Communication Signals Research Articles

A Network-Group Target State and Network Topology Estimation Method Based on Signals Containing Delay, Doppler and Address

Network-group targets are a set of objectives that adhere to a shared communication protocol, perform common tasks, and exhibit relatively coordinated movements. Typically, network-group targets emit radar and communication signals. However, they often employ a silent mode to evade our perception. Despite this, they continue to exchange data through their communication networks. By intercepting the communication signals of these targets, this paper proposes a method for estimating the state and network topology of network-group targets based on random finite set (RFS) theory. This method is based on the modeling of network-group targets using a labeled multi-Bernoulli (LMB) RFS. In state estimation, the usual method involves extracting the localization parameters from the signals in the first step and use these parameters for target tracking in the second step. This study focused on estimating the kinematic states of network-group targets using communication signals containing delay and Doppler information received by multiple mobile sensor platforms. The proposed method considers the coherency between frequency-hopping pulses in the signals, resulting in an improved estimation performance. In addition, considering that network-group targets require network access for information exchange, graph theory concepts were utilized to estimate the network topology of network-group targets by address measurement. The simulation results validated the effectiveness of the proposed method and demonstrated its superior performance.

ISAC towards 6G Satellite–Terrestrial Communications: Principles, Status, and Prospects

With the evolution of fifth-generation (5G) to sixth-generation (6G) communication systems, the utilization of spectrum resources faces incremental challenges. Integrated sensing and communication (ISAC) technology, as a crucial element in 6G technology, is expected to enhance energy efficiency and spectrum utilization efficiency by integrating radar and communication signals, achieving environmental awareness, and enabling scene interconnection. Simultaneously, to realize the vision of seamless coverage in 6G, research on integrated satellite-terrestrial communication has been prioritized. To integrate the advantages, ISAC for integrated satellite–terrestrial networks (ISTNs) in 6G has emerged as a potential research direction. This paper offers an extensive overview of the present state of key technologies for ISAC and the development of ISTNs. Meanwhile, with a focus on the ISTN-oriented 6G ISAC system, several hotspot topics, including future application scenarios and key technological developments, are outlined and demonstrated.

The Tumor Microenvironment: Signal Transduction.

In the challenging tumor microenvironment (TME), tumors coexist with diverse stromal cell types. During tumor progression and metastasis, a reciprocal interaction occurs between cancer cells and their environment. These interactions involve ongoing and evolving paracrine and proximal signaling. Intrinsic signal transduction in tumors drives processes such as malignant transformation, epithelial-mesenchymal transition, immune evasion, and tumor cell metastasis. In addition, cancer cells embedded in the tumor microenvironment undergo metabolic reprogramming. Their metabolites, serving as signaling molecules, engage in metabolic communication with diverse matrix components. These metabolites act as direct regulators of carcinogenic pathways, thereby activating signaling cascades that contribute to cancer progression. Hence, gaining insights into the intrinsic signal transduction of tumors and the signaling communication between tumor cells and various matrix components within the tumor microenvironment may reveal novel therapeutic targets. In this review, we initially examine the development of the tumor microenvironment. Subsequently, we delineate the oncogenic signaling pathways within tumor cells and elucidate the reciprocal communication between these pathways and the tumor microenvironment. Finally, we give an overview of the effect of signal transduction within the tumor microenvironment on tumor metabolism and tumor immunity.

Transcriptional and ultrastructural changes of macrophages after african swine fever virus infection

African swine fever (ASF) is a highly impactful infectious disease in the swine industry, leading to substantial economic losses globally. The causative agent, African swine fever virus (ASFV), possesses intricate pathogenesis, warranting further exploration. In this study, we investigated the impact of ASFV infection on host gene transcription and organelle changes through macrophage transcriptome sequencing and ultrastructural transmission electron microscopy observation. According to the results of the transcriptome sequencing, ASFV infection led to significant alterations in the gene expression pattern of porcine bone marrow derived macrophages (BMDMs), with 2404 genes showing upregulation and 1579 genes downregulation. Cytokines, and chemokines were significant changes in the expression of BMDMs; there was significant activation of pattern recognition receptors such as Toll-like receptors and Nod-like receptors. According to the observation of the ultrastructure, mitochondrial damage and mitochondrial autophagy were widely present in ASFV-infected cells. The reduced number of macrophage pseudopodia suggested that virus-induced structural changes may compromise pathogen recognition, phagocytosis, and signal communication in macrophages. Additionally, the decreased size and inhibited acidification of secondary lysosomes in macrophages implied suppressed phagocytosis. Overall, ASFV infection resulted in significant changes in the expression of cytokines and chemokines, accompanied by the activation of NLR and TLR signaling pathways. We reported for the first time that ASFV infection led to a reduction in pseudopodia numbers and a decrease in the size and acidification of secondary lysosomes.

