 (No. 8) |
| Halaman | : | 1738-1762 |
| Abstrak | : | With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to recommendation systems to video/audio surveillance. More recently, with the proliferation of mobile computing and Internet of Things (IoT), billions of mobile and IoT devices are connected to the Internet, generating zillions bytes of data at the network edge. Driving by this trend, there is an urgent need to push the AI frontiers to the network edge so as to fully unleash the potential of the edge big data. To meet this demand, edge computing, an emerging paradigm that pushes computing tasks and services from the network core to the network edge, has been widely recognized as a promising solution. The resulted new interdiscipline, edge AI or edge intelligence (EI), is beginning to receive a tremendous amount of interest. However, research on EI is still in its infancy stage, and a dedicated venue for exchanging the recent advances of EI is highly desired by both the computer system and AI communities. To this end, we conduct a comprehensive survey of the recent research efforts on EI. Specifically, we first review the background and motivation for AI running at the network edge. We then provide an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning model toward training/inference at the network edge. Finally, we discuss future research opportunities on EI. We believe that this survey will elicit escalating attentions, stimulate fruitful discussions, and inspire further research ideas on EI. |