Cortex: Circuitry, Networks, and Function

Functional magnetic resonance imaging (fMRI) has revolutionized the understanding of the functional and structural architecture of the brain and serves as a lens for reviewing the complex cortical circuitry and networks of the cerebral cortex. The human brain is a complex information processing system whose proper functioning depends on the organization of its processing units. The scale of these processing units spans multiple levels from the genetic level to the systems level.

The complexity of human cooperation under indirect reciprocity

Indirect reciprocity (IR) is a key mechanism to understand cooperation among unrelated individuals. It involves reputations and complex information processing, arising from social interactions. By helping someone, individuals may improve their reputation, which may be shared in a population and change the predisposition of others to reciprocate in the future. The reputation of individuals depends, in turn, on social norms that define a good or bad action, offering a computational and mathematical appealing way of studying the evolution of moral systems. Over the years, theoretical and empirical research has unveiled many features of cooperation under IR, exploring norms with varying degrees of complexity and information requirements. Recent results suggest that costly reputation spread, interaction observability and empathy are determinants of cooperation under IR. Importantly, such characteristics probably impact the level of complexity and information requirements for IR to sustain cooperation. In this review, we present and discuss those recent results. We provide a synthesis of theoretical models and discuss previous conclusions through the lens of evolutionary game theory and cognitive complexity. We highlight open questions and suggest future research in this domain. This article is part of the theme issue ‘The language of cooperation: reputation and honest signalling’.

Parallel decomposition of control algorithms for computational processes based on the use of nondeterministic automaton logic

The paper deals with the issues of decomposition of control algorithms for the processes in parallel computing systems and the use of automaton models. When designing parallel processing systems, an important task is the formal presentation of process control algorithms since they allow achieving a packaged solution to the problems of specification, development, implementation, verification, and analysis of complex control systems, including the control of interacting processes and resources in parallel computing systems. It is especially necessary to use formal methods to verify complex information processing systems by model testing. One of the methods for the formal description of control algorithms is based on the use for these purposes of the nondeterministic automaton (NDA) logic, which is a method that allows one to present control algorithms for information processing in the form of systems of canonical equations describing all particular events implemented in the algorithm. The advantage of such a language is that all transitions in the control system are described not in terms of system states, but in terms of particular events, the simultaneous existence of which determines all states and transitions in the system; this allows avoiding a "combinatorial explosion" in the state space to the possibilities of means verification. Purpose of the paper: research of control algorithms for parallel computing systems using the NDA apparatus. The development and research object is parallel decomposition of control algorithms for parallel computing systems using automatic models.

Artificial Intelligence in Pharma

This paper aims to provide a better understanding of the possible applications of Artificial Intelligence (AI) in the field of Pharmacy. Artificial intelligence basically involves complex information processing. It enables machines to carry out certain functions which were originally done by human and which required human intellect. Over the past few years, the use of artificial intelligence in the pharma has grown unimaginably and is now able to revolutionize the way drugs are discovered and handled. AI is capable of impacting the field of pharmacy at multiple levels. Pharmacy and medical education, drug development, personalization of drug therapy, drug safety, rational drug use, manufacture and formulation of dosage forms are areas of impact by AI. The fact that AI can displace humans at their own tasks is a matter of concern. Although there are ethical concerns regarding the implementation of AI in healthcare, it can be assured that no machine or system can replace many of the humanitarian duties.

Method and algorithms of complex information processing onboard the aircraft for the benefit of definition of accessory of the purposes