Codebook-Based Solutions for Reconfigurable Intelligent Surfaces and Their Open Challenges

Reconfigurable intelligent surfaces (RIS) is a revolutionary technology to cost-effectively improve the performance of wireless networks. We first review the existing framework of channel estimation and passive beamforming (CE & PBF) in RISassisted communication systems. To reduce the excessive pilot signaling overhead and implementation complexity of the CE & PBF framework, we conceive a codebook-based framework to strike flexible tradeoffs between communication performance and signaling overhead. Moreover, we provide useful insights into the codebook design and learning mechanisms of the RIS reflection pattern. Finally, we analyze the scalability of the proposed framework by flexibly adapting the training overhead to the specified quality-of-service requirements and then elaborate on its appealing advantages over the existing CE & PBF approaches. It is shown that our novel codebook-based framework can be beneficially applied to all RIS-assisted scenarios and avoids the curse of model dependency faced by its existing counterparts, thus constituting a competitive solution for practical RIS-assisted communication systems.

INTEGRATED CIRCUITS AND THEIR APPLICATIONS IN ELECTRONICS

The article deals with the integrated circuits and their applications in electronics. Integrated circuits (ICs) have revolutionized the field of electronics by enabling the integration of multiple components onto a single chip. This miniaturization has led to significant advancements in various electronic devices and systems. ICs offer numerous benefits, including compact size, energy efficiency, reliability, high speed, cost-effectiveness, flexibility, and scalability. The ability to combine different functions on a single chip has made ICs indispensable in a wide range of applications, from consumer electronics to industrial automation. The integration of digital signal processing, memory management, communication interfaces, and other functions on a single IC has enabled the development of sophisticated and high-performance devices.

Infants’ brain responses to social interaction predict future language growth

In face-to-face interactions with infants, human adults exhibit a species-specific communicative signal. Adults present a distinctive "social ensemble": they use infant-directed speech (parentese), respond contingently to infants' actions and vocalizations, and react positively through mutual eye-gaze and smiling. Studies suggest that this social ensemble is essential for initial language learning. Our hypothesis is that the social ensemble attracts attentional systems to speech and that sensorimotor systems prepare infants to respond vocally, both of which advance language learning. Using infant magnetoencephalography (MEG), we measure 5-month-old infants' neural responses during live verbal face-to-face (F2F) interaction with an adult (social condition) and during a control (nonsocial condition) in which the adult turns away from the infant to speak to another person. Using a longitudinal design, we tested whether infants' brain responses to these conditions at 5months of age predicted their language growth at five future time points. Brain areas involved in attention (right hemisphere inferior frontal, right hemisphere superior temporal, and right hemisphere inferior parietal) show significantly higher theta activity in the social versus nonsocial condition. Critical to theory, we found that infants' neural activity in response to F2F interaction in attentional and sensorimotor regions significantly predicted future language development into the third year of life, more than 2 years after the initial measurements. We develop a view of early language acquisition that underscores the centrality of the social ensemble, and we offer new insight into the neurobiological components that link infants' language learning to their early brain functioning during social interaction.

Life-cycle profiling of cuticular hydrocarbons in the cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae)

Cuticular hydrocarbons (CHCs) are the main components of the wax layer present on insects’ surface, serving as protective agents against environmental stress and/or as communication signals. It has been documented that the chemical composition of CHCs varies with species and even with developmental stage or sex of the same species. However, studies involving in a life-cycle identification of CHCs are rare. In this work, we attempted to profile the components and relative abundance of CHCs in the cotton bollworm Helicoverpa armigera at all the four developmental stages and in both sexes of pupae and adults. A total of 29 CHCs were putatively identified by gas chromatography-mass spectrometer analysis, including 14 n-alkanes, 4 methyl-branched alkenes and 11 methyl-branched alkanes, with 15 of them being detected at all the four developmental stages. Of the 29 CHCs, the straight-chain alkanes with 27, 29 and 31 carbon atoms were the major CHCs. All three classes of CHCs (n-alkanes, methyl-branched alkanes and methyl-branched alkenes) were found in both larvae and pupae, while no unsaturated hydrocarbons were observed in eggs and adults. Methyl-branched alkanes were the main component found in eggs and adults, while the composition of n-alkanes and methyl-branched alkanes in larvae and pupae varied with ages. Principal component analysis (PCA) revealed that the CHC profiles in larvae and adults changed significantly with ages, while the CHC profiles in early pupae (1-day-old) showed distinct difference from those of late pupae. Furthermore, sexual dimorphism in the CHC profile was observed in mature adults (3-day-old and 5-day-old), with male adults possessing more n-C31 and n-C33, but less 3-MeC29 than females.

Solving Edges Deletion Problem of Generalized Petersen Graphs

The dependability and effectiveness of a network can be investigated using a variety of graph-theoretic techniques, and the network's connectivity determines how reliable it is. Diameter in a network is often used to measure the efficiency of a network in the event that a network experiences issues such as a decline in the communication signal or a breakdown in the communication between its components. This paper examines the increase in diameter of the generalized Petersen graph after removing a certain number of edges. Finding the exact values of f(n,t) that represent the maximum diameter of an altered generalized Petersen graph GP(n,k,t) obtained after removing edges from for k=1 and t≥2.

Multi-antenna dual-blind deconvolution for joint radar-communications via SoMAN minimization

In joint radar-communications (JRC) applications such as secure military receivers, often the radar and communications signals are overlaid in the received signal. In these passive listening outposts, the signals and channels of both radar and communications are unknown to the receiver. The ill-posed problem of recovering all signal and channel parameters from the overlaid signal is termed as dual-blind deconvolution (DBD). In this work, we investigate DBD for a multi-antenna receiver. We model the radar and communications channels with a few (sparse) continuous-valued parameters such as time delays, Doppler velocities, and directions-of-arrival (DoAs). To solve this highly ill-posed DBD, we propose to minimize the sum of multivariate atomic norms (SoMAN) that depend on unknown parameters. To this end, we devise an exact semidefinite program using theories of positive hyperoctant trigonometric polynomials (PhTP). Our theoretical analyses show that the minimum number of samples and antennas required for perfect recovery is logarithmically dependent on the maximum of the number of radar targets and communications paths rather than their sum. We show that our approach is easily generalized to include several practical issues such as gain/phase errors and additive noise. Numerical experiments show the exact parameter recovery for different JRC scenarios.

Level Process Station Control Using ALE111 Communication Module

A noteworthy example of the technological evolution is the ALE111, a cutting-edge system equipped with advanced functionalities designed to monitor the status of field wireless devices. One of its key features is the implementation of bumpless output, a capability that ensures seamless transitions and adjustments in the control process. Remarkably, the ALE111 enables wireless process control, a capability traditionally associated with wired control systems utilizing 4-20 mA signal communication. This wireless paradigm not only introduces a new level of flexibility but also contributes to the overall enhancement of process control reliability. The ALE111 goes a step further by incorporating redundant configurations, a strategic approach that adds an extra layer of reliability to the system. By doing so, potential points of failure are mitigated, and the overall robustness of the process control system is substantially improved. Key Word: ALE111 Communication Module, Ethernet, Level Process Station, Vnet, Field Control Station ,HIS, Data Acquisition Card

Collaborative communication-based ocean observation research with heterogeneous unmanned surface vessels