Formulation of the problem. On board an aircraft, the solution of situational awareness tasks can be achieved as a result of the creation of an integrated multi-sensor information environment for a complex of onboard equipment, including sources of information that are heterogeneous in terms of construction principles and nature. One of the difficulties in creating such a multi-sensor information environment is the lack of specialized functional software for the on-board equipment complex, which allows processing and combining signals and information from heterogeneous sources, providing an assessment of the coordinate characteristics of targets in the form of phase coordinates of their spatial position and movement, as well as recognition and identification observed targets by characteristic features. To solve this problem, a method and interconnected algorithms for complex information processing have been developed that would allow combining heterogeneous information about targets, taking into account the conditions and methods of obtaining it when solving problems of tracking, recognition and identification of targets. Goal. Describe the method and interrelated algorithms for integrated information processing in the aircraft onboard equipment complex, which provide tracking, recognition and identification of targets based on information received from heterogeneous OBE sources. Results. The method of complex information processing on board the aircraft is described. A set of interrelated algorithms has been developed, including: an algorithm for the complex adaptive assessment of the phase coordinates of the observed target, conditional relative to its trajectory and signal signs obtained from the results of observations of heterogeneous sources; an algorithm for determining the nationality of the observed target, taking into account the assessment of its class / type based on the results of assessing the values of its trajectory and signal characteristics, as well as the conditions for assessing the phase coordinates. Practical significance. The optimization of the processes of a complex adaptive assessment of the phase coordinates of the observed target, conditional with respect to its trajectory and signal signs, and optimization of the decision-making process about the nationality of the observed target, taking into account the assessment of its class / type based on the values of the trajectory and signal signs of this target, obtained from the results of observations of heterogeneous sources. A variant of the practical implementation of the developed method and algorithms in the OBE of the aircraft is proposed.

Framing a Consent Form to Improve Consent Understanding and Determine How This Affects Willingness to Participate in HIV Cure Research: An Experimental Survey Study

HIV cure research carries serious risks and negligible benefits. We investigated how participants understand these risks and what influences their willingness to participate. Through internet-based and in-person convenience sampling, 86 HIV+ participants completed an experimental survey. Participants were randomized to read a standard consent form describing a hypothetical HIV cure study or one adapted using Fuzzy Trace Theory—a decision-making model to facilitate complex information processing. We measured consent understanding and cognitive (e.g., safe/harmful) and affective (e.g., concerning, satisfying) evaluations of HIV cure research. Participants who read the adapted consent form had improved consent understanding, but only positive affective evaluations were associated with a willingness to participate. Consent processes can use decision-making theories to facilitate comprehension of study information.

A Novel Walking Speed Control Strategy for Power Augmentation Exoskeletons based on Neural Networks

This paper addresses a novel sensing technique to minimize the interaction force of walking speed transitions during the navigation of a coupled human-exoskeleton power augmentation system. The proposed technique is able to classify the intended walking speed based on Dual Reaction Force (DRF) Sensor. The human brain as a complex information processing device is quite difficult to be simulated, especially when considering the processing speed and the speed of sensed signals through the human nervous system throughout the human body. We developed the DRF sensors for preemptive identification of pilot intentions for walking speed transitions to augment the response of the exoskeleton to shadow pilot's movements. The Dynamic Threshold Neural Networks (DTNNs) is used to classify the input signals and make a decision on the transition of system's walking speed according to the pilot's intentions and walking speed limitation. The actions for walking speed transitions are simulated in MATLAB/Simulink, and Variable Admittance Controller (VAC) and applied. To show the efficiency of the proposed walking speed control strategy, comparison is conducted with ordinary VAC algorithm technique.

RESEARCH AND SIMULATION OF THE LOCAL NAVIGATION SYSTEM OF TERRESTRIAL MOBILE ROBOT

The algorithm of complex information processing in the local navigation system of a terrestrial mobile robot and its physical model is developed. Experimental researches of this physical model have been carried out, as a result of which qualitative characteristics of the developed local navigation system have been determined. The trajectory of the object, based on the calculated navigation parameters, has a configuration identical to the actually passed route (adequate functioning of the system as a course indicator). The error in determining the coordinates of an offline object has value 0.012t2 (1.2 m per 10 s) when moving linearly and 0.022t2 (2.2 m per 10 s) when maneuvering. The orientation angles are worked out with precision (0.1÷0.3)о for roll and pitch angles and (2÷3)о for the angle of the course. Precise characteristics of the developed physical model LNS for determining orientation angles and motion parameters МR similar to the passport serial data SINS, and in some cases due to navigation features МR show even better accuracy.