Unmanned surface vehicles (USVs) are crucial in ensuring maritime safety and observation, attracting widespread attention and research. However, a single USV exhibits limited performance and cannot effectively observe complex marine environments. In contrast, clusters of USVs can collaborate to execute complex maritime tasks, thereby enhancing the overall operational efficiency. USVs typically form heterogeneous clusters by combining vehicles with varying maneuverabilities and communication network capabilities. This has sparked an increased interest in cooperative communication research within heterogeneous USV clusters. The heterogeneous USVs discussed in this paper share the same dynamic model; however, they differ in dynamic parameters and communication capabilities. First, this study establishes a three-degree-of-freedom motion mathematical model for an underdriven USV considering environmental interference. It estimates the dynamic parameters of four USVs and evaluates their communication abilities, laying the foundation for researching the cooperative control of heterogeneous USV clusters and their application in Ocean Observation. Next, the communication capability of the USVs is assessed by studying the communication mode and signal transmission loss within the USV clusters. This study investigates the problem of cooperative communication in USV cluster formation, starting with the communication delay of USV clusters under a directed switching topology. Finally, a coherent formation controller is designed under a switching communication topology to address the dynamic transformation of communication topologies within heterogeneous USV clusters. This verifies that heterogeneous USV clusters can seamlessly form and maintain formation shapes during communication topology transformations through formation simulation experiments involving four heterogeneous USVs was 22% higher than that of dispersed control topology structures. This study provides a solid foundation for future investigations into the cooperative control of heterogeneous USV clusters and their applications in marine observations.

Simulation and analysis of C-V2X data transmission in different traffic scenarios based on MAC layer scheduling algorithms

With the rapid development of communication technology, vehicles are becoming more and more intelligent, and Vehicle to Vehicle (V2V) communication has become an important cornerstone for the future intelligence of vehicles. Because of the high-reliability and low-latency characteristics of 5G networks, many applications can be realized by using Vehicle to Network (V2N) communications. Different applications have different requirements for Quality of Service (QoS), which should be met by the network, and the base station can use different scheduling methods to satisfy these different requirements. This paper focuses on the scheduler at the MAC layer in 5G base stations. The scheduler must handle both video signals and other communication signals transmitted by the vehicle, and must also consider Hybrid Automatic Repeat reQuest (HARQ) retransmissions. We performed a C-V2X signaling network transmission simulation by using OMNeT++. We considered urban and motorway, two public transportation scenarios. Different types of data are set to be transmitted in two scenarios. We used different scheduling schemes for data scheduling, then investigated the performance of these scheduling schemes for transmitting data. The methods and simulation experiments mentioned in this paper are important for practical generalization.

Multiply Guaranteed Catalytic DNA Circuit for Cancer-Cell-Selective Imaging of miRNA and Robust Evaluation of Drug Resistance.

Catalytic DNA circuits are desirable for sensitive bioimaging in living cells; yet, it remains a challenge to monitor these intricate signal communications because of the uncontrolled circuitry leakage and insufficient cell selectivity. Herein, a simple yet powerful DNA-repairing enzyme (APE1) activation strategy is introduced to achieve the site-specific exposure of a catalytic DNA circuit for realizing the selectively amplified imaging of intracellular microRNA and robust evaluation of the APE1-involved drug resistance. Specifically, the circuitry reactants are firmly blocked by the enzyme recognition/cleavage site to prevent undesirable off-site circuitry leakage. The caged DNA circuit has no target-sensing activity until its circuitry components are activated via the enzyme-mediated structural reconstitution and finally transduces the amplified fluorescence signal within the miRNA stimulation. The designed DNA circuit demonstrates an enhanced signal-to-background ratio of miRNA assay as compared with the conventional DNA circuit and enables the cancer-cell-selective imaging of miRNA. In addition, it shows robust sensing performance in visualizing the APE1-mediated chemoresistance in living cells, which is anticipated to achieve in-depth clinical diagnosis and chemotherapy research.

Investigation of cellular communication and signaling pathways in tumor microenvironment for high TP53-expressing osteosarcoma cells through single-cell RNA sequencing.

Osteosarcoma (OS) stands as the most prevalent primary bone cancer in children and adolescents, and its limited treatment options often result in unsatisfactory outcomes, particularly for metastatic cases. The tumor microenvironment (TME) has been recognized as a crucial determinant in OS progression. However, the intercellular dynamics between high TP53-expressing OS cells and neighboring cell types within the TME are yet to be thoroughly understood. In our study, we harnessed the single-cell RNA sequencing (scRNA-seq) technology in combination with the computational tool-Cellchat, aiming to elucidate the intercellular communication networks present within OS. Through meticulous quantitative inference and subsequent analysis of these networks, we succeeded in identifying significant signaling pathways connecting high TP53-expressing OS cells with proximate cell types, namely Macrophages, Monocytes, Endothelial Cells, and PVLs. This research brings forth a nuanced understanding of the intricate patterns and coordination involved in the TME's intercellular communication signals. These findings not only provide profound insights into the molecular mechanisms underpinning OS but also indicate potential therapeutic targets that could revolutionize treatment strategies.

Dynamics-driven allosteric stimulation of diguanylate cyclase activity in a red light-regulated phytochrome

Sensor-effector proteins integrate information from different stimuli and transform this into cellular responses. Some sensory domains, like red-light responsive bacteriophytochromes, show a remarkable modularity regulating a variety of effectors. One effector domain is the GGDEF diguanylate cyclase catalysing the formation of the bacterial second messenger cyclic-dimeric-guanosine monophosphate. While critical signal integration elements have been described for different phytochromes, a generalized understanding of signal processing and communication over large distances, roughly 100 Angstrom in phytochrome diguanylate cyclases, is missing. Here we show that dynamics-driven allostery is key to understanding signal integration on a molecular level. We generated protein variants stabilized in their far-red-absorbing Pfr state and demonstrate by analysis of conformational dynamics using hydrogen-deuterium exchange coupled to mass spectrometry that single amino acid replacements are accompanied by altered dynamics of functional elements throughout the protein. We show that the conformational dynamics correlate with the enzymatic activity of these variants, explaining also the increased activity of a non-photochromic variant. In addition, we demonstrate the functional importance of mixed Pfr/intermediate state dimers using a fast-reverting variant that still enables wild-type-like fold-changes of enzymatic stimulation by red light. This supports the functional role of single protomer activation in phytochromes, a property that might correlate with the non-canonical mixed Pfr/intermediate-state spectra observed for many phytochrome systems. We anticipate our results to stimulate research in the direction of dynamics-driven allosteric regulation of different bacteriophytochrome-based sensor-effectors. This will eventually impact design strategies for the creation of novel sensor-effector systems for enriching the optogenetic toolbox.

Abstract 7356: 3 UTR variations in esophageal squamous cell carcinoma in African Americans

Abstract Esophageal squamous cell carcinoma (ESCC) predominantly affects African Americans (AA). Esophageal Cancer (EC) consists of two major histological subtypes: esophageal adenocarcinoma and squamous cell carcinoma. ESCC ranks among the most lethal cancers and is particularly aggressive among AA, comprising about 75% of total ESCC patients. The 5-year survival rate for localized EC in AA patients is 25%; in contrast, the survival rate for EC patients of Caucasian origin is 48%. However, for metastatic disease, the survival rate decreases dramatically to 5% regardless of race. To conduct an extensive mutation screening, we performed whole exome sequencing (WES) in 10 paired AA ESCC and control tissues. Mutations included nonsynonymous mutations in multiple genes and copy number variations. Here, we report on further analysis of the WES data to identify 3 UTR noncoding region alterations, comprising the highest proportion of noncoding variations. Whole exome sequencing was performed using Agilent SureSelect XT Human All Exon V6 + UTR kit on matched normal-tumor samples from 10 AA patients (nine males and one female) with advanced-stage ESCC. The ages of patients ranged from 53 to 80 years. All patients, except for one, reported tobacco use and alcohol consumption. Our analysis yielded 5378 variants in noncoding regions in our cohort. The most variations were found in the 3UTR location, with 46% of all noncoding variations. In our dataset, variations in the 3UTR region of 48 genes were predicted by CScape to assert an oncogenic effect. The highest ten oncogenic predictive scores are for ETV1, FOXO3, MSI2, TCF7L2, KAT6A, FOXO1, IRF4, TRIM24, ELK4, and FGFR1 genes. Approximately 2500 genes having 3’UTR variations are over-presented in intracellular signaling and cell-cell communications, transcriptional regulation of pluripotent stem cells by OCT4, SOX2, NANOG, generic RNA polymerase II transcription, RHO GTPase cycle, and regulation of cytoskeletal remodeling. The combined effects of noncoding and coding region mutations may largely impact poor prognosis in AA with ESCC and yield targets for developing candidate therapeutics. Citation Format: Ceyda Erkizan, Robert Wadleigh. 3 UTR variations in esophageal squamous cell carcinoma in African Americans [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7356.

Signal detection algorithms for massive MIMO system

As 5G communication networks are maturing, we have higher and higher requirements for the detection of communication signals. In this paper, for the Massive MIMO system signal detection problem, we mainly summarize the detection algorithms that can be used to replace the traditional ZF and MMSE, so as to avoid large-scale matrix inverse and reduce the computational complexity. It mainly includes the general iterative method, typically represented by SSOR, which makes the transmit signal matrix constantly close to the ideal value by iterating; the other is the level expansion class solution method, which takes the order expansion of the level as the initial value of the iteration to accelerate the convergence rate of the algorithm, typically represented by the MLI algorithm. However, today where the demand for communication is gradually increasing and the number of users is constantly getting larger, the performance of the above algorithms may degrade seriously, so the AI signal detection algorithm is a good alternative, which learns autonomously through deep neural networks, including model-driven and data-driven schemes.

Abstract 3877: Multi-modal analysis of paracrine signaling in group 3/4 medulloblastoma

Abstract Medulloblastoma (MB) is the most common primary brain malignancy in kids, with the group 3 and 4 subtypes (G3/4) being the most aggressive. Recent single-cell genomics studies have identified the G3/4 MB cell of origin and point to disrupted stem-cell differentiation as a key factor in MB pathogenesis. However, surprisingly little is known about the contribution of tumor-supportive paracrine signaling to the ontogeny of this disease. The spatial organization of MB cellular hierarchies is not completely understood. We profiled N=24 G3/4 MBs from UCSF patients via single-nucleus RNA sequencing (snRNA-seq). Of these cases, N=10 were profiled via single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq). To capture the spatial context, we profiled an additional 20 samples via spatial transcriptomics using the Visium and Xenium platforms. We found that the standard Xenium brain capture set was inadequate, and we developed a highly specific capture set for G3/4 MBs. In particular, our panel resolves cell-type differences in the stage of MB lineage commitment, from rhombic-lip progenitors to more differentiated unipolar brush-like cells. Altogether, over 110,000 nuclear-sequencing libraries and over 1,898,000 spatially-resolved single-cell libraries were generated. We inferred cell-cell communication signals from our snRNA-seq data by identifying co-expressed receptors and their cognate ligands. We then performed an integrated analysis of our snRNA-seq and scATAC-seq data to infer the cis-regulatory enhancers of those signaling genes, as well as the transcription factors that bind them. We employed our spatial transcriptomics data to confirm paracrine signaling networks inferred from nuclear-sequencing data. We found that distinct MB cell types corresponding to different stages of differentiation occupied specific spatial domains. The results of our ongoing analysis of this spatially-resolved single-cell atlas will be presented. This study paves the way for innovative therapeutic strategies targeting paracrine signaling in G3/4 MB. Citation Format: Bohyeon Yu, Jangham Jung, Aaron Diaz. Multi-modal analysis of paracrine signaling in group 3/4 medulloblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3877.

Attention-sensitive signalling by 7- to 20-month-old infants in a comparative perspective.

Attention-sensitive signalling is the pragmatic skill of signallers who adjust the modality of their communicative signals to their recipient's attention state. This study provides the first comprehensive evidence for its onset and development in 7-to 20-month-olds human infants, and underlines its significance for language acquisition and evolutionary history. Mother-infant dyads (N = 30) were studied in naturalistic settings, sampled according to three developmental periods (in months); [7-10], [11-14], and [15-20]. Infant's signals were classified by dominant perceptible sensory modality and proportions compared according to their mother's visual attention, infant-directed speech and tactile contact. Maternal visual attention and infant-directed speech were influential on the onset and steepness of infants' communicative adjustments. The ability to inhibit silent-visual signals towards visually inattentive mothers (unimodal adjustment) predated the ability to deploy audible-or-contact signals in this case (cross-modal adjustment). Maternal scaffolding of infant's early pragmatic skills through her infant-directed speech operates on the facilitation of infant's unimodal adjustment, the preference for oral over gestural signals, and the audio-visual combinations of signals. Additionally, breakdowns in maternal visual attention are associated with increased use of the audible-oral modality/channel. The evolutionary role of the sharing of attentional resources between parents and infants into the emergence of modern language is discussed.